The Microbiology of Safe Food
The Microbiology
of Safe Food
Third edition
Stephen J. Forsythe
Nottingham Trent University
Nottingham, UK
This edition first published 2020
© 2020 John Wiley & Sons Ltd
Edition History
John Wiley and Sons (1e, 2000), John Wiley and Sons (2e, 2010)
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Library of Congress Cataloging‐in‐Publication Data
Names: Forsythe, S. J. (Steve J.), author.
Title: The microbiology of safe food / Stephen J. Forsythe.
Description: Third edition. | Hoboken, NJ : Wiley-Blackwell, [2019] | Includes bibliographical
references and index.
Identifiers: LCCN 2019024541 (print) | LCCN 2019024542 (ebook) |
ISBN 9781119405016 (paperback) | ISBN 9781119405252 (adobe pdf) | ISBN 9781119405535 (epub)
Subjects: LCSH: Food–Microbiology.
Classification: LCC QR115 .F675 2009 (print) | LCC QR115 (ebook) | DDC 579/.16–dc23
LC record available at https://lccn.loc.gov/2019024541
LC ebook record available at https://lccn.loc.gov/2019024542
Cover Design: Wiley
Cover Image: © Kateryna Kon/Shutterstock
Set in 10/12pts Minion Pro by SPi Global, Pondicherry, India
Copyright for Plate 20 belongs to CDC
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Contents
Preface to third edition
Preface to second edition
Preface to first edition
1
Foodborne infections
1
1.1
1.2
1.3
1.4
1.5
1.6
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1.7
1.8
1.9
1.10
1.11
1.12
1.13
1.14
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The microbial world and its relationship to food
Origins of safe food production
Overview of foodborne illness
Public perception of safe food
Causes of foodborne illness
Food poisoning due to common food commodities
1.6.1 Milk and milk products
1.6.2 Meat products
1.6.3 Fresh produce
1.6.4 Low‐water activity (aw) and low‐moisture foods
Host‐related issues
Hygiene hypothesis
Chronic sequelae following foodborne illness
The size of the foodborne illness problem
The cost of foodborne diseases
Changes in antimicrobial resistance of foodborne pathogens
1.12.1 Bacterial antibiotic resistance in agriculture and aquaculture
1.12.2 Antibiotics of concern and resistance mechanisms
1.12.3 Polymyxin and plasmid‐encoded colistin resistance
1.12.4 Livestock‐associated methicillin‐resistant Staphylococcus
aureus (LA‐MRSA)
Food safety following natural disasters, and conflict
Food microbiology, foodborne diseases and climate change
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Basic aspects
45
2.1 The human intestinal tract
2.2 The normal human intestinal flora
2.3 Host resistance to foodborne infections
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Contents
2.4 Bacterial cell structure
2.4.1 Morphology
2.4.2 Cell membrane structure and the Gram stain
2.4.3 Lipopolysaccharide (LPS, O antigen)
2.4.4 Flagella (H antigen)
2.4.5 Capsule (K and Vi antigen)
2.5 Bacterial toxins and other virulence determinants
2.5.1 Bacterial endotoxins and exotoxins
2.5.2 Pathogenicity islands
2.5.3 Bacterial toxins encoded in bacteriophages
2.6 Microbial growth cycle
2.7 Death kinetics
2.7.1 Expressions
2.7.2 Decimal reduction times (D values) and z values
2.8 Factors affecting microbial growth
2.8.1 Intrinsic and extrinsic factors affecting microbial growth
2.8.2 Water activity
2.8.3 pH
2.8.4 Temperature
2.8.5 Interplay of factors affecting microbial growth in foods
2.9 Microbial response to stress
2.9.1 General stress response (GSR)
2.9.2 pH stress
2.9.3 Heat shock
2.9.4 Cold shock
2.9.5 Osmotic shock
2.10 Predictive modelling
2.10.1 Predicting modelling development
2.10.2 Primary models and the Gompertz and Baranyi equations
2.10.3 Secondary models
2.10.4 Tertiary models
2.10.5 Application of predictive microbial modelling
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Food preservation and spoilage organisms
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3.1 Spoilage micro‐organisms
3.1.1 Spoilage micro‐organisms
3.1.2 Spoilage of dairy products
3.1.3 Spoilage of meat products
3.1.4 Fish spoilage
3.1.5 Egg spoilage
3.1.6 Cereals and grain
3.2 Shelf life indicators
3.2.1 Glucose
3.2.2 Gluconic and 2‐oxogluconic acid
3.2.3 L‐ and D‐lactic acids, acetic acid and ethanol
3.2.4 Biologically active amines
3.2.5 Volatile compounds
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3.3
3.4
3.5
3.6
3.7
3.8
3.9
4
3.2.6 Storage trials
3.2.7 Challenge tests
3.2.8 Predictive modelling
Methods of preservation and shelf life extension
Preservatives
3.4.1 Organic acids
3.4.2 Hydrogen peroxide and lactoperoxidase system
3.4.3 Chelators
3.4.4 Non‐acidic preservatives
3.4.5 Preservation due to weak acids and low pH
3.4.6 Biopreservatives
Physical methods of preservation
3.5.1 Preservation by heat treatment
3.5.2 High‐pressure treatment
3.5.3 Ohmic heating and radio frequency
3.5.4 Pulsed electric fields
3.5.5 Ultrasound
3.5.6 Intense light pulse
3.5.7 Food irradiation
3.5.8 Cold plasma and low‐energy electrons for food
surface decontamination
Packaging
3.6.1 Reduced oxygen packaging, modified atmosphere
packaging and active packaging
3.6.2 Antimicrobial packaging and nanotechnology
Fermented food products
3.7.1 Fermented milk products
3.7.2 Fermented meat products
3.7.3 Fermented vegetables
3.7.4 Fermented protein foods: shoyu and miso
Organisms involved in the production of fermented foods
3.8.1 Lactic acid bacteria
3.8.2 Bifidobacterium species
3.8.3 Other organisms
Functional foods: probiotics and gut modulation
3.9.1 Qualified Presumption of Safety (QPS) and Generally
Regarded As Safe (GRAS)
3.9.2 Functional foods and probiotics
3.9.3 Probiotic studies
3.9.4 Novel organisms – modulation of gut microbiota
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Bacterial foodborne pathogens
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4.1 Indicator organisms
4.1.1 Coliforms
4.1.2 Enterobacteriaceae
4.1.3 Enterococci
4.1.4 Bacteriophages
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Contents
4.2 Campylobacter jejuni, C. coli and C. lari
4.2.1 General description
4.2.2 Campylobacter infections
4.2.3 Campylobacter jejuni typing
4.2.4 Virulence factors
4.2.5 Whole‐genome sequence analysis
4.2.6 Sources and control of Campylobacter jejuni
4.3 Salmonella serovars
4.3.1 General description
4.3.2 Salmonella serotypes
4.3.3 Infections caused by Salmonella serovars
4.3.4 Virulence factors of Salmonella serovars
4.3.5 Whole‐genome analysis
4.3.6 Sources and control of Salmonella serovars
4.3.7 Salmonella serovar outbreaks
4.4 Pathogenic E. coli
4.4.1 General description
4.4.2 E. coli pathovars
4.4.3 Infections caused by E. coli pathovars
4.4.4 Virulence factors
4.4.5 Whole‐genome analysis
4.4.6 Sources and control of E. coli pathovars
4.4.7 Outbreaks caused by E. coli pathovars
4.5 Sh. dysenteriae and Sh. sonnei
4.5.1 General description
4.5.2 Shigellosis
4.5.3 Virulence factors
4.5.4 Sh. sonnei outbreak
4.6 Cronobacter species
4.6.1 General description
4.6.2 Infections due to Cronobacter species
4.6.3 Identification and typing methods for Cronobacter species
4.6.4 Virulence factors
4.6.5 Sources and control of Cronobacter species
4.6.6 Cronobacter outbreaks
4.7 Vibrio cholerae, V. parahaemolyticus and V. vulnificus
4.7.1 General description
4.7.2 Infections due to Vibrio species
4.7.3 Virulence factors
4.7.4 Sources and control
4.8 Brucella melitensis, Br. abortus and Br. suis
4.8.1 General description
4.8.2 Brucellosis
4.9 Yersinia enterocolitica
4.9.1 General description
4.9.2 Yersiniosis
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4.10
4.11
4.12
4.13
4.14
4.15
4.16
4.17
4.18
4.9.3 Sources and control
4.9.4 Outbreaks due to Y. enterocolitica
Aeromonas hydrophila, A. caviae and A. sobria
4.10.1 General description
4.10.2 A. hydrophila gastroenteritis
4.10.3 Sources and control
Plesiomonas shigelloides
4.11.1 General description
4.11.2 Plesiomonas infections
4.11.3 Sources and control
Listeria monocytogenes
4.12.1 General description
4.12.2 Listeriosis
4.12.3 Lineages and typing L. monocytogenes
4.12.4 Virulence factors
4.12.5 Whole‐genome analysis of L. monocytogenes
4.12.6 Sources and control of L. monocytogenes
4.12.7 L. monocytogenes outbreaks
Staphylococcus aureus
4.13.1 General description
4.13.2 Infections associated with St. aureus
4.13.3 Virulence factors
4.13.4 Sources and control
Clostridium perfringens
4.14.1 General description
4.14.2 Cl. perfringens infections
4.14.3 Sources and control
Clostridium botulinum
4.15.1 General description
4.15.2 Cl. botulinum intoxication
4.15.3 Sources and control
B. cereus group
4.16.1 General description
4.16.2 B. cereus foodborne infections
4.16.3 Virulence traits
4.16.4 Sources and control
Enterococcus and Streptococcus species
4.17.1 General description
4.17.2 E. faecalis and E. faecium
4.17.3 Streptococcus pyogenes, group A streptococci
4.17.4 Virulence traits
Emerging and uncommon foodborne pathogens
4.18.1 Arcobacter genus
4.18.2 Campylobacter concisus
4.18.3 EAEC, E. coli O55 and E. coli O26
4.18.4 Escherichia albertii
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4.18.5
4.18.6
4.18.7
4.18.8
4.18.9
5
6
Providencia alcalifaciens
Clostridium difficile
Mycobacterium paratuberculosis
Acinetobacter species
Nanobacteria
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Foodborne pathogens: viruses, toxins, parasites and prions
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5.1 Foodborne viruses
5.1.1 Norovirus
5.1.2 Hepatitis A
5.1.3 Hepatitis E
5.1.4 Rotaviruses
5.1.5 Small round viruses, astroviruses, sapporo‐like viruses,
adenoviruses and parvoviruses
5.1.6 Human enteroviruses
5.2 Seafood and shellfish poisoning
5.2.1 Ciguatera poisoning
5.2.2 Scombroid poisoning
5.2.3 Paralytic shellfish poisoning
5.2.4 Diarrhoeic shellfish poisoning
5.2.5 Neurotoxic shellfish poisoning
5.2.6 Amnesic shellfish poisoning
5.3 Foodborne parasites: eucaryotes
5.3.1 Toxoplasma gondii
5.3.2 Taenia saginata and T. solium
5.3.3 Echinococcus multilocularis and E. granulosus
5.3.4 Cyclospora cayetanensis
5.3.5 Cryptosporidium parvum
5.3.6 Anisakis simplex
5.3.7 Trichinella spiralis
5.4 Mycotoxins
5.4.1 Aflatoxins
5.4.2 Ochratoxins
5.4.3 Fumonisins
5.4.4 Zearalenone
5.4.5 Trichothecenes
5.4.6 Prions and transmissible spongiform encephalopathies
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Methods of detection and characterisation
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6.1 Prologue
6.2 Conventional methods
6.2.1 Culture media
6.2.2 Sublethally injured cells
6.2.3 Viable but non‐culturable bacteria (VBNC)
6.3 Rapid sampling methods
6.3.1 Sample preparation
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Contents
6.4
6.5
6.6
6.7
6.3.2 Separation and concentration of target
Rapid end‐detection methods
6.4.1 ELISA and antibody‐based detection systems
6.4.2 Reversed passive latex agglutination
6.4.3 ATP bioluminescence techniques and hygiene monitoring
6.4.4 Protein detection
6.4.5 Flow cytometry
6.4.6 Biosensors
6.4.7 Impedance (Conductance) microbiology
DNA‐based molecular typing and proteomic methods
6.5.1 Polymerase chain reaction (PCR)
6.5.2 Microarrays
6.5.3 Loop‐mediated isothermal amplification (LAMP) technique
6.5.4 Pulsed‐field gel electrophoresis (PFGE)
6.5.5 Restriction fragment length polymorphism (RFLP)
6.5.6 Amplified fragment length polymorphism (AFLP)
6.5.7 Random amplification of polymorphic DNA (RAPD)
6.5.8 Repetitive‐element polymerase chain reaction (Rep‐PCR)
6.5.9 Nucleic acid sequence‐based amplification (NASBA)
6.5.10 Multiple‐locus variable number tandem (VNTR) repeat analysis
6.5.11 PCR‐probe based serotyping
6.5.12 Ribotyping
6.5.13 Matrix‐associated laser desorption ionisation – time
of flight (MALDI‐TOF)
Identification and typing methods based on high‐throughput
DNA sequencing
6.6.1 Conventional seven‐loci MLST
6.6.2 Genome sequence‐based MLST
6.6.3 CRISPR‐cas array typing
6.6.4 Single nucleotide polymorphism (SNP)‐based analysis
Specific detection procedures and accreditation
6.7.1 Aerobic plate count (APC)
6.7.2 Salmonella serovars
6.7.3 Campylobacter species
6.7.4 Enterobacteriaceae and E. coli
6.7.5 Pathogenic E. coli, including E. coli O157:H7
6.7.6 Shigella species
6.7.7 Cronobacter genus
6.7.8 Aeromonas species
6.7.9 Arcobacter species
6.7.10 Listeria monocytogenes
6.7.11 Staphylococcus aureus
6.7.12 Clostridium perfringens
6.7.13 B. cereus, B. subtilis and B. licheniformis
6.7.14 Mycotoxins
6.7.15 Viruses
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Contents
7
Microbiological criteria
313
7.1 Background to microbiological criteria and end‐product testing
7.2 International commission on microbiological
specifications for foods (ICMSF)
7.3 Codex Alimentarius principles for the establishment and application
of microbiological criteria
7.4 Sampling plans
7.5 Variables plans
7.6 Attributes sampling plan
7.6.1 Two‐class plan
7.6.2 Three‐class plan
7.7 Principles
7.7.1 Defining a ‘lot’ of food
7.7.2 Sample unit number
7.7.3 Operating characteristic curve
7.7.4 Producer risk and consumer risk
7.7.5 Stringency of two‐ and three‐class plans, setting n and c
7.7.6 Setting the values for m and M
7.8 Microbiological limits
7.8.1 Definitions
7.8.2 Limitations of microbiological testing
7.8.3 Examples of sampling plans
7.9 Implemented microbiological criteria
7.9.1 Microbiological criteria in the European Union
7.9.2 EU Directives specifying microbiological
standards for foods
7.10 UK guidelines for ready‐to‐eat foods
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Hygienic production practices
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8.1
8.2
8.3
8.4
8.5
Contribution of food handlers to foodborne illness
Personnel hygiene and training
Cleaning
Detergents and disinfectants
Microbial biofilms
8.5.1 Microbial biofilm formation
8.5.2 Bacterial biofilm induction
8.5.3 Biofilm removal and control
8.6 Assessment of cleaning and disinfection efficiency
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Food safety management tools
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9.1
9.2
9.3
9.4
9.5
9.6
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The manufacture of hygienic food
Microbiological safety of food in world trade
Consumer pressure effect on food processing
The management of hazards in food in international trade
Hazard analysis critical control point (HACCP)
Prerequisite programme
Contents
9.7
9.8
9.9
9.10
9.11
9.12
9.13
10
Outline of HACCP
9.7.1 Food hazards
9.7.2 Preparation for HACCP
9.7.3 Principle 1: hazard analysis (HA)
9.7.4 Principle 2: critical control points (CCPs)
9.7.5 Principle 3: critical limits
9.7.6 Principle 4: CCP monitoring
9.7.7 Principle 5: corrective actions
9.7.8 Principle 6: verification
9.7.9 Principle 7: record keeping
Microbiological criteria and HACCP
Microbiological hazards and their control
9.9.1 Sources of microbiological hazards
9.9.2 Temperature control of microbiological hazards
9.9.3 Non‐temperature control of microbiological hazards
HACCP plans
9.10.1 Production of pasteurised milk
9.10.2 Swine slaughter in the abattoir
9.10.3 Chilled food manufacture
9.10.4 Generic models
GMP and GHP
Quality systems
Total quality management
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Microbiological risk assessment
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10.1
10.2
10.3
10.4
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Risk analysis and microbiological risk assessment
Origin of MRA
MRA – an overview
MRA – structure
10.4.1 Risk assessment
10.4.2 Risk management
10.4.3 Risk communication
10.5 Risk assessment
10.5.1 Statement of purpose
10.5.2 Hazard identification
10.5.3 Exposure assessment
10.5.4 Hazard characterisation
10.5.5 Dose–response assessment
10.5.6 Dose–response models
10.5.7 Dose and infection
10.5.8 Risk characterisation
10.5.9 Production of a formal report
10.5.10 Triangular distributions and Monte Carlo simulation
10.6 Risk management
10.6.1 Risk assessment policy
10.6.2 Risk profiling
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Contents
10.7 Food safety objectives (FSO)
10.8 Risk communication
10.9 Future developments in MRA
10.9.1 International methodology and guidelines
10.9.2 Risk assessment database
10.9.3 Training courses and use of resources
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Application of microbiological risk assessment
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11.1 Salmonella serovars
11.1.1 Salmonella enteritidis in shell eggs and egg products
11.1.2 Hazard identification and hazard characterisation
of Salmonella in broilers and eggs
11.1.3 Exposure assessment of Salmonella serovars in broilers
11.1.4 Salmonella serovars in cooked chicken
11.1.5 Salmonella serovars in cooked patty
11.1.6 Poultry FARM
11.1.7 Domestic and sporadic human salmonellosis
11.2 Campylobacter
11.2.1 C. jejuni risk from fresh chicken
11.2.2 Risk profile for pathogenic species
of Campylobacter in Denmark
11.2.3 Risk assessment of C. jejuni in broilers
11.2.4 Campylobacter fluoroquinolone resistance
11.3 L. monocytogenes
11.3.1 L. monocytogenes hazard identification
and hazard characterisation in ready‐to‐eat foods
11.3.2 L. monocytogenes exposure assessment in RTE foods
11.3.3 Relative risk of L. monocytogenes in selected RTE foods
11.3.4 L. monocytogenes in European Union trade
11.3.5 L. monocytogenes in meat balls
11.3.6 Listeriosis from RTE meat products
11.4 E. coli O157
11.4.1 E. coli O157:H7 in ground beef
11.5 Bacillus cereus
11.5.1 B. cereus risk assessment
11.6 Vibrio parahaemolyticus
11.6.1 Public health impact of V. parahaemolyticus
in raw molluscan shellfish
11.7 Cronobacter species and Salmonella in powdered infant formula (PIF)
11.8 Viral risk assessments
11.8.1 Viral contamination of shellfish and coastal waters
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International control of microbiological hazards in foods:
regulations and authorities
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12.1 Control of foodborne pathogens
12.1.1 Control of Salmonella serovars in poultry
12.1.2 Control of Escherichia coli pathovars and Salmonella
serovars in fresh produce
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Contents
12.2
12.3
12.4
12.5
12.6
12.7
13
14
12.1.3 Control of pathogens in low‐moisture foods (LMFs)
World Health Organisation (WHO), global food security
from accidental and deliberate contamination
Regulations in international trade of food
Codex Alimentarius Commission (CAC)
SPS measures, Technical Barriers to Trade (TBT) and the WHO
EU legislation
International food safety agencies
12.7.1 European Food Safety Authority (EFSA)
12.7.2 Food authorities in the United States
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Surveillance and foodborne outbreak investigation
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13.1 Surveillance programmes
13.1.1 International Food Safety Authorities Network (IFSAN)
13.1.2 Surveillance systems in the United States
13.1.3 PulseNet international
13.1.4 European Centre for Disease Prevention and Control (ECDC)
and European surveillance for salmonellosis and shiga
toxin‐producing E. coli (STEC)
13.1.5 European Food‐Borne Viruses in Europe network (FBVE)
13.1.6 Rapid Alert System for Food and Feed (RASFF)
13.1.7 Global Salm‐Surv (GSS)
13.1.8 Surveillance of ready‐to‐eat foods in the United Kingdom
13.2 Outbreak investigations
13.2.1 Preliminary outbreak investigation
13.2.2 Case definition and data collection
13.2.3 Data collation and interpretation
13.3 Social media, crowd sourcing and reporting food poisoning cases
13.4 Mobile phones and food safety
13.5 Food terrorism and biocrimes
475
476
476
478
479
480
480
483
483
483
486
486
487
492
493
493
Whole‐genome sequencing, microbiomes
and genomic epidemiology
499
14.1 High‐throughput DNA sequencing
14.2 Microbiome analysis
14.3 Genomic epidemiology
14.3.1 Whole‐genome sequencing for microbial source tracking
14.3.2 Genome Trakr network (US)
14.3.3 NCBI pathogen detection site
14.3.4 Center for Genomic Epidemiology (Denmark)
14.4 Key outbreaks investigated using genomic epidemiology
14.4.1 Ready‐to‐eat meat products L. monocytogenes
outbreak, Canada, 2008
14.4.2 E. coli O104:H4 outbreak, Germany, 2011
14.4.3 C. jejuni outbreak investigations
14.4.4 Salmonella enteritidis in eggs, European outbreak, 2014
14.4.5 Multinational outbreak of Salmonella Agona through
infant formula contamination, 2017
499
501
503
503
505
505
505
505
505
506
508
509
510
xvi
Contents
14.4.6
14.4.7
Retrospective Cronobacter sakazakii neonatal
intensive care unit outbreak, France, 1994
L. monocytogenes ST6, polony sausages,
South Africa, 2017–2018
Glossary of terms
List of abbreviations
Food safety resources on the world wide web
Plates and credits
References
Index
512
512
515
521
525
531
533
563
Preface to third edition
I can hardly believe the last (second) edition of MoSF was back in 2009. It seems so long ago
now. But what has changed in the meantime? Well, we have the recognition of various emergent foodborne pathogens as well as new and improved methods of detection, identification
and profiling, not forgetting the increasingly affordability and application of next‐generation
DNA sequencing. But has the incidence and burden of foodborne disease decreased?
Apparently not. Essentially, we are probably more aware and better informed, and through
social media make a complaint quicker.
So what warranted another version of this book? Primarily the area of high‐throughput
sequencing was high on my list of ‘must cover’. It is redefining microbiology as a whole, especially clinical and environmental microbiology, and to an extent food microbiology. Not just
bacterial genome determination of individual laboratory isolates, but microbiome analysis of
the human body flora and the flora of food, leading to an appreciation of interactions between
the ‘normal’ gut flora and human well‐being.
High‐throughput sequencing is now being applied to outbreak investigations. Between the
second edition and this third edition there was a particular Escherichia coli outbreak in
Germany that hospitalised over 1000, and killed over 50 people. This was the first outbreak to
be investigated using whole‐genome sequencing. In fact it became a race between competing
genome sequencing platforms for which one could sequence and publicise their results before
their competitors.
Related to outbreak investigations, in order to distinguish between strains to a greater degree
than ‘conventional’ methods such as pulsed‐field gel electrophoresis (PFGE), which has repetitively (ad nauseum) been cited as the ‘gold standard’ for such analysis, DNA sequencing‐based
methods are now being applied, such as multi‐locus variable analysis (MLVA), clustered regularly interspaced short palindromic repeats (CRISPR)‐cas array profiling and single nucleotide
polymorphism (SNP) analysis. My own research area is being similarly swayed, with genomic
analysis being used to inform laboratory‐based research, and vice versa with laboratory observations guiding areas to investigate bacterial populations at the genomic level. Subsequently,
some useful detection methods (even early molecular ones) are infrequently used now and so
have been removed from this edition – for example, denaturing gradient gel electrophoresis
(DGGE). However, I have reluctantly retained microarrays, despite more cost‐effective equivalent methods involving rapid DNA sequencing being available, as they continue to be referred
to in the literature.
A large number of outbreak investigations have been included in this new edition. This
is because they contain a considerable amount of information and data that can illustrate
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Preface to third edition
important points in food safety, in particular exampling the consequences of failure to produce
safe food.
Another reason for the update has been the expansion of social media and Internet resources.
Social networks can be used to assist and alert possible outbreaks, though the potential
for misinformation and misattribution is considerable causing unwarranted cost to food
producers. Currently social media, high‐throughput sequencing and food poisoning outbreak
investigations are being combined, and these aspects were not covered in the previous two
editions.
Obviously, a single‐author book will have certain biases due to personal experience and
expertise. As such I have tried to bring to this edition an emphasis reflective of my role as advisor to national and international regulatory and non‐regulatory authorities. Also I have drawn
where appropriate on my own publications, but will leave my research students to ‘self‐surf ’
their own papers in the References section.
Will this third edition become dated? Inevitably ‘yes’ – however the major organisms causing food poisoning have not changed since the first edition of MoSF in 2000 and probably will
not change in the near future. Hence food safety advisors have a job for life! Please enjoy reading this latest edition, and please contact me via email (steve.forsythe@foodmicrobe.com) or
various social sites if you want further information or help.
Finally, my latest enterprise, this third edition, is again dedicated to my ever‐supportive wife
Debbie, my now grown up children James and Rachel, and my parents – without whom none
of this would have been possible.
Steve Forsythe
Nottingham, UK
March 2019
Preface to second edition
Although I was pleased with the first edition of this book (MoSF), I nevertheless felt that it was
not complete. This new edition tries to address this by including new sections on bioinformatics,
biothreats and personnel, as well as updating many other sections. Since 2000, the topic of
microbiological risk assessment has increased and subsequently I have incorporated parts of
my other Blackwell’s book Microbiological Risk Assessment of Food (2002) into Chapter 10 as it
was a substantial improvement on the first MoSF edition’s few pages. My appreciation is due to
Simon Illingworth (LabM, Bury, UK) for reviewing Chapter 5 on detection methods for me.
A major change is the complementing websites at www.foodmicrobe.com. This was available
with the first edition, but was an afterthought and so unfortunately was not fully utilised. In
fact it was one of the first web‐based supported books by Blackwells, and the listing of URLs in
the Appendix was considered a ‘novelty’! How much has changed since 2000. I am using the
web for two main purposes. First, to keep some chapters up to date, and second to offer various
data exercises that are not in keeping with the book format. One aspect that I have been
wanting to expand and encourage ‘younger’ readers to explore is the application of genomics,
post‐genomics and bioinformatics to food microbiology. Again the first edition included
microarrays but not the tools for one to investigate microbial genomes for oneself. In fact,
2000, the year MOSF was published, was also the year that the first version of the Campylobacter
jejuni genome was released, and since the MOSF text was written in 1999, the whole topic of
microbial genomics was not even on the radar. The fact that genomes are sequenced faster
than they can be fully annotated means that one can quickly discover something that no‐one
else has even known before, and I hope the bioinformatics aspects will enable and encourage
readers to try in silico research. One topic that was gaining increasing public attention in 1999–
2000 was bovine spongiform encephalopathy‐variant Creutzveldt–Jakob disease (BSE‐vCJD).
It appears in the intervening years that we have possibly passed the peak incidence, fortunately.
However, over the same period, the spectre of bioterrorism has arisen and so this issue is
addressed in a new section of this edition.
One thing that has not changed between these two editions is the unacceptably high
incidence of foodborne disease. Even more alarming is that we still are only aware of the ‘tip of
the iceberg’ with regard to its true incidence. When one considers that it has been estimated
that in the United States 3400 deaths are due to unknown foodborne agents (Frenzen 2004),
then there is evidently a considerable amount of research and investment still to be undertaken.
Confession time: it was my full intention to complete this new edition for publication in
2005. However, our intensive research into Cronobacter spp. (Enterobacter sakazakii) and
related organisms has taken up more of my time than the hours in the day can permit. This
emergent pathogen, sadly, can infect neonates causing severe illness, and even death. In order
not to unbalance this book by excessive reference to this organism of my own personal interest,
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Preface to second edition
readers should consult Enterobacter sakazakii (ASM Press 2007), edited by myself and Jeff
Farber (Health Canada) as well as my homepage www.foodmicrobe.com.
As always my thanks and appreciation go to Nigel Balmforth, David McDade and especially
Katie Loftus at Blackwells for their patience as the deadlines made a whooshing sound as they
went by (frequently). Finally a special thanks to my forever supportive wife Debbie, my
children James and Rachel, and my parents – without whom none of this would have been
possible.
Steve Forsythe
Professor of Microbiology
Nottingham Trent University
July 2009
Preface to first edition
Throughout the world, food production has become more complex. Frequently raw materials
are sourced globally and the food is processed through an increasing variety of techniques. No
longer does the local farm serve the local community through a local shop, nowadays there are
international corporations adhering to national and international regimes. Therefore
approaches to safe food production are being assessed on an expanding platform from national
and European to trans‐Atlantic and beyond. Against this backdrop there have been numerous
highly publicised food safety issues such as bovine spongiform encephalopathy (BSE) and
Escherichia coli O157:H7, which have caused the general public to become more cautious and
vociferous concerning food issues. The controversy in Europe over genetically modified foods
is perceived by the general public within the context of ‘food poisoning’.
This book aims to review the production of food and the level of micro‐organisms that
humans ingest. Certain circumstances require zero tolerance for pathogens, whereas more
frequently there are acceptable limits set, albeit with statistical accuracy or inaccuracy depending upon whether you subsequently suffer from food poisoning. Microbes are traditionally
ingested in fermented foods and this has developed into the subject of pre‐ and probiotics with
reputed health benefits. Whether engineered ‘functional foods’ will be able to attain consumer
acceptance remains to be seen.
Food microbiology covers both food pathogens and food spoilage organisms. This book
aims to cover the wide range of micro‐organisms occurring in food, both as contaminants and
deliberate inoculation. Due to the heightened public awareness over food poisoning it is
important that all companies in the food chain maintain high hygienic standards and assure
the public of the safety of the produce. Obviously over time there are technological changes in
production methods and in methods of microbiological analysis. Therefore the food microbiologist needs to know the effect of processing changes (pH, temperature, etc.) on the microbial
load. To this end this book reviews the dominant foodborne micro‐organisms, the means of
their detection, microbiological criteria as the numerical means of interpreting end‐product
testing, predictive microbiology as a tool to understanding the consequences of processing
changes, the role of ‘Hazard Analysis Critical Control Point’ (HACCP) and the objectives of
microbial risk assessment (MRA) and the setting of Food Safety Objectives, which have
recently become a focus of attention. In recent years the web has become an invaluable source
of information and to reflect this a range of useful food safety resource sites are given in the
back to encourage the reader to boldly go and surf. Although primarily aimed at undergraduate and postgraduate courses I hope the book will also be of use to those working in industry.
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Preface to first edition
The majority of this book was written during the last months of 1999, a time when France
was being taken to the European Court over its refusal to sell British beef due to BSE/new
variant Creutzveldt–Jakob disease and there had been riots in Seattle concerning the World
Trade Organization. Whilst large organisations were wondering about the impact of the
Millennium bug, in the UK the public were waiting to see the impact of the BSE ‘bug’ (a few
hundred or a few thousand cases?).
As usual no book can be achieved without assistance and special thanks are due to Phil
Vosey concerning MRA; Ming Lo for considerable help with the computer packages; Alison at
Oxoid Ltd for the invaluable information on microbiological testing procedures around the
world; Pete Silley and Andrew Pridmore at Don Whitley Scientific Ltd for the RABIT diagrams; and Garth Lang at Biotrace Ltd for the ATP bioluminescence data. Not forgetting of
course Debbie and Cathy for reading through the draft copy – nevertheless all mistakes are the
author’s fault.
This book is especially dedicated to Debbie, James and Rachel, Mum and Dad for their
patience whilst I have been burning the midnight oil.
Dr Steve Forsythe
6 January, 2000
1 Foodborne infections
This may seem a rather self‐defeating opening sentence, but there is no universally accepted
definition of ‘safe food’. The reason is that it is a relative term, which is linked to determining
the acceptable level of risk to a mixed population or maybe a specific subgroup. Our food is
very diverse, and to ensure it is safe requires a systematic, proactive approach of minimising
contamination from ‘farm to fork’. However, our food supply involves international movement
of ingredients and processed products, and therefore the ‘farm’ is much removed from the
‘fork’. Some procedures of food preservation are well known to the general public, such as
refrigeration and canning. There’s also the implementation of ‘hazard analysis and critical control point’ (HACCP), in which the producer anticipates the likely hazards in the final product
and ensures the processing reduces or eliminates them to an acceptable level. Foodborne illness can be defined as diseases commonly transmitted through food, and comprise a broad
group of illnesses caused by microbial pathogens, parasites, chemical contaminants and biotoxins. An alternative phrase ‘food poisoning’ has often been used but nowadays is regarded as
being too restrictive. Unfortunately, illness due to foodborne contamination is still a major
cause of morbidity and mortality.
Dealing with food safety problems is challenging, in part because they change over time. We
have changes in our economy, and therefore lifestyle, eating habits (ranges of food, eating at
home or eating out), and an ageing population who are more prone to infection and are slower
to recover. The causative agents of foodborne illnesses are also changing, with the emergence
of previously unrecognised emergent pathogens. Food producers both industrially and domestically need be aware of these changes in order to improve the safety of our food. This first
chapter will consider the magnitude of the foodborne illness, the diversity of sources and diseases, along with its economic consequences. These key topics will be covered in greater depth
later in specific chapters. Definition of terms will be found in the glossary at the end of the
book, where there is also a listing of useful core hypertext links.
Food microbiology is a multidisciplinary topic, and there are rapid advances being made in
a number of areas. In order to keep this book as up‐to‐date as reasonably possible the reader
should also refer to the supporting websites at www.foodmicrobe.com/info.htm where the
reader will find additional information for specific chapters.
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
1
2
The microbiology of safe food
1.1 The microbial world and its relationship to food
The world of microbiology covers a diverse range of life, albeit very small in size. Simply using
the loose definition that microbiologists study life forms which are not clearly visible to the
naked eye means that it includes complex organisms such as protozoa and fungi, as well as the
simpler bacteria and viruses. Nevertheless, the major micro‐organisms studied to date have
been the bacteria. This is because of their medical importance, and because they are easier to
cultivate than other micro‐organisms such as viruses, let alone prions, which are uncultivable.
Despite this predominance of bacteria in our understanding of microscopic life, there are
numerous important organisms in the other microbial categories.
The cell structure reveals whether an organism is ‘eucaryotic’ (also spelt ‘eukaryotic’) or
‘procaryotic’ (also spelt ‘prokaryotic’). Eucaryotes have cellular organisation with mitochondria, endoplasmic reticulum and a defined nucleus, whereas procaryotes have no obvious
organelle differentiation and are in fact similar in size to the organelles of eucaryotes. Analysis
of the genetic information encoding for part of the ribosome (16S rDNA gene) has revealed a
plausible relationship and evolution of life from procaryotes to eucaryotes through intracellular symbiotic relationships.
Initially, the classification of micro‐organisms has been based on morphology, and phenotypical (biochemical) properties. Morphological analysis considers whether the bacterium is
spherical (coccoid), filamentous, curved or rod‐shaped, and if the bacterium has a Gram‐
negative or Gram‐positive type cell wall (Section 2.4.2). The possession of certain enzymes, i.e.
α‐galactosidase for lactose fermentation, has helped in identifying and defining a general
group of bacteria associated with faecal contamination that would have come from the colon,
the origin of the old term ‘coliforms’ (Section 4.1.1). In general, these biochemical and enzymic activities enabled cultivable organisms to be classified. Inevitably defining species according to biochemical (phenotyping) traits will be problematic, as such functions represent only a
small portion of the total coding of an organism.
DNA sequencing has enabled a fuller understanding of the genetic capabilities of micro‐
organisms (see Chapter 14). Certain genes, termed ‘housekeeping genes’, have undergone limited variation during evolution and can be used as a means of constructing a family tree of
relationships between organisms. This is called ‘phylogenetics’. The 16S rDNA encoding gene
was initially used for this purpose. It is a housekeeping gene as it encodes for one of the rRNA
molecules that is essential for the ribosome to function for protein synthesis. This molecule is
called the 16S rRNA gene in procaryotes, and the 18S rRNA gene in eucaryotes due to the
respective difference in the size of their ribosomal particles (Section 14.2). A phylogenetic tree
using these genes for organisms that cause foodborne disease is given in Figure 1.1. Viruses do
not possess this gene and therefore do not appear on this ‘Tree of life’.
As DNA sequencing became more accessible, other housekeeping genes of longer lengths,
such as gyrB, have been used as their longer lengths enable greater discrimination. The combined sequence of several housekeeping genes is the basis of multi‐locus sequence typing
(Section 6.6.1). Such phylogenetic analysis is now undertaken in silico with core genome
sequences. Being able to sequence genes in organisms of interest, and compare the order of
DNA nucleotides, is just one example of ‘bioinformatics’, which is enabling us to better understand the microbial world (see Chapter 14).
Although the ‘species’ concept is conventionally applied to bacteria and fungi, there are difficulties. In higher organisms, a species can be defined as an interbreeding population that is
reproductively isolated. The genome of each individual is derived most equally from its two
Foodborne infections
Acetobacter pasteurianus
Brucella melitensis
Arcobacter butzleri
Campylobacter jejuni
Bacillus cereus
St aureus
Brochothrix thermosphacta
Listeria monocytogenes
Lactobacillus plantarum
Pediococcus pentosaceus
Lactobacillus acidophilus
Streptococcus thermophilus
Clostridium botulinum
Desulphotomaculum nigrificans
Bifidobacterium longum
Brevibacterium linens
Mycobacterium tuberculosis
Pyrococcus furiosus
Alcaligenes faecalis
Coxiella burnetii
Aeromonas hydrophila
Shewanella putrefaciens
Escherichia coli
Shigella dysenteriae
Salmonella enterica LT2
Yersinia enterocolitica
Vibrio cholerae
Alteromonas stellpolaris
Acinetobacter calcoaceticus
Moraxella
Pseudomonas fluorescens
3
Firmicutes; low GC% Gram-positive organisms
Actinobacteria; high GC% Gram-positive organisms
Taenia solium
Saccharomyces cerevisiae
Penicillium chrysogenum
Aspergillus niger
Rhizopus oryzae
Cyclospora cayetanensis
Eucaryotes
Enterobacteriaceae
Figure 1.1 Phylogenetic tree of organisms associated with food microbiology and the archaea organism
Pyrococcus furiosus, based upon the DNA sequence ribosomal small subunit, constructed using ClustalW
(freeware). Details of sequence accession numbers and tree construction can be obtained from www.
foodmicrobe.com/info.
parents and as species diverge, the hybrids become less viable. In contrast, bacteria multiply by
binary fission. The acquisition of additional genes by bacteria is generally limited to the transfer of genes between related strains, and less often between different species (horizontal gene
transfer or HGT). Whole‐genome sequence analysis can reveal regions of DNA that differ
from the majority of the genome due to their G:C ratio or codon bias. These regions can be
from bacteriophages, and less closely related bacteria. In multi‐locus sequence analysis
(Section 6.6.1), housekeeping genes are sequenced and form a core of genes that help to define
the species. Therefore, although there are differences between the ‘species’ concept in bacteria
and higher organisms, in both cases individual ‘species’ can be recognised by reference to a
gene pool. Inevitably as our knowledge of organisms at the genome level improves, so previous
species may be redefined.
The relatedness of organisms used to be determined using laboratory‐based DNA–DNA
hybridisation analysis. The DNA was extracted from two organisms, heated to separate the
two DNA strands and then they were allowed to anneal to each other and the extent of hybridisation measured. The common standard was that <70% hybridisation meant the organisms
were not in the same species. Whereas now whole‐genome sequencing (WGS) has led to the
use of in silico approaches such as the average nucleotide identity (ANI) (Goris et al. 2007) and
can be undertaken using online tools such as http://enve-omics.ce.gatech.edu/ani. Although a
universal cut‐off value to delineate bacterial species does not exist, an ANI value of >95% ± 0.5%
has been commonly used to indicate that two strains are the same species.
4
The microbiology of safe food
A very brief survey of food poisoning micro‐organisms can start with eucaryotic
organisms such as helminths (See Table 1.1 and Figure 1.1; cf. Section 5.3). These include the
cestode worms that are responsible for taeniasis; Taenia solium the pork tapeworm, and
T. saginata the beef tapeworm. Both have worldwide distribution. Infection results from the
ingestion of undercooked or raw meats containing the cysts. The mature worms can infect
the eye, heart, liver, lungs and brain. A third tapeworm is Diphyllobothrium latum, which is
found in a variety of freshwater fish including trout, perch and pike. Contaminated water
supplies can carry infectious organisms including pathogenic protozoa such as Cyclospora
and Cryptosporidium.
Table 1.1 Diversity of hazards associated with food.
Biological
Chemical
Physical
Macrobiological
Microbiological
Veterinary residues: antibiotics, growth stimulants
Plasticisers and packaging migration: vinyl chloride,
bisphenol A
Glass
Metal
Viruses
Hepatitis A
Norovirus
Rotavirus
Chemical residues: pesticides (DDT), cleaning fluids
Stones
Pathogenic bacteria
Spore‐forming
Bacillus cereus
Clostridium perfringens
Clostridium botulinum
Non‐spore‐forming
Campylobacter jejuni
Pathogenic strains of
Escherichia coli
Listeria monocytogenes
Salmonella serovars
Bacterial toxins
Staphylococcus aureus
B. cereus
Shellfish toxins: domoic acid,
okadaic acid
NSP, PSP
Parasites and protozoa
Cryptosporidium parvum
Entamoeba histolytica
Giardia lamblia
Toxoplasma gondii
Fasciola hepatica
Taenia solium
Anisakis species
Trichinella spiralis
Mycotoxins: ochratoxin,
aflatoxins, fumonisins, patulin
Allergens
Toxic metals: lead, cadmium, arsenic, tin, mercury
Wood
Plastic
Food chemicals: preservatives, processing aids
Parts of pests
Radiochemicals: 131I, 127Cs
Insulation material
Dioxins, polychlorinated biphenyls (PCBs)
Bone
Prohibited substances
Printing inks
Fruit pits
NSP = neurotoxic shellfish poison, PSP = paralytic shellfish poisoning.
Source: Adapted from Snyder (1995) and Forsythe (2000).
Foodborne infections
5
Fungi (a collective term that includes yeast and moulds) are also eucaryotic. Well‐known
examples of moulds are Penicillium chrysogenum and Aspergillus niger. As shown in Figure 1.1,
they form a unique branch of life and, despite their superficial appearance, they are not plants.
They do not differentiate to give the root, stem and leaf systems associated with plants. They
also do not produce the green photosynthetic pigment chlorophyll. Their morphology can be
a branching mycelium with differentiating cells producing hyphae to disperse spores or they
can exist as single‐cell forms, commonly referred to as yeast. Yeasts such as Saccharomyces
cerevisiae are very important in food microbiology. The brewing and bakery industries are
dependent upon yeast metabolism of sugars to generate ethanol (and other alcohols) for beer
and wine production, and carbon dioxide for bread manufacture.
Mycotoxicoses are caused by the ingestion of poisonous metabolites (mycotoxins), which
are produced by fungi growing in food (cf. Section 5.4). Aflatoxins are produced by the fungi
Aspergillus flavus and A. parasiticus. There are four main aflatoxins designated B1, B2, G1 and
G2 according to whether they show blue (B) or green (G) fluorescence when viewed under a
UV lamp. Ochratoxins are produced by A. ochraceus and Penicillium viridicatum. Ochratoxin
A is the most potent of these toxins.
The bacteria are procaryotes and are divided into the ‘eubacteria’ (true bacteria) and archaea
organisms according to 16S rDNA analysis, detailed cell composition and metabolism studies.
Curiously, there are no archaea organisms of clinical relevance or of importance in the food
industry. Pyrococcus furiosus (found in hydrothermal vents, growing at 100°C) has been
included in Figure 1.1 only to illustrate the separation of the archaea from eubacteria and
eucaryotes.
As a gross generalisation the size of a rod‐shaped bacterium is about 2 μm × 1 μm × 1 μm.
Nevertheless, despite their size, even 500 cells of Listeria monocytogenes can cause an infection
in a pregnant woman resulting in a stillbirth. Familiar foodborne pathogens such as Salmonella
serovars, Escherichia coli and Campylobacter jejuni are eubacteria that are able to grow at body
temperature (37°C) and in situ produce various toxins that damage human cells resulting in
‘food poisoning’ symptoms such as diarrhoea and vomiting. See Chapter 4 for more information on (eu)bacteria causing food poisoning.
Viruses, such as noroviruses, are very much smaller than bacteria. The large ones, such
as the cowpox virus are about 0.3 μm; the smaller ones, such as the foot and mouth disease
virus, are about 0.1 μm. See Chapter 5 for more information on foodborne viral pathogens.
Because of their small size, viruses pass through bacteriological filters and are invisible
under a light microscope. Bacterial viruses are termed bacteriophages (or ‘phages’). They
can be used to ‘fingerprint’ bacterial isolates, which is useful in epidemiological studies;
this is termed ‘phage typing’. Bacteriophages are the most abundant micro‐organisms on
Earth, and have had a major role in the evolution of bacteria due to their ability to integrate
with host chromosomes, transferring remnant DNA from their previous host. Bacteria
have evolved immune systems against them, called clustered regularly interspaced short
palindromic repeat (CRISPR)‐cas arrays (Section 6.6.3).
Prions (short for ‘proteinaceous infectious particles’) have a very long incubation period
(months, or even years) and resistance to high temperature, formaldehyde and UV irradiation
(see Section 5.4.6 for more details). With regard to sheep and cattle, the isomer of the normal
cellular protein PrPC, termed PrPSC, accumulates in the brain causing holes or plaques. This
leads to the symptoms of scrapie in sheep and bovine spongiform encephalopathy (BSE) in
cattle. The equivalent disease in humans, variant Creutzfeldt–Jakob disease (vCJD), is probably
due to ingestion of the infectious agent from cattle.
6
The microbiology of safe food
1.2 Origins of safe food production
The necessity of eating safe food must go back to early humans. It presumably developed with
the hunter–gatherer lifestyle, where the domestication of animals and cultivation of crops
required cooking and storage activities. For example, barley production flourished in the
Egyptian Nile Valley about 18 000 years ago. This necessitated the preservation of the grain by
keeping it dry to prevent fungal spoilage. Hence reducing the spoilage of more perishable
foods by drying could easily have co‐developed at this time as well. Preservation by the addition of honey and olive oil was another early form of food preparation. Once salt had been
found to have a preservative capability, it became a major commodity. In fact, the word ‘salary’
originally meant ‘soldier’s allowance for the purchase of salt’.
Over time humans learnt to select edible animals and plants. We also learnt how to cultivate
and farm, to harvest and organise our food resources according to the seasons, and habitat.
Undoubtedly there was considerable trial and error, but gradually the beneficial habits were
learnt and passed down through the generations. Numerous religious and cultural practices
related to food have sound scientific basis. This may include not eating pork, which we now
know carries the tapeworm Trichinella spiralis. The use of running water to bathe is more
hygienic than using standing water.
Various common foods require microbial activity. Beer, wine and bread require the
yeast S. cerevisiae to ferment sugars to produce ethanol and carbon dioxide. Coffee and
chocolate production involve the fermentation of naturally occurring bacteria and yeast to
weaken the outer covering as well as produce desirable odours (Ozturk and Young 2017).
There is a considerable industry centred on the metabolism of lactic acid bacteria and
milk (Section 3.7).
The beginning of a more scientific approach to food preparation occurred with the development of food preservation by heat treatment. In 1795, the French government realised the
strategic usefulness of preserved food for its troops and offered a large reward for anyone who
could develop a new method of preserving food. The prize was won by Nicolas Appert, a
Parisian confectioner by trade. His preservation method was putting the food into wide‐mouth
glass bottles, which were then sealed with a cork and put in boiling water for 6 h. The use of
tins cans instead of glass bottles was the idea of Durand in 1810 and is the basis of the canning
industry today. The thermal processing worked, but the rationale behind the procedures was
not known until the work of Louis Pasteur and Robert Koch.
Although previous workers such as Antonie van Leeuwenhoek in 1677 had discovered
‘little heat‐sensitive animalcules’, it was Louis Pasteur who started the science of microbiology. Due to his studies, between 1854 and 1864, he demonstrated that bacteria were the
causative agents of food spoilage and disease. As a consequence the French wine industry
adopted the process of heating the wine to kill the spoilage organisms, before inoculating
with favourable micro‐organisms for the fermentation process. Due to its success, the ‘pasteurisation’ process was then applied to other foods such as milk, although this later application is principally for the control of pathogenic micro‐organisms. Another founding figure
in microbiology was the German Robert Koch, who first developed a method of growing
pure cultures of micro‐organisms. In 1884 he was the first to isolate the bacterium Vibrio
cholerae (Section 4.7). From then on, the isolation and study of pure cultures has been a
major activity for microbiologists.
From those early days, medical, veterinary, environmental and food microbiology have each
become established disciplines in their own right. Food microbiology itself encompasses a
number of topics such as the detection of unwanted micro‐organisms and their products, as
Foodborne infections
7
well as the desirable use of microbial activity in the production of fermented foods such as beer,
wine, cheese and bread. Or, as more simply put in the cliché, ‘the good, the bad and the ugly’,
referring to food production, food poisoning and food spoilage, respectively. Advances continue to be made and the development of HACCP (Section 9.5) was driven by the need for safe
food for the US manned space programme in the 1960s, and was supported by the US army as
well, a modern‐day echo of Nicolas Appert’s contribution to safe food for Napoleon’s troops.
1.3 Overview of foodborne illness
Problems with food quality and safety have existed for many centuries; for example, the adulteration of milk, beer, wine, tea leaves and olive oil. Contaminated food causes one of the major
health problems in the world, and leads to reduced economic productivity. Table 1.1 lists the
pathogens that may be transmitted through contaminated food. Although foodborne illness is
often presumed to mean illness due to eating food containing bacterial pathogens, as Table 1.2
shows, a wide range of organisms, toxins and chemicals can cause foodborne illness. Some
compounds and organisms are external food contaminants, whereas others are intrinsic; for
example, oxalic acid in rhubarb and the alkaloid solanine in potatoes.
Microbial food poisoning is caused by a variety of micro‐organisms with various incubation periods and duration of symptoms (Tables 1.3 and 1.4). Organisms such as
Salmonella and E. coli O157:H7 are well known by the general public, but there are also
viruses and fungal toxins that have been relatively poorly studied and in the future we
may more fully recognise their contribution to the general incidence of food poisoning.
Micro‐organisms causing food poisoning are found in a diverse range of foods including
milk, meat and eggs. They have a wide range of virulence factors that can cause a range
of adverse responses, which may be acute, chronic or intermittent. Some bacterial pathogens, such as Salmonella spp., are invasive and can get through the intestinal wall into the
bloodstream and cause generalised systemic infections. Other pathogens produce toxins
in the food prior to ingestion, or during infection, and cause severe damage in susceptible organs, such as the kidney as in the case of E. coli O157:H7 infection. Complications
can occur due to immune‐mediated reactions (i.e. Campylobacter infection leading to
reactive arthritis and Guillain–Barré syndrome) where the host immune response to the
pathogen is unfortunately also directed against the host’s tissues. Therefore, foodborne
illness can be much more severe than a short period of gastroenteritis, and instead may
result in hospitalisation. The severity can be such there may be residual (chronic) symptoms and even the risk of death, especially in the elderly and severely immunocompromised. Hence there is a considerable public health burden attributable to foodborne
infections, which is being increasing recognised as causing considerable economic loss.
Estimates of costs of foodborne illness have been made and will be considered in detail
later (Section 1.11).
Because the consumer is unaware that there is a potential problem with the food, a significant amount of contaminated food is ingested and hence they become ill. Consequently it is
hard to trace which food was the original cause of food poisoning since the consumer will not
recall noticing anything relevant in their recent meals. They are likely to recall food that smelt
‘off ’ or looked ‘discoloured’. However these attributes are related to food spoilage and not food
poisoning.
Food poisoning micro‐organisms are normally divided into two groups:
• Infections; for example, Salmonella serovars, C. jejuni and pathogenic E. coli.
• Intoxications; for example, Bacillus cereus, Staphylococcus aureus and Clostridium botulinum.
Table 1.2 Sources of foodborne pathogens.
Food
Pathogen
Meat, poultry and eggs
Arcobacter species
Campylobacter jejuni
Salmonella serovars
Staphylococcus aureusa
Fruit and vegetables
Clostridium perfringensb
Clostridium botulinum
Escherichia coli O157:H7
Bacillus cereusb
Listeria monocytogenes
Yersinia enterocolitica
Hepatitis A virus
Trichinella spiralis
Tapeworms
C. jejuni
Salmonella serovars
St. aureusa
L. monocytogenes
Milk and dairy products
Powdered infant formula
Shellfish and fin fish
Shigella spp.
E. coli O157:H7
Y. enterocolitica
Aeromonas hydrophila
Hepatitis A virus
Norovirus
Giardia lamblia
Cryptosporidium species
Cl. botulinum
B. cereusb
Mycotoxins
Salmonella serovars
Y. enterocolitica
L. monocytogenes
E. coli
C. jejuni
Shigella species
Hepatitis A virus
Norovirus
St. aureusa
Cl. perfringensb
B. cereusb
Mycotoxins
Salmonella serovars,
Cronobacter species
Salmonella serovars
Vibrio species
Shigella species
Y. enterocolitica
B. cereus
E. coli
Incidence (%)
Raw chicken and turkey (45–64)
Raw poultry (40–100), pork (3–20), eggs
(0.1%) and shellfish (16)
Raw chicken (73), pork (13–33)
and beef (16)
Raw pork and chicken (39–45)
Raw beef, pork and poultry
Raw ground beef (43–63), cooked meat (22)
Red meat (75), ground beef (95)
Raw pork (48–49)
Mushrooms (2)
Artichoke (12), cabbage (17), fennel (72),
spinach (5)
Lettuce (14), parsley (8), radish (37)
Potatoes (27), radishes (37), bean sprouts
(85), cabbage (2), cucumber (80)
Celery (18) and coriander (20)
Vegetables (46)
Broccoli (31)
Milk (48–49)
Soft cheese and pâté (4–5)
Pasteurised milk (2–35), milk powder
(15–75) cream (5–11), ice cream (20–35)
Raw seafood (33–46)
Fish products (4–9)
(Continued )
Foodborne infections
9
Table 1.2 (Continued)
Food
Cereals, grains, legumes and nuts
Spices
Water
Pathogen
Cl. botulinumb
Hepatitis A virus
Norovirus
Giardia lamblia
Cryptosporidium spp.
Metabolic byproducts
Algal toxins
Salmonella serovars
L. monocytogenes
Shigella species
E. coli
St. aureusa
Cl. botulinumb
B. cereusb
Mycotoxinsa
Salmonella serovars
St. aureusa
Cl. perfringensb
Cl. botulinumb
B. cereusb
G. lamblia
Vibrio cholerae
Cronobacter species
Incidence (%)
Raw barley (62–100), boiled rice (10–93),
fried rice (12–86)
Herbs and spices (10–75)
Water (30)
Toxin not destroyed by pasteurisation.
Spore‐forming organism. Not killed by pasteurisation.
Source: Various including Synder (Hospitality Institute of Technology and Management, web address in the
Internet directory) and ICMSF (1998a).
a
b
The first group are bacteria that multiply in the human intestinal tract, whereas the second
group are bacteria that produce toxins either in the food or during passage in the intestinal
tract. As a generalisation, bacterial infections cause gastroenteritis, whereas the ingestion of a
toxin causes vomiting. This division is also very useful to help recognise the routes of food
poisoning, since bacterial infection will be due to something ingested in the previous 18–24 h,
whereas vomiting is likely to be due to preformed toxin ingested in the past few hours.
Gastroenteritis with a fever could be due to a Gram‐negative infectious organism, as the host’s
immune system responds to the bacterial outer surface, which will be composed of lipopolysaccharide. This compound can be very pyrogenic in some Gram‐negative bacteria, therefore
causing the symptom of a fever. Viral infections cause both vomiting and gastroenteritis.
Vegetative organisms are killed by heat treatment, whereas spores (produced by B. cereus and
Clostridium perfringens) may survive and hence germinate if the food is not kept sufficiently
hot or cold.
An alternative grouping is according to severity of illness. This approach is useful in setting
microbiological criteria (sampling plans) and risk analysis. The International Commission
on Microbiological Specifications for Foods (ICMSF 1974 and 2002) divided the common
10
The microbiology of safe food
Table 1.3 Incubation period and duration of common food poisoning micro‐organisms.
Micro‐organism
Incubation period
Duration of illness
Aeromonas species
Bacillus cereus emetic
diarrhoeal
Campylobacter jejuni
Clostridium botulinum
Clostridium perfringens
Escherichia coli
ETEC
EPEC
EIEC
EHEC
Hepatitis A
Listeria monocytogenes
Norovirus
Rotavirus
Salmonella serovars
Shigellae
Staphylococcus aureus
Vibrio cholerae
Vibrio parahaemolyticus
Yersinia enterocolitica
Unknown
0.5–6 hours
8–24 hours
3–5 days
12–36 hours
8–12 hours
1–7 days
1 day
1 day
2–10 days
2 h–14 days
1–14 days
16–72 hours
16–48 hours
16–48 hours
72–120 hours
3–60 days
3–70 days
24–48 hours
24–72 hours
16–72 hours
16–72 hours
Few hours
6 hours – 3 days
4–96 hours
3–7 days
3–5 days
2–7 days
2–7 days
2–12 days
2–4 weeks
Variable
1–3 days
4–6 days
2–7 days
2–7 days
2–3 days
1–6 days
3 days
1–3 weeks
foodborne pathogens into such groups in order to aid in the decision making of sampling
plans. These ICMSF groupings are given later in Chapter 7. Detailed descriptions of certain
foodborne pathogens are given in Chapters 4 and 5, and extensive details can be found in the
numerous ICMSF publications listed in the References section.
Despite an increasing awareness and understanding of food and waterborne micro‐
organisms, these diseases remain a significant problem and are an important cause of reduced
economic productivity. While everyone is susceptible to foodborne diseases, there is a growing
number of people within the general population who are more likely to experience such diseases, often with more severe consequences. These people include infants and young children,
pregnant women, those who are immunocompromised through medication or illness and the
elderly. There is evidence that the microbial causes of gastroenteritis vary with age and that viral
agents are probably the major infectious agent in children under 4 years (Figure 1.2). There is
also a difference between the sexes (Figure 1.3), which is possibly due to differences in personal
hygiene, i.e. males have a lower tendency to wash their hands after going to the toilet.
The production of food has increased by 145% since the 1960s. Of particular importance is
the increase in developing countries such as Africa (140%), Latin America (200%) and Asia
(280%). Food production has doubled in the USA, and by 68% in Western Europe. Yet hunger
is still a worldwide problem. In this century there are over 800 million people suffering from
malnutrition. Over the same time period, the world’s population has increased from 3 to 6 billion, and is expected to attain 9 billion by 2050. Subsequently there will be ever‐increasing
demands in food production and food security.
In developing countries, foodborne diseases are a major (up to 70%) cause of diarrhoea in
children under 5 years of age. They may suffer two or three episodes of diarrhoea per year, and
for some this may even be as many as 10. Pathogenic bacteria can contaminate weaning foods
Foodborne infections
11
Table 1.4 Usual incubation and onset period for foodborne illness.
Incubation period
Agent
Symptoms
Chemical allergen
Heavy metal: copper,
tin, lead, zinc
Nausea, vomiting
Fish toxins: PSP,
ciguatera and soon
Gastrointestinal and
neurological symptoms
Monosodium
glutamate
Burning sensation on body,
tingling, dizziness, headache,
nausea
Food allergens: nuts,
eggs, milk, wheat
Anaphylactic shocks. Respiratory
failure, rashes, nausea, vomiting
Bacillus cereus, emetic
Nausea, vomiting, abdominal
pain
Nausea, vomiting, abdominal
pain
Abdominal pain, watery
diarrhoea
Abdominal pain, watery
diarrhoea
Abdominal pain, diarrhoea,
chills, fever, nausea, vomiting,
loss of appetite
Vertigo, blurred vision, difficulty
in speaking, progressive nervous
system failure and paralysis
Sore throat, fever, nausea,
vomiting, rhinorrhoea,
tonsillitis, may be rash
Profuse watery diarrhoea, feer,
chills, headache
S. aureus
Bacillus cereus,
diarrhoeal
Clostridium perfringens
Salmonella serovars
Clostridium botulinum
Streptococcus Group A
Vibrio
parahaemolyticus
<2 hours
2–7 hours
8–14 hours
8–24 hours
Duration (days)
1–2 days
1–7 days
Other
<1
>1
(Continued )
12
The microbiology of safe food
Table 1.4 (Continued)
Incubation period
Agent
Symptoms
Yersinia enterocolitica
May resemble appendicitis.
Gastroenteritis with diarrhoea,
and/or vomiting, fever and
abdominal pain are common.
Profuse watery diarrhoea and
dehydration
Abdominal pain, diarrhoea,
stools may contain mucus and
blood
Infant bacteraemia, septicaemia,
necrotising enterocolitis,
meningitis
Abdominal pain, diarrhoea,
headache, fever, nausea,
vomiting, loss of appetite
Watery diarrhoea, with
frequent, sometimes explosive,
bowel movements.
Abdominal pain, diarrhoea,
stools may contain mucus and
blood. Fever may be present
Nausea, vomiting, diarrhoea,
abdominal pain, myalgia,
headache, malaise
Fever, headache, nausea,
vomiting, diarrhoea, still births,
neonatal meningitis,
Malaise, anorexia, nausea,
abdominal pain, jaundice, dark
urine, light-coloured stools
Vibrio cholerae
Shigella species
Cronobacter species
Campylobacter
Cyclospora
cayetanensis
Pathogenic E. coli
Norovirus
Listeria monocytogenes
Hepatitis A
<2 hours
2–7 hours
8–14 hours
8–24 hours
Duration (days)
1–2 days
1–7 days
Other
1 week
<1
>1
Few days
to a
month
Days to
weeks
15–50
days
Weeks
Foodborne infections
13
Percentage of stools positive
25
20
<1
15
1–4
5–14
15–74
>74
10
5
0
Campylobacter
spp.
Salmonella
spp.
Rotavirus
SRSV and
calicivirus
Figure 1.2 Variation in causative agent of gastroenteritis with age. Source: Forsythe (2000).
70
60
Percentage
50
Male
40
Female
30
20
10
0
All
ages
0–4
5–14
15–24
25–44
45–64
65+
Figure 1.3 Variation in gastroenteritis with sex. Source: Forsythe (2000).
via the food or water supply, causing 25–30% of diarrhoeal infections. The repeated periods of
diarrhoeal disease will have serious detrimental effects. The child’s nutritional status and
immune systems will be impaired due to reduced food intake, malabsorption of nutrients and
vomiting. In addition they will be more susceptible to other infections. Sadly, this cycle of
infection results in about 13 million children under the age of 5 dying each year. Rotavirus
(principally transmitted via the oral–faecal route) is one of the worst infectious organisms and
kills up to 15 000–30 000 children/year in Bangladesh and one in 200–250 Indian children
before they are 5 years old.
Quested et al. (2010) examined how anticipated trends would impact on food safety. The
anticipated drivers for an increase in foodborne disease in the future are predicted to be the
increasing world population, doubling of demand for food and the international trade in food,
14
The microbiology of safe food
along with the consumption of high‐value food commodities (meat, poultry, fresh produce)
rather than convenience foods. In order to reduce the foodborne disease burden it will
require intergovernmental organisations using rapid detection techniques, along with effective
control measures.
By the year 2025 more than 1000 million of the world population will be aged over 60, and
more than two‐thirds of them will live in developing countries. Growing old means increased
risk from foodborne diseases. It is not surprising then that in some countries, one person in
four is especially at risk of foodborne disease.
The exact number of annual foodborne illnesses can only be estimated. In many instances, only
a small proportion of cases seek medical help and not all are investigated. Even where a country
has a reporting infrastructure, only a small proportion of the foodborne‐related cases are reported
to the authorities. In the past it had been assumed that in industrialised countries less than 10% of
the cases were reported, while in developing countries reported cases probably account for less
than 1% of the total. However a better estimate was achieved using sentinel studies as first reported
for USA, and the UK. In the USA, Mead et al. (1999) estimated that 76 million cases of foodborne
diseases might be occurring each year, resulting in 325 000 hospitalisations and 5000 deaths. The
two UK infectious intestinal disease studies similarly estimated that the proportion of the public
experiencing gastroenteritis due to foodborne pathogens was 20% each year and maybe up to 20
people per million died (Wheeler et al. 1999).
Since food poisoning symptoms are generally mild and only last a few days, the person usually recovers without seeking medical care. Nevertheless those at higher risk, such as the very
young, pregnant and elderly may suffer more serious, debilitating even life‐threatening illness.
These have previously been largely overlooked in determinations of the human burden of food
poisoning.
1.4 Public perception of safe food
The increasing number and severity of food poisoning outbreaks worldwide have considerably
increased public awareness concerning food safety. Public concern regarding the safety of the
food they eat was considerably raised due to highly publicised issues such as food irradiation,
BSE, E. coli O157:H7 and genetically modified foods.
The question of ‘What is safe food?’ invokes different answers depending upon who is being
asked. Essentially the different responses depend upon what is perceived as a significant risk.
The general public might consider that ‘safe food’ means zero risk, whereas the food manufacturer would consider ‘What is an acceptable risk?’. The opinion expressed in this book is that
zero risk is not feasible given the range of food products available, the complexity of the distribution chain and human nature. Nevertheless the risks of food poisoning should be reduced
during food manufacture and preparation to an ‘acceptable risk’. Unfortunately there is no
public consensus on what constitutes an acceptable risk, and the general public (rightly or
wrongly) often feels it is not informed of relevant food risks. Table 1.5 shows the possible
causes of death in the next 12 months. Many of these risks are acceptable to the general public:
people continue to drive cars and cross the road. This table can be compared with Tables 1.6
and 1.7, which give the USA and UK data on the chances of food poisoning. The USA data
indicate that each year 0.1% of the population will be hospitalised due to food poisoning. Food
scares cause public outcries and can give the industry an undeserved bad reputation. Whereas,
in fact, the majority of the food industry has a good safety record and is in the business to stay
in business, not to go bankrupt due to adverse publicity.
Foodborne infections
15
Table 1.5 Risk of death during the next 12 months.
Cause
Mortality, chance of 1 in
Smoking 10 cigarettes a day
Natural causes, middle‐aged
Death through influenza
Dying in a road accident
Flying
Pedestrian struck by car
Food poisoning
Dying in a domestic accident
Being murdered
Death in a railway accident
Electrocution
Struck by lightning
200
850
5000
8000
20 000
24 000
25 000
26 000
100 000
500 000
200 000
10 000 000
Public concerns on food related issues vary between countries and change with time. Prior
to the 1990s, food additives were the focus of attention. Then in the 1990s the public became
more aware of foodborne pathogens such as Salmonella, and in the late 1990s the cause for
concern became the link between ‘mad cow disease’ and variant CJD, and also (particularly in
Europe) food biotechnology (Brown et al. 2001). More recently there have been serious cases
of food adulteration and fraudulence. A serious example in 2008 was the addition of melamine
to powdered infant formula to increase apparent protein‐nitrogen content, which also caused
severe brain damage to the infant. Adverse public attention to a specific food sector can lead to
considerable distrust. This caution has been reinforced by numerous publicised instances of
food poisoning or ‘food scares’ that have cost the food industry considerable sums of money
(see Table 1.8).
Although the food industry needs to produce food that is safe to eat, it must also manufacture
food that is of the quality expected by the consumer. However, as previously stated, ‘safe food’ is
an arbitrary term, meaning different things to different people and does not necessarily equate
with ‘zero risk’. Hence risk management and risk communication are important to the food
industry, and are defined in Chapter 10. The ‘zero risk’ approach is not feasible; for example, the
control of a foodborne pathogen requires the use of preservatives (with perceived toxicological
risks) or heat treatment (with the possible production of carcinogens). The concept of a ‘threshold’ means that there exists a limit under which the risk is non‐existent or negligible. In medical
(and consequently food) microbiology, the ‘minimal infectious dose’ has been the threshold.
However, this approach has been re‐evaluated in microbiological risk assessment to estimate
the probability of infection (Pi) by a single cell (Chapter 10; Vose 1998).
Novel foods and alternative methods of processing are being developed. Each new development needs to be considered for possible consequences, whether intentional or not, within
the food chain. Some of these technologies will reduce or eliminate microbial hazards,
whereas others might lead to the emergence of a new pathogen. In the application of HACCP
to a novel process, the hazard analysis needs to be broad enough to consider the associated
microbes, as well as the intrinsic and extrinsic conditions that affect microbial growth and
toxin production. There is an increased market in ‘organic’ foods. This is partially linked to
consumer’s perception of their greater nutritional content and that they are a safer alternative
16
The microbiology of safe food
Table 1.6 Risk of food poisoning in the UK.
Community
Bacteria
Aeromonas spp.
Bacillus spp. (>104/g)
Campylobacter spp.
Clostridium difficile
cytotoxin
Clostridium perfringens
enterotoxin
Escherichia coli O157
E. coli DNA probes
Attaching and
effacing
Diffusely adherent
Enteroaggregative
Enteroinvasive
Enteropathogenic
Enterotoxigenic
Verocytotoxigenic
(non‐O157)
Salmonella spp.
Shigella spp.
Staphylococcus aureus
(>106/g)
Vibrio spp.
Yersinia spp.
Protozoa
Cryptosporidium parvum
Giardia intestinalis
Viruses
Adenovirus group F
Astrovirus
Calicivirus
Rotavirus group A
Rotavirus group C
Norovirus
No organism identified
Total
General practice
Number
of casesa
Rate/1000
person years
Number
of cases
Rate/1000
person years
Number of community
cases/GP cases
46
0
32
6
12.4
0
8.7
1.6
165
4
354
17
1.88
0.05
4.14
0.20
9
2.4
114
1.30
0
0
3
0.03
20
5.4
119
1.32
4.1
23
18
0
1
10
3
6.2
4.9
0
0.27
2.7
0.82
103
141
0
4
52
6
1.18
1.62
0
0.05
0.59
0.06
5.3
3.0
8
1
1
2.2
0.27
0.27
146
23
10
1.57
0.27
0.11
1.4
1.0
2.5
0
25
0
6.8
1
51
0.01
0.58
–
11.7
3
2
0.81
0.54
39
28
0.43
0.28
1.9
1.9
11
14
8
26
2
46
432
781
3.0
3.8
2.2
7.1
0.54
12.5
117.3
194
81
77
40
208
6
169
1305
8770b
0.88
0.86
0.43
2.30
0.06
1.99
14.82
33.1
3.4
4.4
5.1
3.1
8.9
6.3
7.9
5.8
6.7
–
2.1
8.0
1.9
–
–
5.4
4.6
13.4
Excluding cases where individual follow‐up was not known.
Total cases are greater than the sum of individual organisms due to cases for which a stool sample was not
sent for testing. The general practice total includes cases from the enumeration arm, for which full stool testing
was not carried out.
Source: Reproduced from Wheeler et al. (1999), with permission from BMJ Publishing Group Ltd.
a
b
Foodborne infections
17
to conventional produce, which is not necessarily true. Cow manure can contain Salmonella
and E. coli O157:H7, and there have been outbreaks linked with organically grown produce.
Industry and national regulators strive for production and processing systems which ensure
that all food is ‘safe and wholesome’, although complete freedom from risks is an unattainable
goal. Safety and wholesomeness are related to a level of risk that society regards as reasonable
in the context, and in comparison with other risks in everyday life. Putting food poisoning into
context is not an easy task due to the high level of publicity that it receives in some countries.
One can see in Table 1.5 that the risk of death due to food poisoning is nearly equivalent to the
risk of being a pedestrian who is struck by a car. However, such tragic incidences affect individuals and generally only reach the local newspaper headlines, whereas food poisoning outbreaks involving a large number of people are more ‘significant’ to the media.
A reported increase in the number of ‘food poisoning cases’ is commonly cited by the media.
However, these trends must be regarded with caution since they are the number of gastroenteritis cases that have been investigated and the causative organism identified. Not all gastroenteritis cases may be due to food vectors, and an increase in public awareness can increase the
number of members of the general public seeking medical help. Sometimes referred to as the
‘worried well’, this can put a strain on the medical profession and distract from investigating
the real cases. In addition improved detection methods could ‘increase’ the apparent number
of identified cases over time. In fact, across Europe and the United States the number of
reported gastroenteritis cases has been decreasing. In 2005, the Centers for Disease Control
and Prevention (CDC) reported that the most common diseases associated with foodborne
pathogens, parasites and other bacteria were on the decline, or at least not increasing in incidence. Escherichia coli O157:H7 infections decreased by 36% in just 1 year. Similarly, the number of Campylobacter, Salmonella, Yersinia and Cryptosporidium infections declined by 28, 17,
51 and 49%, respectively, in the 8‐year surveillance period. However, this trend did not significantly change in the following 3 years (FoodNet 2009), but did decline thereafter (Imanishi
et al. 2014). In 2009, the number of reported foodborne disease outbreaks declined 32% compared with the mean of 2004–2008, and was below the pre‐2009 average during 2010–2012.
The decline was mainly in norovirus‐related outbreaks.
Figure 1.4 shows the 20‐year trends in Campylobacter and Salmonella cases in England
and Wales; note the decline in Salmonella cases since 1997. As given in Section 1.3, sentinel
studies indicate a more informed incidence of gastroenteritis may be ~20%, though its mild
nature means the illness is unnoticed and hence unreported. Possibly due to changes in
eating habits there is a marked seasonality in food poisoning incidences with pathogens
such as Salmonella and Campylobacter. Figure 1.5 show the peak incidence over the summer months. Typically, Campylobacter infections peak a month or two before Salmonella
serovars do.
1.5 Causes of foodborne illness
There are a number of factors that contribute to food being unsafe and causing illness
(Table 1.9).
The principal causes can be summarised as:
• inadequate control of temperature during cooking, cooling and storage;
• inadequate personal hygiene;
• cross‐contamination of raw and processed products;
• inadequate monitoring of processes.
18
The microbiology of safe food
60 000
Number of reports
50 000
40 000
30 000
20 000
10 000
0
1980
1985
Campylobacter
1990
1995
S. Typhimurium
2000
S. Enteritidis
2005
Other Salmonella
Figure 1.4 Twenty‐year trend in Campylobacter and Salmonella reported cases for England and Wales. Source:
Data source hpa website.
5000
4500
Number of reports
4000
3500
3000
2500
2000
1500
1000
500
0
2
4
2006
6
8
10
12
2
4
6
Four-week period
Campylobacter
8
10
12
2007
Salmonella
Figure 1.5 Example of seasonal trends in reported cases of Salmonella and Campylobacter enteric infections in
England and Wales. Source: Data source hpa site.
Foodborne infections
19
These contributing factors can be considerably reduced by adequate training of staff, implementation of HACCP combined with risk assessment (Chapters 9 and 10). As Chapter 9 will
explain, it is now widely accepted that it is inadequate to rely on testing the final end product
for the presence of micro‐organisms and as a means of controlling the hygienic status of the
process.
The World Health Organisation (WHO) summarises safe food in the ‘Five keys to safer
food’:
1 keep clean;
2 separate raw and cooked;
3 cook thoroughly;
4 keep food at safe temperatures;
5 use safe water and raw materials.
The key to the production of safe food is producing food that is microbiologically stable. In
other words, any intrinsic microbes are unable to multiply to an infectious dose, ideally they
die off and their toxins are absent. In the case of foodborne viruses, they do not multiply in
foods and therefore it is essential to avoid initial contamination from sources such as water and
infected food handlers.
Essentially the cooking and cooling temperature profile should be aimed at:
1 Reducing the number of infectious organisms by 6 log orders (i.e. 106 cells/g to 1 cells/g).
2 Not providing suitable conditions for the outgrowth of microbial spores that survive
cooking.
3 Avoiding conditions that enable bacteria such as St. aureus to produce heat‐stable toxins. By
definition these toxins are resistant to 100°C for 30 minutes and hence are not destroyed by
cooking before eating the food.
Cross‐contamination causes post‐processing (i.e. after the cooking step) contamination of the
food. This can be avoided through:
1 Careful design of the factory layout.
2 Control of personnel movement.
3 Good personal hygiene habits.
Foods that do not undergo a cooking process are normally acidified (i.e. fermented foods) and
stored under chilled conditions. These practices rely upon the pH and temperature of the food
stopping microbial growth. The growth range of the major food poisoning organisms has been
documented (see ICMSF 1996a for details). Hence the pH and storage temperature of the food
that will restrict the growth of foodborne pathogens can be predicted.
Although contamination of food can occur at any point from farm to table, restaurant food
workers are a common source of foodborne illness. Angelo et al. (2017) analysed the characteristics of restaurant‐associated foodborne disease outbreaks and, in particular, the role of
food workers by analysing outbreaks associated with restaurants from 1998 to 2013, as reported
to the CDC. In total there were 9788 restaurant‐associated outbreaks, and most outbreaks
(79%) were reported at sit‐down establishments. The median annual number of outbreaks was
620. Food workers contributed to 2415 (25%) outbreaks. The most commonly reported contributing factors were those related to food handling and preparation practices in the restaurant (2955 outbreaks, 61%). Norovirus caused the largest number of outbreaks (1425/3072,
46%) for which a single confirmed aetiology was reported. Fish (254 outbreaks, 34%) was most
commonly implicated when the outbreak was attributed to a single food and a confirmed aetiology. These outbreaks were commonly caused by scombroid toxin (219 outbreaks, 86% of fish
outbreaks).
20
The microbiology of safe food
1.6 Food poisoning due to common food commodities
1.6.1 Milk and milk products
Milk and milk products used to be a major cause of morbidity and mortality before the
introduction of the pasteurisation process in the 1930s. Those who drank raw milk before then
were at risk of typhoid fever, scarlet fever and tuberculosis. Nevertheless milk and milk products can still be the cause of foodborne disease, albeit a small proportion (1–2%) of the total
number of cases.
Zoonoses, which have been transmitted to humans through unpasteurised milk, include
brucellosis, infections by pathogenic strains of E. coli (including E. coli O157:H7), leptospirosis,
listeriosis, paratyphoid fever, salmonellosis, staphylococcal enterotoxic gastroenteritis, streptococcal infections, tuberculosis, foot and mouth disease, tickborne encephalitis, Q‐fever and toxoplasmosis. The sources of pathogenic bacteria can be the cows, environmental sources and those
involved with the milk handling operations from the farm to food service facilities. The cows can
transmit pathogens through their udders, skin and through faecal contamination. Many of these
organisms are killed by pasteurisation, but post‐pasteurisation contamination has been reported
for Salmonella serovars, L. monocytogenes, Cl. botulinum, Cl. perfringens and St. aureus, as well as
viruses (adenoviruses, enteroviruses, hepatitis A) and protozoa (amoebiasis, giardiasis). Any
subsequent temperature abuse enables the bacteria and protozoa to multiply.
There are various heat treatments used to reduce the microbial load (especially pathogens)
to a level at which they should not be a significant health hazard. The commonly used ones are
thermisation, pasteurisation, ultra‐high temperature treatment (UHT) and sterilisation.
Pasteurisation is intended to inactivate pathogenic vegetative cells. The destruction of spoilage
organisms is often another benefit of pasteurisation, but is not the focus of milk safety
programmes.
1.6.2 Meat products
Meat (beef, pork, poultry, lamb) consumption worldwide is in the order of 41 kg per person.
Poultry consumption in particular is increasing and is ~14 kg per person per year. The largest consumer groups of poultry are in the developed Western countries, with the US being
the largest consumers at ~50 kg per person per year. The importance of microbial safety of
meat products is therefore considerable. Despite advances in animal husbandry, food processing and awareness of good hygienic practices, meat products are still a major source of
foodborne infections. Foodborne bacterial pathogens on meat products may be able to grow
if stored at temperatures >8°C. The pathogens may originate from the intestinal tract of the
animal during slaughter, from the processing environment, as well as from human contact
prior to ingestion. The most prolific causes of food poisoning, Salmonella, pathogenic E. coli
(i.e. E. coli O157:H7) and Campylobacter, are most frequently through the ingestion of
contaminated meat products.
1.6.3 Fresh produce
Eating fresh fruit and vegetables is encouraged as part of a healthy lifestyle. Unfortunately
since a large proportion of them are consumed raw, there have been a significant number of
foodborne outbreaks (Lynch et al. 2009; Olaimat and Holley 2012). In the US between 1996
and 2016, there were 46 reported food poisoning outbreaks linked to sprouts, with a total of
2474 illnesses, 187 hospitalisations and three deaths. The large 2011 E. coli O104:H4 outbreak
Foodborne infections
21
from sprouted fenugreek seeds in Germany and France illustrates the relevance of the consumption of these products with respect to food safety issues (Section 14.4.2). The globalisation of the food trade can further increase the risk, if produce comes from countries with lower
safety standards.
A study of reported foodborne outbreaks over 8 years (2004–2012) associated with fresh
fruit and vegetable consumption in the United States and European Union (EU) showed norovirus and Salmonella serovars were responsible for ~75% of outbreaks; 294/377 in the USA and
148/197 in the EU. Norovirus was responsible for 59 and 55% of outbreaks in the USA and the
EU, respectively, whereas the figures for Salmonella serovars were 19 and 20%, respectively.
Norovirus was mainly linked with salad‐related outbreaks in the USA and with berries in the
EU, while Salmonella serovars were the causative agent for the majority of sprout‐associated
outbreaks.
1.6.4 Low‐water activity (aw) and low‐moisture foods
Low‐water activity (aw) foods and low‐moisture foods are not exactly the same, the latter being
generally described as ‘dry food’. Some foods are not low in moisture (i.e. water content) but
have a low aw due to water‐binding solutes (such as sodium chloride) that bind the available
water, subsequently lowering the aw (see Section 2.8.2). Common examples of water‐binding
solutes in food products are sodium chloride (salt) and sucrose (sugar), which has a water‐
binding ability 6× greater than sodium chloride. Low‐water activity and low‐moisture foods
have aw values of <0.70.
In the past low‐moisture and low‐water activity foods were considered microbiologically
safe as the low amount of free water was considered to be a significant barrier to the growth of
human foodborne pathogenic bacteria. Nevertheless, a number of low‐moisture foods have in
recent years been associated with food product recalls and foodborne outbreaks. This was due
to contamination by human and zoonotic foodborne pathogens, such as Salmonella serovars,
L. monocytogenes, Cronobacter species, B. cereus, Cl. botulinum, C. jejuni, Vibrio species,
Yersinia species, Shigella species, pathogenic variants of E. coli (i.e. E. coli O157:H7) and St.
aureus. Examples of foods causing such outbreaks include an outbreak in 2008 due to flour
(cookie dough) leading to 67 cases and 12 hospitalisations, and two peanut butter or paste
outbreaks between 2006 and 2009, with over 1400 cases in 48 US states and Canada (Sections
4.3.7 and 4.4.7). Other low‐moisture foods that have been implicated in foodborne illness outbreaks include infant formula, milk powder, chocolate, cocoa, coconut, peanuts and breakfast
cereals (Sections 14.4.5 and 14.4.6; Cahill et al. 2008; Neil et al. 2012; Jourdan‐da Silva et al.
2018). Such outbreaks have been increasingly reported possibly due to the development
of sensitive detection methods, as well improved surveillance systems and epidemiological
advancements (Sánchez‐Maldonado et al. 2018).
Contrary to what was commonly presumed, some foodborne bacterial pathogens are able
to persist in a dehydrated/desiccated state for extended periods of time. These products can
be contaminated with foodborne pathogens such as Salmonella serovars and Cronobacter
species, which can persist for long periods of desiccation and grow following reconstitution.
Under such conditions there may actually be some cross‐resistance induced to other stress
such as heat, which therefore increases their resistance to subsequent inactivation interventions or decontamination treatments, such as thermal pasteurisation. Hence these products
can no longer be considered inherently safe simply because the pathogen does not grow
during storage.
22
The microbiology of safe food
1.7 Host‐related issues
The days of food being produced, processed, distributed and consumed locally have significantly decreased in recent decades. The regional, national and global food chain has required
parallel changes in food science and technology, including preservation. At the same time
there have been social changes, with an increasing number of meals being consumed outside
of the home environment and also by an ageing population. Public exposure to a foodborne
pathogen may change due to changes in the processing (i.e. BSE exposure in 1980s), changes
in consumption patterns and the globalisation of the food supply chain. Many ‘risk factors’
influence the host susceptibility to infection. These may be:
• pathogen‐related – ingested dose, virulence;
• host‐related – age, immune status, personal hygiene, genetic susceptibility;
• diet‐related – nutritional deficiencies, ingestion of fatty or highly buffered foods.
The consumer demand for less processed foods and fewer additives means that food processors have less choice in their preservation method. However, since the consumer also expects
a long shelf life, this can lead to problems with psychrotrophic pathogenic bacteria, such as
Listeria, Yersinia and Aeromonas (cf. sous vide). Hence food processors are investigating new
processing and preservation techniques: high pressure, ohmic eating and pulsed electric field
(PEF) (Section 3.5.4).
Eating away from home is a major trend of recent years. Many of these meals require extensive food handling and/or cold foods that are not cooked before consumption. Subsequently,
this leads to an increase in the number of people handling food and hence the potential
increased transmission of foodborne diseases from food handlers to consumers. It is plausible
that since the individual spends less time in daily home food preparation, they have less knowledge regarding safe food preparation. Several studies have documented an increasing lack of
knowledge about safe home food preparation or preservation practices, such as personal or
utensil hygiene and correct temperature storage.
The immune system may be partially compromised or undeveloped in newborn babies, the
very young, pregnant women, those on medication or with an underlying illness and the
elderly. The health effects of foodborne infections and case fatality rates are up to 10 times
greater in this part of the population. Young children are more likely than adults to develop
illnesses from selected pathogens (Figure 1.2). Socio‐economic factors affect vulnerability. For
example, in developed countries the case fatality rate for typhoid is higher amongst individuals
55 years or older. In contrast, in developing countries, the higher risks of complication and
death are for children from birth to 1 year of age and adults over 31.
Women during pregnancy have a suppressed immune system to reduce the chance of rejection of the foetus. Consequently pregnant women have a greater risk of food poisoning due to
L. monocytogenes than the general population. Infection of the foetus or newborn baby passed
on from an infected mother can be extremely severe, resulting in abortion, stillbirth or a critically ill baby that may present with an early onset (mortality rate 15–50%) or late onset (mortality rate 10–20%) form of listeriosis (Radoshevich and Cossart 2018). Neonates are uniquely
susceptible to enterovirus infections such as coxsackie B and echovirus infections.
Infections in the immunocompromised (non‐pregnant) host constitute a severe aspect of
the food safety problem. Advances in medical treatment have resulted in an increased number
of immunosuppressed patients (e.g. cancer cases, organ transplants), and patients with serious
underlying chronic diseases who may have an increased risk from foodborne infection and/or
develop more severe illness. Obviously enteric pathogens can easily cause persistent and
Foodborne infections
23
generalised infection in the immunocompromised host. The majority of AIDS patients
(50–90%) suffer from chronic diarrhoeal diseases, which can be fatal.
The proportion of elderly people in the population is increasing. It has been projected that
in the USA one‐fifth of the population will be over the age of 65 by the year 2030. The increased
susceptibility of the elderly may be due to a number of physiological factors, such as the senescence of the gut‐associated lymphoid tissue and/or the decrease in gastric acid secretion, thus
reducing the natural barriers to gastrointestinal pathogens. Also, the immune system of the
elderly is often weakened due to chronic illnesses. The incidence of salmonellosis,
Campylobacter enteritis or E. coli O157:H7 appears to be higher in the elderly. Epidemiological
studies have shown that the elderly experience higher case fatality rates than the general population. For example, 3.8% vs. 0.1% for Salmonella; 11.8% vs. 0.2% for E. coli O157:H7; and 1%
vs. 0.01% for rotavirus (Gerba et al. 1996).
On a global scale, probably the leading cause of increased host susceptibility to foodborne
infections is malnutrition. In developing countries malnutrition affects about 800 million people. The region with the largest absolute number affected is Asia (524 million) and the region
with the largest population affected is Africa (28%). In some individual countries, the percentage can be as high as 30%. Malnutrition increases host susceptibility to foodborne infections
since it reduces the integrity of the intestinal epithelium and cell‐mediated immunity.
Malnutrition results in a 30‐fold increase in the risk of diarrhoea‐associated death (Morris and
Potter 1997).
1.8 Hygiene hypothesis
Improvements in medical care, living conditions and hygiene have improved our quality of
life and length of life compared with 100 years ago. In the UK, <8 children in every 1000 die
before their 1st birthday, yet in 1921 it was 80/1000. Also, life expectancy for males at birth
is 75–80 years, whereas in the 1850s it was 18–50 depending upon your living conditions
and wealth. However, there is a possibility that the reduction in exposure to bacteria has
resulted in an increase over the past 20 years in diseases such as allergies and asthma. The
‘hygiene hypothesis’ proposes that the immune systems needs frequent challenges, which
do not occur if the environment is ‘too clean’. While the rise in allergies and asthma over
the past decades is real, alternative reasons could include improved diagnosis, and an
increased exposure to diverse allergens. Currently, epidemiological studies on the hygiene
hypothesis are contradictory. A refinement of the hypothesis is that it is the exposure
to certain microbes, i.e. mycobacteria, during infancy that have a protective effect against
allergies.
If the hygiene hypothesis is true, then it will be important to ensure our immune system
is appropriately challenged by exposure to non‐pathogenic organisms and to avoid atopic
disease, without reducing our protection against infectious diseases.
Therefore, hygiene measures will need to be focused where and when they matter most.
1.9 Chronic sequelae following foodborne illness
The potential for chronic sequelae (secondary complications) has been recently recognised
along with the variability of the human response (Table 1.10). It has been estimated that
chronic sequelae occur in 2–3% of foodborne cases and may last weeks or even months.
These sequelae may be more serious than the original illness and result in serious long‐term
24
The microbiology of safe food
disability or even death (Lindsay 1997). The evidence that micro‐organisms are implemented
in chronic sequelae is not always certain because the chronic complications are unlikely to be
epidemiologically linked to a foodborne illness. An appreciation of the chronic sequelae is
necessary to fully appreciate the economic burden of foodborne infections.
A major symptom of food poisoning is diarrhoea, which may consequently lead to anorexia
and malabsorption. Severe cases of diarrhoea may last for months or years and can be caused
by C. jejuni, Citrobacter, Enterobacter or Klebsiella enteric infections. Subsequently the intestinal wall permeability may be increased and absorb significant quantities of unwanted proteins,
which may induce atrophy. Foodborne pathogens may interact with the immune system of the
host to elude or alter the immunological process, which may subsequently induce a chronic
disease. In addition, genetic susceptibility of the host may predispose humans to some types of
infection. Of particular importance are:
• Guillain–Barré syndrome (C. jejuni, Section 4.2);
• Reactive arthritis and Reiter’s syndrome (Salmonella serotypes, Section 4.3.);
• Haemolytic uraemic syndrome (E. coli O157, Section 4.4).
Less well studied chronic sequelae are:
• Chronic gastritis due to Helicobacter pylori.
• Crohn’s disease and ulcerative colitis possibly caused by Mycobacterium paratuberculosis.
• Long‐term gastrointestinal and nutritional disturbances following infection by C. jejuni,
Citrobacter, Enterobacter and Klebsiella.
• Haemolytic anaemia due to Campylobacter and Yersinia.
• Heart and vascular diseases caused by E. coli.
• Atherosclerosis following Salmonella Typhimurium infection.
• Personality changes following toxoplasmosis.
• Graves’ disease (autoimmune disease), which is the result of autoantibodies to the thyrotropin receptor after Yersinia enterocolitica serotype O:3 infection.
• Severe hypothyroidism due to Giardia lamblia infection.
• Crohn’s disease possibly due to M. paratuberculosis (causative agent of Johne’s disease in
ruminants) via pasteurised milk. Other causative bacteria may be L. monocytogenes, E. coli
and Streptococcus species.
• Viral induction of autoimmune disorders such as hepatitis A virus infection causing acute
hepatitis with jaundice in adults. This is probably due to molecular mimicry.
• Mycotoxins have a range of acute, subacute and chronic toxicities as some compounds are
carcinogenic, mutagenic and even teratogenic (Section 5.4).
1.10 The size of the foodborne illness problem
Foodborne illness estimates help to set food safety priorities and create public health policies,
therefore adequate health services and surveillance systems are needed to recognise these
infections. Foodborne illness occurs when a person gets sick by eating food that has been contaminated with an unwanted micro‐organism or toxin. The most common symptoms of foodborne illness include stomach cramps, nausea, vomiting, diarrhoea and fever. Unfortunately,
only a small proportion of cases of foodborne illness are brought to the attention of food
inspection, control and health agencies. This is partially because many foodborne pathogens
cause mild symptoms so the victim may not seek medical help. Hence the notified number of
cases is just the ‘tip of the iceberg’ with regard to true numbers of food poisoning cases
(Figure 1.6).
Foodborne infections
Notified
25
1 case identified
Seen by GP or hospital
doctor but not reported
6.2 cases gave faecal specimens for investigation
Ill but medical attention not sought
23 cases saw a general practitioner
Mild or asymptomatic
136 cases ill in the community
Figure 1.6 The under‐reporting pyramid. Source: Data from Wheeler et al. (1999).
The burden of foodborne diseases estimates is measured in DALYs (Disability‐Adjusted
Life Years) as they are useful as a comparative measure of disease burden and can form a basis
for more detailed cost estimates related to the economic impact. Essentially, DALYs are a
quantitative measure of how many years of life the total population loses when people have to
live with a reduced quality of life and/or die earlier than expected due to these three foodborne
organisms. The DALY measure combines the years of life lost due to premature death and
the years lived with disability for varying degrees of severity, making time itself the common
metric for death and disability. The DALY metric is an internationally recognised summary
measure of population health. One DALY is a health gap measure, equating to 1 year of healthy
life lost. Calculating DALYs facilitates comparing the relative impact of diseases and risk
factors over time.
Estimates of the size of foodborne illness have been made based on the major foodborne
pathogens. These have been at the national and international level. At best we have indicative
data since the mid‐1990s. In the USA, England and the Netherlands there have been sentinel
studies to estimate the proportion of cases which are not recorded and hence obtain a more accurate figure of food poisoning numbers (Meads et al. 1999; Wheeler et al. 1999; de Wit et al. 2001;
Tam et al. 2012). Table 1.11 gives the proportion of under‐reporting for the USA, and the estimated number of foodborne infections for 1997. For comparison, in 2017, the CDC monitored
between 18 to 37 potential foodborne outbreaks each week, and almost 200 multi‐state clusters.
Mead et al. (1999) reported that the total burden of foodborne illness per year foodborne
diseases caused approximately 76 million illnesses, 323 000 hospitalisations and 5000 deaths in
the United States (Table 1.7). Together Salmonella, Listeria and Toxoplasma were responsible
for 1500 deaths per year. Unknown agents caused 62 million illnesses, 265 000 hospitalisations
and 3200 deaths. Using a population size of 270 299 000 for the same time period (US Census
Bureau 1998, www.census.gov) this equates to 28% of the population suffering from food poisoning each year and 0.1% being hospitalised due to foodborne illness. Since 1995, FoodNet in
the USA has been gathering sentinel data from 10% of the population (Section 13.1.2).
Specifically for non‐typhoidal Salmonella infections, Voetsch et al. (2004) reported that over a
similar time period (1996–1999) there were 15 000 hospitalisations and 400 deaths annually.
26
The microbiology of safe food
Table 1.7 Risk of food poisoning in the USA.
Illnesses
Disease or agent
Bacterial
Bacillus cereus
Botulism, foodborne
Brucella spp.
Campylobacter spp.
Clostridium perfringens
Escherichia coli O157:H7
E. coli, non‐O157 STEC
E. coli, enterotoxigenic
E. coli, other diarrhoegenic
Listeria monocytogenes
Salmonella Typhi
Salmonella, non‐typhoidal
Shigella spp.
Staphylococcus food
poisoning
Streptococcus, foodborne
Vibrio cholerae, toxigenic
Vibrio vulnificus
Vibrio, other
Yersinia enterocolitica
Subtotal
Parasitic
Cryptosporidium parvum
Cyclospora cayetanensis
Giardia lamblia
Toxoplasma gondii
Trichinella spiralis
Hospitalisations
Deaths
Total
Foodborne
% Foodborne
transmission
Percentage of
total foodborne
Foodborne
Percentage of
total foodborne
Foodborne
Percentage of
total foodborne
27 360
58
1554
2 453 926
248 520
73 480
36 740
79 420
79 420
2518
824
1 412 498
448 240
185 060
27 360
58
777
1 963 141
248 520
62 458
31 229
55 594
23 826
2493
659
1 341 873
89 648
185 060
100
100
50
80
100
85
85
70
30
99
80
95
20
100
0.2
0.0
0.0
14.2
1.8
0.5
0.2
0.4
0.2
0.0
0.0
9.7
0.6
1.3
8
46
61
10 539
41
1843
921
15
6
2298
494
15 608
1246
1753
0.0
0.1
0.1
17.3
0.1
3.0
1.5
0.0
0.0
3.8
0.8
25.6
2.0
2.9
0
4
6
99
7
52
26
0
0
499
3
553
14
2
0.0
0.2
0.3
5.5
0.4
2.9
1.4
0.0
0.0
27.6
0.1
30.6
0.8
0.1
50 920
54
94
7880
96 368
5 204 934
50 920
49
47
5122
86 731
4 175 565
100
90
50
65
90
0.4
0.0
0.0
0.0
0.6
30.2
358
17
43
65
1105
36 466
0.6
0.0
0.1
0.1
1.8
59.9
0
0
18
13
2
1297
0.0
0.0
1.0
0.7
0.1
71.7
300 000
16 264
2 000 000
225 000
52
30 000
14 638
200 000
112 500
52
10
90
10
50
100
0.2
0.1
1.4
0.8
0.0
199
15
500
2500
4
0.3
0.0
0.8
4.1
0.0
7
0
1
375
0
0.4
0.0
0.1
20.7
0.0
Foodborne infections
Subtotal
Viral
Norovirus
Rotavirus
Astrovirus
Hepatitis A
Subtotal
Grand total
Source: Mead et al. (1999).
2 541 316
357 190
23 000 000
3 900 000
3 900 000
83 391
30 833 391
38 629 641
9 200 000
39 000
39 000
4170
9 282 170
13 814 924
40
1
1
5
2.6
3219
5.3
383
21.2
66.6
0.3
0.3
0.0
67.2
100.0
20 000
500
125
90
21 167
60 854
32.9
0.8
0.2
0.9
34.8
100.0
124
0
0
4
129
1809
6.9
0.0
0.0
0.2
7.1
100.0
27
28
The microbiology of safe food
Table 1.8 Examples of major outbreaks around the world due to contaminated food and water.
Year
Location
Description
1964
1981
Aberdeen, Scotland
Spain
S. Typhi in beef from Argentina; 507 cases, 3 deaths
Toxic cooking oil 1981 with a toll of 800 dead and 20 000
injured (WHO 1984)
1985
USA
S. Typhimurium contamination of pasteurised milk leading to
170 000 infections (Ryan et al. 1987)
1986
Chernobyl, former
USSR
Chernobyl accident led to a subsequent contamination of wide
areas of Western Europe and subsequently food with
radionuclides
1986
Birmingham, UK
Salmonella in tinned salmon, 2 died
1990
USA
Bottled sparkling water contaminated with benzene (up to
22 ppb). More than 160 million bottles of water were recalled
worldwide, at an estimated cost of $263 million
1991
Shanghai, China
Hepatitis A infection of 300 000 people through contaminated
clams (Halliday et al. 1991)
1992–1993
Washington Idaho,
California and
Nevada, USA
>500 cases Escherichia coli O157:H7
1993
1994
USA
41 States, USA
Cryptosporidium in drinking water 403 000 cases
S. Enteritidis in ice cream leading to 224 000 cases (Hennesy
et al. 1996)
1996
Japan
About 10 000 children infected (11 deaths) due to E. coli
O157:H7 contamination of radish sprouts served in school
lunches (Mermin and Griffin 1999)
1998
1999
India
Belgium
Toxic mustard seed oil led to a number of reported deaths
Dioxins that was found in poultry in lead to widespread trade
disruption and losses of hundreds of millions of Euros
1999–2000
2000
France
Japan
UK
Listeria monocytogenes 4b pork tongue in jelly
Staphylococcus aureus in milk powder
BSE‐vCJD has cost the UK more than $6 billion, not including
lost jobs. UK beef product exports in 2000 were down 99%
from 1995. Continental Europe has seen a drop in meat sales
2005
Spain
2138 cases of gastroenteritis caused by S. Hadar due to a single
brand of pre‐cooked, vacuum‐packed roast chicken product
2005
Denmark
Two norovirus outbreaks due to raspberries imported frozen
from Poland. The first outbreak involved 272 patients and
employees at a hospital, and the other outbreak included at
least 289 patients who received meals from the same food
caterer in a home nursing scheme
2006
2006
Seoul, Korea
UK
>1700 children infected with norovirus through school meal
Contamination of chocolate in the UK with S. Montevideo.
£20 million loss by company
2008
2008
USA
Canada
>1000 S. St. Paul infections from jalapeño peppers and tomatoes
28 listeriosis cases, with 1 death, of pregnant mothers and
premature births linked to various cheeses
12 deaths, out of >38 cases linked to meat products
2008
2017–2018
China
South Africa
Melamine in milk products; >50 000 illness, >4 deaths
Listeriosis >1000 cases, 247 deaths, linked with polony
sausages
Foodborne infections
29
Table 1.9 Factors contributing to outbreaks of foodborne disease (various sources).
Contributing factors
Factors relating to microbial growth
Storage at ambient (room) temperature
Improper cooling
Preparation too far in advance of serving
Improper warm holding
Use of leftovers
Improper thawing and subsequent storage
Extra large quantities prepared
Factors relating to microbial survival
Improper reheating
Inadequate cooking
Factors relating to contamination
Food workers
Contaminated processed non‐canned foods
Contaminated raw foods
Cross‐contamination
Inadequate cleaning of equipment
Unsafe source
Contaminated canned foods
Percentagea
43
32
41
12
5
4
22
17
13
12
19
7
11
7
5
2
Percentages exceed a total of 100 since multiple factors often contribute to
foodborne illness.
a
Table 1.10 Chronic sequelae following foodborne infection (based on Lindsay 1997 and Mossel 1988).
Disease
Associated complication
Brucellosis
Campylobacteriosis
Aortitis, orchitis, meningitis, pericarditis, spondylitis
Arthritis, carditis, cholecystitis, colitis, endocarditis, erythema, nodosum,
Guillain–Barré syndrome, haemolytic uraemic syndrome, meningitis, pancreatitis,
septicaemia, reactive arthritis, irritable bowel syndrome
Cronobacter species
E. coli (EPEC and EHEC
types) infections
Meningitis
Erythema nodosum, haemolytic uraemic syndrome, seronegative arthopathy
Listeriosis
Salmonellosis
Meningitis, endocarditis, osteomyelitis, abortion and stillbirth
Aortitis, cholecystitis, colitis, endocarditis, orchitis, meningitis, myocarditis,
osteomyelitis, pancreatitis, Reiter’s syndrome, rheumatoid syndromes, septicaemia,
splenic abscess, thyroiditis, irritable bowel syndrome
Shigellosis
Erythema nodosum, haemolytic uraemic syndrome, peripheral neuropathy,
pneumonia, Reiter’s syndrome, septicaemia, splenic abscess, synovitis
Taeniasis
Toxoplasmosis
Yersiniosis
Arthritis, epilepsy
Foetus malformation, congenital blindness
Arthritis, cholangitis, erythema nodosum, liver and splenic abscesses, lymphadenitis,
pneumonia, pyomositis, Reiter’s syndrome, septicaemia, spondylitis, Still’s disease
Table 1.11 Under‐reporting of foodborne pathogens in the USA.
Organism
Bacterial pathogens
Campylobacter species
Salmonella, non‐typhoid serovars
Clostridium perfringens
Staphylococcus aureus
Escherichia coli O157:H7
STEC other than O157
Shigella species
Yersinia enterocolitica
E. coli enterotoxigenic (ETEC)
Streptococcus Group A
Bacillus cereus
E. coli, other diarrhoegenic
Vibrio species other than those
above
Listeria monocytogenes
Brucella species
S. Typhi
Vibrio cholerae O1 or O139
Vibrio vulnificus
Clostridium botulinum
Parasitic pathogens
Giardia lamblia
Toxoplasma gondii
Cryptosporidium parvum
Cyclospora cayetanensis
Trichinella spiralis
Viral pathogens
Norovirus
Rotavirus
Astrovirus
Hepatitis A
Under‐reporting factor
Estimated
infections (1997)
38
38
38
38
20
Half as common as E. coli O157:H7 cases
20
38
10
38
38
Assumed to be as common as ETEC
20
1 963 000
1 342 000
249 000
185 000
92 000
Combined
90 000
87 000
56 000
51 000
27 000
23 000
5000
2
14
2
2
2
2
2000
777
659
49
47
56
20
7
45
38
2
200 000
112 000
30 000
14 000
52
11% of all acute primary gastroenteritis
Not given (number of cases taken as
equal to birth cohort)
Not given (number of cases taken as
equal to birth cohort)
3
9 200 000
39 000
39 000
4000
Source: Mead et al. (1999), Tauxe (2002).
Table 1.12 Medical costs and productivity losses estimated for selected human pathogens.
Pathogen
Bacillus cereus
Campylobacter jejuni
Clostridium botulinum
Clostridium perfringens
Cronobacter sakazakii
Escherichia coli pathovars
Listeria monocytogenes
Salmonella serovars
Staphylococcus aureus
Vibrio cholerae
Norovirus
Toxoplasma gondii
Total cost
(US$b)a
QALYsa
1.9
13 300
2.8
3.7
94 000
17 000
2.3
3.3
5000
11 000
QALY = Weighted quality‐adjusted life years.
Hoffmann et al. (2012, 2015).
b
Minor et al. (2015).
a
Weighted quality‐adjusted
life daysb
Monetary loss
per case (US$)b
0.18
2.09
29.41
0.18
4023
7.29
23.29
1.62
0.28
0.94
0.28
5.3
208
4903
1 525 594
218
7 013 777
11 936
1 468 384
5915
459
1429
363
41 652
Foodborne infections
31
Table 1.13 Antibiotic resistance changes in Salmonella Typhimurium DT104.
Antibiotic
1990
1991
1992
1993
1994
1995
1996
Ampicillin
Chloramphenicol
Streptomycin
Sulphonamides
Tetracyclines
Trimethoprim
Ciprofloxacin
37a
32
38
37
36
0.4
0
50
49
52
53
50
3
0
72
60
75
76
74
3
0.2
85
83
85
86
83
2
0
88
87
92
93
88
13
1
90
89
97
90
90
30
7
95
94
97
97
97
24
14
a
Percentage resistant.
These US studies can be compared with the two infectious intestinal disease survey sentinel
studies in England (Table 1.6; Sethi et al. 1999; Tompkins et al. 1999; Wheeler et al. 1999; Tam
et al. 2012). These studies were undertaken to determine a more accurate estimate of the incidence of food poisoning in England. The two UK sentinel studies estimated the overall extent
of under‐reporting and found that for every case detected by laboratory surveillance, there
were 136 in the community (Figure 1.6). Hence the scale of infectious intestinal disease in
England was estimated at 9.4 million annual cases, of which 1.5 million cases are presented to
general practitioners. Under‐reporting for individual organisms varied, most likely due to the
severity of the illness. The reporting of Salmonella (3.2:1), Campylobacter (7.6:1) was higher
than rotavirus (35.1:1) and norovirus (approximately 1562:1). These under‐reporting values
differ from those of the USA (Table 1.11). The second sentinel study (Tam et al. 2012) was
based on a population size of 800 000 people served by 88 general practitioners (GPs). It
showed that in the UK, there are up to 17 million cases and 1 million GP consultations due to
intestinal infectious diseases every year. Although the incidence of disease appeared to have
increased since the 1990s, the number of consultations with GPs has halved. Norovirus was the
most common recognised cause of infectious disease (3 million cases, 130 000 GP consultations per year). The total burden of foodborne diseases is that 20% of people in the general
population of the UK are infected. This proportion is similar to the estimate of 28% in the
USA. In England the organisms most commonly detected in patients with infectious intestinal
disease are Campylobacter species (12.2% of stools tested), rotavirus group A (7.7%) and small
round structured virus (6.5%). No pathogen or toxin was detected in 45.1–63.1% of cases.
Surprisingly Aeromonas species, Yersinia species and some enterovirulent groups of E. coli
were detected as frequently from controls as from cases.
It is evident that causes of gastroenteritis vary with age (Figure 1.2). Noroviruses, caliciviruses and rotaviruses probably cause the majority of cases of gastroenteritis in children under
4, whereas bacteria (Campylobacter and Salmonella serovars) are the major cause of gastroenteritis in other age groups. Figure 1.3 indicates that males suffer from gastroenteritis more than
females, except for one age group (>74 years, probably because of the lower ratio of men to
women in this age group). A possible reason for part of this difference is that fewer men than
women wash their hands after using the lavatory (33% compared with 60%, taking an average
of 47 seconds, compared with 79 seconds).
Helms et al. (2003) compared the mortality rates of 48 857 cases of gastrointestinal
infection with 487 138 controls from the general population. In their study they considered
mortality rates over longer periods of time than normal studies (<30 days), and also took coexisting illnesses into account. This large study found that 2.2% of people with gastrointestinal
32
The microbiology of safe food
infections died within 1 year after infection compared with 0.7% of controls. The relative
mortality within 30 days of infection was high for Salmonella, Campylobacter, Y. enterocolitica and Shigella. These organisms were also associated with increased death rates >30 days
of infection.
The Public Health Agency of Canada estimates that, based on data collected for 2000–2010,
the country experiences 4 million cases of foodborne illness each year in Canada, and this total
is due to 30 known pathogens and unspecified organisms (Thomas et al. 2015). Their analysis
accounted for under‐reporting and under‐diagnosis, and estimates of the proportion that were
foodborne and those which were travel‐related were incorporated for each pathogen. Monte
Carlo simulations were performed to account for uncertainty and these generated mean estimates and 90% probability intervals. Their calculations gave total estimated values of 11 600
(range 9250–14 150) hospitalisations and 238 (range 155–323) deaths associated with domestically acquired foodborne illness in Canada. This could be divided between those related to 30
known foodborne pathogens; 4000 hospitalisations (range 3200–4800) and 105 (range 75–139)
deaths, compared with an estimated 7600 (range 5900–9650) hospitalisations and 133 (range
77–192) deaths associated with an unspecified organism. The prominent pathogens associated
with these hospitalisations or deaths were norovirus, non‐typhoidal Salmonella serovars,
Campylobacter species, E. coli O157 and L. monocytogenes. These data illustrate the considerable burden of foodborne illness in Canada.
Even in a country such as Denmark, which has a significant health surveillance system, the
number of people who get food poisoning each year is an under‐estimate and hence the cost
to society has been unknown. Now researchers have calculated the real burden of disease from
infections caused by the major foodborne pathogens Campylobacter species, Salmonella serovars and Shiga toxin‐producing Escherichia coli (STEC) using data for 2012. These calculations
made allowances for under‐reporting and under‐diagnosis, thereby giving a higher number
for how many people actually become ill owing to the three bacteria. The burden of disease is
reported in DALYs. Campylobacter was determined to cause the highest disease burden. This
gives authorities and other decision makers the scientific basis with which to prioritise initiatives aimed at increasing food safety and reducing the health consequences of infection by this
organism.
The amount of under‐reporting for the three organisms in Denmark was (i) Salmonella
serovars – for every reported case, seven cases of disease were not reported; (ii) Campylobacter
species infections – one out of 12 cases was reported; and (iii) for STEC infections –one out of
31 cases. The total burden of disease was highest for Campylobacter species with 1593 DALYs,
followed by Salmonella serovars (389 DALYs) and STEC (113 DALYs). For both Campylobacter
species and Salmonella serovar infections the disease that contributed the most to the total
burden of disease was irritable bowel syndrome, while for STEC it was renal failure. For
Campylobacter infections, 38% of the total number of DALYs was associated with foreign
travel, while the major source of the burden of disease in Denmark was broilers. This was
either from direct consumption of chicken meat or from environmental contamination.
Therefore, reducing broiler contamination by Campylobacter should reduce the number of
days of productivity lost through sickness.
Belgium has estimated and forecast the number of cases due to Salmonella serovars,
Campylobacter species and L. monocytogenes for 2012 through to 2020, and calculated the
corresponding number of DALYs. These were based on the number of cases per month that
were available: from January 2001 to December 2012 for salmonellosis, from January
1993 to December 2013 for campylobacteriosis and from January 2011 to December 2013 for
Foodborne infections
33
listeriosis. The proportion of salmonellosis and campylobacteriosis cases attributable to food
is ~76%. The average monthly number of cases of salmonellosis was 264 in 2012 and is predicted to decrease slightly to 212 in 2020, while the numbers of Campylobacter cases were 633
and 1081, respectively. The numbers of L. monocytogenes infections are much smaller at 5 in
2012 and 6 in 2014. These values can be used to estimate DALYs for the three organisms.
Salmonella serovars would be 102 in 2012 and were predicted to be 82 in 2020. Campylobacter
cases would cause 1019 and 1736 DALYS, while listeriosis DALYs were higher than Salmonella
serovars – 208 in 2012 and 252 in 2014. These figures indicate that Belgium needs to consider
new action to reduce the risk of foodborne infection in particular from Campylobacter species,
since its incidence is predicted to double by 2020.
In England and Wales, Salmonella enterica serovar Enteritidis has caused the largest and
most persistent epidemic of foodborne infection attributable to a single subtype of any pathogen since a systematic national microbiological surveillance programme was established in
the 1940s (Lane et al. 2014). The epidemic was associated with the consumption of contaminated chicken meat and eggs. It has been estimated that during the epidemic >525 000 people became ill, causing 6 750 000 days of illness, 27 000 hospitalisations and 2000 deaths.
There was only a decline in the number of infections when vaccination and other control
measures for Salmonella were introduced for the production and distribution of chicken
meat and eggs. Consequently, there has been a significant reduction in foodborne infections
in England and Wales.
It should be noted that up to 2009 across Europe, the numbers of food poisoning cases have
been decreasing in recent years for all foodborne pathogens except C. jejuni (FoodNet 2009).
The European Food Safety Authority (EFSA) reports (EFSA and ECDC 2007; EFSA 2017) that
in 2016, Campylobacter continued to be the most commonly reported gastrointestinal bacterial pathogen in humans in the EU. The number of reported confirmed cases of human campylobacteriosis was 246 307, giving a notification rate of 66.3 per 100 000 population. Despite the
high number of human campylobacteriosis cases, their severity in terms of reported case fatality rate remains low (0.03%), even though this was the third most common cause of mortality
amongst the pathogens considered. The second most common cause was Salmonella serovars,
with 94 530 confirmed cases, which was at the same notification rate as in the previous 5 years.
There has been a statistically significant decreasing trend of salmonellosis between 2008 and
2016, however during 2012–2016 the trend has not shown any statistically significant increase
or decrease. Seven EU Member States reported an increasing trend and four MS a decreasing
trend over the period 2012–2016. The top five most commonly reported serovars during 2016
were, in decreasing order: S. Enteritidis, S. Typhimurium, monophasic S. Typhimurium, S.
Infantis and S. Derby. The proportion of human salmonellosis illnesses due to S. Enteritidis
has continued to increase in 2016.
In Denmark there were few outbreaks due to Salmonella serovars in 2014 and nearly none
in 2015. The total number of Salmonella infection cases was 925 in 2015 – the first time it has
been lower than 1000, and more than half of these cases were acquired abroad. Salmonella
Enteritidis is now rare in Denmark and has been nearly eradicated from Danish egg and
chicken production. In contrast, S. Typhimurium and its monophasic variant are still recovered frequently in Danish food products and more than 4300 cases of Campylobacter infections were recorded, which was an increase on previous years. This increase could be due to
improved surveillance coordination and methods of detection. As in other European countries, Campylobacter causes more intestinal infections than any other bacteria, with about a
third being associated with travel abroad. It is still not fully established how many sources of
34
The microbiology of safe food
infection there are, though the probable primary source of infection is chicken meat either
through consumption or through cross‐contamination in the kitchen.
It should be noted that these values for clinical cases are where the agent has been isolated
and identified. There are a significantly large number of cases for which the aetiological agent
is unidentified. Frenzen (2004) estimates that such foodborne organisms cause 3400 deaths
annually in the United States.
Salmonella infections are believed to be mostly foodborne. The estimated numbers of
Salmonella infection are 1.4 million and 80 million in the United States and worldwide per
annum, respectively (Lynch et al. 2009). These numbers equate to 27 000 cases of salmonellosis/week in the United States. Despite major strides in foodborne surveillance in the United
States in the past 16 years, detection of the 3800 cases of Salmonella/day in the United States is
now occurring.
In the USA in 2015, there were 902 foodborne disease outbreaks reported, resulting in
15 202 illnesses, 950 hospitalisations, 15 deaths and 20 food product recalls. This did not
include outbreaks that had started before 2015, i.e. L. monocytogenes in caramelised apples
(Section 4.12.7). The most common cause of confirmed, single‐aetiology outbreaks was
norovirus, which accounted for 164 (37%) outbreaks and 3893 (39%) illnesses. This is similar to that already stated for Denmark. Salmonella serovars were the next most common
cause, causing 149 (34%) outbreaks and 3944 (39%) illnesses. Salmonella Enteritidis was the
most common serovar (51 outbreaks, 35%), followed by serovar 1, 4,[5],12:i:‐ (15, 10%), S.
Newport (8, 6%) and S. Braenderup (7, 5%). This was followed by STEC, which caused 27
(6%) confirmed single‐aetiology outbreaks and 302 (3%) illnesses. Seventeen outbreaks
(63%) were caused by serogroup O157, 3 (11%) by O26, 2 (7%) by O103, 1 (4%) by O45, 1
(4%) by O111, 1 (4%) by O121, 1 (4%) by O145 and 1 (4%) by multiple serogroups. Outbreaks
caused by Cl. botulinum resulted in the highest proportion of ill persons hospitalised (97%),
followed by L. monocytogenes (90%) and hepatitis A virus (38%). Amongst the 15 deaths
reported, 14 (93%) were attributed to bacterial pathogens: Salmonella (9), Cl. botulinum (2),
Cl. perfringens (1), L. monocytogenes (1) and Vibrio vulnificus (1). One death was attributed
to norovirus. Fish (34 outbreaks), chicken (22) and pork (19) were the most common single
food categories implicated.
For the period 2009–2015, the CDC recorded 100 939 confirmed food poisoning cases, of
whom 5699 were admitted to hospital and 145 died (Dewey‐Mattia et al. 2018). Chicken was
responsible for the most illnesses with 3114 cases (12% of total). Pork was linked to 2670 cases
(10% of total), and seeded vegetables caused a similar number of infections (2572 cases, 10%
of total). There were 2953 outbreaks with a single confirmed aetiology, for which the four most
prominent pathogens were:
1 Norovirus: 1130 (38%) outbreaks, and 27 623 (41%) of the cases.
2 Salmonella serovars: 896 (30%) outbreaks, and 23 662 (35%) of the cases.
3 Listeria monocytogenes, Salmonella serovars and STEC were responsible for 82% of hospitalisations and 82% of reported deaths.
Amongst 1281 outbreaks in which the food reported could be classified into a single food
category, the top three were:
1 Fish: 222 outbreaks, 17%.
2 Dairy: 136 outbreaks, 11%.
3 Chicken: 123 outbreaks, 10%.
Multi‐state outbreaks were only 3% of all outbreaks reported, but led to 11% of illnesses, 34%
of hospitalisations and 54% of deaths.
Foodborne infections
35
It is obvious from the plethora of differing detection procedures adopted by different
countries that food poisoning statistics cannot be directly compared between countries due
to the differing methods of analysis applied. Nevertheless, for several years the WHO has
been encouraging Member States to quantify the national burden and causes of foodborne
disease. Although there are a number of foodborne disease burden estimates, they are mainly
from developed countries. In large parts of the world the data required to underpin such
estimates are completely lacking. Additionally our understanding of foodborne infections is
changing with the recognition of previously unrecognised pathogens and previously well‐
recognised pathogens that have increased in their prevalence or become associated with new
food vehicles.
In November 2007, the Foodborne Disease Burden Epidemiology Reference Group (FERG)
was established by the WHO (Kuchenmüller et al. 2009). This group is composed of internationally renowned experts in a broad range of disciplines relevant to global foodborne disease
epidemiology. Its objective was to determine the global burden of foodborne disease. This is
the incidence and prevalence of morbidity, disability and mortality associated with acute and
chronic infection. In order to achieve this, FERG needs to collaborate with the Food and
Agriculture Organisation of the United Nations (FAO) and others to undertake regional consultations to discuss the regional specific profiles of foodborne syndromes and aetiological
agents for future burden estimation. FERG’s remit is to consider microbial, parasitic, zoonotic
and chemical contamination of food. Assessing the chemical and parasitic causes of foodborne
disease burden is of particular interest since little work has been done on these topics to date.
See Box 1.1 for a list of action points.
FERG have reported their first estimates of the global incidence, mortality and disease burden (Havelaar et al. 2015; WHO 2015). According to their estimates, in 2010 there were ~600
million cases of foodborne illnesses, which led to >400 000 deaths. These infections could be
attributed to 31 foodborne hazards. The WHO estimates that up to 30% of people in developed
countries are infected by food and water every year (WHO Food safety and foodborne illness.
Fact sheet 237, www.who.int/mediacentre/factsheets/fs237/en/print.html). This number is
supported by US, Canadian and Australian authorities (Mead et al. 1999; Majowicz et al. 2004;
OzFoodNet Working Group 2003).
Box 1.1 FERG Action Points
Acute infectious diseases
Examine pathogen specific global burden in children.
Develop detailed analysis of cause of death data on WHO mortality database.
Conduct or commission relevant burden work.
Develop cause attribution models and estimate percentage foodborne.
Recommend and/or conduct intervention studies to increase data availability.
Chronic infectious diseases
Evaluate the known microbial and chemical causes of foodborne disease.
Develop cause attribution models and estimate percentage foodborne.
Acute and chronic chemicals
Identify major causes, particularly for developing countries, and commission relevant burden work.
Develop cause attribution models and estimate percentage foodborne.
36
The microbiology of safe food
1.11 The cost of foodborne diseases
Several countries have estimated the economic consequences of foodborne illness. These costs
include:
• loss of income by the affected individual;
• cost of health care;
• loss of productivity due to absenteeism;
• costs of investigation of an outbreak;
• loss of income due to closure of businesses;
• loss of sales when consumers avoid particular products.
It is clear that foodborne illness has considerable implications for a country’s economy. The
estimates, reviewed below, are primarily for developed countries. Unfortunately, there are
fewer reliable estimates for developing countries, where the problem of diarrhoeal disease is
far greater, and therefore the economic burden of foodborne illness must be even more severe.
Early economic estimations for Canada were Can$1.3 billion loss due to foodborne pathogens (Todd 1989a). Back in 1991, Sockett estimated that in England and Wales, the 23 000
cases of salmonellosis were estimated to have resulted in an overall cost of £40–50 million
(US$53m–$66m). Five years later Roberts (1996) estimated that the medical cost and value of
lives lost due to just five foodborne infections in England and Wales was £300–700 million per
year (US$400m–$900m). In Australia the cost of an estimated 11 500 food poisoning cases
equated to AU$2.6 billion per year (ANZFA 1999). The Swedish Salmonella‐free poultry programme costs about $8 million per year, but saves an estimated $28 million per year in medical
costs. The cost of Campylobacter infections in the USA has been estimated at $1.5–8.0 billion
(Table 1.12). The total economic impact of foodborne diseases is a loss of $5–17 billion according to the US Food and Drug Administration.
The Economic Research Service (ERS) is part of the United States Department of Agriculture,
and estimates the ‘cost of foodborne illness’ for seven major foodborne pathogens (Plate 19).
These are based on estimated medical costs and productivity losses over the infected individual’s lifetime. The medical costs include both acute illness and long‐term chronic complications. Therefore, the amount of medical attention required is determined according to the
severity of illness. This ranges from those who do not visit the doctor, those who develop
chronic complications, through to those who are hospitalised, and die prematurely. For each of
these groupings the medical costs are estimated for the number of days of treatment, average
cost per treatment or service and the number of patients (Buzby and Roberts 1997a).
Productivity losses include changes in income and fringe benefits. High and low estimates of
economic losses are calculated for cases where the person is unable to resume their normal job.
This can be due to disability or death. The low estimate is based on loss of lifetime earnings and
household production, whereas the high estimate is based on the ‘risk premiums’ in labour
markets. The FDA uses the high estimate for productivity losses in its evaluation of food safety
programmes, and adjusts this according to the person’s age.
The cost of foodborne infections in the USA in 2011 has been estimated as $14.0 billion.
This is based on an estimated total number of 9.4 million cases of infection attributable to 31
known organisms. The vast majority (95%) of these cases were due to 14 pathogens, and 98%
of the deaths. In turn, 90% of the cases were attributable to non‐typhoidal Salmonella serovars,
Campylobacter species, L. monocytogenes, Toxoplasma gondii and norovirus. However, there
were an estimated 38.4 million further cases that were not attributable to an organism (Scallan
et al. 2011). These unattributed cases resulted in approximately 71 878 hospitalisations and
Foodborne infections
37
1686 deaths. It is plausible that the unattributed cases are due to organisms for which detection
methods are currently not sufficiently robust, toxins and as‐yet‐unrecognised emergent pathogens. In the US, each year ~48 million people suffer from foodborne illness, yet only in 20%
of these cases can a specific pathogen be attributed to the infection (Hoffmann et al. 2015). Of
these, 90% are due to 15 pathogens and cost $15.5 billion in economic burden annually (84%
due to deaths). In turn, 90% of the economic burden is due to only 5 of these 15 pathogens:
Salmonella serovars ($3.7b, 17 000 QALYs), T. gondii ($3.3b, 11 000 QALYs), L. monocytogenes
($2.8b, 94 000 QALYs) norovirus ($2.3b, 5000 QALYs) and Campylobacter species ($1.9b,
133 000, QALYs) (Hoffmann et al. 2012 and 2015). According to similar calculations by Minor
et al. (2015) the annual economic burden in the US is ~$36 billion. They also reported that
Cronobacter was associated with the highest monetary loss due to the high incidence of infant
mortality (Section 4.6).
The Centers of Disease Control and Prevention (USA) estimates that 95% of Salmonella infections are foodborne in origin. Consequently the FoodNet estimate of 1.4 million annual salmonellosis cases means that 1.3 million cases were due to consumption of foods contaminated by
Salmonella. The annual cost of campylobacteriosis in the USA is approximately $0.8–$5.6 billion
(Buzby and Roberts 1997b) and estimated total costs of Campylobacter‐associated Guillain–
Barré syndrome (GBS, an autoimmune reaction) are $0.2–$1.8 billion (Section 4.2). Hence
reducing the prevalence of Campylobacter in food could prevent up to $5.6 billion in costs annually in the US. The economic burden of campylobacteriosis has been estimated to be €2.4 billion
annually in Europe, and €82 million in the Netherlands in 2011. In the UK, Campylobacter infections cause more than 100 deaths per year, with considerably more people experiencing disease
symptoms and decreased quality of life. As a result, this pathogen costs the UK economy ~£900
million (~$1.2b) per year. Therefore, it is not surprising that national regulatory authorities have
set targets for the reduction of infections due to major foodborne pathogens.
The estimated productivity costs due to foodborne infections are likely to increase in the
future as the calculation methods improve. One omission is that the current methods do not
include estimates for how much consumers are willing to pay for improved food safety.
Additionally, it is highly probable that more foodborne pathogens will be identified in the
future along with increased recognition of chronic complications. Currently chronic sequelae
are estimated to occur in 2–3% of cases, and therefore the long‐term consequences to the individual and our economy may be more detrimental than the initial acute disease.
Given these economic costs there is a considerable need, even in developed countries, for
more systematic and aggressive steps to be taken to significantly reduce the risk of microbiological foodborne diseases. Since the cost of ‘gastroenteritis’ in developed countries is determined to be in the billions of US$, how much more is the human cost of food and water disease
in developing countries where WHO estimates that worldwide almost 2 million children die
every year from diarrhoea. A significant portion of deaths are caused by microbiologically
contaminated food and water. Hence this is a major challenge for the future, which requires a
global response. Therefore, this book frequently refers to the activity of international organisations activities such as Codex Alimentarius Commission and the WHO.
The microbial contamination of food has a major impact on food production. Worldwide it
is estimated that at least 10% of grain and legume production is lost, annually and this may
even be as high as 50% for vegetables and fruits. This contamination affects trade in two ways.
First, the contaminated food may not be accepted by the importing countries. Second, the loss
in a country’s reputation for food safety may result in loss of further trade.
38
The microbiology of safe food
The cost benefits in preventing food poisoning through the assured food safety system
HACCP (Section 9.5) have been estimated. Due to the range of economic models used the
estimates varied considerably from $1.9 to $171.8 billion. Regardless of the exact figure it can
be predicted that implementing HACCP will on balance cost less than the current medical
costs due to foodborne infections, as well as decreasing productivity losses.
In 2007, following a well‐publicised outbreak of S. Montevideo with ~40 victims, a major
UK manufacturer of chocolate was fined $2 million. The company pleaded guilty to violating
food and hygiene regulations, and was also ordered to pay $309 000 in legal costs. The cost of
the product recall in 2006 was at least $60 million, and the company is reported to have spent
$40 million on improvements, including changes to quality control procedures. Eventually the
company was sold to a major food manufacturer based in another country. The problem came
to light after three people, including two young children, were taken to a hospital in a food
poisoning alert linked to the manufacturer’s chocolate. The victims’ age ranged from babies to
adults of 52, and most were children under 4 years. Sales of the company’s chocolate fell by 14%
during the first 6 months following the outbreak. The crux of the loss of Salmonella control by
the manufacturers was the change to using a Most Probable Number (MPN) approach to
detect the organism, which effectively permitted chocolate to be released onto the market
despite positive results being obtained.
1.12 Changes in antimicrobial resistance of foodborne pathogens
1.12.1 Bacterial antibiotic resistance in agriculture and aquaculture
Antibiotic resistance, or antimicrobial resistance (AMR), is a major area of concern as the
effectiveness of antibiotics to treat infections in humans and animals is falling. This results in
a significant economic burden due to resulting higher costs of treatments and reduced productivity caused by absence. In 2009, the European Centre for Disease Prevention and Control
(ECDC) and the European Medicines Agency (EMA) estimated that each year about 25 000
patients die in the EU from an infection caused by multidrug‐resistant bacteria. The resultant
loss (health care costs and productivity losses) is in the order of €1.5 billion per year (~$1.8b/
year). In the US, antibiotic resistance adds $20 billion in excess direct health care costs, with
additional costs to society for lost productivity as high as $35 billion a year.
The European Commission has published two Action Plans (2011 and 2017) to reduce the
increasing incidence of AMR. There are seven priority areas, which include the monitoring of
AMR in bacteria from food‐producing animals and food. In order to evaluate the level of
AMR, it is necessary to harmonise the method of determining antibiotic susceptibility and
definition of resistance. The microdilution method needs to be used and interpreted according
to the European Committee on Antimicrobial Susceptibility testing (EUCAST) epidemiological cut‐off (ECOFF) values for the interpretation of ‘microbiological resistance’. ECOFF values
are preferred for surveillance purposes as they enable the identification of small changes in
bacterial susceptibility, which may indicate emerging resistance and allow appropriate control
measures to be considered at an early stage. The concentration ranges used in the testing
ensure that both the ECOFF and the clinical breakpoints are included, making comparability
of results with human data possible.
Many bacterial species can develop resistance to the antibiotics they are exposed to in clinical and veterinary settings. An example can be the veterinary use of enrofloxacin causing
cross‐resistance due to selection of DNA gyrase mutants (gyrA) in Salmonella serovars. The
dissemination of antibiotic resistance (regardless of origin) within the microbial gene pool
Foodborne infections
39
means governments are now taking a ‘One Health’ approach for responsible use of antibiotics.
The ‘One Health’ approach recognises that human and animal health are interconnected, with
diseases being transmitted from humans to animals and vice versa.
Resistance can occur by:
• Random mutation with subsequent positive selection of mutants resistant to the antibiotic,
i.e. fluoroquinolone resistance in C. jejuni.
• Mobilisation, including HGT, of resistance genes, i.e. colistin resistance in E. coli.
• Dissemination of strains with previously developed resistance, i.e. S. Typhimurium DT104.
A microbiological risk assessment of fluoroquinolone‐resistant C. jejuni is reviewed in
Section 11.2.4.
Isolation of S. Typhimurium DT104 resistant to ampicillin, chloramphenicol, streptomycin,
sulphonamides and tetracycline (R‐type ACSSuT) was first reported in 1984, and appears to be
highly clonal. It is likely that the genes were acquired through HGT, and afterwards the strain
was widely disseminated due to the veterinary use of antibiotics. It has been proposed that the
selective pressure was in part due to the use of antibiotics in aquaculture (Section 1.12.1). This
organism has been isolated from cattle, poultry, sheep, pigs and horses. Antimicrobial therapy
is used extensively to combat S. Typhimurium infection in animals, and the evolution of a
strain resistant to the commonly used antibiotics has made infections with S. Typhimurium in
food animals difficult to control. The primary route by which humans acquire infection is by
the consumption of a large range of contaminated foods of animal origin.
Concern over the increase in AMR is not new. Table 1.13 shows the significant increase in
antibiotic resistance in S. Typhimurium DT104 isolates between 1990 and 1996 in England
and Wales. In addition to the antibiotic‐resistant type ACSSuT, many isolates are also resistant
to trimethoprim and ciprofloxacin. Ciprofloxacin resistance has been most notable in S. Hadar
(39.6%) compared with other Salmonella serovars.
A number of international surveillance networks monitoring antibiotic resistance are covered later, such as FoodNet and Global Salm‐Surv (Sections 13.1.2 and 13.1.7). In Europe there
have been a number of concerted efforts to control microbial antibiotic resistance including a
ban in 2006 on using antibiotics as growth promoters (Eurosurveillance 2008). It has been
proposed that the reduction in prophylactic use of antibiotics has led to a reduction in animal
health leading to infection by E. coli and Lawsonia intracellularis in early post‐weaning pigs
and clostridial infection in broilers. Consequently there may have been an increased use of
therapeutic antibiotics in animals that are also used in human treatments (Casewell et al.
2003). Nevertheless good husbandry reduces animal infections and subsequently reduces the
use of antibiotics.
While the use of antibiotics in agriculture has received much attention, there is considerable
use of antibiotics in aquaculture (Done et al. 2015). China is the largest single aquaculture
producer and exporter with ~62% of the global aquaculture production volume (2012 figures).
A considerable amount of antibiotics are used in fish cultivation as disease control agents and
growth promoter in aquaculture. This raises concerns as this extensive use of antibiotics may
result in water and sediment contamination and the development of antibiotic resistance genes
(Mo et al. 2017).
There are ~50 antibiotics commonly used in both aquaculture and agriculture, of which ~39
are also of importance in human medicine. Six classes of antibiotics commonly used in both
agriculture and aquaculture are also included on the WHO list of critically important/highly
important/important antimicrobials. The emergence of antibiotic resistance amongst fish bacterial pathogens increases the risk not only of these antibiotic‐resistant bacteria causing an
40
The microbiology of safe food
infection, but also the transfer of antibiotic resistance determinants to other bacteria of concern
in animal and human health. For example, tetracycline resistance, encoded by Tn1721, has been
disseminated between Aeromonas salmonicida, a fish pathogen, and the human pathogens A.
hydrophila, A. caviae and E. coli. Similarly, A. salmonicida plasmids resistant to trimethoprim,
sulphonamide and streptomycin can transfer with high frequency to E. coli and Salmonella. It
has been argued that molecular and epidemiological evidence has demonstrated that multiple
antibiotic resistance determinants in S. Typhimurium DT104 (a major cause of salmonellosis in
humans and animals in Europe and the USA) possibly originated in aquaculture (Section 4.3).
The antibiotic resistance determinants of S. Typhimurium DT104 are encoded by a chromosomal transmissible genetic element that contains a resistance gene (floR) for florfenicol. This is
an antibiotic that is extensively used in aquaculture in the Far East. Additionally, florR was first
reported in the fish pathogen Vibrio damsel (Bolton et al. 1999; Angulo et al. 2004).
The increasing generation of whole‐genome sequences for bacterial isolates means the
organisms can be screened for antimicrobial factors. In the US, the National Antimicrobial
Resistance Monitoring System for enteric bacteria (NAMRS) monitors for changes in the antimicrobial susceptibility of certain enteric bacteria (Salmonella serovars, E. coli, Shigella, Vibrio
and Campylobacter species) isolated from humans, retail meats and food animals. They have
also compared E. coli whole‐genome sequences to a database containing over 2500 resistant
genes and gene variants. They were then able to predict antimicrobial resistant profiles that
correlated with laboratory‐generated profiles (Tyson et al. 2015). Similarly, the Center for
Genomic Epidemiology (Denmark) (www.genomicepidemiology.org) predicts the antibiotic
resistance traits in user’s uploaded genomes. This is accessible to researchers, educators and
non‐governmental investigators unlike NARMS. At present in silico‐predicted antibiotic
resistance profiles cannot be reliably used to replace laboratory‐based antibiotic resistance
determination (ECOFFS, clinical breakpoints, etc.). Nevertheless, using whole‐genome
sequence data in the future will enhance antimicrobial monitoring systems and improve the
tracking of antimicrobial resistant isolates within the food supply, as well as supporting epidemiological investigations.
1.12.2 Antibiotics of concern and resistance mechanisms
Antibiotics are currently our most successful means of treating infectious diseases. However,
resistance to commonly used antibiotics is increasing through various mechanisms and selection pressures. The acquisition of genes from another strain or species can provide resistance
to an entire class of antimicrobials. These genes are frequently associated with large transferable extrachromosomal DNA elements, plasmids, on which there may be other mobile DNA
elements such as transposons and integrons.
Plasmids in the incompatibility group IncA/C are of considerable interest with respect to
multiple antibiotic resistance in enteric pathogens of humans and animals. These large, low‐
copy number plasmids are of increasing relevance in the spread of antibiotic resistance. They
have at least three hotspots for the integration of mobile genetic elements. They were first
identified from multidrug‐resistant fish pathogens A. hydrophila and Vibrio species, and coincided with the use of antibiotics in aquaculture (Section 1.12.1). IncA/C plasmids and their
multiresistance phenotype emerged in clinical isolates of Salmonella Newport after 1980. The
reservoir appears to be environmental bacteria, followed by the acquisition of antibiotic gene
modules due to the selective pressure of antibiotic exposure. IncA/C plasmids have acquired
the NDM‐1 gene encoding the New Delhi metallo‐β‐lactamase (NDM) and are found in clinical strains of E. coli and Klebsiella pneumoniae.
Foodborne infections
41
In Enterobacteriaceae, resistance to β‐lactam antibiotics is mediated by production of β‐
lactamase enzymes, which inactivate the drugs by hydrolysing the β‐lactam ring. Some of
the clinically most important inactivating enzymes are:
1 Extended‐spectrum β‐lactamases (ESBLs). This includes the SHV, TEM and CTX‐M type
β‐lactamases. The prevalence of CTX‐M is increasing in Enterobacteriaceae and predominates as a cause of extended‐spectrum cephalosporin resistance.
2 Carbapenemases. This includes class A (KPC types), class B metallo‐β‐lactamases (MBLs)
and class D oxacillinases. The carbapenem‐resistant Enterobacteriaceae have been increasingly reported worldwide. The carbapenemases include NDMs, KPCs and OXA‐48. KPCs
are currently the most common cause of carbapenem resistance worldwide. The emergence
of New Delhi metallo‐ β‐lactamase (NDM‐1) and its variants has raised a major public
health concern. NDM‐1can hydrolyse a wide range of β‐lactam antibiotics, including
carbapenems.
3 AmpC cephalosporinases.
Another issue with increasing antibiotic resistance is the co‐resistance to microbiocides, such
as triclosan and quaternary compounds. Exposure of Salmonella serovars and E. coli O157 to
sublethal concentrations of antibacterial agents can lead to adaptive resistance to both biocides
and antibiotics. For example, benzalkonium chloride‐resistant Salmonella Virchow showed
elevated resistance to chlorhexidine. Escherichia coli O157 with adapted resistance to triclosan
also had increased resistance to chloramphenicol, erythromycin, imipenem, tetracycline and
trimethoprim. Increased co‐resistance to sanitary products and antibiotics can also occur due
to the co‐location of heavy metal resistance and antibiotic resistance genes on the same plasmid, or the same genes encoding for resistance to both metals and antibiotics.
1.12.3 Polymyxin and plasmid‐encoded colistin resistance
Polymyxins are active against most members of the Enterobacteriaceae family. There is,
however, some natural resistance amongst Proteus, Brucella, Legionella, Campylobacter and
Vibrio species. Acquired resistance to polymyxins in Enterobacteriaceae may be due to genes
encoding lipopolysaccharide‐modifying enzymes, regulators of the PmrAB and PhoPQ two‐
component systems, and the intrinsic regulator RamA (Poirel et al. 2017).
Colistin, also known as polymyxin E, is an antibiotic of last resort for the treatment of
multiple antibiotic‐resistant Gram‐negative infections. Chromosomal‐encoded resistance had
been known for some time. However, it was not until November 2015 that the plasmid‐borne
colistin resistance gene mcr‐1 was first identified in E. coli isolates from Chinese pigs, pork
products and patients (Liu et al. 2016). It has since been reported in food‐producing animals
and people in more than 30 countries across five continents. This caused an international
alarm as plasmid‐borne genes are far more transmissible than if they were chromosomal.
Additionally, mcr‐1 encoding plasmids may also carry other antibiotic resistance genes: carbapenemases and extended‐spectrum β‐lactamases. The mcr‐1 gene (and variants mcr‐2 to ‐5)
has also been identified in other members of the Enterobacteriaceae from South America, Asia,
Europe and Africa, demonstrating that it is widespread though at a low level such that it was
not found in bacterial genome databases (Olaitan et al. 2016).
It is now thought that the mcr‐1 gene emerged about 10 years before it was first identified,
and most likely originated in Chinese livestock (Wang et al. 2018). Analysis of ~450 whole‐
genome sequenced isolates from 31 countries was carried out, with China (212 isolates) and
Vietnam (58) having the most MCR‐1–positive samples. Nearly 90% of the isolates (411)
were E. coli, but isolates carrying the gene were found in seven other bacterial species: S. enterica,
42
The microbiology of safe food
K. pneumoniae, Escherichia fergusonii, Kluyvera ascorbata, Citrobacter braakii and Klebsiella
aerogenes. Between 2002 and 2008, mcr‐1 first became mobilised as part of a composite transposon. The MCR‐1 transposon then jumped to different plasmids resulting in a dramatic
demographic diversification and expansion. The highest proportion of isolates carrying transposon sequences similar to the ancestor are environmental and agricultural isolates from
China, where colistin was used widely in food‐producing animals until 2016. Dissemination
globally was probably primarily driven by the trade of food animals and meat, although movement of colonised humans may have contributed as well.
1.12.4 Livestock‐associated methicillin‐resistant Staphylococcus aureus (LA‐MRSA)
Methicillin‐resistant Staphylococcus aureus (MRSA) can cause a severe invasive disease in
humans, as well as infections in animals – mastitis in cattle, exudative dermatitis in swine and
mild skin infections. Unfortunately, it can be a commensal of humans and other mammals.
MRSA started to circulate in hospitals in the 1960s. Since then MRSA has been isolated outside
the hospital setting (community‐acquired MRSA, CA‐MRSA) and from livestock (livestock‐
associated MRSA, LA‐MRSA).
The prototypical LA‐MRSA isolate was characterised by multi‐locus sequence typing
(MLST; Section 6.6.1) and defined as sequence type 398 (ST398). The identification and prevalence of this strain in livestock species indicate that livestock are potentially the largest reservoir for MRSA outside the hospital setting. This lineage has been identified in a variety of
livestock species and is considered to be adapted for the colonisation of non‐human mammals,
although colonisation and infection have been noted in humans. In Europe and Asia, LA‐
MRSA isolates are primarily MLST sequence type (ST) 398 and ST9, respectively, while in the
United States it also contains ST5. These latter strains are of concern because, unlike ST398
and ST9, which are considered livestock‐adapted, ST5 isolates are a widespread and successful
hospital‐acquired MRSA lineage. The pathogenicity of ST5 isolates may be associated with the
capacity and ease with which they acquire mobile genetic elements.
1.13 Food safety following natural disasters, and conflict
Following natural disasters, it is essential that safe water and food are available. The victims
may be suffering from injuries, shock, disorientation and fear. The risk of further illness will
be high due to poor hygiene, inability to cook and the lack of toilet facilities. Hence food and
water can quickly become contaminated with microbial pathogens causing hepatitis A, typhoid
fever, cholera and dysentery. To help governments in their planning and response to natural
disasters, the WHO has developed the guide Ensuring Food Safety in the Aftermath of Natural
Disasters (see www.who.int/foodsafety/foodborne_disease/emergency/en/). It offers specific
advice to those involved in food storage, handling and preparation during disaster situations.
In summary:
1 Preventive food safety measures in the aftermath of natural disasters. All water should be
treated as contaminated with surface water unless it is boiled or otherwise made safe. Only
after treatment can it be consumed or used in preparing food. However, the food may still
contain chemical hazards. Agricultural areas should be assessed for where food can still be
harvested or where food has been safely stored after harvesting.
2 Inspecting and salvaging food. All food stocks should be inspected and assessed for their
safety. Canned foods with broken seams, serious dents or leaks, and jars with cracks should
be discarded. Food deemed as safe should be segregated from other foods. In areas of flooding,
Foodborne infections
43
food should be stored in a dry area. Mould growth (and possible toxin production) is more
likely to occur on vegetables, fruits and cereals that are stored under moist conditions, or
have become wet. Refrigerated food, in particular meat, fish, poultry and milk, that can no
longer be kept cold should be consumed before it has been in the ‘danger zone’ (5–60°C) for
more than 2 hours. Other foods, normally refrigerated, can be kept for longer than 2 hours,
but should be discarded if showing signs of spoilage.
3 Provision of food after a natural disaster. When cooking facilities become re‐established it is
usual to distribute dried food. Therefore, instructions on food preparation, especially the
crucial need for safe water not only for reconstitution, but also washing hands and utensils,
will be needed.
1.14 Food microbiology, foodborne diseases and climate change
There is now widespread consensus that the Earth’s climate is changing, especially in regions
that will affect humans. With respect to food production global climate change may have various effects, some of which may include the microbial safety of food (Tirado et al. 2010; Lake
and Bakker 2018). The geographic distribution and production of crops used for our staple
diet and the phyllosphere microflora of those crops may be strongly affected by climate change.
A few examples are given below.
Aspergillus flavus is able to grow under high temperatures and drought conditions and can
produce highly toxic mycotoxins called aflatoxins (Section 5.4.1). It is able to persist under
extreme heat and dry conditions and is an increasing problem in the Mediterranean and other
temperate regions (Cotty and Jamie‐Garcia 2007; Perrone et al. 2014). For example, the impacts
of climate change have been observed in Serbia, where no contamination occurred previously,
but prolonged hot and dry weather in the year 2012 resulted in 69% of maize plants being
contaminated with A. flavus. A similar case was also found in Hungary, where the increase in
A. flavus contamination may be due to climate change conditions.
The world’s largest agri‐food exporters include countries such as Brazil and Argentina and
parts of Asia including China and India. These are also areas predicted to be impacted by climate change. Therefore, a greater understanding of the effect of climate change on fungal
contamination and mycotoxin production is needed for food security.
Warming seas will have an effect on the distribution of bacterial pathogens. Vibrio vulnificus
is rarely isolated from waters with salinities greater than 2%, consequently it is not found in
regions such as the Mediterranean Sea, and hence no reported infections. It also rarely occurs
when water temperatures are less than 13°C, so the vast majority of cases occur in the warmer
summer months of May to October. Vibrio vulnificus is known to enter a viable but non‐
culturable state (VBNC; Section 6.2.3) at temperatures below 13°C. Within these limits,
this pathogen occurs in estuarine environments worldwide, but with an increasing incidence
and geographic distribution due to global climate change. Similarly, the rise in sea water
temperature from 1982 to 2010 in the Baltic Sea coincides with the increase in Vibrio infections
in the Baltic region and western North Sea, especially in 2006 when there was a heatwave
(Baker‐Austin et al. 2013).
2 Basic aspects
2.1 The human intestinal tract
The human intestinal tract is approximately 30 ft. (~9 m) long, and is divided into a number of
regions: oesophagus, stomach, small intestine, large intestine and anus (Figure 2.1). In the
mouth food is chewed, which breaks it into smaller pieces and mixes it with saliva. On
swallowing, the food passes through the pharynx and oesophagus into the stomach. The
stomach produces gastric enzymes (endopeptidases, gelatinase and lipase) to start the
breakdown of food components, and has a low acidic pH (~pH 2). Most digestion and
absorption occurs in the small intestine, which is about 20 ft. (~6 m) long. The structure of the
small intestine maximises the area available for absorption. The surface of the mucosa is
convoluted and folded. The surface is covered with finger‐like projections called villi, which
are, in turn, covered with absorptive cells. The effective surface area of the mucosal cells is
further increased by the microvilli that occur on the luminal membrane of the enterocyte
(Figure 2.2). The brush border of the enterocytes contains various enzymes including many
disaccharides such as maltase, isomaltase, sucrase and lactase. These are involved in both the
digestion and absorption of carbohydrates. Pancreatic enzymes, which include trypsin,
chymotrypsin, carboxypeptidase, amylase, lipases, ribonuclease, deoxyribonuclease,
collagenase and elastase, assist in digestion. Also bile salts secreted from the liver aid the
absorption of fats. The tissue underneath the epithelial cells contains blood capillaries that
absorb monosaccharides and amino acids, and lymph capillaries to absorb fatty acids and
glycerol. Mucosal enzyme levels are affected by bacterial activity and lactose deficiency is a
sensitive indicator of the colonisation of the small intestine by pathogenic bacteria. Interactions
between the cell membranes and the luminal contents are facilitated by the glycocalyx, a
complex mucus layer overlaying the enterocytes.
The small intestine is the site where major absorption (>80%) occurs, but is also perturbed
by many intestinal infections, leading to acute diarrhoea and dehydration. For example, the
cholera toxin inhibits sodium uptake, and stimulates chloride secretion (Figure 2.3). This
results in fluid and electrolyte loss. Undigested food enters the colon, which has a neutral pH
and a slow transit time (up to 60 h).
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
45
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The microbiology of safe food
Mouth
Stomach
Duodenum
Jejunum
Small
intestine
Ileum
Colon
and
appendix
Large
intestine
Anus
Figure 2.1 The human intestinal tract.
2.2 The normal human intestinal flora
In the womb, the intestinal tract of the human foetus is microbiologically sterile. However,
during birth the neonate acquires a microbial flora from the vagina, contact with the environment and through feeding. Consequently a dense, complex bacterial community becomes
established in the intestinal tract (O’Hara and Shanahan 2006). The maturation of the immune
system requires continual stimulation from the developing gut flora. The lack of immunity
development has been linked with an increase in prevalence of atopic diseases: the ‘hygiene
hypothesis’ (Section 1.8). The intestinal flora changes in relationship to diet, age and disease.
It is a complex ecosystem and may have a number of effects on the health of the host.
Microbiome studies of the infant and adult intestines based on high‐throughput sequencing
(Section 14.1) have significantly expanded the study of the human intestinal flora. This is primarily because it is culture‐independent and is therefore not dependent upon the use of
numerous isolation agars, and incubation conditions. This enables larger and more in‐depth
studies to be undertaken, including the interaction between the intestinal flora, immune status
and cognitive behaviour (Fung et al. 2016; Feng et al. 2018). The role of the intestinal microbiome in multiple diseases identifies it as a potential therapeutic target through the ingestion of
live probiotic bacteria or their modulation by dietary prebiotics.
Microvili
Lamina propria
Villus crypt
Figure 2.2 Gut mucosal structure.
Intestinal lumen
Vibrio cholerae
K+ Na+ HCO3– Cl– H2O
Type II secretion
system
Neuramidase
A1–A2:B5 toxin
A1–A2:B5 toxin
GM1 ganglioside
CFTR
Cystic fibrosis transmembrane
A1–A2
A2
A1
cAMP-dependent protein kinase A
G protein
Adenylate cyclase
cAMP
GTPase inhibited
Figure 2.3 Osmotic balance; NaCl flux across gut mucosa.
Mucosal cell
48
The microbiology of safe food
Bacterial colonisation of neonates starts soon after birth and facultative anaerobic bacteria
can initially be detected in faecal samples indicating their presence in the large intestines.
These organisms remove oxygen and subsequently lower the redox potential, which enables
strict anaerobes to grow. In vaginally delivered neonates the first colonising bacteria are of
maternal origin. In Caesarean section‐delivered neonates, the environment and hospital staff
are a major source of the colonising bacteria. After this initial colonisation, the diversity of the
subsequent bacterial flora community is influenced by the diet.
Human breast milk is not necessarily sterile, and can have low numbers of streptococci,
micrococci, lactobacilli, staphylococci, diphteroids and bifidobacteria. Breast‐fed infants are
often colonised by staphylococci due to increased contact with the mother’s skin during feeding. In breast‐fed full‐term infants, Gram‐positive bifidobacteria, lactobacilli and streptococci
dominate. The intestinal microbial flora of formula‐fed infants is initially more diverse than
that of breast‐fed infants. Instead, the predominant flora is a mixture of Enterobacteriaceae
(Escherichia coli and Klebsiella species), Staphylococcus, Clostridium, Bifidobacterium,
Enterococcus and Bacteroides species. Despite this common distinction between breast‐ and
formula‐fed infants there is a significant issue if the neonate is born prematurely (low birth
weight).
Premature neonates do not have the teat/suckling reaction and need to be fed either the
mother’s milk or reconstituted formula through nasogastric tubes. These tubes rapidly
become colonised with a large variety of bacteria, yeast and fungi. For example, single nucleotide polymorphism (SNP) analysis has shown the colonisation of the infant intestines by
antibiotic resistance‐encoding bacteria (Enterococcus faecalis and Enterobacter hormaechei),
which were <20 SNPs different from those recovered from the faeces (Hurrell et al. 2009;
Ogrodzki et al. 2017).
The intestinal flora diversity changes at weaning with the introduction of solid food, and the
two groups (breast and formula fed) become indistinguishable and resemble the adult flora.
Breast milk is not sterile and can contain bacteria from the mother’s skin cells; however, the
initial portion of breast milk (colostrum) will contain the mother’s antibodies, giving the neonate a level of protection. However, expressed breast milk can be contaminated by the preparation equipment and has caused severe infections (Bowen et al. 2017). While ready‐to‐feed
formula is commercially sterile, it can become contaminated through use and needs to be
discarded if not used within a short period of time. Powdered infant formula is not manufactured as a sterile product but must conform to strict microbiological criteria with respect to
absence of Salmonella serovars and Cronobacter species, as well as a limited number of
Enterobacteriaceae (See Sections 4.6 and 11.7).
The adult intestinal flora is a complex ecosystem, which is ~55% of the solids and is dominated by strict anaerobes (Table 2.1). The indigenous flora is composed of the normal flora,
micro‐organisms that persist in the large intestines and the transient autochthonous flora.
There are ~1800 genera representing ~16 000 species in the human intestine microbiome. Of
these, only ~20% have been cultured. As stated above, the adult intestinal flora is primarily
composed of a number of strictly anaerobic bacteria. The dominant bacterial species belong to
the Gram‐negative Cytophaga‐Flavobacterium‐Bacteroides (23%) and the Gram‐positive low
GC% Firmicutes (64%) phyla. The Proteobacteria (including Enterobacteriaceae) only form a
minor component (~8%). Commonly isolated genera are:
1 Bacteroides species such as Bacteroides fragilis. These are Gram‐negative, non‐spore‐forming rods. They produce volatile and non‐volatile fatty acids (VFA and n‐VFA): acetic,
succinic, lactic, formic, propionic, N‐butyric, isobutyric and isovaleric acids.
Basic aspects
Table 2.1 Microbial flora of the human intestinal tract.
Organism
Cell density (cfu/g)a
Protozoan parasites
Ascaris
Enteric viruses
Enteroviruses
Rotaviruses
Adenovirus
Enteric bacteria
Acidaminococcus fermentans
Bacteroides ovatus
Bacteroides uniformis
Bacillus coagulans
Bacteroides eggerthii
Bacteroides merdae
Bacteroides stercoris
Bifidobacterium bifidum
Bifidobacterium breve
Clostridium cadaveris
Clostridium clostridioforme
Clostridium innocuum
Clostridium paraputrificum
Clostridium perfringens
Clostridium ramosum
Clostridium tertium
Coprococcus cutactus
Enterobacter aerogenes
Enterococcus faecalis
Escherichia coli
Eubacterium limosum
Eubacterium tenue
Fusobacterium mortiferum
Fusobacterium naviforme
Fusobacterium necrogenes
Fusobacterium nucleatum
Fusobacterium prausnitzii
Fusobacterium varium
Klebsiella pneumoniae
Klebsiella oxytoca
Lactobacillus acidophilus
Lactobacillus brevis
Lactobacillus casei
Lactobacillus fermentum
Lactobacillus leichmannii
Lactobacillus minutus
Lactobacillus plantarum
Lactobacillus rogosa
Lactobacillus ruminis
Lactobacillus salovarius
Megamonas hypermegas
Megasphaera elsdenii
Methanobrevibacter smithii
Methanosphaeraa stadtmaniae
106–107
104–105
103–107
1010
1012
107–108
109–1010
108–109
108–109
107–108
105–106
105–106
106–107
108–109
106–107
105–106
107–108
107–108
107–108
Undetectable–109
Undetectable–109
(Continued)
49
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The microbiology of safe food
Table 2.1 (Continued)
Organism
Morganella morganii
Peptostreptococcus assccharolyticus
Peptostreptococcus magnus
Peptostreptococcus productus
Proteus mirabilis
Salmonella serovars
Shigella species
Veillonella parvula
Indicator bacteria
Coliforms
Faecal coliform
Cell density (cfu/g)a
108–109
105–106
104–1011
105–109
105–106
107–109
106–109
Sources: Haas et al. (1999) and Tannock (1995).
a
Values are given as concentration per gram of faeces as representative of the
large intestinal tract.
2 Bifidobacterium species, such as Bifidobacterium bifidium. These are Gram‐positive, non‐
spore‐forming rods with characteristic club‐shaped ends. They produce acetic and lactic
acids (3:2 ratio).
3 Clostridium species, such as Clostridium innocuum. These are Gram‐positive spore‐forming
rods.
4 Enterococcus species, such as Enterococcus faecalis. These are Gram‐positive cocci that are
aerotolerant. They are in Lancefield group D and can grow in 6.5% NaCl and under alkaline
conditions <pH 9.6.
5 Eubacterium species are Gram‐positive non‐spore‐forming rods. They produce butyric,
acetic and formic acids.
6 Fusobacterium species are Gram‐negative non‐spore‐forming rods that produce N‐butyric
acid.
7 Peptostreptococcus species are Gram‐positive cocci that can degrade peptone and amino
acids.
8 Ruminococcus are Gram‐positive cocci that produce acetic, succinic and lactic acids, ethanol,
carbon dioxide and hydrogen from carbohydrates.
As given above, the dominant genus of intestinal bacteria in animals and humans is the
Bacterioides (1011 cfu/g), which are Gram‐negative, strict anaerobes. The intestinal microflora
also contains Gram‐positive non‐sporing strictly anaerobic rods. There are many other genera
of organisms present, including Bifidobacterium, Lactobacillus and Clostridium species. Gram‐
positive cocci are numerically important in the intestinal tract, including Peptostreptococcus
and Enterococcus species. The facultative Gram‐negative rods, such as Proteus, Klebsiella and
E. coli, are not numerically important, being outnumbered by Bacteroides by ~1000:1.
Escherichia coli are Gram‐negative, catalase‐positive, oxidase‐negative, facultatively anaerobic short rods (Section 4.4). They are members of the Family Enterobacteriaceae and most
isolates ferment lactose. The majority of E. coli serotypes are not pathogenic and are part of the
normal intestinal flora (~106 organisms/g). Consequently they are used as indicator organisms, as one of the ‘coliforms’, to indicate faecal pollution of water raw ingredients and foods
(Section 4.1.1). Non‐pathogenic strains of E. coli typically colonise the infant gastrointestinal
tract within a few hours after birth. The presence of this bacterial population in the intestine
Basic aspects
51
suppresses the growth of harmful bacteria and is important for synthesising appreciable
amounts of B vitamins. Escherichia coli usually remains harmless when confined to the intestinal lumen. However, in debilitated or immuno‐suppressed humans, or when gastrointestinal
barriers are violated, even normal, ‘non‐pathogenic’ strains of E. coli can cause infection.
As given earlier, the human intestinal flora is the focus of many microbiome and metagenomic
studies to reveal the diversity of organisms, and their interaction with intestinal function and
illness. Over the next few years our knowledge will considerably increase, and in turn we will
better understand their respective roles in foodborne illness.
2.3 Host resistance to foodborne infections
The human body has a variety of non‐specific (innate) and specific immune system mechanisms to protect us from foodborne infections. However, many factors can weaken the defences
and increase the risk of illness. Additionally, some foodborne pathogens are able to evade the
body’s defence mechanisms.
The innate immunity is the initial host defence mechanism against micro‐organisms in the
intestinal tract. The high acidity and pepsin of gastric juices kill many microbial pathogens. The
enzymes in pancreatic secretions and bile acids are also antimicrobial. The epithelial lining is
constantly being replaced, and the constant peristaltic movement keeps the intestinal contents
and microbial flora in the small intestines low compared with the colon, which is a more static
environment. The gastric and intestinal epithelia are lined with a layer of mucus that protects
against proteolytic attack and microbial attachment. It also contains antibacterial agents, such as
secretory immunoglobulin A and enzymes. Mucus also acts as a barrier preventing large‐
molecular‐weight compounds from passing into the enterocytes in the epithelial layer.
The intestinal tract is particularly prone to microbial penetration and toxin uptake, due to
the large surface area, the level of nutrients and high absorptive capacity. However, it is also
equipped with an array of defence mechanisms. The host defence system is able to distinguish
commensal organisms from potential pathogens and elicit subsequent responses to infection.
The epithelium provides the first sensory line of defence. There is active sampling of resident
bacteria, pathogens and other antigens by three main types of immunosensory cell: surface
enterocytes, M cells and dendritic cells.
Surface enterocytes secrete chemokines and cytokines, which result in direct innate and
adaptive immune responses at the infected site. The M cells overlie lymphoid follicles. These
sample the environment and transport luminal antigens to subadjacent dendritic cells and
other antigen‐presenting cells. In turn, the intestinal dendritic cells directly sample gut contents by either entering or extending dendrites between surface enterocytes without disrupting
tight junctions. These dendritic cells can ingest and retain live commensal bacteria and travel
to the mesenteric lymph node where immune responses to commensal bacteria are induced
locally. Consequently, the mesenteric lymph node prevents access of commensal bacteria to
the internal milieu.
As a stable ecosystem, the normal intestinal flora reduces the opportunities for microbial
infection. The normal flora will occupy any binding sites on the enterocytes, and decrease the
lumen pH due to their production of VFA. Microbes that do penetrate the epithelial barrier are
likely to encounter mononuclear phagocytes (blood monocytes or tissue macrophages), and
polymorphonuclear phagocytes.
The innate immune system prevents infection by enteric microbes, and the entry of large
microbial toxins. However, a variety of factors may depress it, such as the use of antacids, which
52
The microbiology of safe food
suppress gastric acid production; reduction in normal gut flora due to antibiotic usage; and
damage to the epithelial barrier. This is when the specific immune system becomes important.
The specific immune system recognises antigens that are high‐molecular‐weight (>10 kD)
proteins or polysaccharides. These include the bacterial cell wall, capsule, lipopolysaccharide
(LPS), flagella, fimbriae and toxins. Many specialised cells are involved in the humoral
(antibody‐mediated) and cell‐mediated immune reactions to infection.
Many different micro‐organisms cause gastroenteritis or systemic infection by overcoming
the intestinal defence mechanisms. There are essentially five pathogenic mechanisms:
1 Bacteria that produce toxin(s), but do not adhere to or multiply in the intestinal tract; i.e.
Bacillus cereus, Staphylococcus aureus, Clostridium perfringens and Clostridium botulinum.
2 Bacteria that adhere to the intestinal tract epithelium and excrete a toxin; i.e. enterotoxigenic E. coli and Vibrio cholerae.
3 Bacteria that adhere to and damage the brush border microvilli; i.e. enteropathogenic E. coli,
and enterohaemorrhagic E. coli.
4 Bacteria that invade the mucosal layer and initiate intracellular multiplication; i.e. Shigella
species.
5 Bacteria that penetrate the mucosal layer and spread to the underlying lamina propria and
lymph nodes; i.e. Yersinia species.
The antigen sampling process of M cells, in the Peyer’s patches, may be an entry route. Motile
phagocytes may ingest a bacterium from the lumen, which survives intracellular killing by the
lysosomes, and spreads systemically.
The immune system clears high‐molecular‐weight toxins. However, low‐molecular‐weight,
non‐polar compounds such as mycotoxins are not cleared and hence these are rapidly absorbed
through the intestinal tract. They are metabolised in the liver by a process called ‘biotransformation’. However, biotransformation can make a compound more toxic. For example, aflatoxin
B1 is converted to a reactive epoxide that can react with nuclear DNA causing DNA damage
that may lead to liver cancer (see Section 5.4).
2.4 Bacterial cell structure
2.4.1 Morphology
Bacteria are characteristically unicellular organisms. Essentially, they are bags of self‐replicating information within a controlled micro‐environment that is semi‐protected from extremes
of variation in the external environment by a semi‐permeable, cytoplasmic membrane.
Bacterial morphology can be straight or curved rods, cocci or filaments depending upon the
organism concerned. The morphology of the organism is consistent with the type of organism
and to a lesser extent with the growth conditions.
Bacteria in the genera Bacillus, Clostridium, Desulphotomaculum, Sporolactobacillus and
Sporosarcina form spores in the cytoplasm under certain environmental stress‐related
conditions. The spore is more resistant to heat, drying, pH, etc. than the vegetative cell. Hence
it enables the organism to persist until more favourable conditions when the spore can
germinate and grow into a vegetative cell.
2.4.2 Cell membrane structure and the Gram stain
The structural integrity of the cytoplasmic membrane is maintained by the peptidoglycan
layer, which allows the cell to cope with extremes in osmolarity in the external environment.
There is, however, a price to pay for maintaining homeostasis within the cytoplasm. This is in
Basic aspects
53
the energy costs of transporting nutrients into the cell and harmful materials out of the cell.
There are many specialised transport proteins within the cell, which are from five separate
super‐families. The super‐families contain both permeases that transport materials in to the
cell, and efflux pumps that transport materials out of the cell. The energy for transportation is
derived from hydrolysis of adenosine triphosphate, ion gradients across the cytoplasmic
membrane or from hydrolysis of phosphoenolpyruvate.
Gram‐negative organisms have an additional structure in the cell wall called the outer
membrane that acts as a barrier to limit diffusion of harmful materials into the cell. The outer
membrane, together with efflux pumps, enables Gram‐negative bacteria to survive and thrive
in environments that are harmful to other types of micro‐organisms. The outer membrane
would also limit diffusion of nutrients into the cell, but there are channels in the outer
membrane called porins (see Figure 2.4). These allow passive diffusion of nutrients into the
periplasmic space, but may have size exclusion limits and some have specificities for the charge
on molecules. These proteins have evolved to allow some Gram‐negative organisms to survive
in the gut where there are bile salts, which act as detergents, present at around 20 mM. After
nutrients have crossed into the periplasmic space they are then taken up by substrate‐specific
permeases and transported across the cytoplasmic membrane. Some of the permeases are
highly specific for their substrates, particularly those of the phosphotransferase system (PTS).
Others, particularly those of the proton symport type, are much less discriminatory.
Christian Gram was a Danish microbiologist who wanted to visualise bacteria in muscle
tissue. He tried a range of histological staining protocols and eventually came up with the,
nowadays ubiquitous, ‘Gram stain’ procedure. It was noted by Christian Gram that the bacteria
either stained dark blue or red. This was due to the precipitation of crystal violet with Lugol’s
Gram-negative organism (i.e. S. enteritidis)
O antigen
Lipopolysaccharide (LPS)
Gram-positive organism (i.e. St. aureus)
Core region
Lipid A
Outer membrane
Teichoic
acids
Porin
(three in cluster)
Peptidoglycan
Periplasm
Lipid bilayer
Inner membrane
Figure 2.4 General structure of the bacterial cell wall.
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The microbiology of safe food
iodine in the cell cytoplasm, which could not be extracted using solvents such as ethanol or
acetone from certain organisms (Gram‐positives) but was extracted from others (Gram‐
negatives). Since the latter cells are no longer stained by the crystal violet–iodine complex,
counterstaining is required with safranine or basic fuschin.
The differential extraction of the crystal violet–iodine complex is due to differences in the
cell wall structure (Figure 2.4). Gram‐positive organisms have a thick cell wall surrounding the
cytoplasmic membrane. This is composed of peptidoglycan (also known as murein) and
teichoic acids. The Gram‐negative organisms have a thinner cell wall that is surrounded by an
outer membrane. Hence Gram‐negative organisms have two membranes. This outer membrane
differs from the inner membrane and contains the molecule known as LPS. Since peptidoglycan
is the site of action for the original penicillin antibiotic (penicillin G) the difference in the cell
wall structures explains why the antibiotic was initially so effective against streptococci and
staphylococci (both Gram‐positive) rather than Gram‐negative organisms, such as E. coli.
Consequently the semi‐synthetic penicillins were developed to widen the range of sensitive
organisms to penicillin.
2.4.3 Lipopolysaccharide (LPS, O antigen)
The outer membrane of Gram‐negative organisms contains the molecule LPS. It is composed
of three regions: lipid A, core and O antigen (Figure 2.5). Lipid A anchors the molecule in the
outer membrane. It is toxic to human cells and so is also known as ‘endotoxin’. During an
infection it causes fever symptoms and is therefore referred to as ‘pyrogenic’. This is a virulence
factor for Gram‐negative organisms such as Salmonella and Chlamydia.
The LPS core region is composed of sugar molecules, the sequence of which reflects the
organism’s identity. The O‐region is more variable than the core region. In some organisms the
O‐region may only contain a few sugar residues, whereas in others there are repeating units of
sugars. Isolates of a single species vary in the amount of O‐region present and this gives rise to
the ‘smooth’ and ‘rough’ variants due to colony morphology. The antigens are on the body of
the organism and are known as the ‘somatic’ or ‘O antigens’. ‘O’ is for ‘Ohne’ the German for
‘without’, which originally referred to non‐swarming or non‐flagellated forms. The LPS structure is resistant to boiling for 30 minutes and is therefore also referred to as a ‘heat‐stable’
antigen. One of the factors causing fatality following Gram‐negative septicaemia is that the
n repeating units
Lipid A
Core polysaccharide
Fatty acid tail
Phosphate group
O antigen, composed of repeating sugar units
Sugar unit
Figure 2.5 The structure of the lipopolysaccharide (LPS) molecule of Gram‐negative organisms, such as
Salmonella.
Basic aspects
55
presence of LPS causes the overproduction of tumour necrosis factor (TNF), which leads to
overstimulation of nitric oxide synthase.
The O antigen is used in serotyping as it induces antigen production, unlike the K antigen,
which is also found on the surface of Gram‐negative organisms.
2.4.4 Flagella (H antigen)
Most rod‐shaped (and a few coccoid) bacteria are motile in liquid media. Motility occurs due to
the rhythmic movement of thin filamentous structures called flagella. The cell may have a single
flagellum (monotrichus) or a tuft of flagella (lophotrichus) at one or both poles, or many flagella
(peritrichous) over the entire surface. The proteinaceous nature of the flagellum gives rise to its
antigenicity. The flagellar antigen is called the H antigen. ‘H’ is from the German word ‘Hauch’
meaning ‘breath’, which originated from describing the appearance of Proteus swarming on
moist agar plates being similar to the light mist caused by breathing on cold glass. Flagella are
denatured by heat (100°C, 20 minutes) and therefore the H antigen is referred to as ‘heat‐labile’
(LT) in contrast to the heat‐stable LPS antigen. Flagella are also denatured by acid and alcohol.
Salmonella serovars may express two flagellar antigens. Phase 1 antigen is represented by
letters, Phase 2 antigen by numbers in the serotyping (Kauffmann–White scheme) of
Salmonella serovars. This is covered in more detail in Section 4.3.2. A culture may be entirely
expressing one phase (monophasic culture), which will give rise to mutants in the other phase
(diphasic culture), especially if the culture is incubated for more than 24 h. Escherichia coli has
in the order of 180 O antigens and 56 H antigens. Escherichia coli O157:H7 is a very pathogenic
variety of E. coli that is recognised by serotyping the strain’s O and H antigens, though these are
unrelated to the toxins.
2.4.5 Capsule (K and Vi antigen)
Some bacteria secrete a slimy polymeric material composed of polysaccharides, polypeptides
or polynucleotides (Schmid et al. 2015). In Enterobacteriaceae it may include colanic acid, K
antigen, cellulose and the Enterobacteriaceae common antigen. The familiar K1 and K12
designations of E. coli strains refer to the K antigen (Whitfield 2006). Unlike the O antigen, the
K antigen does not stimulate the immune system and therefore is not used for serotyping. If
the layer is very dense then it can be visualised as a capsule. The possession of the capsule
endows a resistance to white blood cell engulfment. The capsule’s antigenicity is called the Vi
antigen and was originally thought to be responsible for the virulence of S. Typhi. See
Section 4.3.2 for more information on Salmonella serotyping.
2.5 Bacterial toxins and other virulence determinants
The ability of micro‐organisms to cause disease is dependent up the possession of various
virulence determinants. These include the previously covered LPS (pyrogenic), capsule
(engulfment evasion), flagella (motility towards target cells), outer membrane vesicles as well
as adhesins, invasins and toxins. To infect the host, most pathogens must adhere to the intestinal surface to overcome peristalsis. Adhesins are molecules on the cell surface composed of
glycoproteins or glycolipids, which bind to specific host surface structures. Fimbriae, also
known as pili, are hair‐like structures on the bacterial surface. Bacterial pathogens may have
several different adhesins that result in host and tissue specificity. Invasins are molecules that
enable the pathogen to invade a host cell where they can persist intracellularly. Salmonella
serovars, Shigella species and Listeria monocytogenes are able to invade the intestinal epithelial
56
The microbiology of safe food
layer. Listeria has a surface protein, ‘internalin’, to facilitate invasion. Some pathogens have
Type III secretory systems that pump bacterial proteins into the host cell. These cause changes
on the host cell surface, such as membrane ruffling and macropinocytosis, leading to engulfment and internalisation. These are covered in more detail for each pathogen in Chapter 4.
2.5.1 Bacterial endotoxins and exotoxins
Bacterial endotoxins and exotoxins are potent inducers of inflammatory cytokines, which
include TNF, interleukin‐1β (IL‐1β), gamma interferon (IFNγ) and chemokines. Together
these form the innate immune response. However, excessive production can result in mortality
as with sepsis and toxic shock syndrome. While pre‐exposure to exotoxins such as LPS can
enhance cytokine production, pre‐exposure to endotoxin often leads to tolerance.
There are a number of different bacterial toxin definitions, some of which overlap:
1 Exotoxins. These are essentially the same as ‘bacterial protein toxins’, and are also called
‘secreted toxins’. The term ‘exotoxin’ emphasises the nature of the substance, being extracellular, excretory, heat‐labile and antigenic. They exert their biological activity (often lethal)
in minute doses and are released during the death phase of the organism. These are considered in more detail below.
2 Enterotoxins are exotoxins that result in extremely watery diarrhoea. They are further categorised by their mode of action:
a Enterotoxins that induce illness by direct action on gut tissue, biochemical and/or structural lesions, leading to diarrhoea.
b Enterotoxins that cause a specific action (i.e. net fluid loss) in the gut.
c Enterotoxins responsible for elevating cyclic adenosine monophosphate (cAMP) levels,
which subsequently causes ion flux changes and excess fluid secretion.
3 Cytotonic enterotoxins is the term applied to those toxins, such as cholera toxin, that induce
net fluid secretion by interfering with biochemical regulatory mechanisms without causing
overt histological damage.
4 Cytotoxic enterotoxins induce actual damage to intestinal cells as a necessary prelude to
onset of net fluid secretion. Cytotoxins can be a protein or LPS (endotoxin) and may also be
called ‘cell‐associated’ toxins and ‘cytolysins’. They are invasive and kill target cells. Their
mode of action is either intracellular or by formation of pores within cells. Intracellular
cytotoxins inhibit cellular protein synthesis and/or actin filament formation. Cytotoxins
that cause pore formation in target cells can also be detected by their lytic activity upon
erythrocytes, and hence are also known as ‘haemolysins’. The result of cytotoxin invasion is
inflammatory diarrhoea, which often contains blood and leukocytes.
5 Endotoxins are heat‐stable, cell‐associated, complex LPS structures. The LPS is part of the
outer membrane of Gram‐negative bacteria (Figure 2.5). Lipid A is the part of the LPS that
is responsible for toxicity. They cause toxic shock, inflammation and fever as occurs with
Salmonella serovar infections. This is the result of monocyte/macrophage activation leading
to auto‐amplificatory loops. LPS (and pore‐forming exotoxins) also activate the inflammasome, which leads to the release of IL‐1β and IL‐18.
6 Cytolethal distending toxins (Cdt) affect host cell cycle regulation. These have been found
in a variety of unrelated organisms: Campylobacter jejuni, E. coli, Shigella dysenteriae,
Haemophilus ducreyi and Actinobacillus actinomycetemcomitans (Scuron et al. 2016). The
toxin blocks cells in G2. Cdt inhibits the dephosphorylation of the protein kinase cdc2 and
this prevents the cells entering into mitosis.
Exotoxins are toxic bacterial proteins. The term is derived from the early observation that
many bacterial exotoxins were excreted into the medium during growth. This differentiated
Basic aspects
57
them from endotoxins (LPS). This differentiation is not exact since some exotoxins are localised in
the cytoplasm or periplasm and are released upon cell lysis. The naming of exotoxins is not systematic. Some toxins are named to indicate the type of host cell. Exotoxins that attack a variety of different cell types are called cytotoxins, whereas exotoxins that attack specific cell types can be
designated by the cell type or organ affected, such as neurotoxin, leukotoxin, hepatotoxin and cardiotoxin. Exotoxins can also be named after their mode of action, i.e. lecithinase produced by Cl.
perfringens. However exotoxins can also be named after the producer organism, or the disease that
they cause. Two examples are (i) cholera toxin, which causes cholera and is produced by V. cholerae,
and (ii) Shiga toxin, which causes bacterial dysentery and is produced by Shigella species.
Some toxins have more than one name, such as the Shiga‐like toxin of E. coli O157:H7,
which is also called a verotoxin since it affects the mammalian Vero cell culture line. This
confusion is reflected in alternative uses of the terms verocytotoxigenic E. coli (VTEC) and
Shiga toxin‐producing E. coli (STEC) (Section 4.4).
Exotoxins can be divided into four groups:
1 Those that act at the cell membrane.
2 Those that attack the membrane.
3 Those that penetrate the membrane to act inside the cell.
4 Those that are directly transported from the bacterium into the target eucaryotic cell by a
secretion system.
Food poisoning by St. aureus is specifically caused by its production of enterotoxins. These
enterotoxins are low molecular weight proteins (26,000–34,000 Da) that can be differentiated
by serology into a number of antigenic types. They share a common sequence (and hence
phylogenetic relationship) with streptococcal pyrogenic exotoxins as shown in Figure 2.6.
Toxins that Act at the Cell Membrane
Although proteins are normally sensitive to high temperatures (such as 100°C; LT toxins) there
are a few small exotoxins that are heat stable (ST toxins). The heat‐stable toxin of E. coli is a
peptide of 18–19 amino acids with three disulphide bonds. This structure is responsible for the
toxin’s resistance to heat denaturation. The toxin causes diarrhoea since it binds to the
endogenous ligand guanylin, a peptide hormone that regulates salt and water homeostasis in
the gut and kidney (Figure 2.7). The B. cereus emetic toxin (also called cereulide) is a ring of
three repeats of four amino and/or oxy acids ‘‐D‐O‐leucine‐D‐alanine‐O‐valine‐L‐valine‐’. It
SEA
SEE
SEP
SEJ
SED
SEN
SEO
SEH
SEB
SEC3
SpSSA
SEG
SpeA
SEI
SEK
SEM
SEQ
SEL
Group 1
Group 2
Group 3
Spec
Figure 2.6 Phylogenetic analysis of Staphylococcus aureus enterotoxin and streptococcal pyrogenic toxins.
58
The microbiology of safe food
LT
STa
Adenylate
cyclase
Guanylate
cyclase
cAMP
increase
cGMP
increase
Figure 2.7 Mode of action of LT and ST toxins produced by pathogenic strains of Escherichia coli.
is plausible that this toxin binds to the 5‐HT3 receptor to stimulate the vagus afferent nerve,
leading to vomiting (see Section 4.16 for more detail).
Superantigens are toxins that act by stimulating T cells to release cytokines and so induce an
inappropriate immune response. Superantigens are produced by St. aureus and Streptococcus
pyogenes, and lack an AB subunit structure. One of the most studied is TSST‐1 (~22 kDa) from
St. aureus, which causes toxic shock syndrome (associated with the use of tampons).
Staphylococcus aureus also produces the enteroxins A–Q (~27 kDa), which are responsible for
food poisoning (see Section 4.13 for more detail).
Membrane‐Damaging Toxins
These toxins have A and B subunits that do not separate and act by disrupting the host cell
membranes, i.e. listeriolysin O. This group is subdivided into channel‐forming (pore‐forming)
toxins that allow cytoplasmic contents to leak out of the host cell. The thiol‐activated cholesterol‐
binding cytolysins (52–60 kDa) bind to the cholesterol of the host cell to form pores of about
30–40 nm. Examples include listeriolysin O (L. monocytogenes), perfringolysin O (Cl. perfringens)
and cereolysin O (B. cereus). These may sometimes be called ‘haemolysins’ due to the common
use of blood cells to detect the presence of a toxin. In the past they have also been termed ‘oxygen
labile’ and ‘sulphydryl activated’ toxins, though these terms are now recognised as misleading. The
second type is phospholipase C (PLC), which removes the charged head group from the lipid
portion of phospholipids. A number of both Gram‐positive and Gram‐negative bacteria produce
phospholipases. Listeria monocytogenes produces a phophoinositol‐specific PLC that enables the
organism to escape the vacuole after engulfment and a broad‐range PLC involved in cell‐to‐cell
spread (see Section 4.12 for more detail). Clostridium perfringens produces PLC also known as
α‐toxin, which has necrotic and cytolytic activity (Sakurai et al. 2004). Staphylococcus aureus
produces a β‐haemolysin.
Membrane Penetrating Toxins
The membrane penetrating toxins have a so‐called AB structure, where A is the catalytic subunit
and the B subunit binds to the host cell receptor. There are two common types of AB toxins:
1 A and B are joined in one molecule, though the structure can be disrupted to yield two
subunits joined by a disulphide bridge. Examples include botulinum toxins types A–F and
tetanus toxin (Figure 2.8). These are large (>150 kDa) single‐chain toxins that are proteolytically cleaved during activation and cellular entry. The botulinum toxin blocks the action of
peripheral nerves (Figure 2.9). See Section 4.3.9 for more detail.
Basic aspects
59
150 kDa toxin activated by protease activity, either gastric or clostridial
Toxin is a zinc-requiring endoprotease
Nicked AB toxin:
A, 50 kDa (light chain)
B, 100 kDa (heavy chain)
B subunit binds to sialic acid containing glycoprotein on
peripheral neurons
Toxin internalised into neuron
Toxin prevents release of the neurotransmitter acetylcholine
Consequently, nerve pulse transmission stops causing
flaccid paralysis
Figure 2.8 Structure and activation of Cl. botulinum toxin.
C
S
S
N
Protease cleavage
Heavy chain (100 kDa)
C
N
S
S
N
C
Light chain (50 kDa)
Figure 2.9 Cl. botulinum toxin mode of action.
2 AB5 where five B subunits (pentamer) form a doughnut‐like ring structure and possibly the A
subunit enters the cell through the central hole. Examples include cholera toxin, E. coli heat‐
labile toxin and the Shiga toxins (Figure 2.10). Cholera and Shiga toxins bind to glycolipid
ganglioside receptors on the host cell. The Shiga toxins attack 28S rRNA to depurinate adenine
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The microbiology of safe food
A subunit 32 kDA
B subunit 7.7 kDA
Figure 2.10 AB5 structure of Shiga toxin.
4324, which is involved in elongation factor 1‐mediated binding of tRNA to the ribosomal
complex and subsequently inhibits protein synthesis. The A subunit of Shiga toxin has
sequence and structural homology with the ricin family of plant toxins, which have an identical mode of action. The A subunit is activated by proteolytic cleavage on cell entry to yield two
fragments joined by a disulphide bridge, which is subsequently reduced: cholera toxin and
E. coli heat‐labile (LT) toxin ADP‐ribosylate G3, a heterotrimeric G protein involved in the
stimulation of adenylate cyclase (Figure 2.11). The A subunit of Gs is modified at Arg201,
which inhibits the GTPase activity. This keeps the Gs protein in the ‘on’ position, leading to
permanent activation of adenylate cyclase. The resultant high concentration of cAMP in the
gut epithelial cells causes massive fluid accumulation in the gut lumen and watery diarrhoea,
which can be fatal. Cholera toxin is chromosomally encoded on a phage, whereas E. coli LT
and ST toxins are plasmid‐encoded and Shiga toxin is chromosomally encoded.
Transported Toxins
Toxins in this group do not display toxic activity when purified from bacteria. They are transported directly from the bacterial cytoplasm to the eucaryotic cytoplasm by a complex array of
proteins that bridge the membranes of the two cell types. An example is the Type III secretion
system of Salmonella and E. coli O157. This secretion system is often encoded on pathogenicity
islands (PAIs), described in the next section. Bacteria known to produce such toxins include
Salmonella, E. coli, Shigella and Yersinia species.
2.5.2 Pathogenicity islands
PAIs are large (>30 kb) distinct chromosomal elements encoding virulence‐associated genes
(Table 2.2) (Schmidt and Hensel 2004; Bertelli and Brinkman 2018). Because the %GC content
of PAIs are often distinct from the rest of the bacterial DNA %GC content, it has been proposed
that they may have been acquired in the past by horizontal gene transfer from other bacterial
species. They are often found at tRNA loci. In addition to PAIs, there are shorter sequences of
DNA, termed ‘pathogenicity islets’, which are transferred between bacterial pathogens. PAIs
constitute major routes in the evolution of bacterial pathogens since in one acquisition they
Basic aspects
61
Vibrio cholerae ingested
Virulence genes expressed
in stomach
Adherence to small intestinal mucosa
Colonisation of small intestinal mucosa
Production of cholera toxin which
activates adenylate cyclase
Extensive fluid loss due to osmotic effect
caused by sodium loss into gut lumen.
Production of rice water stools
Figure 2.11 Mode of action of cholera toxin.
can transform a benign organism into a virulent one; for example, the PAI called locus of
enterocyte effacement (LEE) in E. coli pathovars.
Both enterohaemorrhagic E. coli and enteropathogenic E. coli (EHEC and EPEC) contain a
35‐kb PAI called the LEE island (Section 4.4). This encodes for a Type III secretion system and
other virulence factors that are essential for disease. It induces the attaching and effacing
lesions on enterocytes and encodes the secretion system for toxin transfer from the E. coli cell
to the host cell. This results in cytoskeletal rearrangements and the formation of a pedestal on
which the E. coli cell is located. Uropathogenic E. coli cause urinary tract infections. These have
a completely different PAI inserted in exactly the same site as EPEC strains. The PAI encodes
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The microbiology of safe food
Table 2.2 Pathogenicity islands of three important foodborne pathogens.
Pathogen
PAI designation
Size (kb)
G + C ratio
(PAI/host)
Escherichia coli
PAI I
PAI II
LEE (PAI III)
70
190
35
40/51
40/51
39/51
Salmonella
Typhimurium
SPI‐1
40
42/52
Vibrio cholerae
SPI‐2
SPI‐3
VPI
40
17
39.5
45/52
Unknown
35/46
Listeria monocytogenes
Listeria ivanovii
LIPI‐1
LIPI‐2
9
22
Phenotype
Haemolysin production
Haemolysin, P fimbriae production
Induction of attaching and effacing
lesions on enterocytes
Invasion of non‐phagocytic cells
Survival in macrophages
Survival in macrophages
Colonisation, expression of phage
CTXɸ receptor
Intracellular survival and spread
Cell and host trophism
Source: Adapted from Henderson et al. (1999).
PAI = Pathogenicity island.
for P fimbriae (an adhesin) and haemolysin (a toxin), which together are virulence factors
required for urinary tract colonisation. PAIs are covered in more detail with the specific pathogens E. coli (Section 4.4) and Salmonella (Section 4.3).
Although Yersinia and Shigella species have Type III systems on their plasmids, they have
other virulence attributes that are on the chromosome and not localised in islands.
Vibrio cholerae produces cholera toxin encoded by the ctxA and ctxB genes that are encoded
by the filamentous phage CTX. The bacterial receptor for phage infection is the toxin co‐regulated
pilus (TCP), which is also an important adherence determinant. TCP is found on the
39.5‐kb PAI called VPI in V. cholerae. It is believed that the acquisition of VPI enables
aquatic V. cholerae strains to colonise the human intestine and the subsequent generation
of epidemic and pandemic V. cholerae strains. Pathogenic strains of L. monocytogenes
contain LIPI‐1. The 9‐kb element encodes for six genes required for listeriolysin O (LLO),
a thiol‐activated haemolysin (hly), actA and plcB (responsible for intra‐ and intercellular
movement). A second island LIPI‐2 (22 kb) is found in L. ivanovii. This encodes for several
secreted internalin genes and the sphingomyelinase gene (smlC), which may be important in
the organism’s tropism for ruminants.
2.5.3 Bacterial toxins encoded in bacteriophages
Bacteriophages are involved in the transfer of virulence factors between pathogens. For example, the Shiga toxin of Sh. dysenteriae is encoded on a bacteriophage that is integrated in the
chromosome. Escherichia coli O157:H7 causes haemorrhagic colitis and haemolytic uraemic
syndrome and contains the Shiga toxin genes. It is plausible that a bacteriophage encoding the
Shiga toxin from Sh. dysenteriae was transferred to an EPEC strain and this led to the generation
of a new pathogen, EHEC. Under certain circumstances, the phage encoding the Shiga toxin
becomes lytic, multiples and subsequently releases the toxin. Another example of bacteriophage‐
encoded toxin is in V. cholerae, which produces cholera toxin encoded by the ctxA and ctxB genes.
These are encoded by the filamentous phage CTX. The bacterial receptor for phage infection is the
TCP, which is also an important adherence determinant. Consequently, the phage only infects
bacteria that already possess an essential adhesin, thus ensuring virulence.
Basic aspects
63
2.6 Microbial growth cycle
Microbial growth cycle is composed of six phases (See Figure 2.12):
• Lag phase: cells are not multiplying, but are synthesising enzymes appropriate for the environment. Lag times are more variable than growth rate possibly due to the effects of the
physiological history of the cell, and the environment.
• Acceleration phase: an increasing proportion of the cells are multiplying.
• Exponential (or log) phase: the cell population are multiplying by binary fission
(1‐2‐4‐8‐16‐32‐64, etc.). The cell numbers are increasing at such a rate that to graphically
represent them it is best to use exponential values (logarithms). This results in a straight line,
the slope of which represents the μmax (rate of maximum growth) and the doubling time ‘td’
(time required for the cell mass to increase twofold) can be determined.
• Deceleration phase: an increasing proportion of cells are no longer multiplying.
• Stationary phase: the rate of growth equals the rate of death, resulting in equal numbers of
cells at any given time. Death is due to the exhaustion of nutrients, the accumulation of toxic
end products and/or other changes in the environment, such as pH changes. The length of
the stationary phase is dependent upon a number of factors such as the organism and environmental conditions (temperature, etc.). Spore‐forming organisms will develop spores due
to the stress conditions.
• Death phase: the number of cells dying is greater than the number of cells growing. Cells that
form spores will survive longer than non‐spore‐formers.
The length of each phase is dependent upon the organism and the growth environment,
temperature, pH, water activity, etc. The growth cycle can be modelled using sophisticated
computer programs and leads to the area of microbial modelling and predictive microbiology
(see Section 2.10).
2.7 Death kinetics
2.7.1 Expressions
There are a number of expressions used to describe microbial death:
• D value: decimal reduction time. Defined as the time at any given temperature for a 90%
reduction (=1 log value) in viability to be effected.
Viable count (log10 cfu/ml)
10
9
Stationary
8
Exponential
7
6
5
4
Lag
3
2
Time
Figure 2.12 The microbial growth curve.
Death
64
The microbiology of safe food
• z value: temperature increase required to increase the death rate tenfold; or in other words
reduce the D value tenfold.
• P value: time at 70 °C. A cook of 2 minutes at 70 °C will kill almost all vegetative bacteria. For
a shelf life of 3 months the P value should be 30–60 minutes according to other risk factors.
• F value: this value is the equivalent time, in minutes at 250°F (121°C), of all heat considered,
with respect to its capacity to destroy spores or vegetative cells of a particular organism.
Since these values are mathematically derived they can be used in predictive microbiology
(Section 2.10) and microbiological risk assessment (Chapter 10).
2.7.2 Decimal reduction times (D values) and z values
To design an effective temperature treatment regime, it is imperative to have an understanding
of the effects of heat on micro‐organisms. The thermal destruction of micro‐organisms (death
kinetics of vegetative cells and spores) can be expressed logarithmically. In other words for any
specific organism, in a specific substrate and at a specific temperature, there is a certain time
required to destroy 90% (=1 log reduction) of the organism. This is the decimal reduction time
(D value). Plotting the survival numbers (as log10 cfu/ml) for an organism against time generally
gives a straight‐line relationship, which is more precisely known as a log‐linear relationship
(Figure 2.13 ).
The rate of death depends upon the organism, including the ability to form spores, and the
environment (Table 2.3). Free (or planktonic) vegetative cells are more sensitive to detergents
than fixed cells (i.e. biofilms). The heat sensitivity of an organism at any given temperature varies
according to the suspending medium. For example, the presence of acids and nitrite will increase
the death rate, whereas the presence of fat may decrease it. The D value is also dependent upon
the inoculum preparation and the enumeration conditions. This has been demonstrated for
E. coli O157:H7 and is summarised in Figure 2.14 (Stringer et al. 2000). Hence D values quoted
in books and journals cannot be taken as fixed values and directly applied to processes.
Although most frequently applied to thermal death rates, D values can also be used to
express the rate of death due to other lethal affects such as acid and irradiation.
Note, it is questionable whether the first order death kinetics (log‐linear) with temperature
dependence is always appropriate for survival curve calculations. Although the log‐linear
relationship has been the standard approach to thermal susceptibility determination, a
straight‐line relationship does not always occur when plotting experimental data. Complications
arise because the microbial cell can become non‐viable for various reasons: disruption of the
cell envelope, protein denaturation or nucleic acid damage. Shoulders and tails can be obtained
when plotting log (N/N0) survival curves. This may be for reasons such as cell clumping, mixed
populations with varying thermal sensitivities, changes in resistance during treatment or inactivation of a number of essential loci. Various mathematical models are available to address
this issue, the derivation of which is outside the scope of this book. However a useful Excel™
add‐on called ‘GInaFIT’ is available as freeware (see www.ginafit.be) that enables the user to
try nine different mathematical fits to their data from within Excel (Geeraerd et al. 2005). The
models are (i) classical log‐linear curves; (ii) curves with a shoulder; (iii) curves showing tailing; (iv) survival curves with both shoulder and tailing; (v) concave curves; (vi) convex curves;
(vii) convex/concave curves followed by tailing; (viii) biphasic inactivation kinetics; and (ix)
biphasic inactivation kinetics preceded by a shoulder.
Plotting the D value against temperature can be used to determine the change in temperature required to obtain a tenfold increase (or decrease) in the D value. This co‐efficient is
called the z value (Figure 2.15). The integrated lethal value of heat received by all points in a
Basic aspects
65
Viable count (log10 cfu/g)
8
6
4
1 log
D value
2
2.9 minutes
0
0
2
4
6
Time (minutes)
8
10
(a)
Viable count (log10 cfu/g)
8
6
1 log
4
D value
5.2 minutes
2
0
0
5
10
Time (minutes)
D value (log10)
(b)
3
2.5
2
1.5
1
0.5
0
–0.5
–1
–1.5
–2
Liquid whole egg
Egg yolk
Meat
50
(c)
15
55
60
65
Temperature (°C)
Figure 2.13 (a) Death rate of Escherichia coli O157:H7 in beef at 60°C. (b) Death rate of Staphylococcus aureus in
liquid egg at 60°C. (c) D value for Salmonella Enteritidis in eggs and meat. Source: FSIS (1998); Fazil et al. (2000a).
container during processing is designated Fs or Fo. This represents a measure of the capacity of
a heat process to reduce the number of spores or vegetative cells of a given organism per container. When we assume instant heating and cooling throughout the container of spores, vegetative cells or food, Fo may be derived as follows:
Fo
Dr log a log b
66
The microbiology of safe food
Table 2.3 Variation in microbial heat resistance of micro‐organisms according to test conditions.
Organism
Medium
pH
Aeromonas hydrophila
Brucella species
Bacillus cereus
(spores)
(toxin destruction; diarrhoeal/emetic)
Bacillus coagulans
Saline
–
–
–
–
Buffer
Red pepper
Buffer
“
4.5
“
7.0
4.0
–
Buffer
Beef
–
–
–
7.0
–
–
–
–
–
–
Bacillus licheniformis
Bacillus stearothermophilus
Bacillus subtilis
Campylobacter jejuni
Clostridium butyricum
Clostridium perfringens
(spores)
(toxin)
Clostridium botulinum type A and B
proteolytic strains spores
Type E and non‐proteolytic types B & F
(toxin destruction)
Clostridium thermosaccharolyticum
Desulphotomaculum nigrificans
Escherichia coli O157:H7
Listeria monocytogenes
Salmonella Enteritidis
Salmonella Senftenberg
Staphylococcus aureus
(toxin destruction)
Streptococcus Group D
Yersinia enterocolitica
Saccharomyces cerevisiae
Zygosaccharomyces bailii
–
–
Beef
Apple juice
Growth, 23°C
Growth, 37°C
Beef
Liquid whole egg
Beef
–
Cured meat
Saline
“
“
“
3.6
4.5
–
4.5
“
“
Temperature
(°C)a
D value
(minutes)
51.0
65.5
100
100
56.1/121
110
“
110
“
120
100
50
50
100
100
98.9
90
121.1
8.08–122.8
0.1–0.2
5.0
2.7–3.1
5/Stable
0.064–1.46
5.5
0.27
0.12
4.0–5.0
11.0
0.88–1.63
5.9–6.3
0.1–0.5
0.3–20.0
26–31 minutes
4
0.2
82
85
120
120
62.8
58
58
58
58
62.0
62.8
62.0
65.5
98.9
0.49–0.74
2.0
3–4
2–3
0.47
1.0
2.5
1.6
5.0
2.9–4.2
0.06
2.65
0.2–2.0
>2 hours
70
60.0
60
2.95
0.4–0.51
22.5b
0.4c
14.2b
“
“
z value
5.22–7.69
–
6.9
6.1
–
–
–
–
10
6.0–6.4
3.8
7.2
10
5.6–10.7
4.0–6.2
7.2–10
4.65
4.8
4.8
4.8
4.8
5.98
3.30
5.91
4.8–5.4
(approx.
27.8)
10
4.0–5.2
5.5
3.9
–
To convert to °F use the equation °F = (9/5)°C + 32. As a guidance: 0 °C = 32 °F, 4.4 °C = 40 °F, 60 °C = 140 °F.
Ascospores.
c
Vegetative cells.
a
b
Where a = number of cells in the initial population, and b = number of cells in the final
population.
See Table 2.4 for an example of the effect of cooking temperature on the survival of E. coli
O157:H7 in beef using D and z values.
Basic aspects
Inoculum grown
25°C D 60 = 0.74 min
37°C D 60 = 1.02 min
67
Pre-treatment heat shock 45°C, 5 minutes
D 60 = 1.1 minutes
Control
Inoculum grown 30°C, 24 hours
Suspended in peptone salt dilution fluid
Enumerated on TSA, aerobically, 30°C, 7 days
D 60 = 0.79 min
Enumeration:
Incubation 4 days D 60 = 0.80 minutes
Incubation 37°C D 60 = 0.62 minutes
Enumeration:
MPN-cooked meat broth D 60 = 1.24 minutes
MPN TSB
D 60 = 1.22 minutes
Figure 2.14 Changes in Escherichia coli O157:H7 D value at 60°C with inoculum and recovery conditions.
Source: Adapted from Stringer et al. (2000).
1
0.5
Log10 D value
0
–0.5
1 log
–1
–1.5
–2
Z value
–2.5
8°C
–3
–3.5
50
60
70
Temperature (°C)
80
Figure 2.15 Campylobacter jejuni z value in lamb cubes.
12‐D Concept
The 12‐D concept refers to the process lethality requirement, which has for a long time been
used in the canning industry. It implies that the minimum heat process should reduce the
probability of survival of the most resistant Cl. botulinum spores to 10−12. Since Cl. botulinum
spores do not germinate and produce toxin below pH 4.6, this concept is observed only for
foods above this pH value.
Fo
Dr log a log b
Fo
0.21 log 1 log 10 12
68
The microbiology of safe food
Table 2.4 Effect of cooking temperature on the survival of Escherichia coli O157:H7.
Temperature (°C)
Time for viable count to be reduced
by 6 log cyclesa (minutes)
58.2
62.8
67.5
28.2
2.8
0.28
Source: Data derived from D62.8 = 0.4, z = 4.65.
a
For example, 107 cfu/g to 10 cfu/g.
Fo
0.21 12 2.52
Processing for 2.52 minutes at 250 °F (121 °C) should reduce the Cl. botulinum spores to one
spore in 1 million containers (1012). When it is considered that some flat‐sour spores have Dr
values of about 4.0 and some canned foods receive Fo treatments of 6.0–8.0, the potential number of Cl. botulinum spores is reduced even more (See Table 2.3).
Application of D Value Concept in Pasteurisation
Pasteurisation treatment aims to reduce the number of pathogenic spoilage organisms by a set
amount (frequently a 6 log reduction) and to ensure that the product formulation and storage
conditions inhibit the growth of any surviving cells during the intended shelf life of the product. For more detail, see Section 3.2. For example, if the D value of a target organism is
0.5 minutes at 70°C and the z value was 5°C, a process of 3 minutes at 70°C would give a
6 log reduction. At 75°C the organism would die 10 times faster hence 0.3 minutes
(20 seconds) at 75°C is an equivalent treatment giving a 6 log reduction.
Since the determination of actual z values for each organism and product would require
considerable work, assumed appropriate values are often used. Although this may be satisfactory for general quality assurance purposes, it is important to establish accurate values for the
most appropriate micro‐organism present in the product.
2.8 Factors affecting microbial growth
Traditional ways to control microbial spoilage and safety hazards in foods are summarised in
Table 2.5. How these are used in methods of food preservation is considered in more detail in
Sections 3.4 and 3.5. In order to design adequate treatment processes an understanding of the
factors affecting microbial growth is necessary. To complement this, Table 2.6 lists the common
faults during processing that result in the growth of foodborne pathogens or toxin
production.
2.8.1 Intrinsic and extrinsic factors affecting microbial growth
Food is a chemically complex matrix, and predicting whether or how fast micro‐organisms
will grow in any given food is difficult. Most foods contain sufficient nutrients to support
microbial growth. Several factors encourage, prevent or limit the growth of micro‐organisms
in foods, the most important are aw, pH and temperature.
Basic aspects
69
Table 2.5 Methods of food preservation.
Operation
Intended effect
Cleaning, washing
Cold storage (below
8°C)
Freezing (below −10°C)
Pasteurising (60–80°C)
Blanching (95–110°C)
Canning (above 100°C)
Drying
Salting
Syruping (sugars)
Acidifying
Reduces microbial load
Prevents the growth of most pathogenic bacteria; slows the
growth of spoilage microbes
Prevents growth of all microbes
Kills most non‐sporing bacteria, yeast and moulds
Kills surface vegetative bacteria, yeast and moulds
‘Commercially sterilises’ food; kills all pathogenic bacteria
Stops growth of all microbes when aw < 0.60
Stops growth of most microbes at ~10% salt
Halts growth when aw < 0.70
Halts growth of most bacteria (effects depend on acid type)
Source: ICMSF (1988).
aw denotes water activity.
Table 2.6 Most common faults in handling food which allow growth or formation of toxins
by micro‐organisms.
Temperature abuse
Other process parameters
No or not sufficient chilling
Inadequate heat processing
temperature too low
process time too short
holding time too long at ≤65°C
Not properly controlled
aw
pH
NO2 / NO3 and concentration of other preservatives not adequate
Source: Sinell (1995).
A useful acronym is ‘FAT TOM’, which stands for
1 Food refers to the nutritional content.
2 Acidity, is the pH inhibitory to microbial growth?
3 Time and Temperature are together and can refer, for example, to cooking time and
temperature.
4 Oxygen presence and the retardation of microbial growth under modified atmosphere and
vacuum packaging.
5 Moisture refers to the amount of available water.
Factors affecting microbial growth are divided into two groups: intrinsic and extrinsic parameters (Table 2.7).
2.8.2 Water activity
When other substances (solutes) are added to water, water molecules orient to the surface of
the solute and the properties of the solution change dramatically. The microbial cell must compete with solute molecules for free water molecules. Except for St. aureus, bacteria are rather
poor competitors for free water, whereas moulds are excellent competitors.
Water activity (aw) is defined as the vapour pressure of the food being tested divided by the
vapour pressure of pure water (i.e. distilled water) at the same temperature. Pure water is prescribed a baseline aw reading of 1.0 under standardised conditions. Thus, all aw measurements
in foods will be <1.0.
70
The microbiology of safe food
Table 2.7 Intrinsic and extrinsic parameters affecting microbial growth.
Intrinsic parameters
Extrinsic parameters
Water activity, humectant identity
Oxygen availability
pH, acidity, acidulant identity
Buffering capacity
Available nutrients
Natural antimicrobial substances
Presence and identity of natural microbial flora
Colloidal form
Temperature
Relative humidity
Atmosphere composition
Packaging
aw
Water vapour pressure of sample
Pure water vapour pressurre
From the above equation, a solution of pure water has an aw value of 1.00. The addition of
solute decreases the aw value to <1.00. The aw value varies very little with temperature over the
range of temperatures that support microbial growth.
The aw of a solution may dramatically affect the ability of heat to kill a bacterium at a given
temperature. For example, a population of Salmonella Typhimurium is reduced 1tenfold in
0.18 minutes at 60°C if the aw of the suspending medium is 0.995. If the aw is lowered to 0.94,
4.3 minutes are required at 60°C to cause the same tenfold reduction.
An aw value stated for a bacterium is generally the minimum aw that supports growth. At the
minimum aw, growth is usually minimal, increasing as the aw increases. At aw values below the
minimum for growth, bacteria do not necessarily die. The bacteria may remain dormant, but
infectious. Most importantly, aw is only one factor, and the other factors (e.g. pH and
temperature) of the food must be considered. It is the interplay between factors that ultimately
determines if a bacterium will grow or not. The aw of a food may not be a fixed value. It may
change over time, or may vary considerably between similar foods from different sources. The
minimum water activity supporting growth for various micro‐organisms is given in Table 2.8.
The water activity has been widely used as the preservation factor by the addition of salt and
sugar. Sugar has been traditionally used in the preservation of fruit products (jams and
preserves). In contrast, salt has been used for the preservation of meat and fish. The water
activity of a range of foods is given in Table 2.9.
2.8.3 pH
The pH range for growth of a micro‐organism is defined by a minimum value (at the acidic
end of the scale) and a maximum value (at the basic end of the scale). In addition, there is a pH
optimum for each micro‐organism at which its growth is maximal (Table 2.8). Moving away
from the pH optimum in either direction slows microbial growth. A range of food pH values
is given in Table 2.10. Shifts in pH of a food with time may reflect microbial activity, and foods
that are poorly buffered (i.e. do not resist changes in pH), such as vegetables, may shift pH
values considerably. For meats, the pH of muscle from a rested animal may differ from that of
a fatigued animal.
A food may start with a pH that precludes bacterial growth, but as a result of the metabolism
of other microbes (yeasts or moulds), pH shifts may occur and permit bacterial growth. This
Basic aspects
71
Table 2.8 Limits of microbial growth; water activity (aw), pH and temperature.
Organism
Aeromonas hydrophila
Bacillus cereus
Bacillus stearothermophilus
Campylobacter jejuni
Clostridium botulinum type A
and proteolytic B & F
Cl. botulinum type E and
non‐proteolytic B & F
Clostridium perfringens
Escherichia coli
Lactobacillus species
Listeria monocytogenes
Salmonella serovars
Shigella species
Staphylococcus aureus
(toxin production)
Vibrio cholerae
Vibrio parahaemolyticus
Vibrio vulnificus
Yersinia enterocolitica
Saccharomyces species
Aspergillus oryzae
Fusarium moniliforme
Penicillium verrucosum
Minimal water
activity (aw)
pH range
Temperature
range (°C)a
0.970
0.930
–
0.990
0.935
(7.2 optimum)
4.3–9.3
5.2–9.2
4.9–9.5
4.6–9.0
−0.1–42
4–55
28–72
30–45
10–48
12 h, 4°C
4 h/generation, 8°C
0.965
5.0–9.0
3.3–45
(8 days, 10°C)c
0.945
0.935
0.930
0.920
0.940
0.960
0.830
5.0–9.0
4.0–9.0
3.8–7.2
4.4–9.4
3.7–9.5
4.8–9.3
4.0–10
10–52
7–49.4
5–45
−0.4–45
5–46
6.1–47.1
7–50
12 h, 12°C
25 h/generation, 8°C
0.850
0.970
0.936
0.960
0.945
0.85
0.77
0.87
0.79
4.0–9.8
5.0–10.0
4.8–11
5.0–10
4.2–10
2.1–9.0
1.6–13.0
<2.5–>10.6
<2.1–>10.0
10–48
10–43
5–44
8–43
−1.3–45
–
10–43
2.5–37
0–31
Growth rateb (td)
6 h/generation, 32°C
(8 days, 10°C)c
1 day, 4.4°C
(60 h),d 10 h, 10°C
(3.6 days, 8°C)e
(2.8 days),d 1 day,
10°C
(4 h)d, 98 min, 20°C
60 min, 18°C
17 h, 5°C
Source: Various sources used, principally ICMSF (1996a), Corlett (1998), Mortimore and Wallace (1994); where
data have differed between sources the wider growth range has been quoted.
a
To convert to °F use the equation °F = (9/5)°C + 32. As a guidance: 0 °C = 32 °F, 4.4 °C = 40 °F, 60 °C = 140 °F.
b
These are only examples of doubling time (td). The values will vary according to food composition.
c
Time to toxin production.
d
Lag time.
e
Average time to turbidity (inoculation from 1:1 dilution of 5 hours, 37°C culture).
can occur during the cold maturation period for cheese, whereby moulds produce ammonia
(alkaline), which neutralises the lactic acid‐generated acidic pH creating a neutral environment for Listeria to grow – other foodborne pathogens (in general) being unable to grow at the
low storage temperature.
2.8.4 Temperature
Temperature values for microbial growth, like pH values, have a minimum and maximum
range with an optimum temperature for maximal growth. The optimum growth temperature
determines its classification as a thermophile, mesophile or psychrophile (Table 2.11). A thermophile cannot grow at room temperature and therefore canned foods can be stored at room
temperature even though they may contain thermophilic micro‐organisms that survived the
high processing temperature.
Table 2.9 Water activity of various foods.
Water activity
(aw) range
Foods
1.00–0.95
Highly perishable foods:
Meat, vegetables, fish, milk, fresh and canned fruit
Cooked sausages and breads
Foods containing up to 40% sucrose or 7% NaCl
Some cheeses (i.e. Cheddar)
Cured meat (i.e. ham)
Some fruit juice concentrates
Foods containing 55% sucrose or 12% NaCl
Fermented sausages (salami), sponge cakes, dry cheeses, margarine
Foods containing 65% sucrose or 15% NaCl
Most fruit juice concentrates, sweetened condensed milk, chocolate syrup,
maple and fruit syrups, flour, rice, pulses containing 15–17% moisture, fruit cake
Jam, marmalade, marzipan, glace fruits
Rolled oats, fudge, jelly, raw cane sugar, nuts
Dried fruits, some toffees and caramels, honey
Noodles, spaghetti
Whole egg powder
Cookies, crackers
Whole milk powder, powdered infant formula, dried vegetables, cornflakes
0.95–0.91
0.91–0.87
0.87–0.80
0.80–0.75
0.75–0.65
0.65–0.60
0.60–0.50
0.50–0.40
0.40–0.30
0.30–0.20
Table 2.10 pH values of various foods.
pH range
Food
pH
Low acid (pH 7.0–5.5)
(Whole eggs
(Frozen eggs
(Camembert cheese
Cheddar cheese
Roquefort cheese
Bacon
Carcass meat
Red meat
Ham
Canned vegetables
Poultry
Fish
Crustaceans
Milk
Butter
Potatoes
Rice
Bread
Fermented vegetables
Cottage cheese
Bananas
Green beans
Mayonnaise
Tomatoes
Fruits
Canned pickles & fruit juice
Sauerkraut
Citrus fruits
Apples
7.1–7.9)
8.5–9.5)
7.44)
5.9
5.5–5.9
6.6–5.6
7.0–5.4
6.2–5.4
5.9–6.1
6.4–5.4
5.6–6.4
6.6–6.8
6.8–7.0
6.4–6.8
6.1–6.4
5.6–6.2
6.0–6.7
5.3–5.8
5.1–3.9
4.5
4.5–5.2
4.6–5.5
4.1–3.0
4.0
Medium acid (pH 5.3–4.5)
Acid (pH 4.5–3.7)
High acid (<pH 3.7)
3.9–3.5
3.3–3.1
3.5–3.0
2.9–3.3
Foods in parenthesis are outside the pH range, but are included for comparison.
Basic aspects
73
Table 2.11 Grouping of micro‐organisms according to temperature growth range.
Group
Minimum (°C)
Optimum (°C)
Maximum (°C)
Psychrophiles
Mesophiles
Thermophiles
−5
5
40
12–15
30–45
55–75
20
47
60–90
Note: To convert to °F use the equation °F = (9/5)°C + 32. As a guidance: 0 °C = 32 °F, 4.4 °C = 40 °F,
60 °C = 140 °F.
2.8.5 Interplay of factors affecting microbial growth in foods
Although each of the major factors listed above plays an important role, the interplay between
the factors ultimately determines whether a micro‐organism will grow in a given food. Often,
the results of such interplay are unpredictable, as poorly understood synergism or antagonism
may occur. Advantage is taken of this interplay with regard to preventing the outgrowth of Cl.
botulinum. Food with a pH of 5.0 (within the range for Cl. botulinum) and an aw of 0.935
(above the minimum for Cl. botulinum) may not support the growth of this bacterium. Certain
processed cheese spreads take advantage of this fact and are therefore shelf stable at room temperature even though each individual factor would permit the outgrowth of Cl. botulinum.
Therefore, predictions about whether or not a particular micro‐organism will grow in a
food can, in general, only be made through experimentation. Also, it should be noted that
many micro‐organisms do not need to multiply in food to cause disease.
2.9 Microbial response to stress
The common procedures for food preservation (Table 2.5) are being expanded by new techniques such as:
• mild heating;
• modified atmosphere and vacuum packaging;
• inclusion of natural antimicrobial agents;
• high hydrostatic pressure;
• pulse electric field and high intensity laser.
The development of these techniques is partially due to consumer demand for foods that are
less processed, less heavily preserved yet of higher perceived quality (see Sections 3.4 and 3.5).
They are ‘milder’ treatments than traditional methods and commonly rely on storage and distribution at refrigeration temperatures for their preservation. These are commonly called
‘minimal processed foods’.
The micro‐organisms of concern in minimal processed foods are psychrotrophic and mesophilic micro‐organisms. The psychrotrophic organisms, by definition, can grow at refrigeration temperatures, whereas mesophilic pathogens can survive under refrigeration and grow
during periods of temperature abuse (Table 2.12).
Micro‐organisms are able, within limits, to adapt to stress conditions such as thermal stress,
pH stress, osmotic shock, oxidative stress and nutrient limitation (Table 2.13). The mechanism
of adaptation is by signal transduction systems, which control the coordinated expression of
genes involved in cellular defence mechanisms. Microbial cells are able to adapt to many processes used to retard microbial growth. These include cold shock, heat shock, (weak) acids,
high osmolarity and high hydrostatic pressure. The easiest mechanism of survival to recognise
is in Bacillus and Clostridium species. These organisms form spores under stress conditions,
74
The microbiology of safe food
Table 2.12 Food poisoning micro‐organisms of concern in minimally processed foods.
Heat resistance
Minimum growth
temperature (°C)
Lowa
Highb
0–5
Listeria monocytogenes
Clostridium botulinum type E and
non‐proteolytic type B
Bacillus cereus
Bacillus subtilis
Bacillus licheniformis
Yersinia enterocolitica
5–10
Salmonella serovars
Vibrio parahaemolyticus
Pathogenic strains of
Escherichia coli
Staphylococcus aureus
10–15
Cl. botulinum type A and proteolytic type B
Clostridium perfringens
Source: Adapted from Abee and Wouters (1999).
Note: To convert to °F use the equation °F = (9/5)°C + 32. As a guidance: 0°C = 32°F, 4.4°C = 40°F,
60°C = 140°F.
a
Organisms undergo a 6 log kill following heat treatment of 70°C for 2 minutes.
b
Organisms require heat treatment of 90°C or above to destroy spores.
Table 2.13 Response mechanisms in micro‐organisms.
Environmental stress
Stress response reaction
Low nutrient levels
Nutrient scavenging, oligotrophy, generation of viable
non‐culturable forms
Extrusion of hydrogen ions, maintenance of cytoplasmic pH and
membrane pH gradient
Osmoregulation, avoidance of water loss, maintenance of
membrane turgor
Membrane lipid changes, cold shock response
Membrane lipid changes, heat shock response
Enzymic protection from oxygen‐derived free radicals
Phenotypic adaptation and development of resistance
Excision of thymine dimers and repair of DNA
Repair of DNA single strand breaks
Low water content in the spore protoplast
Low spore protoplast water content?
Low conductivity of spore protoplast
Structural rigidity of cell wall
Impermeable outer layers of cells
Formation of biofilms, aggregates with some degree of symbiosis
Low pH, presence of weak organic acids
Reduced water activity
Low temperature – growth
High temperature – growth
High oxygen levels
Biocides and preservatives
Ultraviolet radiation
Ionising radiation
High temperature – survival
High hydrostatic pressure –survival
High voltage electric discharge
Ultrasonication
High levels of biocides
Competition
Source: Adapted from Gould (1996) and reprinted with permission from Elsevier.
which can germinate under favourable conditions later. Other organisms, such as E. coli,
undergo significant physiological changes to enable the cell to survive environmental stresses
such as starvation, near‐UV radiation, hydrogen peroxide, heat and high salt. As already
shown, due to adaptation, the D60 value of E. coli O157:H7 is dependent upon the inoculum
preparation and the enumeration conditions (Figure 2.14).
Basic aspects
75
The regulatory mechanism involves the modification of sigma (δ) factors. Their primary
role is to bind to core RNA polymerase conferring promoter specificity. The sigma factors of
Bacillus subtilis and E. coli have been extensively studied. The main sigma factor is responsible
for the transcription from the majority of the promoters. Alternative sigma factors have different promoter specificities, directing expression of specific regulons involved in heat shock
response, the chemotactic response, sporulation and general stress response (GSR).
2.9.1 General stress response (GSR)
Bacterial responses to stress can be either general or specific. The specific responses to acid,
heat, cold and osmotic stress will be covered in the next sections. The GSR regulon is a group
of genes concerned with growth and survival under various stress conditions. In E. coli there
are more than 50 genes involved in the GSR, and these are coordinately regulated by the sigma
factor σs, which is encoded by the rpoS gene. This is an alternative sigma subunit of RNA
polymerase, which accumulates (due to decreased degradation) in the cell during stress
exposure, and activates the genes that express the GSR. This response regulator controls the
stability of the protein and hence its degradation rate. In B. subtilis, GSR is modulated
principally by an alternative sigma factor known as σB. When B. subtilis cells are stressed, an
anti‐sigma factor is produced that binds to σB making it no longer accessible. Several genes in
the E. coli rpoS‐mediated stress protection system have homologues in the B. subtilis σ32 stress
protection system regulon. These are likely to encode traits that help protect the organisms
during stress conditions in the soil and intestinal environments.
The GSR for one stress may induce cross‐protection whereby one stress causes the organism
to be less sensitive to a second stress; for example, heat exposure and acid resistance. When
Salmonella Enteritidis is heat shocked by shifting the incubation temperature from 20 to 45°C,
there is a threefold increase in the D value at pH 2.6. This acid tolerance is increased tenfold
when the incubation temperature is raised to 56°C.
Since bacteria are constantly mutating, pathogens will continue to emerge that may have
new characteristics enabling them to cause infections. This can include activating certain virulence determinants to survive in an otherwise incompatible environment. Therefore, inducing
these responses during food processing and preparation could increase their infectivity.
Examples include desiccation inducing acid tolerance, and the GSR regulatory protein rpoS
enabling the survival of Salmonella inside phagosomal vacuoles.
2.9.2 pH stress
Acidification is a commonly used method of preserving food, such as dairy products. This
method is very effective since the main foodborne pathogens grow best at neutral pH values.
These organisms however are able to tolerate and adapt to weak acid stresses and this possibly
enables them to survive passage through the acidic human stomach. Additionally acid resistance
can cross‐protect against heat treatment (cf. E. coli Table 2.3; Vidovic and Korber 2016).
Acid stress is the combined effect of low pH and weak (organic) acids such as acetate,
propionate and lactate. Weak acids in their unprotonated form can diffuse into the cell and
dissociate (see Section 3.4.1). Consequently they lower the intracellular pH (pHin) resulting in
the inhibition of various essential cytoplasmic enzymes. In response micro‐organisms have
inducible acid survival strategies. Regulatory features include an alternative sigma factor σs, an
acid shock protein, two‐component signal transduction systems (e.g. PhoP and PhoQ) and the
major iron regulatory protein FUR (ferric uptake regulator).
76
The microbiology of safe food
The important aspect of the acid tolerance response (ATR) is the induction of cross‐
protection to a variety of stresses (heat, osmolarity, membrane active compounds) in
exponentially grown (log phase) cells. Acid‐adapted cells are those that have been exposed
to a gradual decrease in environmental pH, whereas acid‐shocked cells are those that have
been exposed to an abrupt shift from high pH to low pH. It is important to differentiate
between these two conditions since acid‐adapted, but not acid‐shocked E. coli O157:H7
cells in acidified tryptone soya broth and low pH fruit juices have enhanced heat tolerance
in TSB at 52°C and 54°C, and in apple cider and in orange juice at 52°C. Acid‐induced
general stress resistance may reduce the efficiency of hurdle technologies that are dependent
upon multiple stress factors (see Section 3.3).
Acid resistance can be induced by factors other than acid exposure. Salmonella Typhimurium
acid tolerance can be induced by exposure to short‐chain fatty acids, as used as food preservatives and which also occur in the intestinal tract. Subsequently the virulence of S. Typhimurium
may be enhanced by increasing acid resistance upon exposure to short‐chain fatty acids, such
as propionate, and further enhanced by anaerobiosis and low pH.
2.9.3 Heat shock
Food preservation by heat is a common food preservation method, i.e. blanching, pasteurisation and sterilisation (Table 2.5). The targets for heat inactivation of microbes are the intrinsic
stability of macromolecules, i.e. ribosomes, nucleic acids, enzymes and intracellular proteins
and the membrane. The exact primary cause for cell death due to heat exposure is not fully
understood. Bacterial thermotolerance increases upon exposure to sublethal heating temperatures, phage infection and chemical compounds such as ethanol and streptomycin.
Microbes can adapt to mild heat treatment in a variety of ways:
• Cell membrane composition changes by increasing the saturation and the length of the fatty
acids in order to maintain the optimal membrane fluidity and the activity of intrinsic proteins.
• Accumulation of osmolytes that may enhance protein stability and protect enzymes against
heat activation.
• Bacillus and Clostridium species produce spores.
• Heat shock proteins (HSPs) are produced.
When bacteria cells are exposed to higher temperatures, a set of HSPs is rapidly induced. The
primary structure of most HSPs appears to be highly conserved in a wide variety of micro‐
organisms. HSPs involve both chaperones and proteases, which act together to maintain
quality control of cellular proteins. Both types of HSPs have as their substrates a variety of
misfolded and partially folded proteins that arise from slow rates of folding or assembly, chemical or thermal stress, intrinsic structural instability and biosynthetic errors. The primary
function of classical chaperones, such as the E. coli DnaK (Hsp70) and its co‐chaperones, DnaJ
and GrpE, and GroEL (Hsp60) and its co‐chaperone, GroES, is to modulate protein folding
pathways, thereby preventing misfolding and aggregation, and promoting refolding and proper
assembly. HSPs are induced by several stress situations, for example, heat, acid, oxidative stress
and macrophage survival, which suggests that HSPs contribute to bacterial survival during
infection. In addition HSPs may enhance the survival of foodborne pathogens in foods during
exposure to high temperatures. It is important to note that micro‐organisms develop a complicated, tightly regulated response following an upshift in temperature. Different stressors can
activate (parts of) this stress regulon by which they can induce an increased heat tolerance.
The process of adaptation and initiation of defence against elevated temperature is an important
target when considering food preservation and the use of hurdle technology (see Section 3.3).
Basic aspects
77
The GSR becomes more stable at higher temperatures due to decreased degradation, as the
heat shock response involves the synthesis of an alternative sigma factor, σ32. This results in an
increased rate of heat shock promoters being transcribed by the σ32 RNA polymerase. The heat
shock regulon encodes ~30 proteins. In E. coli there is a second heat shock system that is
controlled by σE (σ24), which includes a mechanism for sensing and coordinating responses to
thermal stress in the periplasm.
2.9.4 Cold shock
Cold adaptation by micro‐organisms is of particular importance due to the increased use of
frozen and chilled foods and the increased popularity of fresh or minimally processed food,
with few or no preservatives. The relevant growth ranges of L. monocytogenes, Yersinia enterocolitica, B. cereus and Cl. botulinum are of particular importance (see Table 2.8).
Mechanisms of cold adaptation are:
• Membrane composition modifications, to maintain membrane fluidity for nutrient uptake.
• Structural integrity of proteins and ribosomes.
• Production of cold shock proteins (CSPs).
• Uptake of compatible solutes (i.e. betaine, praline and carnitine).
To maintain membrane fluidity and function at low temperatures, micro‐organisms increase
the proportion of shorter and/or unsaturated fatty acids in the lipids. In E. coli the proportion
of cis‐vaccenic acid (C18:1) increases at low temperatures at the expense of palmitic acid
(C16:0). The increase in average chain length has the opposite effect on membrane fluidity, but
is outweighed by the greater fluidity of increased unsaturation. In L. monocytogenes, the fatty
acid composition is altered in response to low temperature by an increase of a C15:0 fatty acid
and a decrease of a C17:0 fatty acid. Compatible solutes (such as betaine, proline and carnitine)
may play a role in osmoprotection and in cold adaptation. At 7°C, L. monocytogenes increases
its uptake of betaine 15‐fold compared with growth at 30°C. CSPs are small (7 kDa) proteins
that are synthesised when bacteria are subjected to a sudden decrease in temperature. CSPs are
involved in protein synthesis and mRNA folding.
Different cold shock treatments prior to freezing results in differences in microbial survival
of bacteria after freezing. This might result in a high survival rate of bacteria in frozen food
products. Furthermore, low temperature‐adapted bacteria may be relevant to food quality and
safety.
2.9.5 Osmotic shock
Lowering water activity (aw) is one of the common ways of preserving food (see Tables 2.5 and
2.8). This works by increasing the osmotic pressure on the microbial cell. This is achieved by
the addition of high amounts of salts and sugar (osmotically active compounds) or desiccation.
The internal osmotic pressure in bacterial cells is higher than that of the surrounding medium.
This results in an outward pressure called ‘turgor pressure’. This pressure is necessary for cell
elongation.
The microbial response to loss of turgor pressure is the cytoplasmic accumulation of ‘compatible solutes’ that do not interfere too seriously with cellular functions. These compounds
are small organic molecules, which share a number of common properties:
• Soluble to high concentrations.
• Can be accumulated to very high levels in the cytoplasm.
• Neutral or zwitterionic molecules.
• Specific transport mechanism present in the cytoplasmic membrane.
78
The microbiology of safe food
• Do not alter enzyme activity.
• May protect enzymes from denaturation by salts or protect them against freezing and
drying.
The adaptation of E. coli O157:H7, S. Typhimurium, B. subtilis, L. monocytogenes and St. aureus
to osmotic stress is mainly through the accumulation of betaine (N,N,N‐trimethylglycine)
via specific transporters. Other compatible solutes include carnitine, trehalose, glycerol, sucrose,
proline, mannitol, glucitol, ectoine and small peptides.
2.10 Predictive modelling
The major factors affecting microbial growth are:
• pH;
• water activity;
• atmosphere;
• temperature;
• presence of certain organic acids, such as lactate.
However, our ability to predict accurately the subsequent growth of microbes in food with
regard to the safety and shelf life of food is very limited.
Predictive food microbiology combines elements of microbiology, mathematics and statistics to develop models that describe and predict the growth and decline of microbes under
prescribed (including varying) environmental conditions (Whiting 1995). Obviously, if food is
subjected to temperature fluctuations during distribution and storage then the rate of microbial growth will be affected. There are ‘kinetic’ models that model the extent and rate of microbial growth, and ‘probability’ models that predict the likelihood of a given event occurring,
such as sporulation (Ross and McMeekin 2003).
The main objective is to describe mathematically the growth of micro‐organisms in food
under prescribed growth conditions. Initially the data for models are collected using a range of
bacterial strains to represent the variation of the target organism present in the commercial
situation. Ideally this will include strains associated with outbreaks, the fastest growing strains
and the most frequently isolated strain. Although there is a considerable wealth of knowledge
from the growth of microbes in bioreactors (fermenters), this is not directly applicable to the
food industry. In food the environmental factors are more varied and fluctuate, and one is
often dealing with a mixed population. Predictive microbiology has become established as a
scientific discipline. A detailed study of predictive microbiology is given by McMeekin and
Ross (2002), and for microbial risk assessment in ILSI (2012). A list of useful programs and
URLs is given in the ‘Food Safety Resources’ section at the end of the book.
2.10.1 Predicting modelling development
Predictive models have various applications:
• Prediction of risk: the model can estimate the likelihood of pathogen survival during
storage.
• Quality control: predicting the effect of environmental factors can assist deciding on critical
control points in a hazard analysis critical control point (HACCP) plan (see Chapter 9).
• Product development: microbial survival can be predicted for changes in processing and new
product formulation without the need for extensive laboratory analysis.
• Education: the implications of changes in temperature, pH, etc. can be visualised during a
staff training programme.
Basic aspects
79
The origin of predictive microbiology is in the canning industry and the D values used to
describe the rate of microbial death. However, the ability to routinely solve complex
mathematical equations required the revolution in computing power and this, in turn, has
greatly facilitated the development of predictive modelling. Models developed to predict
microbial survival and growth may become an integral tool to evaluate, control, document and
even defend the safety designed into a food product. The application of microbial models in
HACCP and microbial risk assessment are covered in Chapters 9 and 10. A form of predictive
microbiology is the development of expert systems that can quantify the safety risks of food
products without the necessity for extensive laboratory work (Schellekens et al. 1994; Wijtzes
et al. 1998).
Predictive models can work at three levels:
1 Primary level models describe changes in microbial numbers (or equivalent) with time.
2 Secondary level models show how the parameters of the primary model vary with environmental conditions.
3 Tertiary level models combine the first two types of models with user‐friendly application
software or expert systems that calculate microbial behaviour under changing environmental conditions.
2.10.2 Primary models and the Gompertz and Baranyi equations
Primary models quantify the increase in microbial biomass as colony forming units per millilitre or absorbance at a specific environmental condition, i.e. temperature, pH, water activity.
Alternatively, it could quantify changes in media composition, such as metabolic end products,
conductivity or toxin production.
According to Whiting (1995) the first primary models were simple equations such as growth
versus no‐growth conditions, i.e. acetic acid and sugar concentrations preventing the growth
of spoilage yeast. Subsequent models described the time between inoculation and growth (or
equivalent). This approach was used to model the time required for toxin production by Cl.
botulinum. Primary models describing growth parameters started by plotting the growth curve
and determining the rate of growth from the exponential phase:
Nt
N o e kt / ln2
Where Nt = population size (logarithm) at a specified time; No = initial population size (logarithm) at time 0; k = slope; t = time.
This simple modelling was applied to the growth of L. monocytogenes in milk in the presence of pseudomonads (Marshall and Schmidt 1988) and in various meats (Yeh et al. 1991;
Grau and Vanderlinde 1992). Further models were developed that included the lag phase.
Gompertz Model
The Gompertz function has become the most widely used primary model (Figure 2.16).
The Gompertz function can be represented as:
log N t
A C
e exp
B t M
Where: Nt = population density (cfu/ml) at time t (hours); A = initial population density [log{cfu/ml}];
C = difference in initial and maximum population densities [log{cfu/ml}]; M = time of maximum
growth rate (hours); B = relative maximum growth rate at M [log(cfu/ml])/hour].
80
The microbiology of safe food
Predicted growth curve
10
9
8
C
8.57
7
M
23.0
B
0.0935
Log (cfu/g)
6
B
5
C
Generation time = log(2)e/BC = 1.5 hours
4
Exponential rate = BC/e = 0.20 (log cfu/ml)/hour
3
Lag phase duration = M–(1/B) = 12.4 hours
2
1
A
0
–1
–2
0
M 40
160
80
120
Time (hour)
200
Figure 2.16 Predicted microbial growth curve using the Gompertz function.
This Gompertz function produces a sigmoidal curve that consists of four phases comparable with the phases of microbiological growth: lag, acceleration, deceleration and stationary.
Baranyi Model
Baranyi and co‐workers developed an alternative equation based on the basic growth model,
which incorporated the lag, exponential and stationary phases and the specific growth rate:
Nt
N max ln 1
exp N max N 0
1exp
max
A t
Where: Nt = population size (logarithm); No = initial population size (logarithm); Nmax = maximum population (logarithm); μmax = maximum specific growth rate; A(t) = integral of the
adjustment function.
The model fitted experimental data better than the Gompertz function with regard to predicting the lag time and exponential growth phase.
2.10.3 Secondary models
Commonly used secondary models describe the responses to changes in an environmental factor,
i.e. temperature, pH and aw. Other models determine the time required for a tenfold log reduction
in viability or the length of the lag phase in response to changes in pH, temperature, etc.
There are three types of models: second‐order response surface equation, the square root
model (Belehardek) and Arrhenius relationships. The Arrhenius equation is applicable if the
growth rate is determined by a single rate‐limiting enzymic reaction. Initially the response
surface equation was used when a number of factors affected the primary model. The square
root model (Ross 1993) is based on the linear relationship between the square root of growth
rate and temperature. An important feature is that the equation includes the concept of a ‘biological zero’, which is the temperature when growth rate is zero. The square root model has
Basic aspects
81
Table 2.14 Examples of predictive modelling of microbial growth and toxin production.
Organism
Brochothrix
thermosphacta
Clostridium botulinum
types A & B
Cl. botulinum
Escherichia coli O157:H7
Staphylococcus aureus
Salmonella Typhimurium
Yersinia enterocolitica
Comments
References
McClure et al. (1993)
Growth and toxin
production
Toxin production
Lund et al. (1990), Roberts and Gibson (1986),
Robinson et al. (1982)
Lindroth and Genigeorgis (1986), Baker and
Genigeorgis (1990), Hauschild et al. (1982),
Meng and Genigeorgis (1993)
Sutherland et al. (1995)
Broughall et al. (1983), Sutherland et al. (1994)
Broughall et al. (1983)
Sutherland and Bayliss (1994)
been applied to the growth of E. coli, Bacillus sp., Y. enterocolitica and L. monocytogenes (Adams
et al. 1991; Gill and Phillips 1985; Wimptheimar et al. 1990). In order to have sufficient data
for model fitting a large number of data points must be collected. Growth can be measured by
a number of methods such as turbidity and plate counts. Methods of automatic data collection
are of obvious benefit since it is less laborious and the data are digitised. The Bioscreen
(Labsystems) automatically records turbidity of a large number of samples at any given time.
Alternative measurements include changes in the media conductivity (Borch and Wallentin
1993). The growth rate of Y. enterocolitica in pork was modelled using conductance microbiology and the data closely fitted to the Gompertz function. A listing of selected modelling papers
is given in Table 2.14.
2.10.4 Tertiary models
Tertiary models use the primary and secondary models to generate models to calculate the
microbial response to changing conditions and to compare the effects of different conditions.
A number of models have been developed and are accessible via the Internet. See the ‘Food
Safety Resources’ section for web addresses.
The ‘Pathogen Modeling Program’ is an easily available tertiary model. It is a spreadsheet
software‐based system. It includes models for the effect of temperature, pH, water activity,
nitrite concentration and atmospheric composition on the growth and lag responses of major
food pathogens, as well as survival curves following heat treatment and gamma irradiation.
Figures 2.17 and 2.18 show examples of screen grabs. The ‘Pathogen Modeling Program’ currently covers the following organisms: Aeromonas hydrophila, B. cereus, Cl. perfringens, E. coli
O157:H7, L. monocytogenes, Salmonella serovars, Shigella flexneri, St. aureus and Y. enterocolitica. ‘Growth Predictor’ has a series of models for predicting the growth of a various pathogenic and spoilage bacteria and yeast at a range of temperatures, pH and water activity values.
The ‘Food Spoilage and Safety Predictor’ was developed to predict the shelf life of seafood
under both constant and fluctuating temperature storage conditions. The software can be
linked to temperature loggers and therefore evaluate the effect of fluctuating temperatures
on the shelf life. The Sym’Previus software is combined simulation tool and a database for
L. monocytogenes, Salmonella, B. cereus and E. coli. Strains can be selected according to their
source (i.e. dairy, seafood and meat products).
The microbiology of safe food
log(cfu/mL)
82
11
10
9
8
7
6
5
4
3
2
1
0
Escherichia coli O157:H7
Listeria monocytogenes
Salmonella spp.
0
25 50 75 100 125 150 175 200 225 250
Time (hours)
Figure 2.17 Pathogen Modeling Program simulation for the growth of Escherichia coli O157:H7, Listeria
monocytogenes and Salmonella spp. at 10°C, pH 6.5 and 0.9% NaCl.
11
10
9
8
7
6
5
4
3
2
1
0
Bacillus cereus
Salmonella spp.
Bacillus cereus
Salmonella spp.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5
Time (days)
Time (days)
(d)
11
10
9
8
7
6
5
4
3
2
1
0
Bacillus cereus
Salmonella spp.
0
1
2
3
4
5
6
7
8
9
10
log10 (cfu/ml)
(c)
log10 (cfu/ml)
log10 (cfu/ml)
(b)
11
10
9
8
7
6
5
4
3
2
1
0
log10 (cfu/ml)
(a)
11
10
9
8
7
6
5
4
3
2
1
0
Bacillus cereus
Salmonella spp.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5
Time (days)
Time (days)
Figure 2.18 The growth of Salmonella species and Bacillus cereus under different growth conditions as
predicted using the Pathogen Modeling Program. (a) Temperature 20°C, pH 6.9, aw 0.997. (b) As per (a) except
pH 5.6. (c) As per (a) except temperature is 10°C. (d) As per (a) except aw 0.974. Note change in scale for (c).
2.10.5 Application of predictive microbial modelling
Predictive microbial modelling has many applications:
1 product research and development;
2 shelf life studies (Section 3.2);
3 education and training (Section 10.9.3);
Basic aspects
83
Probability of infection (%)
80
70
60
50
40
30
20
10
0
0
100
200
300
400
500
Temperature abuse (15°C) period (hours)
Figure 2.19 The predicted effect of temperature abuse on the probability of infection for Shigella flexneri.
4 HACCP (Section 9.5);
5 risk assessment studies (Chapter 10).
Growth models have been generated for most food pathogens. The Gompertz equation and
non‐linear regression can be used to predict the survival curve shape and response to heat of
L. monocytogenes under many environmental conditions.
Zwietering et al. (1992) described an expert system that modelled bacterial growth and
spoilage in food production and distribution chains. The system combined two databases of
physical parameters of the food (temperature, aw, pH and oxygen level) with the physiological
data (growth kinetics) of spoilage organisms. This enables the prediction of possible spoilage
types and kinetics of deterioration to be made.
Predictive models are available for use in HACCP and microbiological risk analysis (Van
Gerwen and Zwietering 1998; Ross and McMeekin 2003). Models can be used to assess the risk
or probability and determine the consequence of a microbiological hazard in food (see
Chapter 11 for detailed examples). By using predictive models, ranges and combinations of
process parameters can be established as critical limits for critical control points in HACCP
implementation. Predictive microbiological models are tools to aid in the decision‐making
processes of risk assessment and in describing process parameters necessary to achieve an
acceptable level of risk. Using a combination of risk assessment and predictive modelling it is
possible to determine the effect of processing modifications on food safety. Figure 2.19 shows
the predicted effect of temperature abuse on the probability of infection for Sh. flexneri. The
Pathogen Modeling Program was used to predict the rate of Sh. flexneri growth under defined
conditions (pH, salt, temperature) for increasing time periods and the subsequent likelihood
of infection (Buchanan and Whiting 1996).
3 Food preservation and spoilage organisms
3.1 Spoilage micro‐organisms
Although this book is primarily concerned with foodborne pathogens, this chapter on food
spoilage is included as the preservation of food has an influence on the presence of foodborne
pathogens. It should be emphasised that, in general, spoilt food does not cause food poisoning –
because you should not eat it. Spoilt food is food that tastes and smells ‘off ’. This is due to the
undesirable growth of micro‐organisms that produce volatile compounds during their metabolism, and which the human nose and mouth detect as repugnant. The food is not of the quality
expected by the consumer and therefore it is a quality, not safety, issue. The terms ‘spoilt’ and
‘unspoilt’ are subjective since acceptance is dependent upon consumer expectation and is not
related to food safety. Soured milk is unacceptable as a drink, but can be used to make other
foods such as scones. The overgrowth of Pseudomonas organisms is undesirable in red meat, yet
desirable in hung game birds. Acetic acid production during wine storage is unacceptable, yet
acetic acid production from wine (and beer) is necessary for the production of vinegar.
Food spoilage involves any change that renders the food unacceptable for human consumption. It may have a number of causes:
1 Insect damage.
2 Physical injury due to bruising, pressure, freezing, drying and radiation.
3 The activity of indigenous enzymes in animal and plant tissues.
4 Chemical changes not induced by microbial or naturally occurring enzymes.
5 The activity of bacteria, yeasts and moulds.
Adapted from Forsythe and Hayes (1998).
Food may become contaminated with a wide range of micro‐organisms during growth, harvesting, processing and handling operations. Subsequently, during distribution and storage the
conditions will be favourable for certain organisms to multiply and cause spoilage. Which
micro‐organisms will develop or what biochemical and chemical reactions occur is dependent
upon the food, along with the intrinsic and extrinsic parameters (Section 3.8). Spoilage can be
delayed by lowering the storage temperature (Figure 3.1).
For fresh foods, the primary quality changes may be categorised as:
• Bacterial growth and metabolism resulting in possible pH changes and formation of toxic
compounds, off‐odours, gas and slime formation.
• Oxidation of lipids and pigments in fat‐containing foods resulting in undesirable flavours,
formation of compounds with adverse biological effects or discolouration.
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
85
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The microbiology of safe food
9
Viable count (log10 cfu/g)
8
7
7°C
6
4°C
5
0°C
4
3
2
1
0
Time (days)
Figure 3.1 Temperature effect on food.
9
Viable count (log10 cfu/g)
8
7
Total count
6
5
Specific
spoilage
organism
4
3
Chemical
spoilage
indicator
2
1
0
Storage time (days)
Figure 3.2 Food spoilage indicators.
Spoilage is not only the visible growth of micro‐organisms but also the accumulation of metabolites that result in off‐odours, gas and slime. The spoilage of milk (Section 3.1.2) illustrates
these two aspects with the visible growth of thermoduric micro‐organisms (Bacillus cereus)
and the production of undesirable taste (bitterness due to thermostable proteases).
Although progress has been made in the characterisation of the total microbial flora and
metabolites developing during spoilage, not much is known about the identification of specific
micro‐organisms in relation to food composition. Despite the fact that food spoilage is a huge
economical problem worldwide, the mechanisms and interactions leading to food spoilage are
poorly understood. Although during storage the total microbial flora number may increase, it
is specific spoilage organisms that cause the chemical changes and the production of off‐
odours (Figure 3.2). The shelf life is dependent upon the growth of the spoilage flora and can
be extended through cold storage to retard microbial growth and packaging (vacuum
packaging and modified atmosphere packaging (MAP), see Section 3.6). The higher the initial
microbial load, the shorter the shelf life due to increased microbial activities (Figure 3.3).
Food preservation and spoilage organisms
87
10
Viable count (log10 cfu/g)
9
8
7
6
5
4
Shortening of
shelf-life
3
2
1
0
0
2
4
6
8
Storage time (days)
10
12
Figure 3.3 Effect of initial microbial load on shelf life.
A wide variety of micro‐organisms may initially be present on food and grow if favourable
conditions are present. On the basis of susceptibility to spoilage, foods may be classed as non‐
perishable (or stable), semi‐perishable or perishable. The classification depends on the intrinsic
factors of water activity, pH, presence of natural antimicrobial agents, etc. Flour is a stable
product because of the low water activity. Apples are semi‐perishable since poor handling and
improper storage can result in slow fungal rot. Raw meat is perishable since the intrinsic factors
of pH and water activity favour microbial growth.
3.1.1 Spoilage micro‐organisms
Gram‐negative spoilage micro‐organisms
Pseudomonas, Alteromonas, Shewanella putrefaciens and Aeromonas species spoil dairy
products, red meat, fish, poultry and eggs during cold storage. These foods have high water
activity and neutral pH and are stored without a modified atmosphere (i.e. normal levels of
oxygen). There are a variety of spoilage mechanisms including the production of heat‐stable
proteases and lipases that produce off‐flavours in milk after the organism has been killed by
pasteurisation. They also produce coloured pigments in egg spoilage. Erwinia carotovora and
various Pseudomonas species are responsible for ~35% of vegetable spoilage.
Gram‐positive, non‐spore‐forming spoilage micro‐organisms
The lactic acid bacteria (Section 3.8.1) and Brochothrix thermosphacta are Gram‐positive rods
that typically cause spoilage of meats stored under MAP or vacuum packaging. Acetobacter
and Pediococcus species can produce a thick polysaccharide slime in beer, termed ‘rope’. The
production of diacetyl by lactic acid bacteria causes beer spoilage. The organisms can also
produce lactic acid in wine giving it a sour taste. The Acetobacter produce acetic acid in beer
giving it a sour taste.
Gram‐positive spore‐forming spoilage micro‐organisms
The spore‐forming Bacillus and Clostridium species can be important spoilage organisms
of heat‐treated foods, since the spores may survive processing. Bacillus cereus can grow in
pasteurised milk at 5°C and cause ‘sweet curdling’ (renin coagulation without acidification)
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The microbiology of safe food
and ‘bitty cream’. Bacillus stearothermophilus causes ‘flat sour spoilage’ of canned foods. It
grows in the can, producing acids (hence the term ‘sour’) but without any gas production
and subsequently the can does not swell. Clostridium thermosaccharolyticum spoils canned
foods and due to gas production the can swells. Desulphotomaculum nigrificans produces
hydrogen sulphide, which causes canned foods to swell and smell. This is known as ‘sulphur
stinker’ spoilage. Bacillus stearothermophilus, D. nigrificans and Cl. thermosaccharolyticum
are thermophilic organisms. They are therefore only able to grow at temperatures above
ambient. Hence canned foods are processed to be ‘commercially sterile’ since under normal
storage conditions microbial growth is not expected to occur.
Yeast and mould spoilage micro‐organisms
Yeast and moulds are more tolerant of low water activity and low pH than bacteria. Subsequently
they typically spoil foods such as fruit and vegetables and bakery products (Table 3.1). They
produce pectinolytic enzymes that soften the plant tissues causing ‘rot’. As much as 30% of all
fruit spoilage may be due to Penicillium. Fungi also produce large quantities of coloured sporangia that visibly colour the food. Bread is spoilt by Rhizopus nigricans (‘bread mould’, black
spots), Penicillium (green mould), Aspergillus (green mould) and Neurospora sitophila (‘red
bread’). Osmophilic yeast (Saccharomyces and Torulopsis species) are able to grow in high sugar
concentrations (65–70%) and spoil jams, syrups and honey. Fungi also cause various types of
meat spoilage such as ‘whiskers’ due to Mucor, Rhizopus and Thamnidium. Of particular note
is Zygosaccharomyces bailii. This is a non‐Saccharomyces budding yeast that can contaminate
many acidic, high‐sugar and canned foods, and wine production processes. The spoilage ability
is due to the organism’s ability to tolerate the common preservatives including acetic acid, sorbic acid and sulphite, as well as dimethyl dicarbonate used in wine and fruit juice production.
Table 3.1 Food spoilage fungi.
Organisms
Products typically affected
Aspergillus versicolor
Aspergillus flavus
Aspergillus niger
Byssochlamys fulva
Fusarium oxysporum
Mucor spp.
Neosartorya fischeri
Neurospora sitophila
Penicillium roqueforti
Penicillium expansum
Penicillium commune
Penicillium discolor
Penicillium spp.
Rhizopus nigricans
Rhizopus spp.
Saccharomyces spp.
Thamnidium spp.
Torulopsis spp.
Trichoderma harzianum
Zygosaccharomyces bailii
Bread and dairy products
Cereals and nuts
Spices
Cereals in airtight packs
Fruit
Meat
Pasteurised foods
Bread
Meat, eggs and cheese
Fruit and vegetables
Margarines
Cheese
Bread
Bread
Meat
Soft drinks, jams, syrups and honey
Meat
Jams, syrups and honey
Margarines
Dressings
Source: Adapted from Brul and Klis (1999).
Food preservation and spoilage organisms
89
Standard preservation methods to control fungal growth are high temperatures to denature
spores, weak acid preservatives such as sorbic acid and antibiotics such as natamycin. However,
some fungi have become resistant to sorbic acid and some fungi degrade sorbic acid to the
malodorous compound pentadiene.
3.1.2 Spoilage of dairy products
Milk is an ideal growth medium for bacteria and therefore needs to be kept refrigerated. The
intrinsic flora (~102–104 cfu/ml) is derived from the cow’s milk ducts in the udder and the
milking equipment etc. during production. The flora includes Pseudomonas species, Alcaligenes
species, Aeromonas species, Acinetobacter‐Moraxella species, Flavobacterium species,
Micrococcus species, Streptococcus species, Corynebacterium species, Lactobacillus species
and lactose‐fermenting Enterobacteriaceae. Milk spoilage is primarily due to the growth of
psychrophilic micro‐organisms, which produce heat‐stable lipases and proteases that are not
denatured during pasteurisation. The pseudomonads, flavobacteria and Alcaligenes species
produce lipases that produce medium‐ and short‐chain fatty acids (SCFAs) from milk
triglycerides. These fatty acids spoil the milk due to their rancid off‐flavour. Proteases are
produced by pseudomonads, aeromonads, Serratia and Bacillus species. The enzyme hydrolyses
milk proteins to produce bitter peptides. Therefore, it is undesirable to have a high microbial
count before pasteurisation as the action of the residual enzymes during storage will result in
a shortening of the milk’s shelf life.
Pasteurisation at 72°C for 15 seconds is designed to kill all pathogenic bacteria such as
Mycobacterium tuberculosis, Salmonella serovars and Brucella species at levels expected in
fresh milk. Thermoduric organisms are those that survive pasteurisation. These include
Streptococcus thermophilus, Enterococcus faecalis, Micrococcus luteus and Microbacterium
lacticum. The spores of B. cereus and B. subtilis will survive the heat treatment. Bacillus cereus
growth causes pasteurised milk spoilage known as ‘bitty cream’.
3.1.3 Spoilage of meat products
Meat (usually muscle) is a highly perishable food product with water activity (Section 2.8.2)
suitable for the growth of most micro‐organisms. Since meat is highly proteinaceous, it is
relatively strongly buffered and the growth of micro‐organisms does not significantly lower
the pH. Because it is nutritious it can quickly become spoilt through the growth of micro‐
organisms and even poisonous if contaminated with foodborne pathogens. The meat itself is
sterile within the animal’s body. However, it can easily become contaminated during slaughter,
abattoir practice, handling during processing and improper storage. If micro‐organisms such
as Pseudomonas species, B. thermosphacta and lactic acid bacteria grow on the meat, then it
will become spoilt and unacceptable for eating. It is the growth of foodborne pathogens such
as Salmonella, toxin‐producing strains of Escherichia coli, Listeria monocytogenes, Clostridium
perfringens and toxin production by Staphylococcus aureus that are of concern with meat and
poultry products.
Poultry skin can carry a range of spoilage organisms: Pseudomonas species, Acinetobacter/
Moraxella species, Enterobacter species, Sh. putrefaciens, B. thermosphacta and Lactobacillus
species. The foodborne pathogen Campylobacter jejuni may also be present on the skin and
subsequently transferred to work surfaces. Pathogens such as Salmonella Enteritidis can infect
the ovaries and the oviducts of hens and subsequently the egg prior to shell formation.
Additionally eggshells become contaminated with intestinal bacteria during passage through
the cloaca and the incubator surface. Clostridium perfringens is isolated in small numbers from
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The microbiology of safe food
raw poultry. It is unable to grow due to the cold temperature of storage and the presence of
competitive psychrotrophic organisms. Bacteria found on poultry include St. aureus, L. monocytogenes and Cl. botulinum type C (not toxic to healthy adults). The St. aureus strains found on
poultry are not normally pathogenic to humans, and staphylococcal food poisoning associated
with poultry is normally due to contamination of cooked meat by an infected food handler.
Carcass meat at temperatures above 20°C will readily be spoilt by bacteria originating from
the animal’s intestines that have contaminated the meat during slaughtering. The spoilage flora
is dominated by mesophilic organisms such as E. coli, Aeromonas species, Proteus species and
Micrococcus species. At temperatures below 20°C, the spoilage flora will be predominantly
psychrotrophs such as Pseudomonas species (fluorescent and non‐fluorescent types) and
B. thermosphacta. Poultry meat will also contain small number of Acinetobacter species and Sh.
putrefaciens. At refrigeration temperatures of 5°C and below, the spoilage flora will be dominated by pseudomonads. The pseudomonads are aerobes and hence only grow on the food
surface to a depth of 3–4 mm in the underlying tissues. The spoilage is due to the degradation
of proteins producing volatile off‐flavours such as indole, dimethyl disulphide and ammonia.
Chemical oxidation of unsaturated lipids results in a rancid off‐flavour.
Fungal growth occurs under prolonged storage periods:
• ‘Whiskers’ are due to Mucor, Rhizopus and Thamnidium.
• Black spot is due to Cladosporium herbarum and Cladosporium cladosporoides.
• Penicillium species and Cladosporium species cause coloured spoilage due to their yellow
and green coloured spores.
• ‘White spot’ is caused by Sporotrichum carnis growth.
3.1.4 Fish spoilage
Bacteria can be detected from fresh fish from the slime coat on the skin (103–105 cfu/cm2), gills
(103–104 cfu/g) and the intestines (102–109 cfu/g). Fish from the marine environments of the
North Sea will be dominated by psychrotrophs, whereas the fish from warmer waters will be
colonised by a higher proportion of mesotrophs. The psychrophilic flora will be composed
of Pseudomonas species, Alteromonas species, Sh. putrefaciens, Acinetobacter species and
Moraxella species. The mesophilic flora will contain micrococci and coryneforms as well as
the acinetobacters. The flora of fish landed at ports will also include organisms from the ice
used to preserve the fish and the flora of the boat holds. Due to the high levels of psychrotrophic
flora, spoilage occurs very rapidly since the low temperature storage favours psychrotrophs. At
7°C for 5 days the microbial load can be as high as 108/g. This is faster than meat spoilage,
which would take about 10 days to obtain this microbial load. The off‐odours of spoilt fish are
probably produced by certain strains of Pseudomonas‐producing volatiles esters (ethyl acetate,
etc.) and volatile sulphide compounds (methyl mercaptan, dimethyl sulphide, etc.).
Trimethylamine oxide is reduced by certain fish spoilage organisms, such as Sh. putrefaciens to
produce trimethylamine, which gives a characteristic smell of spoilt fish. Photobacterium
phosphoreum (a luminescent bacterium) causes the spoilage of vacuum packed cod.
3.1.5 Egg spoilage
Eggs contain a barrage of antimicrobial factors including iron chelating agents (conalbumin)
and lysozyme in the albumen (egg white). The shell is covered with a water‐repellent cuticle
and has two inner membranes. In contrast, the yolk does not contain any antimicrobial factors.
Egg spoilage is principally due to Pseudomonas species as well as Proteus vulgaris, Alteromonas
species and Serratia marcescens. These produce a variety of coloured rots (Table 3.2).
Food preservation and spoilage organisms
91
Table 3.2 Bacterial causes of egg spoilage.
Spoilage organism
Type of rot
Pseudomonas spp.
Pseudomonas, Proteus, Aeromonas
Alcaligenes and Enterobacter spp.
Pseudomonas spp.
Pseudomonas and Serratia spp.
Acinetobacter‐Moraxella spp.
Green
Black
Pink
Red
Colourless
3.1.6 Cereals and grain
Because of their extensive use as human foods and livestock feeds, the microbiology of cereal
grains and cereal products is an often overlooked, though very important subject. Microbial
contamination of cereals will occur from the environment during growth, harvesting and processing. Bacteria are frequent surface contaminants of cereal grains. However, in order to grow,
they require relatively high humidity (moisture). Subsequently they are not significantly
involved in the spoilage of dry grain and only become a spoilage factor after extensive deterioration of the grain has occurred. However, spore‐forming bacteria such as B. cereus may persist
through to the final product, and cause rope spoilage in bread. Similarly, lactic acid bacteria on
grain may survive in flour and spoil doughs prepared with them. However, filamentous fungi
are the main spoilage organisms in cereal grains (Table 3.1).
The filamentous fungi that occur on cereal grains are divided into two groups: field
fungi and storage fungi. Field fungi invade grain in the field when the grain is high in moisture (18–30%) and at high relative humidities (90–100%). Field fungi include species of
Alternaria, Cladosporium, Fusarium and Helminthosporium. Storage fungi invade grain in
storage at lower moisture contents (14–16%), and lower relative humidities (65–90%).
These main storage fungi are species of Eurotium, Aspergillus and Penicillium. Therefore,
the moisture content of starchy cereal grains should be <14.0%, soybeans 12.0% and other
oilseeds, such as peanuts and sunflower seeds, 8.5%. Fungal deterioration of grains leads to
decreased germination, discolouration, odours and the potential production of mycotoxins
(Section 5.4).
3.2 Shelf life indicators
The shelf life is an important attribute of all foods. It can be defined as the time between the
production and packaging of the product and the point at which it becomes unacceptable to
the consumer. It therefore is related to the total quality of the food and linked to production
design, ingredient specifications, manufacturing process, transportation and storage (at retail
and in the home). The shelf life depends upon the food itself (Table 3.3) and it is essential for
the food manufacturer to identify the intrinsic and extrinsic parameters that limit the shelf life.
Shelf life can be determined by combined microbiological and chemical analysis of food
samples taken over the products anticipated shelf life. There are two approaches to shelf life
determination:
1 Direct determination and monitoring. This requires batches of samples to be taken at specified stages in the development of the product. Typically these samples are taken at intervals
equal to 20% of the expected shelf life to give samples of six different ages. The samples are
stored under controlled conditions until their quality becomes unacceptable. Attributes
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The microbiology of safe food
Table 3.3 Food products and associated shelf lives.
Food product
Typical shelf life
Bread
up to 1 week at ambient temperature
Sauces, dressings
1 to 2 years at ambient
Pickles
2 to 3 years at ambient
Chilled foods
Up to 4 months at 0–8°C
Frozen foods
12 to 18 months in freezer cabinets
Canned foods
Unlacquered cans, 12 to 18 months
Lacquered cans, 2 to 4 years
Table 3.4 Suggested microbiological limits for end of shelf life.
Product
Microbial count
Comments
Raw meat
1 × 106 cfu/g aerobic plate
count
1 × 107 cfu/g
Visible deterioration and/or slime at
1 × 107 cfu/g
End of shelf life, colour begins to fade
and slime forms
Represents the point where a >0.25 pH
shift occurs
Ground beef
Vacuum packaged cooked
products
Fully cooked products
1 × 106 cfu/g aerobic plate
count
1 × 106 cfu/g aerobic plate
count
1 × 103 cfu/g
Enterobacteriaceae
1 × 103 cfu/g lactic acid
bacteria
500 cfu/g yeast and moulds
tested range from smell, texture, flavour, colour and viscosity. This method is not ideal for
products with shelf lives in the order of 1 year.
2 Accelerated estimation. The need to meet product launch dates may require the use of accelerated shelf life estimations by raising the storage temperature to increase any ageing processes. This method has to be used with care since different microbial floras may develop,
which differ in off‐flavour formation from the unaccelerated spoilage flora.
Suggested microbiological shelf life limits (index of spoilage) are given in Table 3.4.
There is a wide range of compounds, principally end‐products of microbial growth, which
have potential for use in the determination and prediction of shelf life (Dainty 1996):
Chemical indicators of food spoilage are:
3.2.1 Glucose
Glucose is the main substrate for microbial growth of red meats, including modified atmosphere and vacuum packaged. Spoilage is associated with post‐glucose utilisation of amino acids
by pseudomonads and hence monitoring glucose depletion can indicate onset of spoilage. The
technique is of limited value, however, due to an ill‐defined lag phase before spoilage.
3.2.2 Gluconic and 2‐oxogluconic acid
Pseudomonas metabolism of glucose results in the accumulation of gluconic and 2‐oxogluconic
acids in beef.
Food preservation and spoilage organisms
93
3.2.3 L‐ and D‐lactic acids, acetic acid and ethanol
There is an ill‐defined lag between maximum microbial cell number and sensory detection
of spoilage on vacuum packed and low oxygen MAP red meats. Therefore the production of
L‐ and D‐lactic acids, acetic acid and ethanol from glucose may be good indicators of the onset
of spoilage in certain foods, such as pork and beef. Dainty (1996) reported that acetate levels
greater than 8 mg/100 g meat indicated a microbial flora >106 cfu/g.
3.2.4 Biologically active amines
Tyramine is produced by certain lactic acid bacteria and has no sensory property of relevance
to spoilage but has vasoactive properties. It is detectable (0.1–1.0 mg/100 g meat) in vacuum
packed beef with high microbial loads (>106 cfu/g).
3.2.5 Volatile compounds
The major advantages of volatile compound determination are that no method of extraction
from food is required and it enables the simultaneous determination of microbial and chemical activities. Nine volatile compounds during milk spoilage can be attributed to spoilage
bacteria; 2‐ and 3‐methylbutanals, 2‐propanol, ethyl hexanoate, ethyl butanoate, 1‐propanol,
2‐methylpropanol and 1‐butanol. Other volatile compounds could be attributed to chemical
oxidation of lipids. Acetone, methyl ethyl ketone, dimethyl sulphide and dimethyl disulphide
are indicators of ground beef spoilage. Other volatiles include acetoin and diacetyl for pork
spoilage and trimethylamine for fish.
Shelf life of foods can be determined microbiologically using the following.
3.2.6 Storage trials
As described above, samples are taken at timed intervals and analysed for total microbial load
and specific spoilage organisms such as pseudomonads, B. thermosphacta and lactic acid bacteria. The viable counts are compared with chemical and sensory evaluation of the product and
correlations between the variable determined to identify key indicators of early food spoilage.
3.2.7 Challenge tests
Samples of the food are incubated under conditions that reproduce the large‐scale food production and storage period. The food may be inoculated with specified target organisms of
interest, such as the spore‐former Clostridium sporogenes, as a surrogate model of Cl. botulinum
survival for obvious laboratory safety reasons.
3.2.8 Predictive modelling
This technique is described in more detail in Section 2.10. Its advantage is that the method can
simultaneously predict the growth of micro‐organisms over a range of conditions broader than
it is feasible to replicate in a microbiology laboratory. The essential aspect is the need to validate
the model using published and in‐house laboratory data. A major limitation at present is that
the majority of predictive models are concerned with food pathogens, whereas it is the food
spoilage organisms that primarily limit a product’s shelf life.
3.3 Methods of preservation and shelf life extension
Preservation methods either:
1 Prevent pathogen access to the food.
2 Inactivate any pathogens that have gained entry.
3 Prevent or slow down the growth of pathogens, if previous methods have failed.
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The microbiology of safe food
Table 3.5 Preservation methods and effect on micro‐organisms.
Effect
on micro‐organisms
Preservation factor
Method of achievement
Reduction or
inhibition of growth
Low temperature
Low water activity
Restriction of nutrient
availability
Lowered oxygen level
Raised carbon dioxide
Acidification
Alcoholic fermentation
Use of preservatives
Inactivation of
micro‐organisms
Heating
Irradiation
Hydrostatic pressure
Chill and frozen storage
Drying, curing and conserving
Compartmentalisation in water‐in‐oil emulsions
Vacuum and nitrogen packaging
Modified atmosphere packaging
Addition of acids: fermentation
Brewing: vinification; fortification
Addition of preservatives: inorganic (sulphite,
nitrite); organic (propionate, sorbate, benzoate,
parabens); antibiotic (nisin, natamycin)
Pasteurisation and sterilisation
Ionising irradiation
Application of high hydrostatic pressure
Source: Adapted from Gould (1996), and reprinted with permission from Elsevier Science.
All foods can be spoilt between harvesting, processing and storage before consumption (Gould
1996). Spoilage can be due to physical, chemical and/or microbial factors. Most preservation
methods are designed to inhibit the growth of micro‐organisms (Table 3.5).
Methods that prevent or inhibit microbial growth are chilling, freezing, drying, curing, conserving, vacuum packaging, MAP, antimicrobial packaging, acidifying, fermenting and adding
preservatives (Table 2.5). Other methods inactivate the micro‐organisms, i.e. pasteurisation,
sterilisation and irradiation. Novel methods include the use of high pressure.
The major preservation methods are based upon the reduction of microbial growth due to
unfavourable environmental conditions (cf. intrinsic and extrinsic parameters, Section 2.8.1)
such as temperature reduction, lowering of pH and water activity, and denaturation due to heat
treatment. Due to consumer pressure, the trend in recent years has been to use less severe,
milder preservation methods including combined methods such as cook‐chill foods (prolonged
shelf life) and MAP (prolonged quality). The effect on microbial growth with regard to adaptive
stress response is considered in Section 2.9.
Conventional food processing has relied on heat to kill microbial contaminants, which
simultaneously results in physical and chemical changes in the food. Increasingly the public
have requested ‘fresh’ produce, which has helped drive the development of alternative
technologies that result in minimal changes in sensory and nutritional characteristics. Methods
of predicting food safety have largely been based on thermal treatments, and these must be
compared with alternative technologies to evaluate their contribution to food safety.
To validate the effectiveness of a preservation treatment, microbial survival must be evaluated. The term ‘surrogate’ can be used for micro‐organisms added to the food as a ‘spike’.
Surrogates can be laboratory cultures, which have well‐defined characteristics and are non‐
pathogenic. For example, surrogates for Cl. botulinum include Cl. sporogenes and B. stearothermophilus. They should also have inactivation characteristics that can be used to predict
the survival of the target organism. The validity of a preservation method is usually confirmed
using an inoculated test pack, which is subject to representative conditions of processing,
handling and packaging.
Food preservation and spoilage organisms
95
Sublethal cellular damage of bacteria is of particular significance with preservation methods
(cf. Section 6.2.2). Processes aimed at inactivating pathogenic bacteria should also consider
the susceptibility of other micro‐organisms such as viruses, fungi and parasites to the treatment. Two bacterial genera of importance to food safety produce spores: the aerobic Bacillus
and anaerobic Clostridium species. The spores are resistant to heat, chemicals, irradiation and
other environmental stresses. The pasteurisation process inactivates vegetative bacterial cells,
and therefore is ineffective for bacterial spores. Consequently commercial sterilisation
processes are designed to inactivate bacterial spores of B. stearothermophilus (a thermophile)
and Cl. botulinum.
Inhibiting microbial growth, as opposed to killing microbes by heat treatment, can be used
to preserve foods. Processes that inhibit microbial growth include low temperature (chilling,
freezing), reduced water activity (dried products) and acidification. These can be combined as
a series of barriers, or hurdles, to the growth of food spoilage and poisoning organisms. Hence
the ‘hurdle concept’ combines both physical and chemical parameters to preserve food. The
interaction of these factors and their effect on microbial growth can be seen in Figure 2.17.
3.4 Preservatives
Preservative agents are required to ensure that manufactured foods remain safe and unspoilt
during their whole shelf life. A range of preservatives are used in food manufacture including
traditional foods (Table 3.6). Many preservatives are effective under low pH conditions: benzoic acid (<pH 4.0), propionic acid (<pH 5.0), sorbic acid (<pH 6.5), sulphites (<pH 4.5). The
parabens (benzoic acid esters) are more effective at neutral pH conditions.
Table 3.6 Antimicrobial food preservatives.
Preservative
(typical concentration range, mg/kg)
Weak organic and ester preservatives
Propionate (1–5000)
Sorbate (1–2000)
Examples of use
Benzoate (1–3000)
Benzoate esters (parabens, 10)
Bread, bakery and cheese products
Fresh and processed cheese, dairy products, bakery products,
syrups, jams, jellies, soft drinks, margarines, cakes, dressings
Pickles, soft drinks, dressings, semi‐preserved fish, jams, margarines
Marinated fish products
Organic acid acidulants
Lactic, citric, malic, acetic acids
(No limit)
Low pH sauces, mayonnaises, dressings, salad creams, drinks, fruit
juices and concentrates
Meat and vegetable products
Inorganic acid preservatives
Sulphite (1–450)
Nitrate and nitrite (50)
Fruit pieces, dried fruit, wine, meat sausages
Cured meat products
Mineral acid acidulants
Phosphoric acid, hydrochloric acid
Drinks
Antibiotics
Nisin
Natamycin (pimaricin)
Smoke
Cheese, canned foods
Soft fruit
Meat and fish
Source: Adapted from Gould (1996) and reprinted with permission of Elsevier Science.
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3.4.1 Organic acids
Weak organic acids are the most common classical preservative agents. Examples are acetic,
lactic, benzoic and sorbic acid, which inhibit the growth of both bacterial and fungal cells.
Sorbic acid also inhibits the germination and outgrowth of bacterial spores. The addition of
0.2% calcium propionate to bread dough delays B. cereus germination sufficiently to reduce
the risk of food poisoning to negligible. Benzoic acid at 500 ppm is used to preserve fruit juice‐
based beverages. Sulphur dioxide concentrations are controlled in European regulations to a
limit of 10 ppm
In solution, weak acid preservatives exist in a pH‐dependent equilibrium between the undissociated and dissociated state (measured as the pK value). Weak acid preservatives have an
optimal inhibitory activity at low pH because of the higher concentration of the uncharged,
undissociated state of the acid. The plasma membrane is freely permeable to this molecule
(Figure 3.4). Inside the cell it will dissociate due to the near‐neutral pH, resulting in the generation of charged anions and protons that accumulate. The inhibition of bacterial growth can
therefore be due to several factors – disruption of membrane function and the inhibition of
essential metabolic reactions – whereas in yeast, the inhibitory action may be due to the induction of a stress response to restore the cell homeostasis, which is energetically demanding. The
concentration of undissociated acids that inhibit micro‐organisms is given in Table 3.7.
Neutral pH
CH3CHOHCOOH
CH3CHOHCOO– + H+
ATP
CH3CHOHCOOH
ADP
CH3CHOHCOO– + H+
Lactic acid
Acidic pH environment
Figure 3.4 Mode of action of organic acids.
Table 3.7 Inhibitory concentration (%) of dissociated organic acids.
Acid
Enterobacteriaceae
Bacillaceae
Yeasts
Moulds
Acetic
Benzoic
Sorbic
Propionic
0.05
0.01
0.01
0.05
0.1
0.02
0.02
0.1
0.5
0.05
0.02
0.2
0.1
0.1
0.04
0.05
Source: Various sources including Mortimore and Wallace (1994),
Borch et al. (1996) and ICMSF (1996a).
Food preservation and spoilage organisms
97
3.4.2 Hydrogen peroxide and lactoperoxidase system
The lactoperoxidase system, found in fresh milk, has profound antimicrobial effects against
both bacteria and fungi. The system requires hydrogen peroxide (H2O2) and thiocyanate for
optimal activity and is primarily active against micro‐organisms producing H2O2. Alternatively,
hydrogen peroxide can be added to the foods that are to be preserved. Under suitable experimental conditions, the reaction generates short‐lived singlet oxygen molecules, which are
extremely biocidal (Figure 3.5). Furthermore, during incomplete reduction of molecular oxygen, the superoxide radical is generated. Due to the Fenton reaction, H2O2 together with the
peroxide radical and trace amounts of transition metal ions (e.g. Fe [II]) form the extremely
biocidal hydroxyl radical. A wide range of both Gram‐negative and Gram‐positive bacteria are
inhibited by the lactoperoxidase system. However, studies have shown that Gram‐negative
bacteria are generally more sensitive to lactoperoxidase‐mediated (food) preservation than
Gram‐positive species.
Hydrogen peroxide on its own is also known to be bactericidal, depending on the concentrations applied and on environmental factors such as pH and temperature. Temperature is
an extremely important parameter in determining the sporicidal efficacy of H2O2. It is weakly
sporicidal at room temperatures but very potent at higher temperatures. While the mechanism by which H2O2 kills spores is not known, the killing of vegetative bacteria and fungi is
known to involve DNA damage. In the USA, the regulatory authorities allow the direct addition of H2O2 to food products such as raw milk for the preparation of certain cheese variants,
whey intended for use in modified whey preparation, corn starch and dried eggs, and for the
decontamination of packaging material. Several other procedures where H2O2 is used as
a preservative have been reported, such as fruit and vegetable disinfection and raisin
decontamination.
3.4.3 Chelators
Chelators that can be used as food additives include the naturally occurring acid, citric acid,
and the disodium and calcium salts of ethylenediaminetetraacetic acid (EDTA). EDTA is
known to potentiate the effect of weak acid preservatives against Gram‐negative bacteria. Citric acid inhibits the growth of proteolytic Cl. botulinum due to its Ca2+ chelating
activity.
Lactoperoxidase
Derived from sulphur
containing glucosides
CN– from clover
Thiocyanate
H2O2
Produced by lactic acid bacteria
especially when milk is aerated
Hypothiocyanate [HOSCH]
Unstable
SO4– + NH4– + CO2
Figure 3.5 The lactoperoxidase system.
Antimicrobial agent
Kills bacteria
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3.4.4 Non‐acidic preservatives
Nitrate and nitrite are traditional curing salts used to prevent microbial growth, especially Cl.
botulinum. Many organisms in the microbial flora on the food are able to reduce nitrate to
nitrite, which is subsequently reduced to nitric oxide and ammonia. Nitric oxide in Cl. botulinum binds to the pyruvate phosphotransferase enzyme preventing ATP generation. Nitric
oxide also binds to the haem ring of myoglobin in meat tissue forming nitrosomyglobin, which
produces nitrosylhaemochrome, therefore generating the characteristic pink colouration of
cooked cured meats.
Nisin and pediocin PA‐1 are examples of Class IIa bacteriocins from lactic acid bacteria that
are used as food preservatives, primarily in dairy products, and have an established safety
record. Nisin has a broad inhibitory spectrum against Gram‐positive organisms and even prevents the outgrowth of bacterial spores. It is an antibacterial peptide composed of 34 amino
acids that is produced on an industrial scale from certain strains of Lactococcus lactis belonging to serological group N. It is a lantibiotic, which is a novel class of antimicrobial peptides
that contain atypical amino acids and single sulphur lanthionine rings (Figure 3.6). It has two
natural variants ‘nisin A’ and ‘nisin Z’, which differ in a single amino acid residue at position 27
(histidine in nisin A and asparagine in nisin Z). Their mode of action is primarily at the cytoplasmic membrane of susceptible micro‐organisms. The bacteriocins dissipate the proton
motive force, which stops the generation of ATP via oxidative phosphorylation. Models for
nisin interaction with membranes propose that the peptide forms poration complexes in the
membrane through a multi‐step process of binding, insertion and pore formation that requires
a trans‐negative membrane potential of 50–100 mV.
Intermediate moisture foods have water activity values between 0.65 and 0.85 (Section 2.8.2).
This is equivalent to moisture content of ~20–40%, but this conversion must be used with care
as free water is not synonymous with available water.
Ala
Dha
Ile
Dhb
Ile
Leu
Ala
Ala
S
Abu
Ala
Pro
S
Lys
Leu
Gly
Met
Abu
Gly
Gly
S
Ala
Asn
S
His
Lys
Dha
Val
His
Ile
Ser
S
Figure 3.6 The structure of nisin.
Ala
Abu
Abu
Ala
Met
Ala
Lys
Food preservation and spoilage organisms
99
Heat treatment can be used synergistically with water activity. Food with pH values greater
than pH 4.5 would normally require a botulinum cook (Section 3.5.2) to ensure safety.
However, in the presence of curing salt (nitrate and nitrite) the water activity is reduced and a
shelf‐stable product with a long, safe ambient stability can be achieved that has had a milder
(pasteurisation) heat treatment.
Note, due to the rise in antibiotic resistance amongst bacterial pathogens, antimicrobial
agents based on the nisin structure and modes of action are under evaluation for use as
therapeutic antibiotics. Current food usage of nisin has not been associated with any acquired
resistance, but whether this will change in the future due to the use of nisin‐based antibiotics
remains to be seen.
3.4.5 Preservation due to weak acids and low pH
Foods can be divided into two groups: low‐acid food with pH values above pH 4.5 and high‐
acid foods with pH values less than pH 4.5. The importance of the pH value is that Cl. botulinum
is unable to grow at pH values less pH 4.5. Therefore the processing of high‐acid foods does
not need to take into account the possible growth of Cl. botulinum.
Most food preservatives are effective at acid pH values. Organic acids include: acetic, propionic, sorbic and benzoic acids. These compounds in their undissociated form are membrane
soluble. In the cytoplasm the acid dissociates with the resultant release of a proton. The expulsion of the proton is energy demanding and therefore restricts cell growth. Carbon dioxide
forms a weak acid, carbonic acid, in solution. It prevents the growth of pseudomonads at levels
as low as 5%, whereas the lactic acid bacteria are unaffected. Therefore MAP (Section 3.6.1)
principally changes the spoilage flora.
3.4.6 Biopreservatives
In recent years there has been a change towards more physiologically based approaches to food
preservation. In addition to the weak organic acids, H2O2 and certain chelators, a few other
antimicrobial compounds are permitted by the regulatory authorities for inclusion in foods.
Some of these compounds are naturally present in spices (Table 3.8). The compounds are
eugenol in cloves, allicin in garlic, thymol in rosemary, cinnamic aldehyde and eugenol in cinnamon, and allyl isothiocyanate in mustard.
Essential oils from plants such as basil, cumin, caraway and coriander have inhibitory effects
on organisms such as Aeromonas hydrophila, Pseudomonas fluorescens and St. aureus and
therefore have been regarded as possible biopreservatives. Since many of the essential oils are
hydrophobic the mode of action is probably that they disrupt the cell membrane resulting in
the loss of function. However, the concentrations at which cell death is achieved are above
tolerable taste thresholds for them to be used as major preservatives. Also it is debatable
whether the levels in fresh garlic are significant enough to exert any antibacterial affect; there
is no allicin in cooked garlic. In practice most of the above‐mentioned compounds are used at
concentrations that may have only limited growth inhibitory effects on micro‐organisms.
Overviews of the antimicrobial (and antioxidant) properties of essential oils can be found in
Seow et al. (2014), Gottardi et al. (2016) and Gutiérrez‐Del‐Rio et al. (2018). However the
concern over hepatotoxicity due to herbal and other ‘natural’ remedies should be noted (Avigan
et al. 2016).
Alternative biopreservatives can be bacteriophages and endolysins (Misiou et al. 2018).
These can be chosen to target the major foodborne bacterial pathogens – the advantage being
they have no known harmful effects on humans. Commercial products have been approved by
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Table 3.8 Concentration of essential oils in some spices and antimicrobial activity of active components.
Spice
Essential oil in
whole spice (%)
Antimicrobial
compounds in
distillate or extract
Antimicrobial
concentration
(ppm)
Allspice (Piementa
dioica)
3.0–5.0
Eugenol
Methyl eugenol
1000
150
Cassis (Cinnamomum
cassis)
Clove (Syzgium
aromaticum)
1.2
Cinnamic aldehyde
Cinnamyl acetate
Eugenol
Eugenol acetate
10–100
Cinnamon bark
(Cinnamomum
zeylanicum)
Garlic (Allium
sativum)
0.5–1.0
Cinnamic aldehyde
Eugenol
10–1000
100
0.3–0.5
Allyl sulphonyl
Allyl sulphide
10–100
Mustard (Sinapis
nigra)
Oregano (Origanum
vulgare)
Paprika (Capsicum
annuum)
Thyme (Thymus
vulgaris)
0.5–1.0
Allyl isothionate
22–100
0.2–0.8
Thymol
Carvacrol
Capsicidin
100
100–200
100
2.5
Thymol
Carvacrol
100
100
16.0–19.0
1000
150
Organisms
Yeast
Acetobacter
Clostridium botulinum 67B
Yeast
Acetobacter
Yeast
Cl. botulinum
Vibrio parahaemolyticus
Yeast, Acetobacter
Cl. botulinum 67B
Listeria monocytogenes
Cl. botulinum 67B
L. monocytogenes
Yeast, bacteria
Yeast, Acetobacter
L. monocytogenes
V. parahaemolyticus
Cl. botulinum A, B, E
Bacillus
V. parahaemolyticus
Cl. botulinum 67B Gram‐
positive bacteria
Aspergillus parasiticus
Aspergillus flavus
Aflatoxin B1 and G1
Source: Adapted from International Commission on Microbiological Specification for Foods (ICMSF) (1998a),
with kind permission of Springer Science and Business Media.
the Food and Drug Administration (FDA) and have GRAS (generally recognised as safe) status
but not qualified presumption of safety (QPS) approval (Section 3.9.1). They are sometimes
single, but most often mixtures of multiple bacteriophages. For example:
1 ListShield – six L. monocytogenes phages.
2 Listex – single phage targeting L. monocytogenes.
3 EcoShield – mixture of three E. coli O157:H7 specific phages.
4 SalmoFresh – cocktail of six phages targeting Salmonella serovars.
These phage products can be used in foods as biopreservatives, as well as on food contact surfaces, utensils and hands to reduce cross‐contamination.
3.5 Physical methods of preservation
This section covers a wide range of non‐chemical methods of preservation, ranging from
traditional heat treatment to developments in MAP. These methods, such as milk pasteurisation, are often used for the control of foodborne pathogens as well as total flora and spoilage
organisms.
Food preservation and spoilage organisms
101
3.5.1 Preservation by heat treatment
Heat treatment is a ubiquitous means of preparing food and has been in use for thousands
of years. This can be in the form of cooking, boiling, roasting or baking, and can be at the
domestic as well as industrial level of food preparation. These procedures will cause physico‐
chemical changes that may improve the food’s taste, smell, appearance and digestibility. In
addition, it can reduce the level of microbial contamination. All micro‐organisms have a
temperature growth range (see Section 2.8, Table 2.8). Since most pathogenic bacteria are
mesophilic they will die at cooking temperatures, and heat‐labile toxins will be inactivated.
In addition, spoilage organisms will be killed and so the heat treatment of food can prolong
its shelf life as well as reduce bacterial pathogens. Heat treatment of food is necessary to kill
bacterial pathogens that may be present from environmental and intestinal contamination.
Similarly, fruits and vegetables need to be heat‐treated due to possible contamination from
water and handling.
The large‐scale heat treatment of food for preservation can be traced back to Napoleon
Bonaparte, who knew how important food provisions were to his army. In order to address the
issue of safe food for his army, he offered 12 000‐franc prize to anyone who could invent a food
preservation method. Nicolas Appert, a chef and distiller, demonstrated that boiled foods
placed in airtight glass containers would not spoil and claimed the prize. Later, in 1810, Peter
Durand patented the use of tin containers for heat‐treated food, which led to the canning
industry of today.
Pasteurisation
Milk is often pasteurised using the high‐temperature short time (HTST) 72°C, 15‐second
process. This is designed to kill all pathogenic bacteria at levels expected in fresh milk such as:
• M. tuberculosis;
• Salmonella serovars;
• Brucella species;
• Campylobacter species;
• Cryptosporidium parvum;
• diphtheria, Corynebacterium diphtheriae;
• L. monocytogenes;
• poliomyelitis;
• Q fever, Coxiella burnetii;
• pathogenic Streptococcus species.
Thermoduric organisms are those that survive pasteurisation. These include Strep. thermophilus, Ent. faecalis, M. luteus and M. lacticum. The spores of B. cereus and B. subtilis will survive
heat treatment. As mentioned earlier, Bacillus cereus growth causes pasteurised milk spoilage
known as ‘bitty cream’. Pasteurisation time and temperature regimes for other food products
are given in Table 3.9.
Sterilisation
Milk sterilisation (130°C, at least 1 second) is a well‐established method for prolonged milk
storage. The heat treatment is severe to kill all micro‐organisms present, bringing both spoilage
and foodborne pathogens down to an acceptable level. There is a statistical chance of an
organism surviving the process, but this is acceptable in the normal sense of safe food production. The 12D botulinum cook of canned foods is considered in Section 2.7.2.1.
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Table 3.9 Pasteurisation time and temperature regimes.
Food
Pasteurisation process
Main objective
Secondary effects
Milk
63°C, 30 minutes
71.5°C, 15 seconds
Kill spoilage micro‐organisms
Liquid egg
64.4°C, 2.5 minutes
60°C, 3.5 minutes
65°C, 30 minutes
71°C, 10 minutes
80°C, 15 seconds
65°C, 30 minutes
77°C, 1 minute
88°C, 15 seconds
65–68°C, 20 minutes
(in bottle)
72–75°C, 1–4 minutes
(900–1000 kPa)
Kill pathogens: Brucella abortus,
Mycobacterium tuberculosis, Coxiella
burnetii
Kill pathogens
Kill pathogens
Kill spoilage micro‐organisms
Enzyme inactivation: pectin esterase
and polygalacturonase
Kill spoilage yeast and fungi
Ice cream
Fruit juice
Beer
Kill spoilage micro‐organisms
Kill spoilage micro‐organisms: yeast
and lactic acid bacteria
Sous‐vide
Sous‐vide products are vacuum packed, undergo a mild heat treatment and have very carefully
controlled chilled storage to prevent the outgrowth of spore‐forming pathogens, notably Cl.
botulinum. The heat treatment should be equivalent to 90°C for 10 minutes to kill the spores of
psychrotrophic Cl. botulinum. Spoilage organisms, especially psychrotrophs, are also reduced
during the heat treatment and this prolongs the shelf life (i.e. 3 weeks, 3°C). Mesophiles and
thermophiles tend to survive mild heat treatments to a greater extent than psychrophiles, but
are unable to multiply at the chill storage temperatures.
3.5.2 High‐pressure treatment
The use of pressure technology is a novel means of food preservation. High‐pressure treatment
can be used to preserve food as it kills micro‐organisms, including spores. The advantage of
high‐pressure treatment is that the nutritional and sensory qualities of the food are only
slightly affected, unlike with thermal (heat) processes.
The key objective of pressure treatment is the reduction in foodborne pathogens by ~8 log
cycles (8D). Inhibition of microbial growth is found at pressures of 20–130 MPa. Higher
pressures of 130–800 MPa (depending on the organism and food matrix) are necessary for
microbial cell death. Figure 3.7 shows the recovery of St. aureus following high‐pressure
treatments. The number of survivors depends upon the pressure treatment, and also the
recovery media, with greater recovery being achieved using non‐selective media. The site of
cell damage is possibly the cytoplasmic membrane and ribosomes. Exposure of E. coli to high
pressure results in the synthesis of heat shock proteins, cold shock proteins and proteins only
associated with high‐pressure exposure. Intracellular membrane damage is the most likely initial target in high‐pressure treatment of yeast cells.
The use of pressure technology has been proposed to inactivate bacterial spores. Spore
germination is induced at low pressure (100–250 MPa) followed by inactivation at high pressure (500–600 MPa). A combination of pressure cycling and other preservation methods
may be required for the control of Clostridium species as the spores of these organisms have
greater pressure tolerance than the Bacillus species spores. Moderate hydrostatic pressure
Food preservation and spoilage organisms
103
Viable count (log10 cfu/ml)
12
10
8
6
4
2
0
0
200
400
600
Pressure (MPa)
Figure 3.7 Staphylococcus aureus survival following high pressure treatment. Plated onto selective (filled in
square symbol) and non-selective (filled in diamond symbol) media (Kalchayanard et al., 1998).
(270 MPa) at 25°C only reduces the viable count by ~1.3 log cycles. However 5 log cycle kills
can be achieved by combined treatments conditions of 35°C and the inclusion of bactericidal
compounds such as pediocin and nisin. The process can be combined (synergistically) with
heat treatment such that lower pressures of 100–250 MPa are required.
As high pressure has little effect on chemical constituents, the natural flavour, texture,
appearance and nutrient content of the food are similar to fresh or raw food. Hence this
technology has considerable potential in the future for the production of safe food that is
acceptable to the consumer.
3.5.3 Ohmic heating and radio frequency
In pasteurising meat, the aim is to eliminate pathogens and reduce the number of spoilage
organisms. Consequently, under refrigerated conditions, the meat will have a reasonable shelf
life. However with large meat products it is necessary to extend the cooking period as the heat
transfer within meat is relatively slow. This can result in overheating of the surface. Alternative
heating methods include ohmic heating and radio frequency. With both methods, heat is
generated within the product due to ionic friction. In ohmic heating, electrical energy is passed
directly into the meat, whereas in radio frequency, the electrical energy is initially converted to
electromagnetic radiation, which is then transferred to the food. Therefore, radio frequency
radiation will pass through plastic packaging materials without any requirement for direct
contact with electrodes, as per ohmic heating.
The heating is due to the generation of an electric field with positive and negative regions.
The ions in the food move to the corresponding region of the field. In ohmic heating the
polarity of the field is changing at 50–60 Hz, whereas in radio frequency, the polarity changes
at a high frequency of 27.12 mHz. The oscillation of the ions causes the internal heating.
3.5.4 Pulsed electric fields
Pulsed electric fields (PEF) is one of the most promising emergent technologies for achieving
a gentle, non‐thermal pasteurisation process. The first applications were proposed in the
1960s, but it took until 2005 for the first commercial use. The process can be applied continuously, with very little residence time.
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The microbiology of safe food
For PEF treatment, a pulse modulator and a treatment chamber are required. The pulse
modulator transforms the sinusoidal alternating current to pulses with sufficient peak voltage
and pulse energy. Disintegration of plant or animal cells requires ~1 kV/cm electric field,
whereas microbial disintegration requires electric strengths above 15 kV/cm. In PEF 20–100
electric pulses of field strengths from 25 to 70 kV/cm are applied in microsecond periods to the
food. The PEF generates pores in the membranes of micro‐organisms due to dielectric
breakdown, resulting in the loss of membrane integrity and function.
3.5.5 Ultrasound
Ultrasound waves inactivate micro‐organisms by introducing alternating compression and
expansion cycles in a liquid medium. The bactericidal effect of high‐intensity ultrasound
waves is caused during the expansion phase of ultrasound, when small bubbles grow until they
implode. The temperature and pressures reached inside these bubbles can become extremely
high. Ultrasound has not been adapted for food preservation, probably because of its adverse
effect on the quality of the treated food when applied at the intensity required to kill bacteria.
However, by using ultrasound in conjunction with pressure and heat, it may be possible to
enhance the lethality of this technology for food applications.
3.5.6 Intense light pulse
Intense light pulse (ILP) is another non‐thermal preservation technology. This uses intense
and short‐duration pulses of a broad spectrum of light 20 000 times more intense than sunlight
to inactivate micro‐organisms due to photochemical and/or photothermal effect. The degree
of inactivation is dependent upon the light intensity and the number of pulses delivered.
The method works on vegetative bacterial cells and spores. The process can decontaminate
the surface of the food, without penetrating, and therefore retains the organoleptic qualities.
3.5.7 Food irradiation
Food irradiation is the exposure of food, either packaged or in bulk, to controlled amounts of
ionising radiation for a specific period of time to achieve certain desirable objectives.
Regulations vary worldwide, but in general irradiation may only be authorised if four
cumulative requirements are met: (i) there is a reasonable technological need; (ii) it presents
no health hazard; (iii) it is of benefit to the consumer; and (iv) it is not used as a substitute for
good hygiene and other practices.
The three main approved methods are:
• Gamma rays from radionuclides 60Co or 137Cs.
• X‐rays generated from machine sources operated at or below a nominal level of 5 MeV.
• Electrons generated from machine sources operated at or below a nominal level of 10 MeV.
These processes do not increase the background radioactivity of the food.
Irradiation prevents the growth of bacteria by damaging their DNA. It can also delay ripening
and maturation by causing biochemical reactions in the plant tissues. Food irradiation reduces
the microbial load at the packaging stage. However, just like other preservation processes,
irradiation does not protect against future contamination through handling, storage and preparation of food.
Irradiation technology
The type of radiation used in processing materials is limited to radiations from high‐energy
gamma rays, X‐rays and accelerated electrons. These radiations are also known as ionising
Food preservation and spoilage organisms
105
radiations because their energy is high enough to dislodge electrons from atoms and molecules
and to convert them to electrically charged particles called ions. Gamma and X‐rays, like radio
waves, microwaves, ultraviolet and visible light rays, form part of the electromagnetic spectrum,
occurring in the short wave length, high‐energy region of the spectrum. Only certain radiation
sources can be used in food irradiation. These are the radionuclides 60Co or 137Cs, X‐ray
machines having a maximum energy of 5 MeV or electron machines having a maximum
energy of 10 MeV. Energies from these radiation sources are too low to induce radioactivity in
food. 60Co is used considerably more than 137Cs. The latter can only be obtained from nuclear
waste reprocessing plants, whereas 60Co is produced by neutron bombardment of 59Co in a
nuclear reactor. High‐energy electron beams can be produced from machines capable of
accelerating electrons, but electrons cannot penetrate very far into food, compared with
gamma radiation or X‐rays. X‐rays of various energies are produced when a beam of accelerated electrons bombards a metallic target.
Radiation dose is the quantity of radiation energy absorbed by the food as it passes through
the radiation field during processing. It is measured in the unit called the Gray (Gy). One Gray
equals one joule of energy absorbed per kilogram of food being irradiated. International health
and safety authorities have endorsed the safety of irradiation for all foods up to a dose level of
10 kGy.
Reasons for the application of food irradiation
The reasons for using food irradiation are:
• Decrease the considerable food losses due to infestation, contamination and spoilage.
• Concerns about foodborne diseases.
• Increase in international trade in food products that must meet strict import standards of
quality.
The Food and Agriculture Organisation of the United Nations (FAO) has estimated that
worldwide about 25% of all food products is lost after harvesting to insects, bacteria and
rodents. Irradiation could reduce losses and dependence upon chemical pesticides. Many
countries experience considerable losses of grain due to insect infestation, moulds and premature germination. Sprouting is the major cause of losses for roots and tubers. Countries including Belgium, France, Hungary, Japan, the Netherlands and Russia irradiate grains, potatoes
and onions on an industrial scale.
Belgium and the Netherlands irradiate frozen seafood and dry food ingredients to control
foodborne diseases. France uses electron beam irradiation on blocks of mechanically deboned,
frozen poultry products. Spices are irradiated in Argentina, Brazil, Denmark, Finland, France,
Hungary, Israel, Norway and the United States. In December 1997 the FDA approved
irradiation for beef, pork and lamb. The irradiation of poultry was approved by the FDA in
1990 and poultry processing guidelines were approved by the US Department of Agriculture
(USDA) in 1992. In the US the volume of irradiated ground beef and poultry is in the order of
15−18 million lb per year (~7 k tons).
In most countries irradiated foods must be labelled with the international symbol for irradiation (the radura), simple green petals in a broken circle. This symbol must be accompanied
by the words, ‘Treated by Irradiation’ or ‘Treated with Radiation’. Processors may add information explaining why irradiation is used; for example, ‘treated with irradiation to inhibit spoilage’ or ‘treated with irradiation instead of chemicals to control insect infestation’. When used
as ingredients in other foods, however, the label of the other food does not need to describe
these ingredients as irradiated. Irradiation labelling also does not apply to restaurant foods.
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The microbiology of safe food
The world trade in food has increased and subsequently the health and safety requirements
of importing countries must be met. There are differences in requirements however, for
example not all countries allow the importation of chemically treated fruit, some countries
(USA and Japan) have banned the use of certain fumigants. Ethylene oxide is extremely toxic.
Methyl bromide, which was a fumigant for fruits, vegetables and grain, has been subject to
several bans. In 2005, it was banned as a pesticide/fumigant under the Montreal Protocol on
Substances that Deplete the Ozone Layer, apart from quarantine and shipping uses. Then in
2010 this use was also banned because of safety to human health and environmental issues.
Food irradiation technology may be of particular usefulness to developing countries, whose
economies rely on food and agricultural production, as it is an alternative to fumigation with
ethylene bromide and ethylene oxide.
Irradiation technology can be used as an alternative to chemical additives to reduce the
number of spoilage organisms, and will also delay sprouting or maturation.
Food irradiation standard
The FDA approved the first use of irradiation on a food product (wheat and wheat flour) in
1963. Currently the technology of food irradiation has been accepted in about 60 countries for
40 different foods, and about 24 countries are using food irradiation at a commercial level. The
standard covering irradiated food has been adopted by the Codex Alimentarius Commission
(Section 12.4). It was based on the findings of a Joint Expert Committee on Food Irradiation
(JECFI), which concluded that the irradiation of any food commodity up to an overall average
dose of 10 kGy presented no toxicological hazard and required no further testing. It stated that
irradiation up to 10 kGy introduced no special nutritional or microbiological problems in
foods. The accepted dosage (10 kGy) is the equivalent of pasteurisation and cannot sterilise
food. The method does not inactivate foodborne viruses such as norovirus or hepatitis A, and
irradiation does not inactivate enzymes. Therefore, despite the lack of microbial growth,
residual enzymes could limit a product’s shelf life. It is very important that foods intended for
processing (as for any other preservation method) are of good quality and are prepared
according to good manufacturing practice established by national or international authorities.
At low doses of up to 0.5 kGy, irradiation may be used to kill Trichinella spiralis and Taenia
saginata in meat, or to inactivate metacercariae of Clonorchis and Opisthorchis in fish. Higher
doses of 3–10 kGy will kill non‐spore‐forming bacteria such as Salmonella, Campylobacter and
Vibrio. Irradiation can also be used to reduce the microbial load of spices and dried vegetables
and thus prevent the contamination of foods to which these are added. Irradiation is a very
useful pathogen control method for foodstuffs that are eaten raw or undercooked. Pork meat
may cause half to three‐quarters of Toxoplasma gondii infections in the USA. Infections due to
protozoa and helminths are very common in certain tropical countries, and therefore the
irradiation of meat and meat products can significantly reduce these risks. Similarly, the risk of
foodborne infections from poultry and seafood can be reduced by irradiation.
Table 3.10 gives the levels of approved doses for different products. The microbial survival
rates following irradiation for different organisms are given in Figure 3.8.
Testing for irradiated food
Irradiated food can be detected to a limited extent. Tests include thermoluminescence measurement for detection of irradiated spices and electron spin resonance spectroscopy for determining irradiation of meats, poultry and seafood containing any bone or shells and some
specific chemical tests. However, no single method has been developed that reliably detects
Food preservation and spoilage organisms
107
Table 3.10 Approved food irradiation levels.
Average
dose (kGy)
Food
Purpose
Chicken
Prolong storage life
Reduce the number of certain pathogenic micro‐organisms, such as
salmonella from eviscerated chicken
Control insect infestation in storage
Reduce microbial load of fermented beans with or without heat
treatment
Control insect infestation during storage
Control insect infestation
Improve keeping quality by delaying ripening
Reduce microbial load by combining irradiation and heat treatment
Inhibit sprouting during storage
Control insect infestation and improve its keeping quality by
delaying ripening
Inhibit sprouting during storage
Control insect infestation in storage
Control insect infestation in storage
Control insect infestation
Reduce microbial load
Reduce the number of pathogenic micro‐organisms
Prolong shelf life by partial elimination of spoilage organisms
Control insect infestation of dried fish during storage
and marketing
Reduce microbial load of the packed or unpacked fish and fish
productsa
Reduce the number of certain pathogenic micro‐organisms in
packaged or unpackaged fish and fish productsa
Control insect infestation in the stored product
Cocoa beans
Dates
Mangoes
Onions
Papaya
Potatoes
Pulses
Rice
Spices and condiments
Dehydrated onions
Onion powder
Strawberry
Teleost fish and fish
products
Wheat and ground
wheat products
a
7
7
1
1
1
1
1
1
0.15
1
0.15
1
1
1
10
10
3
1
2.2
2.2
1
During irradiation and storage the fish and fish products should be kept at the temperature of melting ice.
8
Survivors (log10 cfu/ml)
7
Enterovirus
6
5
St. aureus
4
L. monocytogenes
3
2
C. jejuni
1
0
E. coli
0
2
4
6
Irradiation dose (kGy)
Figure 3.8 Survival of micro‐organisms following irradiation.
8
10
108
The microbiology of safe food
irradiation of all types of foods or the radiation dose level that was used. This is partly because
the irradiation process does not physically change the appearance, shape or temperature of
products and causes negligible chemical changes in foods.
After irradiation treatment the bacterial viability will have decreased by >104 cfu/g. The
dead bacteria can be detected using the direct epifluorescent filter technique (DEFT) or by the
limulus amoebocyte lysate (LAL) tests, and the viable organisms enumerated using conventional colony count methods (Anon. 2000, 2004). If the difference is >3 log units then the
sample may be presumptively identified as having been irradiated. Since other processes will
cause bacterial cell death, the result should be confirmed using electron spin resonance, thermoluminescence or lipid radiolytic compound. There is still considerably more research
required in order to determine whether ingredients have been irradiated, which will have been
added at low quantities.
It should be noted that irradiation should be regarded as complementing good hygienic
practice and not as a replacement for it.
Acceptability of Food Irradiation by the Consumer
One major factor influencing the large‐scale application of food irradiation is public understanding and acceptance of the technology. Consumer reservation is based upon a number of
issues:
1 Fears linked to other nuclear‐related technologies. However, irradiated food cannot become
radioactive itself.
2 Ingestion of radiolytic product. The maximum dose (10 kGy) produces 3–30 ppb radiolytic
products. This would account for 5% of the total diet. The probability of harm occurring
from radiolytic product formation from food additives is extremely low.
3 Food irradiation would mask poor quality (i.e. spoilt) food. However, although spoilage
bacteria may not be detectable, the off‐odours and poor appearance would still be evident.
4 The lack of a suitable detection method is also of concern. But this uncertainty also occurs
with others food that are accepted; organically grown produce cannot be identified analytically, nor can unacceptable temperature fluctuations of chilled and frozen foods be
determined.
5 Vitamin losses, especially B1 in pork and vitamin C in fruit. The vitamin B1 loss is estimated at
2.3% of vitamin B1 in an American diet and vitamin C is converted into an equally usable form.
6 Induction of chromosomal abnormalities. The publicised polypoidy from the consumption
of irradiated wheat in India has never been reproduced by subsequent investigations and the
validity of the original data has been disputed by international scientific committees.
Current consumer pressure has hindered the large‐scale expansion of irradiation technology
despite its promise of safe food production.
3.5.8 Cold plasma and low‐energy electrons for food surface decontamination
Many food products need surface decontamination as they are perishable and have a high microbial load on/near the surface. One possible solution is the use of cold plasma to decontaminate
the surfaces of the food or food ingredient. Cold plasma is a novel non‐thermal food processing
technology that uses energetic, reactive gases, which has been shown in laboratory studies to kill
bacteria (spoilage and infectious) and viruses (norovirus and hepatitis A) on the surface of fresh
fruits and vegetables, dry fruits, spices, nuts and seeds, meat and cold cuts and eggshells. The
gases are made by ionising with corona discharges. Another example of a novel technology is
the use of low‐energy electrons (0.3 MeV or lower) to decontaminate product surfaces only,
Food preservation and spoilage organisms
109
therefore maintaining germination potential and nutritional value. It is unclear whether these
two technologies will be legislated in the future under the umbrella term of ‘irradiation’. Currently
they are not used by the food industry but are under further investigation with respect to colour
changes and inactivation of naturally occurring enzymes in the food, such as polyphenoloxidase,
peroxidase, superoxide dismutase and lysozyme (Chizoba Ekezie et al. 2017; Pignata et al. 2017).
Cold plasma can be used at room temperature on food contact surfaces to disrupt bacterial
biofilms (Niemira et al. 2014). Such biofilms often form during food production in areas that
are inaccessible and not easy to clean, and therefore the plasma technology needs to be designed
with this difficult issue in mind. They can also be used to kill bacterial pathogens that are
internalised in plant material and therefore not susceptible to conventional cleaning by washing and chlorine drips (Ziuzina et al. 2015).
3.6 Packaging
3.6.1 Reduced oxygen packaging, modified atmosphere packaging
and active packaging
Reduced oxygen packaging (ROP) results in the food being surrounded by an atmosphere that
contains little or no oxygen. The term ROP is defined as any packing procedure that results in
a reduced oxygen level in a sealed package. It covers a range of packaging processes: sous‐vide,
vacuum packaging, cook‐chill, controlled atmosphere packaging (CAP) and MAP.
In cook‐chill, a plastic bag is filled with hot cooked food from which the air has been
expelled and which is closed with a plastic or metal crimp.
Sous‐vide is a specialised process for partially cooked ingredients alone or combined with
raw foods that require refrigeration (<3°C) or frozen storage until the package is thoroughly
heated immediately before service. The sous‐vide process is a pasteurisation step that reduces
bacterial load but is not sufficient to make the food shelf‐stable.
Vacuum packaging reduces the amount of air from a package and hermetically seals it so
that a near‐perfect vacuum remains inside.
CAP is an active system in which a desired atmosphere is maintained for the duration of the
shelf life by the use of agents to bind or scavenge oxygen or a gas generating kit. CAP is defined
as packaging of a product in a modified atmosphere followed by maintaining subsequent
control of that atmosphere.
MAP is defined as the enclosing of food products in an atmosphere inside gas‐barrier
materials, in which the gaseous environment has been modified to slow down respiration rate,
microbial growth and reduce enzymic degradation, with the intention of extending the shelf
life. Controlled atmosphere storage (CAS) and/or active or passive MAP can be used. In active
MAP a slight vacuum inside the package is generated that is replaced by a chosen mixture of
gases. Passive MAP is when the product is packaged with a specific film, and the desired
atmosphere develops naturally due to the product’s metabolism activity and the diffusion of
gases through the film. The choice of the film and storage temperature are crucial, due to their
effects on gas diffusion rates. Carbon dioxide is the most important headspace gas. It is a non‐
combustible, colourless gas that is favoured as a preservative since it leaves no toxic residues in
the food. Hence it can also be used in MAP. A concentration of 20–60% retards the spoilage
due to pseudomonads. Recent trends have seen the use of argon instead of nitrogen to reduce
food spoilage. Also the application of MAP has been extended to fresh produce, fresh meat,
poultry, fin fish, ready meals and bakery products.
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The microbiology of safe food
Solid CO2 (dry ice) controls microbial growth by acting as a refrigerant during transport
and storage. Then, as the dry ice sublimes, the CO2 gas further inhibits bacterial growth by
displacing the oxygen required by aerobic organisms, as well as by forming carbonic acid and
thus possibly lowering the pH of the food to bacteriostatic levels.
Oxygen is a major cause of food deterioration due to the oxidation of fats and oils, enzymic
discolouration, and enabling the growth of many micro‐organisms. To scavenge oxygen a
sachet of iron powder may be placed under the label. This can reduce the oxygen levels to
<0.01% (MAP is 0.3–3%). In the US there are between 1500 and 200 million active packaging
units with oxygen scavengers per annum. Carbon dioxide can extend a product’s life by
retarding microbial growth. Carbon dioxide emitters are frequently sachets containing ascorbic acid, sodium hydrogen carbonate and ferrous carbonate. These can emit an equal amount
of gas to the oxygen absorbed, to prevent pack collapse, or can replace the carbon dioxide that
has permeated through the packaging. Ethylene scavenging systems may be used to reduce the
ripening process of fruit and vegetables. Potassium permanganate is very efficient, but is toxic
and therefore must not come into contact with the food. Alternatives are activated carbon and
titanium dioxide. Ethanol is antimicrobial and may be incorporated into packaging. The level
is very important as too low will be ineffective, but too high will lead to an unwanted taint.
ROP can prevent the growth of aerobic spoilage organisms and hence extend the shelf life
for foods in the distribution chain. However, foods may be subject to temperature abuse during
distribution and therefore at least one more barrier (or hurdle, Section 3.3) needs to be
incorporated into the ROP process. ROP products commonly do not contain preservatives and
do not have the intrinsic factors (pH, aw, etc.) to prevent microbial growth. Subsequently to
prevent the growth of Cl. botulinum and L. monocytogenes, the storage temperature must be
maintained below 3.3°C (cf. Table 2.8) for an extended shelf life, otherwise 5°C for the duration
of the shelf life. The temperature treatment for ready‐to‐eat, including cook‐chill products,
should achieve a 4 D kill of L. monocytogenes (US recommendations). In Europe, sous‐vide
products should be subjected to a 12–13D Ent. faecalis heat treatment. This organism is used
on the assumption that thermal inactivation of Ent. faecalis would ensure the destruction of all
other vegetative pathogens.
3.6.2 Antimicrobial packaging and nanotechnology
A current drawback with food packaging materials is their permeable nature. None of the
packaging materials are a complete barrier to atmospheric gases and water. Polypropylene,
polyethylene, polyethylene terephthalate, polystyrene and polyvinyl chloride are used because
of their low cost, ease of production and light weight. In the future nanomaterials could
be incorporated into the packaging.
Nanotechnology is concerned with compounds in the 1–100 nm size range. The concept
was introduced by Richard Feynman in 1959, though the term ‘nanotechnology’ is attributed
to Norio Taniguchi in 1974. Currently, it is a major focus of research by industry, and is
receiving considerable governmental funding for research. It is applied in engineering, the
chemical industry and medical sciences. There are more than 200 companies involved in this
area worldwide, with the leaders being the USA, followed by Japan and China. By 2021 the
market size for antimicrobial food packaging is predicted to be ~$10.4 billion.
Nanocomposites have been made as packaging materials or as coatings on plastic containers
to control gas diffusion and to prolong the shelf life (Sozer and Kokini 2009). Another application is the production of antimicrobial food contact materials.
Food preservation and spoilage organisms
111
Active packaging is designed such that the packaging material contains compounds that
can, for example, release antimicrobial or antioxidant agents, or control the internal atmosphere
by absorbing oxygen or water vapour. The technology may even lead to ‘smart’ surfaces that
can detect bacterial contamination and inhibit its growth, indicate temperature changes, pH
and CO2 levels, as well as remove taints and odours (Sharma et al. 2017).
As for all new compounds that come into contact with food, the potential health risks of
nanoscale materials needs to be evaluated before their use. While the risk of the same material
as a macroscale particle may already have been determined, nanoscale materials can behave
differently. It is already known that some nanoparticles can cross the blood–brain barrier. One
identified problem is the transfer of nanoparticles from packaging material to food. Similarly
food technologists could use nanoparticles of previously approved macroscale ingredients
without considering whether there are possibly new toxicological aspects (Oberdörster et al.
2005; Bouwmeester et al. 2009).
Various metals such as gold, silver and zinc, as well as metal oxides of titanium (TiO2), zinc
(ZnO), silicon (SiO2) and magnesium (MgO) have been considered for active food packaging
applications. These can be formulated with organic biodegradable material such as chitosan
films as an alternative to traditional plastics. Zinc oxide (ZnO) and copper oxide nanomaterials are already used in medical dressings because of their antimicrobial activities, and low
toxicity to human cells. Also conventional (non‐nano) titanium dioxide (E171) is approved as
a food colourant in products such as in milk powder. These compounds either function on
direct contact or migrate slowly from the packaging to the food. Their antimicrobial activity
may be due to direct interaction with the microbial cell (i.e. disrupting membrane functions),
oxidising cellular components or producing secondary products such as reactive oxygen species, or dissolved heavy metal ions, leading to microbial cell damage. Their attraction for the
food industry is that they retain their antimicrobial activity following food processing steps
such as high temperature and pressures, and have long shelf life. Additionally, their antimicrobial activity is very non‐specific, which makes the development of resistance less likely.
Further developments in packaging include intelligent or smart packaging systems that can
indicate the condition of the food with respect to its potential microbial safety. This includes the
development of nano‐sensors, time–temperature indicators, oxygen sensors and freshness indicators that indicate the status within the packaging without opening. Brief examples include:
• Bacterial sensors: antibiotics coupled to quantum dots for fluorescence‐based detection
systems.
• Freshness indicators: Detection of microbial metabolites such as volatile sulphides using
silver or copper coatings, which darken due to production of metal sulphide.
• Humidity indicators: Nanocrystalline cellulose film with an iridescent film; blue‐green colour
changes to red‐orange in high humidity.
• Oxygen sensors: SnO2 and TiO2 nanoparticles that are colourless in the absence of gaseous
oxygen.
• Carbon dioxide sensor: Combination of a phosphorescent reporter dye (phosphorescent
Pt‐porphyrin) and naphtholphthalein (a colourimetric pH indicator).
3.7 Fermented food products
Our diet often includes microbially fermented foods. These have been a traditional means of
food preservation and geographically vary according the fermentable foods available. These
foods may have an important role in a country’s economy and food sustainability (Table 3.11).
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The microbiology of safe food
Table 3.11 Fermented foods from around the world.
Product
Substrate
Micro‐organism(s)
Bread
Bongkrek
Cheese
Cheddar
Grain
Grain
Millet
Grain
Coconut
Saccharomyces cerevisiae
Saccharomyces carlsbergensis
Saccharomyces fibulger
Sac. cerevisiae, other yeasts, lactic acid bacteria
Rhizopus oligosporus
Milk
Cottage
Mould‐ripened
Swiss
Coffee
Milk
Milk
Milk
Bean
Cocoa
Bean
Fish, fermented
Gari
Fish
Cassava
Idii
Rice
Kimchi
Mahewu
Cabbage, nuts,
vegetables,
seafood
Maize
Streptococcus cremoris, Streptococcus lactis, Streptococcus
diacetylactis, lactobacilli
Strep. diacetylactis
Strep. cremoris, Strep. lactis, Penicillium caseicolum
As per ‘cheddar’, plus Propionibacterium shermanii
Leuconostoc, Lactobacillus, Bacillus, Erwinia, Aspergillus and
Fusarium spp.
Lactobacillus plantarum, Lactobacillus mali, Lactobacillus fermentum,
Lactobacillus collinoides, Acetobacter rancens, Acetobacter aceti,
Acetobacter oxydans, Sac. cerevisiae var. ellipsoideus, Saccharomyces
apiculata
Bacillus pumilus, Bacillus licheniformis
Corynebacterium manihot, Geotrichum spp., Lb. plantarum,
streptococci
Leuconostoc mesenteroides, Enterococcus faecalis, Torulopsis, Candida,
Trichosporon pullulans
Lactic acid bacteria
Nan
Ogi
Wheat
Maize
Olives
Oncom
Pickles
Green olives
Peanuts
Vegetables
Sauerkraut
Cabbage
Sausages,
fermented
Soy sauce
Meat
Corynebacterium spp., Aerobacter spp., Sac. cerevisiae, Lactobacillus
spp., Candida mycoderma
Sac. cerevisiae, lactic acid bacteria
Lactic acid bacteria, Cephalosporium, Fusarium, Aspergillus,
Penicillium spp., Sac. cerevisiae, Can. mycoderma, Candida valida,
Candida vini
Ln. mesenteroides, Lb. plantarum
Neurothemis intermedia, Rhizopus oligosporus
Leuconostoc mesenteroides, Lactobacillus brevis, Pediococcus
cerevisiae, Lac. plantarum.
Leuconostoc mesenteroides, Lac. brevis, Pediococcus cerevisiae, Lac.
plantarum
Pediococcus cerevisiae, Lac. plantarum, Lactobacillus curvatus
Soybeans,
wheat
Soybeans
Wine
Aspergillus oryzae, Aspergillus soya, Mucor spp., Rhizopus spp., Ped.
soyae, Zygosac. rouxii, Lactobacillus spp.
Rhizopus oligosporus
Ac. aceti
Cactus
Grape
Palm
Rice
Milk
Saccharomyces carbajaoli
Sac. cerevisiae var. ellipsoideus
Zymomonas mobilis
Saccharomyces sake
Streptococcus thermophilus, Lactobacillus bulgaricus
Beer
Ale
Lager
Tempeh
Vinegar
Wine
Agave
Common
Sake
yogurt
Food preservation and spoilage organisms
113
However, in some circumstances, traditional fermented foods may be prepared at the household
level using poor sanitary conditions, and not under any regulatory standards. Fermented foods
often have anecdotal health benefits attributed to them. However, such health claims need to be
verified and appropriate microbiological risk assessments undertaken (Benkerroum 2013).
Fermented legumes (often soybeans) vegetables, pickles, fish and meat are eaten in Far East
Asia, South Asia, North Asia and the Indian subcontinent excluding western and northern
India, while the diet in the western and northern parts of India, the West Asian continent,
Europe, North America and even Australia and New Zealand includes fermented milk products, meat and fermented meats (sausages). Africa and South America have many fermented
sorghum, meat and milk products. The microbes will originate from the vegetables, environment and preparation utensils. Their fermentation will cause acidification or alkalisation of
the food as well as desirable organoleptic traits.
3.7.1 Fermented milk products
There are many regional fermented milk products produced around the world (Table 3.12).
The production of most fermented milk products (such as cheese and yogurt) requires the
addition of starter cultures. These are laboratory‐maintained cultures of lactic acid bacteria.
The cultures may be well defined or composed of different strains depending upon the scale
of production and historical experience (Table 3.13). The cultures will be rotated at regular
intervals to avoid the possible accumulation of lactic acid bacteria‐specific bacteriophages in
the production plant. Bacteriophages would slow the fermentation activity of the starter cultures and even enable pathogenic organisms to multiply in the fermented food. Typical
starter cultures include the mesophiles: Lc. lactis subsp. lactis and Lc. lactis subsp. cremoris or
Table 3.12 Fermented milk products around the world.
Product
Type
Micro‐organisms
Yogurt
Cheddar cheese (UK)
Moderate acid
Moderate acid
Cultured buttermilk (USA)
Acidophilus milk (USA)
Bulgarian milk (Europe)
Dahi (India)
Moderate acid
High acid
High acid
Moderate acid
Leben (Egypt)
Surati cheese (India)
Kefir (Russia)
Koumiss (Russia)
High acid
Mild acid
High alcohol
High alcohol
Streptococcus thermophilus, Lactobacillus bulgaricus
Streptococcus cremoris, Streptococcus lactis, Streptococcus
diacetylactis
Lactococcus cremoris, Lactococcus lactis, Leuconostoc citrovorum
Lactobacillus acidophilus
Lactobacillus bulgaricus
Lactococcus lactis, Lactococcus cremoris, Lactococcus
diacetylactis, Leuconostoc spp.
Streptococci, lactobacilli, yeast
Streptococci
Streptococci, Leuconostoc spp., yeast
Lb. acidophilus, Lactobacillus bulgaricus, Saccharomyces lactis
Table 3.13 Lactic acid bacteria and bifidobacteria in the human intestinal tract.
Location
Species
Oral cavity
Large intestines
Streptococcus mutans, Bifidobacterium longum
Lactobacillus acidophilus, Lactobacillus gasseri, Lactobacillus johnsonii, Lactobacillus plantarum,
Streptococcus agalactiae, Enterococcus faecalis
Bif. longum, Strep. agalactiae, Lactobacillus crispatus
Vagina
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The microbiology of safe food
Raw milk
Pasteurisation
Addition of starter culture
Addition of rennin or
protease from Mucor pusillis
Separate curds and whey
Addition of salt
Ripen 6–8°C
Figure 3.9 Generalised production of cheese.
thermophilic Strep. thermophilus, Lactobacillus helveticus and Lactobacillus delbrueckii subsp.
bulgaricus.
In cheese manufacture (Figure 3.9) the addition of the protease rennin, either from calf
stomachs or from the fungus Mucor pusillis, and acidification from microbial lactic acid production results in the precipitation of caesin as ‘curds’, which are separated from the remaining
liquid fraction (‘whey’). The curds are salted and pressed into shape and left to ripen at 6–8°C.
The characteristics of many regional products are dependent upon secondary bacterial or fungal colonisation (Table 3.14). For example Propionibacterium shermanii causes the production
of carbon dioxide gas and the characteristic eyes in Swiss cheese. Penicillium roqueforti (a
fungus) produces the blue veining in certain cheeses. Candida utilis and C. kefir are involved
in the production of blue cheese and kefir, respectively. Brevibacterium strains are widely used
for the manufacturing of surface‐ripened cheeses, contributing to the breakdown of lipids and
proteins and producing volatile sulphur compounds and red‐orange pigments.
Microflora studies have revealed differences in the microbial ecosystem of the cheese surface and the interior. Microbial communities in the rinds of surface‐ripened cheeses are composed of bacteria and yeasts, which contribute to the flavour, texture and appearance of the
final product. The aerobic surface flora is dominated by a very diverse range of G+C rich species, whereas the interior is composed of fewer species, which are lower in G+C content (Ogier
et al. 2004). The organisms will be naturally occurring in the production environment, milk or
innocula of ripening cultures. The function of the ripening cultures is to generate cheese with
Food preservation and spoilage organisms
115
Table 3.14 Categories of lactic starter strains.
Type
Species
Application method
Single strain
Streptococcus cremoris
Streptococcus lactis
Streptococcus lactis subsp.
diacetylactis
As above plus Leuconostoc spp.
Streptococcus cremoris
Single or paired
Multiple strains
Mixed strain starters
Defined mixture of two or more strains
Unknown proportions of different strains, which
may vary on subculturing.
Glucose
Homofermentative
Heterofermentative
Glucose-6-phosphate
Glucose-6-phosphate
Fructose-6-phosphate
6-Phosphogluconate
Fructose-1,6-diphosphate
Ribulose-5-phosphate
Xylulose-5-phosphate
Glyceraldehyde-3-phosphate
Dihydroxyacetone phosphate
Glyceraldehyde-3-phosphate Acetyl phosphate
2 Pyruvate
Pyruvate
Acetaldehyde
2 Lactate
Lactate
Ethanol
Figure 3.10 Production of lactic acid by homo‐ and heterofermentative lactic acid bacteria.
consistent organoleptic properties, as well as outcompete undesirable pathogenic and spoilage
organisms.
Pathogenic bacteria are killed by pasteurisation and therefore cheese made from pasteurised
milk should be safe. However, inadequate pasteurisation and post‐pasteurisation contamination can occur. In addition some cheeses are made from non‐pasteurised milk. Nevertheless
the rapid acidification of the milk due to lactic acid production should inhibit the multiplication of any pathogens present. However, if the starter culture is not fully active, possibly due to
bacteriophage infection, then pathogens can multiply to infectious levels. A number of food
poisoning incidences linked to cheese have been reported.
Yogurt manufacture uses the complementary metabolic activities of Strep. thermophilus and
Lactobacillus bulgaricus (1:1 inoculation ratio). The Lactobacillus requires the initial growth of
the streptococci to produce folic acid, which is essential for the Lactobacillus growth.
Subsequently Lb. bulgaricus produces diacetyl and acetaldehyde, which add flavour and aroma
to the product (Figures 3.10–3.12). A slow fermentation by the starter cultures can enable St.
aureus to multiply to numbers sufficient to produce enterotoxins at levels high enough to
induce vomiting.
Kefir is an acidic‐alcoholic fermented milk product with a creamy consistency. It can be
produced by fermenting milk with commercially available freeze‐dried kefir starter cultures,
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The microbiology of safe food
3 Citric acid
3 Acetate 3 Oxaloacetic acid
3 CO2
3 Pyruvic acid
3 Lactic acid
CO2
CO2
Acetyl-CoA
Acetaldehyde
Diacetyl
Figure 3.11 Production of diacetyl by lactic acid bacteria.
Raw milk
Pasteurisation
Cooled and homogenised
Strep. thermophilus
and Lb. bulgaricus (1:1 ratio)
Incubate
(4–16 hours, 30–45°C)
Cool
Add flavourings and fruit
Packaging and storage
Figure 3.12 Production of yogurt.
Food preservation and spoilage organisms
117
Table 3.15 Secondary flora of fermented dairy products.
Type
Micro‐organism
Cheese types
Bacteria
Corynebacteria
Micrococcus spp.
Lactobacillus spp.
Pediococcus spp.
Propionibacteria
Kluyveromyces lactis
Saccharomyces cerevisiae
Candida utilis
Debaryomyces hansensii
Rhodosporidium infirmominiatum
Candida kefir
Penicillium camemberti
Geotrichum candidum
Penicillium roqueforti
Penicillium nalgiovense
Verticillium lecanii
Red smear‐ripened, washed rind
Yeasts
Mould
Hard and semi‐hard
Swiss types
Blue, soft mould‐ripened, red smear‐ripened, washed rind
Kefir
Soft mould‐ripened (Brie, Camembert, Coulommiers)
Blue cheese (Danish Blue, Roquefort, Stilton)
Tomme
Tomme
Source: Adapted from Stanley (1998), with kind permission of Springer Science and Business Media.
traditional kefir grains or liquid that remains after the removal of kefir grains from a previous
fermentation. The milk can be cow, sheep, goat or buffalo. Kefir grains contain a microbial
symbiotic mixture of lactic acid bacteria (108 cfu/g), yeast (106–107 cfu/g) and acetic acid
bacteria (105 cfu/g). The predominant lactic acid bacteria are Lactobacillus paracasei ssp. paracasei, Lb. acidophilus, Lb. delbrueckii ssp. bulgaricus, Lactobacillus plantarum and
Lactobacillus kefiranofaciens. Yeast that have been isolated are mainly Saccharomyces cerevisiae, S. unisporus, Candida kefyr and Kluyveromyces marxianus ssp. marxianus, with the acetic acid bacteria being Acetobacter aceti and A. rasens. The exact microbial flora will vary
according to production region and process. In kefir grains the main polysaccharide is kefiran. It is mainly produced by the bacterial species Lb. kefiranofaciens, which dominates at the
end of the fermentation period. The heteropolysaccharide is composed of equal proportions
of glucose and galactose.
There are many health benefits attributed to the ingestion of fermented milk products:
• Increased digestibility and the nutritive value of milk itself.
• Reduced lactose content, important to a lactose‐intolerant population.
• Increased absorption of calcium and iron.
• Increased content of some B‐type vitamins.
• Control of the intestinal microbial flora composition.
• Inhibition of pathogenic micro‐organism multiplication in the intestinal tract.
• Decreased cholesterol levels in blood.
Consequently there are a number of commercially available fermented milk products that
claim to promote health (Table 3.21).
3.7.2 Fermented meat products
Fermented sausages are produced from the bacterial metabolism of meat. The meat is first
comminuted and mixed with fat, salt, curing agents (nitrate and nitrite), sugar and spices
before being fermented. The sausages have a low water activity (Section 2.8.2) and are generally
118
The microbiology of safe food
classified as either dry (aw < 0.9) or semi‐dry (aw 0.9–0.95). The dry sausage is normally eaten
without any cooking or other form of processing. In contrast the semi‐dry sausages are smoked
and hence receive a heat treatment of between 60 and 68°C. Sausages produced without the
addition of a starter culture have a pH of 4.6–5.0, whereas sausages with starter cultures usually
have a lower final pH of 4.0–4.5. These low pH values are inhibitory to the growth of most food
pathogens (Table 2.8). The starter cultures are composed of lactobacilli (such as Lb. sake and
Lb. curvatus), pediococci, Strep. carnosus and Micrococcus varians. The fungi Debaryomyces
hansenii, Candida famata, Penicillium nalgiovense and P. chrysogenum may also form part of
the starter culture.
The bacterial pathogens that are potential hazards in fermented sausages are salmonellae, St.
aureus, L. monocytogenes and the spore‐forming bacteria Bacillus and Clostridium. The high
level of salt (~2.5%) inhibits pathogen growth and during the drying process Salmonella
(and other Enterobacteriaceae) die off. Controlling salmonellae contamination also controls
the growth of L. monocytogenes. Although St. aureus is resistant to nitrite and salt, it is a
poor competitor with the remnant microflora under the acidic anaerobic conditions. See
Section 14.4.7 for details of a major L. monocytogenes outbreak with over 200 deaths in South
Africa due to polony sausage.
3.7.3 Fermented vegetables
There are a large number of commercial vegetable fermentations. Additionally there are a large
variety of fermented vegetable juices, olives, cucumbers and cabbage that are produced domestically. Vegetables have a high microbial load; however, if they were pasteurised this would
affect their final properties and would be detrimental to the product’s quality. Therefore the
majority of vegetable fermentations use lactic acid production and no heat treatment (smoking, etc.). Lactic acid bacteria are present only in low numbers on vegetables and therefore
starter cultures are usually used: Lb. plantarum, Lb. casei, Lb. acidophilus, Lc. lactis and
Leuconostoc mesenteroides.
3.7.4 Fermented protein foods: shoyu and miso
In the Orient the fungi Aspergillus (Aspergillus oryzae, A. sojae and A. niger), Mucor and
Rhizopus have been used to ferment grain, soybeans and rice (Table 3.16). This is called the
koji process (Figure 3.13). The main microbial activity is amylolytic degradation. The presence
of mycotoxins has not been reported in koji products despite extensive investigations.
Mycotoxins can potentially be produced after prolonged incubation by commercial strains of
Aspergillus under specific environmental stress conditions (Table 3.17). In contrast, Aspergillus
fermentations in the koji process seldom exceed 48–72 hours.
3.8 Organisms involved in the production of fermented foods
Fermented foods are one of the oldest means of food processing. It is thought that the civilisations in the fertile crescent of the Middle East ate fermented milk, meats and vegetables. This
established traditions of production methods and the incidental selection of microbial strains.
In 1910 Metchnikoff proposed that lactic acid bacteria could be used to aid human health, a
topic that resurfaced in the area of ‘probiotics’ (see Section 3.9 for details). Nowadays the
production of fermented foods is practised across the world, with many diverse national
products (Tables 3.11 and 3.12). The important microbial strains have been identified through
conventional techniques and their metabolic pathways studied. Such fermented foods are
Food preservation and spoilage organisms
119
Table 3.16 Yeast and moulds from koji starter cakes.
Starter cake
Moulds
Yeasts
Chinese yeast
Rhizopus javanicus
Rhizopus chinensis, Amylomyces rouxii
Amy. rouxii, Mucor dubius, Mucor
javanicus
Rhizopus oryzae, Aspergillus niger
Rhizopus stolonifer, Mucor rouxii
Rhizopus cohnii, Zygorrhynchus moelleri
Endomycopsis spp.
Ragi
Loog‐pang
Murcha
Bubod
Aspergillus oryzae, Aspergillus flavus,
Rhizopus oligosporus, Rhizopus arrhizus
Fusarium spp.
Amy. rouxii, Mucor spp., Rhizopus spp.
A. oryzae
Mucor fragilis, M. rouxii, R. arrhizus
Rhizopus spp., Mucor spp.
Toruia indica, Hansenula anomala,
Saccharomyces cerevisiae
Endomycopsis chodati, Endomycopsis fibuligera
Hansenula subpelliculosa, Hansenula malanga,
Candida guilliermondii, Cryptococcus humicola,
Cryptococcus intermedia, Cryptococcus japonica,
Cryptococcus pelliculo
E. fibuligera
Saccharomyces cerevisiae
H. anomala
Endomycopsis spp.
Saccharomyces spp.
Source: Adapted from Lotong (1998), with kind permission of Springer Science and Business Media.
Raw materials
(grain, soya bean or rice)
Cook
Inoculate with cake
containing yeast and moulds
(i.e. Asp. oryzae)
Incubate at 25–30°C
Koji
Soya sauce Miso Rice wine (sake)
Figure 3.13 Production of Koji.
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Table 3.17 Mycotoxins produced in cheese.
Organism
Mycotoxin
Aspergillus oryzae
Aspergillus sojae
Aspergillus tamarii
Aspergillus versicolor
Penicillium camemberti
Penicillium rogueforti
Cyclopiazonic acid, kojic acid, maltoryzine, β‐nitropropionic acid
Aspergillic acid, kojic acid
Kojic acid
Sterigmatocystin
Cyclopiazonic acid
Cyclopiazonic acid, mycophenolic acid, patulin, penicillic acid, roquefortine,
PR toxin
Source: After Rowland (1999) and Hymery et al. (2014).
consequently heavily colonised by bacteria and yeast, depending upon the specific product,
yet there is no associated health risk. The reason is that the organisms are non‐pathogenic
having been selected during the passage of time through trial and error. In fact the organisms
inhibit the growth of pathogens and food products termed ‘functional foods’, in particular
probiotics (i.e. Yakult), have arisen from the ancient practice of fermented food production.
The lactic acid bacteria used in the production of most fermented foods produce a range of
antimicrobial factors including organic acids, hydrogen peroxide, nisin and bacteriocins.
Because lactic acid bacteria have such a proven history of being non‐pathogenic they are
termed GRAS organisms (Section 3.9.1). This title, however, may come under closer scrutiny
with the use of genetically engineered strains and the area of probiotics. Only the essential
aspects of fermented foods as pertaining to their safety will be covered here. For a detailed
study of fermented foods, the reader is directed to Wood (1998), a double‐volume book
entitled Microbiology of Fermented Foods.
The main factors resulting in the safety of fermented foods are:
• their acidity generated through lactic acid production;
• the presence of bacteriocins;
• high salt concentration;
• the anaerobic environment.
There are many sources quoting the pH growth range of bacterial pathogens (See Table 2.8);
however, it is very important to appreciate that the acid tolerance of bacterial pathogens can be
enhanced during processing. The stress response (heat shock proteins, etc.) of bacterial pathogens is under current investigation and is summarised in Section 2.9. Also any preformed
bacterial or fungal toxins and viruses will persist during storage before ingestion. Examples of
foodborne illness related to fermented products can be found under the individual pathogens
in Chapter 4.
3.8.1 Lactic acid bacteria
General aspects
Lactic acid bacteria are mainly Gram‐positive, anaerobic, catalase‐negative, non‐spore‐forming
bacteria. They have numerous associations with us, both as part of the indigenous intestinal
flora acquired soon after birth, attaching to mucosal surfaces, and as part of the microflora of
a very wide range of foods: vegetables, wine, milk and meats (Table 3.13). They are integral to
the production of many well‐known foods; not only acidified dairy products and vegetables,
but also wine, coffee and cocoa (Tables 3.11 and 3.12). Some members are pathogenic, and
others produce antimicrobial agents called ‘bacteriocins’.
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121
The lactic acid bacteria are primarily mesophiles (with a few thermophilic strains) and are
able to grow in the range 5–45°C. They are acid tolerant, and are able to grow at pH values as
low as pH 3.8. Many species are proteolytic with fastidious amino acid growth requirements.
The organisms are so‐called due to their ability to produce lactic acid. The lactic acid may be
either or both of the L(+) and D(−) isomers. However, the grouping of bacteria as ‘lactic acid
bacteria’ is purely based on biochemical characteristics. It is not a taxonomic description, and
they do not comprise a single monophyletic group of bacteria. The majority are in the Gram‐
positive low GC% group called Firmicutes, although some are in the Gram‐positive high GC%
group called Actinobacteria (Figure 3.14).
Metabolism
The lactic acid bacteria include both homofermenters and heterofermenters (Table 3.18). The
homofermentative lactic acid bacteria produce two molecules of lactic acid for each molecule
of glucose fermented, whereas the heterofermentative produce a variety of end‐products,
including lactic acid, ethanol, acetic acid, carbon dioxide and formic acid (Figure 3.10). The
homofermentative lactic acid bacteria are Pediococcus, Streptococcus, Lactococcus and some
lactobacilli. The heterofermentative lactic acid bacteria are Weisella, Leuconostoc and some
lactobacilli. The uptake of lactose (a disaccharide) is facilitated either by a carrier, permease, or
via the phosphoenolpyruvate‐dependent phosphotransferase (PTS) system (Figure 3.15).
Lactose is cleaved to yield galactose (or galactose‐6‐phosphate) and glucose. Since lactose is
Lactobacillus casei
Lactobacillus plantarum
Lactobacillus brevis
Pediococcus pentosaceus
Bacillus cereus
St aureus
Lactobacillus gasseri
Lactobacillus johnsonii
Lactobacillus acidophilus
Lactobacillus delbrueckii
Leuconostoc mesenteroides
Oenococcus oeni
Bifidobacterium longum
Brevibacterium linens
Micrococcus luteus
Clostridium botulinum
Streptococcus thermophilus
Lactococcus lactis
Figure 3.14 Phylogenetic tree of lactic acid bacteria and other Gram‐positive organisms.
Table 3.18 Lactic acid bacteria groups.
Fermentation type
Main products
Lactate isomer
Organism
Homofermentative
Lactate
L(+)
Homofermentative
Homofermentative
Heterofermentative
Heterofermentative
Lactate
Lactate
Lactate, ethanol, CO2
Lactate, ethanol, CO2
DL, L(+)
D(−), L(+), DL
DL
D(−)
Lactobacillus bulgaricus, Lactococcus lactis,
Enterococcus faecalis
Pediococcus pentosaceus
Lactobacillus plantarum
Lactobacillus brevis
Leuconostoc mesenteroides
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The microbiology of safe food
Milk lactose
PEP-dependent
lactose phosphotransferase
system
Cytoplasmic membrane
Pyruvate
Lactose 6-phosphate
Phospho-β-galactosidase (plasmid-borne)
Galactose-6-phosphate
Glucose
Tagatose-1,6-bisphosphate
Fructose-1,6-biphosphate
TBP aldolase*
Diacetohydroxyacetone
Glyceraldehyde-3-phosphate
Phosphenol pyruvate
Pyruvic acid
Lactic acid
Figure 3.15 Lactose metabolism.
the major sugar in milk, its metabolism has been well studied. Subsequently it has been demonstrated that the dairy starter culture Lc. lactis has the PTS system encoded on a plasmid,
which may partially explain the instability of certain starter cultures. Although their primary
contribution to food is the rapid acidification, they also contribute to the flavour, texture and
nutritional content. The lactic acid bacteria are ubiquitous, being found in dairy, meat, vegetable, cereal and plant environments. Historically, they have been used for thousands of years
(albeit unknowingly) as starter cultures for the preservation through acidification of dairy,
vegetable and meat products.
Citrate metabolism is of particular importance in Lc. lactis subsp. lactis (biovar diacetylactis)
and Leu. mesenteroides subsp. cremoris. These organisms metabolise excess pyruvate via an
unstable intermediate, α‐acetolactate, to produce acetoin via the enzyme α‐acetolactate decarboxylase. However, in the presence of oxygen α‐acetolactate is chemically converted into diacetyl (Figures 3.11 and 3.12). It is the diacetyl that gives the characteristic aroma of butter and
certain yogurt.
The proteolytic activity of lactic acid bacteria, especially Lactococcus, has been studied in
detail (Figure 3.16). Proteolysis is a prerequisite for the growth of lactic acid bacteria in milk
and the subsequent degradation of milk proteins (casein) is of central importance in the production of cheese. Hence a fundamental understanding of the process is necessary. The growth
Food preservation and spoilage organisms
Extracellular
Cell wall
Membrane
123
Intracellular
Casein
Proteinase
Peptides and
amino acids
Peptide transport
Peptidase
Amino acid
transport
Amino acids
Peptidases
Amino acids
Cell protein
Figure 3.16 Protein metabolism in lactic acid bacteria.
of Lc. lactis is enhanced by the overproduction of the membrane‐anchored serine proteinase
(PrtP), which can degrade casein. The resultant oligopeptides enter the cell via an oligopeptide
transport system (OPP) where they are further degraded by intracellular peptidases. The complete degradation of peptides is achieved by a wide range of intracellular peptidases with overlapping specificities. The metabolism of proteins and amino acids by the lactic acid bacteria is
part of the ripening process of cheese and flavour development.
Lactic acid bacteria produce a range of antimicrobial factors including organic acids, hydrogen peroxide, nisin and bacteriocins. Organic acids such as lactic acid, acetic acid and propionic acid interfere with the proton motive force and active transport mechanisms of the
bacterial cytoplasmic membrane (Section 3.4.1). The production of H2O2 is due to the lactic
acid bacteria lacking the enzyme catalase. H2O2 can consequently cause membrane oxidation
of other bacteria. Additionally H2O2 activates the lactoperoxidase system of fresh milk causing
the formation of antimicrobial hypothiocyanate (Section 3.4.2).
Lactic acid bacteria produce bacteriocins. These are antimicrobial peptides ~2–10 kDa in
size, which target closely related bacteria, and are in two broad main groups: class I (post‐
translationally modified) and class II (unmodified) bacteriocins. The most studied bacteriocins are the lantibiotics, which belong to class I bacteriocins. These are characterised by the
unusual amino acids, dehydroalanine and dehydrobutyrine, as a result of the dehydration of
serine and threonine residues, as well as the presence of lanthionine (Lan) and β‐methyllanthionine
(MeLan) intramolecular bridges. Nisin and pediocin are bacteriocins used in food preservation,
showing bactericidal or bacteriostatic activity towards closely related organisms. Nisin is already
used commercially in food preservation and could be of further use in the design of novel
antibiotics. Nisin is a Class I bacteriocin, which is a post‐translationally modified amino acid
(also known as a lantibiotic; Figure 3.6). Nisin is produced by Lc. lactis subsp. lactis and has a
broad inhibitory spectrum against Gram‐positive bacteria (Section 3.4.4). It is formulated
(concentration range 2.5–100 ppm) into a range of food products including cheeses, canned
foods and baby foods and is particularly stable in high‐acid foods.
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The microbiology of safe food
Using genome comparisons, possible genes encoding for other bacteriocins have been identified in lactic acid bacteria, and these may be of commercial importance in the future. See the
‘Food Safety Resources’ section for BAGEL, a web‐based bacteriocin genome mining tool
(http://bagel4.molgenrug.nl/).
Probiotic aspects
Over 100 years ago, Elie Metchnikoff proposed that lactic acid bacteria in fermented milk
could promote the development of a healthy intestinal microflora, and prolong the individual’s
life by preventing putrefaction. Although these ideas are not entirely accurate, they do reflect
the current trend of probiotics covered in Section 3.9. Additionally, it is now known that the
human intestinal tract is colonised by the lactic acid bacteria, and Bifidobacterium species,
which may also have a role in health (Table 2.1).
The lactic acid bacteria are a heterogenous family of bacteria that are grouped together
on the basis of being Gram‐positive rods or cocci, produce lactic acid from sugars and are
catalase‐negative. The bifidobacteria are also Gram‐positive rods, which show a bifurcating
morphology and are generally grouped with the lactic acid bacteria. However, this phenotypical
basis of grouping does not fully reflect the diversity of the group as shown by 16S rDNA
sequence analysis (Figure 1.1). Figure 3.14 shows the Gram‐positive organisms are split into
two groups: the Firmicutes (low GC% content) and the Actinobacteria (high GC% content).
The lactic acid bacteria, as well as the Staphylococcus and Listeria genera are in the Firmicutes,
whereas the bifidobacteria are in the Actinobacteria and therefore are genetically very dissimilar in origin.
Whole‐genome sequencing
Initially, genome sequencing of the lactic acid bacteria was primarily focused on pathogenic
species from the Streptococcus genera. It then broadened to include a large number of non‐
pathogenic, even probiotic‐associated, human intestinal species. Table 3.19 lists representative
genomes of selected lactic acid bacteria, brevibacteria and bifidobacteria species that have
been sequenced. The Lactobacillales (phylum Firmicutes, class Bacilli, sister taxon to the order
Bacillales) have relatively small genomes (~2 Mb), with evidence of gene inactivation, acquisition and duplication. The large number of genomes sequenced from multiple strains within
the same species, and related species will enable insights into genome evolution, and structure
unrivalled by other bacterial groups (Wu et al. 2017). There appear to be three lineages within
the order Lactobacillales:
1 Leuconostoc group: Leu. mesenteroides and Oenococcus oeni.
2 Lactobacillus casei‐Pediococcus group: Lb. plantarum, Lb. casei, Pediococcus pentosaceus and
Lactobacillus brevis.
3 Lb. delbrueckii group: Lb. delbrueckii, Lb. gasseri and Lb. johnsonii.
The Streptococcus and Lactococcus species form a separate branch.
The availability of these genome sequences has improved the phylogenetic analysis of this
important group of bacteria. The common ancestor of the Lactobacillales had at least 2100–
2200 genes, and after divergence from the Bacilli ancestor, it lost 600–1200 genes and gained
<100 genes. Many of these changes reflect an evolution to growth in nutritionally rich environments, such as milk and intestinal contents. Horizontal gene transfer has resulted in the acquisition of at least 84 genes from different sources. Interestingly, during the evolution of the
Lactobacillales, many genes involved in sugar metabolism and transport were duplicated.
These included several phosphotransferase systems (PTS), β‐galactosidase and enolase.
Food preservation and spoilage organisms
125
Table 3.19 Genomes of selected lactic acid bacteria, brevibacteria and bifidobacteria.
Genus
Species
Strain
Size (Mb)
%GC
Accession number
Brevibacterium
Bifidobacterium
linens
adolescentis
longum
faecalis
acidophilus
brevis
casei
delbrueckii subsp. bulgaricus
delbrueckii subsp. bulgaricus
gasseri
helveticus
johnsonii
plantarum
reuteri
sakei subsp. sakei
salivarius subsp. salivarius
lactis spp. cremoris
lactis spp. cremoris
lactics ssp. lactis
mesenteroides
oeni
pentosaceus
fredenreichii subsp. shermanii
agalactiae
agalactiae
mutans
pneumoniae
pyogenes
thermophilus
thermophilus
thermophilus
BL2/ATCC9174
ATCC 15703
NCC2705
V583
NCFM
ATCC 367
ATCC 334
ATCC BAA365
ATCC 11842
ATCC 333323
DPC 4571
NCC533
WCFS1
F275
23 K
UCC118
SK11
MG1363
IL1403
ATCC 8293
PSU‐1
ATCC 25745
CIP 103027
2603 V/R
A909
UA159
TIGR4
M1 GAS
LMD‐9
LMG18311
CNRZ1066
4.4
2.1
2.3
3.36
2.0
2.35
2.93
1.9
1.86
1.9
2.1
2.0
3.3
2.0
1.9
2.1
2.6
2.5
2.4
2.0
1.8
1.8
Incomplete
2.2
2.1
2.0
2.2
1.9
1.9
1.8
1.8
62.9
59.3
60.1
37.2
34.7
46.1
46.1
49.7
49.7
35.3
37.1
34.6
44.4
38.9
41.3
33.0
35.8
35.7
35.3
37.7
37.9
37.4
67
35.6
35.6
36.8
39.7
38.5
39.1
39.1
39.1
NZ_AAGP00000000
AP009256
AE014295
AE016830
CP000033
CP000416
CP000423
CP000412
CR954253
CP000413
CP000517
AE017198
AL935263
CP000705
CR936503
CP000233
CP000425
AM406671
AE005176
CP000414
CP000411
CP000422
Incomplete
AE009948
CP000114
AE014133
AE005672
AE004092
CP000419
CP000023
CP000024
Enterococcus
Lactobacillus
Lactococcus
Leuconostoc
Oenococcus
Pediococcus
Propionibacterium
Streptococcus
The genome‐scale analysis has revealed their broad saccharolytic ability as would be
expected from their wide range of environmental niches. There is a noted predominance of
PTS transporters, which enable the organisms to metabolise various carbohydrates. As well as
sugar uptake, 13–17% of genes in many genomes encode for protein transport, and amino acid
uptake systems predominate over sugar and peptide uptake systems.
There is evidence that the lactic acid bacteria have evolved to nutritionally complex environments such as milk through gene decay with the loss of dispensable functions, and, second,
gene acquisition via horizontal gene transfer along with gene duplication. Apart from Lb. lactis,
amino acid biosynthetic pathways are incomplete in most other lactic acid bacteria reflecting
their fastidious nature. For example, Lb. plantarum is deficient in a few pathways such as those
for the synthesis of branched chain amino acids, whereas species of the ‘Lb. acidophilus complex’ (Lb. acidophilus, Lb. gasseri, Lb. johnsonii) are largely deficient in amino acid biosynthetic
capacity. To compensate for this deficiency, the organisms have a large number of peptidases,
amino acid permeases and multiple oligo‐peptide transporters. In Strep. thermophilus 10% of
genes are pseudogenes and non‐functional. This genome decay is particularly noted for genes
involved in carbohydrate metabolism, uptake and fermentation, and may be an adaptation to
126
The microbiology of safe food
the nutritionally rich environments of milk and the human intestinal tract. In fact a specific
lactose transport system is found in Strep. thermophilus, which is absent in other pathogenic
streptococci. There is also some evidence of horizontal gene transfer from Lb. bulgaricus and
Lb. lactis for methionine biosynthesis, which is a rare amino acid in milk. In turn, Lb. lactis has
acquired plasmid DNA encoding important genes for growth and survival in milk: lactose
metabolism, proteolytic activity, exopolysaccharide production, bacteriocin production and
bacteriophage resistance.
Whole‐genome comparison of Lb. plantarum shows a lack of synteny (co‐localisation of
genes) with the three species of the Lb. acidophilus complex: Lb. acidophilus, Lb. johnsonii and Lb.
grasseri. These three show extensive conservation of gene content and gene order, except for two
apparent chromosomal inversions in Lb. gasseri (Plate 1). The high degree of similarity amongst
the three species explains the difficulty normally experienced when attempting to differentiate
these organisms using phenotyping or molecular techniques. It is possible to find genes unique
to one species by (electronically) subtracting one genome from another, and thereby design species‐specific DNA probes. Due to variation in genomes between strains in the same species,
these DNA probes would need to be further validated using a strain collection for each species.
3.8.2 Bifidobacterium species
General aspects
Bifidobacterium species are Gram‐positive, heterofermentative, mainly strict anaerobes, non‐
motile and non‐spore‐forming. They can display a range of cell morphologies including rods
and branched (bifurcating) shapes. However, unlike the lactic acid bacteria considered above,
bifidobacteria are found in the Actinobacteria branch of the Gram‐positive organisms, with
high %GC content (42–67%; Figure 3.14). Currently, the Bifidobacteriaceae family includes 55
(sub)species of the genus Bifidobacterium. They are one of the first commensal micro‐
organisms that colonise the human gut, and can dominate the intestinal flora of infants and
remain as one of the main inhabitants of the healthy adult intestinal flora. Changes in the
Bifidobacterium species population present in the human microbiome has been correlated
with several intestinal and immunological disorders such as irritable bowel syndrome,
inflammatory bowel disease (IBD) and obesity. Subsequently, they have been trialled as
probiotics for restoring normal gut function (Tojo et al. 2014) (Section 3.9.3). Bifidobacterium
species also inhabit the oral cavity and the (social) insect gut. They can be found in blood and
sewage, though this is probably due to environmental contamination.
The Bifidobacterium species are associated with the colonisation of the gut soon after birth,
metabolism of breast milk (glycobiome) and are health promoting (Zivkovic et al. 2011). In
contrast, the other genera of the Bifidobacteriaceae family are often associated with human and
animal dental caries, and are commonly isolated from human clinical samples of tonsil
abscesses and bacterial vaginosis. Furthermore, in contrast to Bifidobacterium animalis subsp.
lactis and Bifidobacterium asteroides, other members of the family can grow under aerobic
conditions and possess DNA with a lower G+C content.
Whole‐genome sequencing
The genome of Bifidobacterium longum has been sequenced and therefore direct genome
comparison with other lactic acid bacteria is possible (Table 3.19). The Bif. longum genome is
~2.3 Mb and is of similar size to that of other lactic acid bacteria. Despite living in the same
habitat as several Lactobacillales, there are few genes in common between Bif. longum and
other lactic acid bacteria that are not found in other Actinobacteria. Nevertheless, there are
Food preservation and spoilage organisms
127
similar trends in the loss and gain of genes. Losses in both Bif. longum and Lactobacillales
include oxidases, catalase, heme and fatty acid biosynthesis. Both groups have gained additional
amino acid metabolism by the acquisition of dipeptidase activity.
Bifidobacteria are part of the early flora that develops in breastfed infants and are regarded
as beneficial to infant health (Section 2.2). Therefore, it is interesting to learn that genomic
analysis has revealed that Bif. longum subsp. infantis has adapted to metabolise human milk
by the presence of a 43‐kb cluster of catabolic genes, and permeases for the uptake of milk
oligosaccharides (Sela et al. 2008). Five of these oligosaccharides are not degraded by host
enzymes and apparently are of no nutritional benefit to the infant, but are preferred substrates
for Bif. longum subsp. infantis.
Genomic analysis of lactic acid bacteria and Bif. longum have revealed a number of features
of importance to probiotic functions. These include attachment factors (fimbriae, mucus‐
binding proteins and mannose‐specific adhesion proteins), exopolysaccharide synthesis, bacteriocin production, stress and acid tolerance factors (Pridmore et al. 2004).
Clustered regularly interspaced short palindromic repeat (CRISPR)‐Cas systems present in
bacteria and archaea organisms are a type of bacterial immune system against foreign nucleic
acids (DNA and RNA) from phages and plasmids (Barrangou and Doudna 2016) (Section 6.6.3).
It has been widely studied and characterised during the past 10 years, especially with respect to
gene editing (Barrangou and Horvath 2017) as well as bacterial genotyping. In brief, the
CRISPR‐Cas regions may be composed of up to three sections (i) cas genes; (ii) an AT‐rich
leader sequence upstream of the array; and (iii) a CRISPR array, composed of short (~24–48
nucleotide lengths) (Plate 18). This array is composed of direct repeat sequences that are separated by similarly sized, unique spacers. These spacers are usually derived from mobile genetic
elements such as bacteriophages and plasmids.
Bifidobacterium longum encodes various CRISPR‐Cas immune systems and analysis of
CRISPR spacer origin suggests the organism has adapted to the human gut phage environment.
The CRISPR‐Cas systems belong to four different subtypes, with large and diverse repeat‐
spacer arrays. This indicates that these systems are likely to be active and protective against
invasive DNA. Such hypervariable loci give insights into strain origin, evolution and phylogeny.
Furthermore, CRISPR locus diversity shows potential for precise genotyping being able to
distinguish between clonal isolates. The characterisation of CRISPR‐Cas immune systems in
Bif. longum provides opportunities to develop genome editing tools using the endogenous
systems for the development of next‐generation probiotic bacteria.
3.8.3 Other organisms
As well as lactic acid bacteria and bifidobacteria, other less well‐studied organisms are involved
in the production of non‐milk fermented foods globally (Tamanga et al. 2016). In contrast to
the familiar bacterial preservation by the production of organic acids, Bacillus is used to produce alkaline‐fermented legume‐based foods in Asia and Africa. These are fermented by
B. amyloliquefaciens, B. circulans, B. coagulans, B. firmus, B. licheniformis, B. megaterium,
B. pumilus, B. subtilis (including B. subtilis variety natto) and B. thuringiensis. Despite the association with food poisoning, B. cereus has been isolated from the fermentation of Prosopis
africana seeds for the production of okpehe in Nigeria. Some strains of B. subtilis produce
γ‐polyglutamic acid (PGA), which is an amino acid polymer commonly present in Asian fermented soybean foods, giving the characteristic of a sticky texture to the product and a strong
(acquired) taste. Other bacteria include several species of Staphylococcus, Micrococcus and
Kocuria in the production of various fermented milk products, meat and fish products.
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Various yeast genera are reported for fermented foods, alcoholic beverages and non‐
food mixed amylolytic starters. These include Candida, Geotrichum, Hansenula,
Hyphopichia, Issatchenkia, Kazachstania, Kluyveromyces, Pichia, Rhodotorula, Saccharomyces,
Schizosaccharomyces, Torulaspora, Torulopsis and Zygosaccharomyces. Filamentous fungi
such as Aspergillus, Mucor, Neurospora, Penicillium and Rhizopus are reported for many
fermented foods, Asian non‐food amylolytic starters and alcoholic beverages. These contribute to the fermentation by the production of enzymes that break down the complex
carbohydrates.
3.9 Functional foods: probiotics and gut modulation
3.9.1 Qualified Presumption of Safety (QPS) and Generally Regarded As Safe (GRAS)
In order to harmonise the assessment of biological agents the European Food Safety Authority
(EFSA) introduced the concept of QPS as a generic risk assessment approach (EFSA 2007;
Leuschner et al. 2010). The QPS approach also enables attention to be given to agents with
higher risk potential. The QPS concept is intended to establish a safety assessment for micro‐
organisms used in both feed and food production.
If a specific strain notified for market authorisation can unambiguously be connected to a
taxonomic unit on the QPS list, then if any safety assessment is needed then it will be indicated
in the list for that taxonomic unit. Bacteria with a previous history of safe use are usually
included on the QPS list. Therefore micro‐organisms on the QPS list do not need an exhaustive safety assessment.
The assessment for QPS suitability is well structured and relies on the following criteria:
1 Taxonomic unit: This is a crucial aspect of the assessment procedure. The genus and all
known species, including type species, are listed and described according to their main characteristics. The evaluated taxonomic unit must be unambiguously defined. If the assessed
bacterial agent cannot be connected to any known species, it will not be recommended for
the QPS list. QPS status is also denied if the taxonomic identification is insufficient.
2 Body of knowledge: This should be related to the history of use for the assessed bacterial
agent, the field of application, the existence of sufficient scientific literature about the micro‐
organism and the possibility to avoid potential adverse effects for humans, livestock and the
wider environment.
3 Possible pathogenicity: The organism’s lack of pathogenic and virulence properties is
confirmed, and the findings must be supported by clinical data and scientific literature.
4 Description of end use: This includes the presence and viability of the micro‐organism in the
final product.
Most bacteria recommended for the QPS list are Gram‐positive non‐spore‐forming bacteria.
They include specific species (too many to list here) within the following genera with the qualification that they do not have toxigenic potential, or harbour acquired antibiotic resistance
genes to clinically relevant antibiotics: Bacillus (12 species), Bifidobacterium (6 species),
Corynebacterium glutamicum, Geobacillus stearothermophilus, Gluconobacter oxydans,
Lactobacillus (35 species), Leuconostoc (3 species), O. oeni, Pediococcus (3 species),
Propionibacterium (2 species) and Strep. thermophilus. Many of these are inhabitants of the
digestive tract and have long histories in food and feed production. For this group, the EFSA’s
Scientific Committee applies a generic qualification for all taxonomic units on the list, requiring that all strains do not carry any transferable antimicrobial resistance unless the final product
contains no viable cells. There is only one Gram‐negative bacterium on the list, G. oxydans.
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Escherichia coli strain Nissle 1917 has long been used as a probiotic but E. coli can cause a variety of diseases and exhibits versatile virulence mechanisms. Nevertheless, opportunistic
bacteria may be placed on the QPS list with additional qualifications, but pathogenic and
toxin‐producing bacteria are not included.
There is a large and wide variety of yeast species: D. hansenii, Hanseniaspora uvarum,
Kluyveromyces lactis and K. marxianus, Saccharomyces bayanus, S. cerevisiae, Saccharomyces
pastorianus, Schizosaccharomyces pombe, Xanthophyllomyces dendrorhous; and for enzyme
production purposes only, Pichia angusta, P. anomala, P. jardinii and P. pastoris. The baculoviruses (plant protection agents) have been approved for QPS. They have a long history of safe
use as biocontrol agents for insects. Neither filamentous fungi nor bacteriophages have QPS
approval: the former due to concerns of toxin production, and the latter due to uncertain taxonomic designations.
The QPS approach is similar to the American GRAS concept. Whereas QPS is defined as an
‘assumption based on reasonable evidence’ as a useful assessment tool for EFSA, GRAS does
not give any legal status. Also EFSA is responsible for providing the burden of proof, while
GRAS places the responsibility on the food business operator. Another difference is QPS
assessment’s emphasis on the absence of acquired antibiotic resistances and virulence factors.
3.9.2 Functional foods and probiotics
Functional foods can be defined as foods in which concentrations of one or more ingredients
have been modified to enhance their contributions to a healthy diet. The concept is a logical
extension of the more conventional viewpoint that a balanced diet is important for health. For
example, eating products low in fat, low in cholesterol or sugar and high in vegetable and fruit
intake are encouraged. Currently food scientists are identifying an increasing list of food components that promote health, and this has led to the general acceptance that individual foods
can promote health.
Probiotics, prebiotics and synbiotics are controversial topics in the general area of ‘functional foods’. Prebiotics are ‘non‐digestible food components that beneficially affect the host
by selectively stimulating the growth and/or activity of one or a limited number of bacteria in
the colon that have the potential to improve host health’ (Gibson and Roberfroid 1995). A
probiotic was initially defined as ‘a live microbial food supplement which beneficially affects
the host animal by improving its intestinal microbial balance’ (Fuller 1989). This definition
was broadened by Havenaar and Huis in’t Veld (1992) to a ‘mono‐ or mixed‐culture of live
microorganisms which benefits man or animals by improving the properties of the indigenous
microflora’. The Lactic Acid Bacteria Industrial Platform workshop proposes a different definition for probiotics as ‘oral probiotics are living microorganisms, which upon ingestion in
certain numbers, exert health benefits beyond inherent basic nutrition’ (Schaafsma 1996).
This definition means that probiotics may be consumed either as a food component or as a
non‐food preparation (Guarner and Schaafsma 1998). Synbiotics can be described as ‘a mixture of probiotics and prebiotics that beneficially affects the host by improving the survival
and implantation of live microbial dietary supplements in the gastrointestinal tract’ (Gibson
and Roberfroid 1995).
A variety of probiotic foods have been developed and marketed. They can be divided into
the following categories:
1 Conventional fermented foods that are consumed primarily for nutritional purposes.
2 Food supplements and fermented milk with food formulations that are used to deliver probiotic bacteria.
3 Dietary supplements, which are in the form of capsules and other formulations.
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These products usually contain members either of the Lactobacillus and/or Bifidobacterium
genera. As such these cultures are accepted to be safe for consumption due to their long history
of use in conventional fermented foods. The idea of using lactic acid bacteria as an aid to
improved health is not new: see Section 3.7 on fermented foods for related stories. However,
the current trend is largely driven by consumer demands rather than scientific investigation.
The probiotic preparation needs to be defined viable, micro‐organisms, in sufficient numbers
to alter the intestinal microflora. A daily intake of 109–1010 viable cells is considered the minimum dose. Not all products contain correctly identified species, nor can it be assumed that the
organisms are viable. For example, Green et al. (1999) demonstrated that two B. subtilis oral
probiotics did not contain B. subtilis. Some products may contain undeclared organisms, non‐
viable organisms or even pathogens (Hamilton‐Miller et al. 1999). Similarly, Fasoli et al. (2003)
investigate commercial probiotic yogurts and lyophilised products. There were discrepancies
in the identification of Bifidobacterium and Bacillus species, as well as the presence of non‐
declared organisms.
The gastrointestinal tract is the most densely colonised region of the human body (Townsend
and Forsythe 2008; Section 2.2). There are approximately 1012 bacteria per gram (dry weight)
of contents of the large intestine, which is estimated to contain several hundred bacterial
species. It is widely accepted that this collection of microbes has a powerful influence on the
host in which it resides. The production of bacterial fermentation products (acetate, butyrate
and propionate) commonly known as short‐chain fatty acids (SCFAs) for colonic health has
been documented. For example, butyrate has a trophic effect on the mucosa, is an energy
source for the colonic epithelium, and regulates cell growth and differentiation. The human
intestinal gut‐associated lymphoid tissue represents the largest mass of lymphoid tissue in the
body, and about 60% of the total immunoglobulin produced daily is secreted into the
gastrointestinal tract. The colonic flora is the major antigenic stimulus for specific immune
responses at local and systemic levels. Abnormal intestinal response to foreign antigen, as well
as local immunoinflammatory reactions, might, as a secondary event, induce impairment of
the intestine’s function because of breakdown of the intestinal barrier (Diplock et al. 1999).
It is implicit in the definition of probiotics that consumption of probiotic cultures positively
affect the composition of this microflora and extends a range of host benefits (Sanders et al.
2013), including:
1 Pathogen interference, exclusion and antagonism.
2 Immunostimulation and immunomodulation.
3 Anticarcinogenic and antimutagenic activities.
4 Alleviation of symptoms of lactose intolerance.
5 Reduction in serum cholesterol.
6 Reduction in blood pressure.
7 Decreased incidence and duration of diarrhoea (Clostridium difficile, traveller’s and
rotaviral).
8 Prevention of vaginitis.
9 Maintenance of mucosal integrity.
It has been proposed that prebiotics help the colonic microbial flora to maintain a composition
in which bifidobacteria and lactobacilli become predominant in number. This change in flora
composition is regarded by believers in probiotics as optimal for health promotion. Non‐
digestible carbohydrates (e.g. inulin and fructo‐oligosaccharides) increase faecal mass both
directly by increasing non‐fermented material and indirectly by increasing bacterial biomass;
they also improve stool consistency and stool frequency. Promising food components for
Food preservation and spoilage organisms
131
functional foods will be those, such as specific non‐digestible carbohydrates, that can provide
optimal amounts and proportions of fermentation products at relevant sites in the colon,
particularly the distal colon, if they are to help reduce the risk of colon cancer.
3.9.3 Probiotic studies
Many of the specific effects attributed to the ingestion of probiotics, however, remain
controversial and it is rare that specific health claims can be made (Sanders et al. 2013; Wan
et al. 2018). In order to test the claims of pre‐ and probiotics there need to be advances in the
detailed characterisation of the intestinal microflora, especially the organisms currently
regarded as unculturable. Molecular biology has been used to establish the phylogenetic
relationship amongst members of the Lb. acidophilus complex. This may in part explain the
variation in effects observed in earlier studies. It is plausible that unrelated organisms with
identical names were used by different research groups, as the organisms had been misidentified
using biochemical (phenotypic) identification techniques.
The lactobacilli and the bifidobacteria constitute the most important probiotic organisms
under investigation (Reid 1999; Vaughan et al. 1999; Liévin‐Le Moal and Servin 2014; Wu et al.
2017). The reason for this is that they are recognised as part of the human intestinal tract flora
(especially in the newborn infant) and they have been safely ingested for many centuries in
fermented foods. Particular lactic acid bacteria strains that have been investigated as probiotics
include Lb. rhamnosus GG, Lb. casei strains Shirota YIT9029and DN‐114001, Lb. acidophilus
strain LB, Lb. johnsonii NCC533, Lb. reuteri MM53 (cured of antibiotic‐encoding plasmids),
Bif. lactis Bb12 and Bif. longum NCC2705 (Table 3.20). Important attributes of probiotic strains
are colonisation factors and conjugated bile salt hydrolysis which aid persistence in the intestinal tract. Additional characteristics include effects on immunocompetent cells and antimutagenicity. Some probiotics demonstrate bacteriostatic activity against Helicobacter pylori,
Shigella, Salmonella and Campylobacter. Others have bactericidal activities against Salmonella
serovars (including Typhi), Campylobacter and E. coli (Liévin‐Le Moal and Servin 2014).
Lactobacillus rhamnosus GG is probably the most studied probiotic preparation. There is
some evidence that Lb. rhamnosus GG colonises the intestine and reduces diarrhoea (Kaila
et al. 1995). The oral dose required is greater than 109 cfu/day. There are many fermented milk
products commercially available that claim to promote health (Table 3.21). Lactobacillus casei
(Shirota strain) fermented milk is sold as a produced called ‘Yakult’ and is estimated to be consumed daily by 10% of the Japanese population. In the UK the volume is about 190 000 bottles
per day. On a worldwide basis it has been predicted that 37 million people ingest this product
each day. It is prepared from skimmed milk with the addition of glucose and a Chlorella (algae)
extract followed by inoculation with Lb. casei (Shirota). The fermentation takes 4 days at 37°C.
Table 3.20 Lactic acid bacteria used as probiotics.
Genus
Species
Lactobacillus
Lb. acidophilus, Lb. amylovorus, Lb. bulgaricus, Lb. casei,
Lb. crispatus, Lb. gallinarum, Lb. gasseri, Lb. johnsonii, Lb. plantarum, Lb. reuteri, Lb.
rhamnosus, Lb. salivarius
Bif. adolescentis, Bif. animalis, Bif. bifidum, Bif. breve, Bif. infantis, Bif. longum, Bif. lactis
Strep. salivarius, Strep. thermophilus
Ent. faecium
Bifidobacterium
Streptococcus
Enterococcus
Source: Adapted from Tannock (1995) and Klaenhammer and Kullen (1999).
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Table 3.21 Microbial composition of fermented milk products claiming health benefits.
Product
Country of origin
Micro‐organism
A‐38 fermented milk
AB‐fermented milk
Acidophilus milk
Activia
Kyr
Liquid yogurt
Mio
Miru‐Miru
Real Active
Yakult
Denmark
Denmark
USA
Italy
Italy
Korea
Switzerland
Japan
UK
Japan
Lactobacillus acidophilus and mesophilic lactic acid bacteria
Lb. acidophilus, Bifidobacterium bifidum
Lb. acidophilus
Bifidobacterium bifidus (Bif. animalis lactis)
Lb. acidophilus and Bifidobacterium spp.
Lactobacillus bulgaricus, Lactobacillus casei, Lactobacillus helveticus
Bifidobacterium lactis
Lb. acidophilus, Lb. casei, Bifidobacterium breve
yogurt culture, Bif. bifidum
Lb. casei (Shirota)
The Lactobacillus strain was initially isolated in 1930 and appears to colonise the intestine and
improve infant recovery time from rotaviral gastroenteritis (Sugita and Togawa 1994). The
strain appears to have antitumour and antimetastasis effects in mice (Matsuzaki 1998). In
Canada, the application of probiotics via the urogenital tract has been investigated. Trials with
Lb. rhamnosus GR‐1 and Lb. fermentum B‐54 (applied as a milk‐based suspension or freeze‐
dried preparations) have indicated that the vaginal microflora can be re‐established and the
incidence of urinary tract infections reduced (Reid et al. 1994).
Although probiotics are promoted as aids to health, it is plausible that there may be some
risks associated with the ingestion of probiotic bacteria. The major risk would be the unrestricted stimulation of the immune system in people suffering from autoimmune diseases
(Guarner and Schaafsma 1998).
Lactic acid bacteria are also being studied for vaccine delivery in the intestinal tract. A strain
of Lb. lactis containing the luciferase gene has been used as an experimental model to study
gene promoter activities in the intestinal tract as a first step to predicting the expression of
heterogenous proteins in vivo.
3.9.4 Novel organisms – modulation of gut microbiota
In the European Union, QPS status has been given to members of the lactic acid bacteria based
on their long history of safe use. Other organisms have also received approval for certain
processes, but are not included on the QPS list:
1 Leuconostoc mesenteroides for dextran production as a novel food ingredient in bakery
products.
2 Bacillus subtilis natto‐derived Vitamin K2 as a novel food ingredient to be used in foods that
served particular nutritional uses and that had added vitamins and minerals.
3 Clostridium butyricum CBM 588 was authorised as novel food ingredient in food supplements at a maximum dose of 1.35 × 108 cfu/day. Beneficial effects include the production of
SCFA, and its role in lipid metabolism.
4 Pasteurised milk products fermented using Bacteroides xylanisolvens DSM 23964 are
approved. However this strain is only permitted as the starter culture, and only heat‐
inactivated cells of B. xylanisolvens are allowed in the final product.
There is increasing interest in ‘novel’ microbes that potentially could preserve and modify
foods and also modulate gut microbiota. The use of such organisms is of particular interest
because of growing evidence for the importance of the gut microbiota in human health.
Food preservation and spoilage organisms
133
Current organisms being studied for their safety include B. xylanisolvens, Akkermansia muciniphila, fructophilic lactic acid bacteria (FLAB) and Faecalibacterium prausnitzii. Their acceptance may vary according to differences in food safety evaluation requirements by regulatory
authorities, and so just their potential benefits will be covered in general terms here.
1 Akkermansia muciniphila, a Gram‐negative strict anaerobe. Ubiquitous occurrence in the
intestines of many vertebrates, and may have probiotic properties (Cani and de Vos 2017).
2 FLAB: These are a subgroup of lactic acid bacteria that use fructose in preference to glucose.
They inhabit fructose‐rich niches such as flowers, fruits, wine and cocoa beans.
3 Faecalibacterium prausnitzii is a Gram‐positive, strict anaerobe in the Clostridia class. It
constitutes 3–5% of total faecal bacteria. Its benefits include producing mostly butyrate,
along with other SCFA following the degradation of dietary fibres. It may have a role in
human health because changes in levels of F. prausnitzii have been associated with several
gastrointestinal diseases, such as Crohn’s disease, and depressive disorders. The micro‐
organism also displays beneficial anti‐inflammatory effects on the host, suggesting that it
may be used to counterbalance the dysbiosis linked to certain diseases.
4 Eubacterium hallii. This is a common inhabitant of the human gut microbiota. It can metabolise a range of carbon sources, producing butyrate and acetate. It is one of the first butyrate
producers in the infant gut. In addition, it may have a role in treating insulin resistance. Its
early appearance in the human intestine and production of essential SCFAs may lead to
novel food applications.
5 The Roseburia genera account for 2–15% of the total human gut microbiota that produce
SCFAs. They have potential as future novel probiotics.
4 Bacterial foodborne pathogens
Food poisoning is caused by food that:
1 looks normal;
2 smells normal;
3 tastes normal.
Because the consumer is unaware that there is a potential problem with their food, a significant
amount of the food is ingested and hence they become ill. Consequently it is hard to trace
which food was the original cause of food poisoning since the consumer will not recall noticing
anything untoward in their recent meals.
Food poisoning is caused by a variety of organisms and the incubation period and duration
of illness vary considerably (Table 1.2). The often‐used term ‘infectious dose’ is not a precise
threshold value below which a person does not become infected, but is useful as a relative
indicator of the infectivity of a foodborne pathogen. Values for a number of foodborne pathogens are given in Table 4.1. Section 10.5.7 covers ‘infectious dose’ in greater detail, and how it
depends upon the organism, host and food.
Food poisoning organisms are normally divided into two groups:
1 Infections: for example, Salmonella, Campylobacter and pathogenic Escherichia coli.
2 Intoxications: for example, Bacillus cereus, Staphylococcus aureus, Clostridium botulinum.
The first group are organisms that multiply in the human intestinal tract, whereas the second
group are organisms that produce toxins either in the food or during passage in the intestinal
tract. This division is very useful to help recognise the routes of food poisoning. Vegetative
organisms are killed by heat treatment, whereas spores may survive and hence germinate if the
food is not kept sufficiently hot or cold.
An alternative grouping would be according to severity of illness. This approach is useful in
setting microbiological criteria (sampling plans) and risk analysis. The International
Commission on Microbiological Specifications for Foods (ICMSF) (1974, 1986, 2002) divided
the common foodborne pathogens into such groups in order to aid decision‐making of sampling plans (Chapter 7). The ICMSF groupings are given in Table 4.2. Detailed descriptions of
foodborne pathogens are given in the following sections of this chapter. Initially, however, it is
useful to appreciate that some foodborne pathogens are very difficult to detect and hence
‘indicator’ organisms, whose presence may indicate the possible presence of a pathogen, may
be used that are easier to detect.
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
135
Table 4.1 Infectious dose of enteric pathogens.
Organism
Estimated minimum infectious dose
Non‐spore‐forming bacteria
Campylobacter jejuni
Salmonella serovars
Shigella flexneri
Shigella dysenteriae
Escherichia coli
E. coli O157:H7
Staphylococcus aureus
Vibrio cholerae
Vibrio parahaemolyticus
Yersinia enterocolitica
Spore‐forming bacteria
Bacillus cereus
Clostridium botulinum
Clostridium perfringens
Viruses
Hepatitis A
Norovirus
a
1000
104–1010
102–>109
10–104
106–>107
10–100
105–>106/ga
1000
106–109
107
104–108
103a
106–107
<10 particles
<10 particles
Viable count able to produce sufficient toxin to elicit a physiological response.
Table 4.2 Microbiological hazards categorisation according to ICMSF.
Effects of hazards
Pathogen
Categorisation of common foodborne pathogens
(ICMSF 1986)
Moderate, direct, limited spread, death rarely
occurs
Bacillus cereus, Campylobacter jejuni, Clostridium
perfringens, Staphylococcus aureus, Yersinia enterocolitica,
Taenia saginata, Toxoplasma gondii
Moderate, direct, potentially extensive spread,
death or serious sequelae can occur. Considered
severe
Pathogenic Escherichia coli, Salmonella Enteritidis and
other salmonellae other than S. Typhi and S. Paratyphi,
shigellae other than Shigella dysenteriae, Listeria
monocytogenes
Severe, direct
Clostridium botulinum types A, B, E and F, hepatitis A virus,
Sh. dysenteriae, S. Typhi and S. Paratyphi A, B and C,
T. spiralis
Updated categorisation (ICMSF 2002).
Food poisoning organisms causing moderate
illness, not life‐threatening, no sequelae, normally
short duration, self‐limiting
B. cereus (including emetic toxin), Cl. perfringens type A,
Norwalk‐like viruses, E. coli (enteropathogenic E. coli
[EPEC], Enterotoxigenic E. coli [ETEC]), St. aureus, Vibrio
cholerae non‐O1 and non‐O139, Vibrio parahaemolyticus
Serious hazard, incapacitating but not
life‐threatening, sequelae rare, moderate
duration
C. jejuni, Campylobacter coli, S. Enteritidis, S. Typhimurium,
shigellae, hepatitis A, L. monocytogenes, Cryptosporidium
parvum, pathogenic Y. enterocolitica, Cyclospora
cayetanensis
Severe hazard for general population,
life‐threatening, chronic sequelae, long
duration
Brucellosis, botulism, EHEC (HUS), S. Typhi, S. Paratyphi,
tuberculosis, Sh. dysenteriae, aflatoxins, V. cholerae O1 and
O139
Severe hazard for restricted populations,
life‐threatening, chronic sequelae, long
duration
C. jejuni O:19 (GBS), Cl. perfringens type C, hepatitis A,
C. parvum, Vibrio vulnificus, L. monocytogenes, EPEC (infant
mortality), infant botulism, Cronobacter species
Bacterial foodborne pathogens
137
4.1 Indicator organisms
The term ‘indicator organisms’ can be applied to any taxonomic, physiological or ecological group of organisms whose presence or absence provides indirect evidence concerning
a particular feature in the past history of the sample. It is often associated with organisms
of intestinal origin but other groups may act as indicators of other situations. For example,
the presence of members of ‘all Gram‐negative bacteria’ in heat‐treated foodstuffs is indicative of inadequate heat treatment (relative to the initial numbers of these organisms) or
of contamination subsequent to heating. Coliform counts, since coliforms represent only
a subset of ‘all Gram‐negative bacteria’, provide a much less sensitive indicator of problems
associated with heat treatment, but are still frequently used in the examination of heat‐
treated foodstuffs. The term ‘index organism’ was suggested by Ingram in 1977 (cited in
Mossel et al. 1995) for a marker whose presence indicated the possible presence of an
ecologically similar pathogen.
Microbial indicators are more often employed to assess food safety and hygiene than quality.
Ideally, a food safety indicator should meet certain important criteria. It should:
• Be easily and rapidly detectable.
• Be easily distinguishable from other members of the food flora.
• Have a history of constant association with the pathogen whose presence it is to indicate.
• Always be present when the pathogen of concern is present.
• Be an organism whose numbers ideally should correlate with those of the pathogen of
concern.
• Possess growth requirements and a growth rate equalling those of the pathogen.
• Have a die‐off rate that at least parallels that of the pathogen and ideally persists slightly
longer than the pathogen of concern.
• Be absent from foods that are free of the pathogen except perhaps at certain minimum
numbers.
Common indicator organisms are:
• E. coli;
• Enterobacteriaceae;
• enterococci (formerly known as faecal streptococci);
• bacteriophages.
4.1.1 Coliforms
‘Coliforms’ is a general term for Gram‐negative, rod‐shaped facultatively anaerobic bacteria. They are also known as the ‘coli‐aerogenes’ group. Identification criteria used are the
production of gas from glucose (and other sugars) and fermentation of lactose to acid and
gas within 48 hours at 35°C (Hitchins et al. 1998). The coliform group includes species
from the genera Escherichia, Klebsiella, Enterobacter and Citrobacter, and includes E. coli.
Coliforms were historically used as indicator micro‐organisms to serve as a measure of
faecal contamination, and therefore potentially the presence of enteric pathogens in fresh
water. However, since most coliforms are found throughout the environment they have
little direct hygiene significance. In Europe the wider Enterobacteriaceae grouping is
favoured over ‘coliforms’, but the latter term has been retained here due to its frequent
usage. Since coliforms are easily killed by heat, coliform counts can be useful when testing
for post‐processing contamination.
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The microbiology of safe food
In order to differentiate between faecal and non‐faecal coliforms, the faecal coliform test
was developed. Faecal coliforms are defined as coliforms that ferment lactose in EC medium
with gas production within 48 hours at 45.5°C (except shellfish isolates, 44.5°C). Escherichia
coli is the major species in the faecal coliform group. Of the groups of bacteria that comprise
the total coliforms, only E. coli is generally not found growing and reproducing in the environment. Consequently, E. coli is considered to be the species of coliform bacteria that is the best
indicator of faecal pollution and the possible presence of enteric pathogens. The use of coliform tests is declining as improved specific detection methods are developed, and the wider
range of Enterobacteriaceae organisms have been used as an indicator group.
4.1.2 Enterobacteriaceae
The Enterobacteriaceae family includes many genera, such as E. coli, Salmonella, Shigella,
Yersinia and Enterobacter. They are Gram‐negative bacilli and facultative anaerobes that
display many properties in common. Biochemically, Enterobacteriaceae display the following
characteristics: they ferment glucose, are cytochrome oxidase‐negative, reduce nitrate to
nitrite, are found in nature, and most are part of the normal gut flora in humans and animals.
The Enterobacteriaceae family includes some species that generally ferment lactose (i.e. E. coli),
whereas others do not (i.e. Salmonella). Therefore the use of violet red bile glucose agar
(VRBGA) is applicable for the Enterobacteriaceae, whereas violet red bile lactose agar is more
applicable for the coliforms. There has been a general trend away from using coliforms as indicators of the possible presence of enteric pathogens to Enterobacteriaceae. This is in part due
to their ease of detection. Water that is contaminated with faecal matter may contain a range
of pathogens including Vibrio cholerae, S. Typhi, other Salmonella serovars, Shigella dysenteriae, Campylobacter jejuni, pathogenic strains of E. coli and the protozoan Giardia lamblia.
4.1.3 Enterococci
The enterococci include two species found in the human and animal intestines: Enterococcus
faecalis and E. faecium. The former is mainly associated with the human intestinal tract,
whereas the latter is found in both humans and animals. The enterococci are sometimes used
as indicators of water contaminated with faeces. The advantage of testing for enterococci is
that they die more slowly than E. coli, which therefore reduces the risk of false‐negative results.
It is plausible that they are a better indication of hygienic quality in food as they are more
resistant to drying, etc. than coliforms. This is especially true for frozen and dried foods, and
foods receiving moderate heat treatment. However, their resilience further undermines their
value as indicator organisms as their presence in foods may be of little consequence if the
pathogens have been killed during processing.
Enumeration of enterococci usually involves sodium azide, thallous acetate or antibiotics as
selective agents and raised incubation temperature (45°C). Some media include tetrazolium
chloride, which leads to red colony formation, and therefore enhances visualisation of enterococci colonies.
4.1.4 Bacteriophages
It is impractical to routinely screen water for the presence of pathogenic viruses. However
bacteriophages (coliphages, F′‐specific phages and Bacteroides phages) have been proposed as
more appropriate indicators of waterborne viruses than bacterial indicators (Lees 2000).
Bacteriophages are of similar size and have similar surface characteristics to viruses, are present in human faeces and are easier to detect using the agar overlay technique with a tester
Bacterial foodborne pathogens
139
bacterial strain, and the enumeration of plaques. This has been a topic of considerable debate,
largely due to the lack of carefully validated comparative methodologies.
4.2 Campylobacter jejuni, C. coli and C. lari
4.2.1 General description
Campylobacter species are Gram‐negative thin rods (0.2–0.9 × 0.2–5.0 μm). The genus is in the
Family Campylobacteraceae, which in turn belongs to the Order Campylobacterales and Class
Epsilonproteobacteria. Hence in Figure 1.1, it can be seen that the Gram‐negative organisms
split into various groups, with Campylobacter, Helicobacter and Arcobacter being more closely
related to each other than to the Enterobacteriaceae (Salmonella, E. coli and Shigella species)
and Pseudomonas species. The majority of Campylobacter infections are sporadic and self‐
limiting, therefore the reported number of cases is a considerable under‐estimate of the true
incidence. Campylobacter jejuni is responsible for nearly 80% of human Campylobacter
infections while C. coli accounts for around 15%. Only in severe cases are antibiotics prescribed, with the first choice options being fluoroquinolones and macrolides.
The first isolation of the organism was in 1972 in Belgium from faecal samples, thereafter
the application of selective media and incubation conditions became more common place in
clinical laboratories. Nowadays it is accepted as a leading cause of global bacterial gastroenteritis, totalling as many as 400–500 million cases worldwide each year (Kaakoush et al. 2015).
Campylobacter infections have also has been linked to serious neurological disorders such as
Guillain–Barré syndrome (GBS) and Miller–Fisher syndrome. In developing countries,
infections are endemic and disproportionately affect young children.
The genus Campylobacter comprises a group of bacteria with about 30 taxa with a mol%
G + C content of the DNA of 27–31. There are 16 described species, six subspecies and two
biovars. Their maximum growth is at 42–46°C and no growth occurs below 30°C. Therefore,
Campylobacter do not multiply at ambient, let alone refrigeration temperatures. Four
Campylobacter species, C. jejuni, C. coli, C. lari and Campylobacter upsaliensis, can grow at
Box 4.1
Organism
C. jejuni and C. coli
Onset of symptoms
2–5 days
Food source
Raw chicken, beef, milk, mushrooms, clams, hamburger, water, cheese, pork, shellfish, eggs, cake
icing.
Acute symptoms and chronic complications
Abdominal pain, watery diarrhoea (sometimes bloody), fever, malaise, vomiting. Chronic symptoms:
colitis, Guillain–Barré syndrome, Reiter syndrome.
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42°C and have often been called ‘thermotolerant’ species. However, this term is normally used
for organisms that typically grow at high temperatures, i.e. >50°C and therefore, to avoid confusion, this term is not further used in this book. A temperature of 42°C is frequently used for
isolation purposes, especially for the isolation of C. jejuni and C. coli colonies from food and
clinical samples.
Campylobacter lari was first isolated from mammalian and avian species, especially seagulls
of the genus Larus, hence its name. It is a potential human pathogen causing enteritis and diarrhoea in immunocompetent patients and bacteraemia in immunocompromised patients.
Although such cases are infrequently reported, there appears to be an increasing number of
reports. It is also been isolated from chickens, mussels and oysters as well as dogs and cats.
In general, all Campylobacter species are microaerobic, requiring higher concentrations of carbon dioxide (~10%) than that in ambient air (0.04%). The usual atmosphere
for isolation contains around 5% oxygen, 10% carbon dioxide and 85% nitrogen, which
is an inert gas. However, some Campylobacter species are ‘capnophilic’ because
they require 35% carbon dioxide to grow. Also their tolerance to oxygen is strain‐ and
species‐dependent. Some species require hydrogen or formate with fumarate to grow
under microaerobic conditions. If not available, anaerobiosis becomes an optimal growth
condition for these species.
Campylobacter species are chemoorganotrophs and do not ferment or oxidise carbohydrates. Therefore they need nutrient‐rich media for cultivation and the lack of carbohydrate
utilisation limits identification using phenotypic methods. The organism’s morphology can
change between vibroid (curved), spiral, doughnut, S‐shaped and coccoid. The short coccoid
morphology is associated with the ‘viable but non‐culturable’ (VBNC) state of stressed cells.
By definition these are not recoverable using conventional methods from the VBNC condition
(Section 6.2.3). They are motile, with a characteristic corkscrew‐like swimming motion by
means of a single polar unsheathed flagellum at one or both ends of the cell.
The organism is very sensitive to drying and is readily destroyed by cooking at 55–60°C for
several minutes (D50 0.88–1.63 minutes). Temperature, pH and water activity growth ranges
and D values for Campylobacter are given in Tables 2.3 and 2.8. The infectious dose is approximately 1000 cells and a fuller description of the dose–response relationship is given in
Section 9.5.
4.2.2 Campylobacter infections
Reported Campylobacter food poisoning cases are mainly due to C. jejuni, which causes the
majority of outbreaks (80%) of cases, and C. coli (15%), whereas C. upsaliensis and C. lari have
only occasionally been implicated. This may in part be due to inefficient isolation methods,
since the use of filtration methods has revealed that C. upsaliensis is associated with human
disease more than previously recognised.
The characteristics of Campylobacter enteritis are:
• flu‐like illness;
• abdominal pain;
• fever;
• diarrhoea, may be profuse, watery and often bloody in children.
The incubation period is 2–10 days, with most people showing symptoms by 4 days (Tables 1.3
and 1.4). The disease lasts for about 1 week and is usually self‐limiting after a period of bed
rest. The organism is excreted in the faeces for several weeks after the symptoms have ceased.
Relapses occur in about 25% of cases.
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141
Disease outcome in humans varies substantially from mild, non‐inflammatory, self‐limiting
diarrhoea to severe, inflammatory, bloody diarrhoea and abdominal pain lasting for several
weeks. In some patients, C. jejuni is also associated with more severe sequelae such as
the development of reactive arthritis and peripheral neuropathies, Miller–Fisher syndrome
and GBS.
The annual incidence of campylobacteriosis varies substantially between countries. For
example, per 100 000 population the values ranges from 14 for USA, 30–35 cases for Canada,
110 cases for Australia and 160 cases for New Zealand. They infect an estimated 1% of the
population of Western Europe. The annual cost of campylobacteriosis in the USA is estimated
at $5–17 billion (Section 1.11).
Although there has been a reduction in the incidence of infections by a number of major
foodborne pathogens (i.e. Salmonella serovars) due to improvement in food safety,
Campylobacter infections have continued to increase in both developed and developing countries. Additionally, Campylobacter strains may carry antimicrobial resistance genes with the
capability of horizontal transfer between pathogenic and commensal micro‐organisms, which
could possibly lead to the emergence of multidrug‐resistant micro‐organisms. An increase in
ciprofloxacin resistance (a medically important antibiotic) has been reported possibly due to
the veterinary use of the structurally related (fluoroquinolone) antibiotic enrofloxacin used in
poultry husbandry (see Section 11.2.4).
Campylobacter species were initially recognised as animal pathogens and only in the past
15–20 years have been recognised as human pathogens (Butzler et al. 1973; Skirrow 1977,
1991; Humphrey et al. 2007). Our awareness of the considerable health burden of Campylobacter
infections has considerably increased in recent decades. It was recognised as a veterinary pathogen by McFaydean and Stockman in 1913, and in 1957 by King from blood samples of children
with diarrhoea. However the scale of Campylobacter infections was greatly under‐reported
due to the lack of suitable isolation and cultivation techniques for many years until 1970s.
4.2.3 Campylobacter jejuni typing
For microbial source tracking, i.e. epidemiological investigations, DNA sequencing techniques
such as multi‐locus sequence typing (MLST) and more recently whole‐genome sequencing are
favoured. Normally determining the genomic diversity of a bacterial population is central to
deciding whether genomic differences between any two isolates are sufficiently small to assume
a high likelihood of epidemiological relatedness, i.e. whether the isolates share a source. Source
attribution studies for C. jejuni have primarily been based on seven‐loci MLST (Section 6.6.1)
of aspA (aspartase), glnA (glutamine synthetase), gltA (citrate synthase), glyA (serine hydroxy
methyl transferase), tkt (transketolase), pgm (phosphoglucomutase) and uncA (ATP synthase
alpha subunit). This has identified chicken as a major source of human infection worldwide, as
well as ruminants, pets and environmental sources.
However, seven‐loci MLST has limited efficacy for source attribution of clinical cases of
isolates of a sequence type that is isolated from multiple hosts, since by definition they have
identical allelic variation. Subsequently, whole‐genome‐based techniques of genotyping are
being considered. For example, a comparative genomic fingerprinting approach (CGF) has
also been developed to genotype C. jejuni isolates with a high resolution and has been extensively used in Canada for routine surveillance of campylobacteriosis. The CGF40 approach
consists of determining the presence/absence of 40 genes belonging to the accessory genome
of C. jejuni through gene amplification. This shows concordant results with MLST and has a
higher discriminatory power.
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In C. jejuni (and possibly other Campylobacter species) there is considerable genetic heterogeneity
within the various lineages that need to be recognised. If the lineage diversity is generally low,
then the observed genetic distance between two isolates may be below a pre‐determined cutoff
value for cluster definition, even in the absence of epidemiological linkage. For the three common C. jejuni sequence types, ST230, ST267 and ST677, there is limited genomic diversity. Yet
ST45 is notably more diverse and separates into three main sublineages. The population structure of ST45 clonal complex (CC) does seem to vary according to geographic location, and not
date of isolation (i.e. not temporal variation). Additionally, there are some sublineages of ST45
with extremely similar genomes (monomorphic clones) that have been isolated from animal
hosts and human patients for over a decade, from several countries around the world.
Pathogen source attribution studies are a useful tool for identifying reservoirs of human
infection. For example, seven‐loci MLST of C. jejuni has identified chicken as a major source
of Campylobacter infection. However, lineages that do not adapt to host colonisation complicate source attribution. For example, C. jejuni ST21 CC and ST45 CC undergo rapid host
switching, and subsequently whole‐genome sequencing (WGS) is not more informative than
conventional seven‐loci MLST in defining the source of infections for these generalist lineages.
There also appears to have been a clonal expansion of the highly virulent ST8 lineage during
the 1970s. This lineage is now causing vast numbers of ovine abortions in the United States.
Expanding conventional seven‐loci MLST analysis by combining with WGS‐based typing
methods should improve the ability to distinguish between unrelated strains. Thépault et al.
(2018) used three types of genotype data to analyse >2100 strains in France: comparative
genomic fingerprints, MLST genes and 15 host segregating genes. The clinical isolates were
from 54 different STs, of which 79% belonged to the 12 most common CCs: ST21, ST206,
ST257, ST353, ST48, ST464, ST22, ST283, ST42, ST45, ST52 and ST658 CCs. In agreement
with previous studies, chicken was an important source of campylobacteriosis (31–63% of
clinical isolates assigned). There was also evidence for ruminants being a major source of
infection (22–55% of clinical isolates assigned). Therefore, potential transmission routes from
ruminants to human need to be further considered. Additionally, there was evidence of environmental and pet sources of human infection. However, the relative importance as sources
varied according to the year of isolation and the genotyping technique used. These annual
variations in attribution emphasise the dynamic nature of Campylobacter transmission and
genomic variability.
The presence of clonal populations makes genomic distinction between epidemiologically
associated and non‐related isolates difficult and can adversely affect the use of WGS methodology in surveillance and outbreak investigations for public health purposes; more studies
exploring the genomic diversity and possible occurrence of clonal subpopulations in other C.
jejuni lineages are therefore needed.
4.2.4 Virulence factors
Campylobacter jejuni enters the host intestinal tract via the faecal–oral route and colonises the
distal ileum and colon of humans. How C. jejuni achieves this is uncertain, but somehow from
an apparently low infectious dose (ingested dose) of 100–1000 cells the organism is able to
overcome the host’s larger intestinal flora and epithelial barrier. The process of infection is in
various stages.
1 Attachment to intestinal cells. After entering the gastrointestinal tract, C. jejuni cells swim to
the mucus layer and bind to the epithelial cells of the intestine. Campylobacter jejuni produces
a number of adhesion factors (adhesins), which are important for efficient interaction
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143
with host target cells; therefore, the presence of receptor(s) on target cells allows for direct
participation of the cell in the invasion process. CadF is the best‐studied binding factor of
C. jejuni. This protein allows the Campylobacter cells to attach to the extracellular matrix
protein fibronectin of target cells, and is essential for their uptake at the basolateral host cell
surface. Attachment to fibronectin by CadF activates downstream signal transduction to small
Rho GTPases. A second adhesin FlpA acts cooperatively in mediating C. jejuni attachment to
host cells via fibronectin, and consequently to epithelial cells. Other possible adhesins are JlpA,
PEB1, CapA, p95 and MOMP. However these proteins have not been studied in as much detail.
2 Host cell invasion. In general, epithelial cell invasion by C. jejuni is the primary mechanism
leading to tissue damage and pathogenesis. The organism enters by a microtubule‐dependent
(actin‐filament‐independent) and/or actin‐filament‐dependent (microtubule‐independent)
mechanism. In contrast to invasive Salmonella serovars and Shigella species, C. jejuni does
not encode typical disease‐related type III or type IV secretion systems (T3SS or T4SS).
Instead, C. jejuni uses its rapid motility to pass through the high viscosity of the intestinal
mucosa to adhere and enter into host cells. The flagellum can also function as a secretion
system for the export of proteins that control bacteria–host interactions. These are called
flagellar co‐expressed determinants (FedA–D) and Campylobacter invasion antigens
(CiaA–H). One of the best characterised Cia proteins is the ~70‐kDa protein CiaB. This is
necessary for the secretion process itself, and is required for maximal invasion of the organism into host cells. CiaI is involved in efficient intracellular survival. Another protein that is
secreted from the flagellar export apparatus is FlaC, mutants of which express a functional
flagellum, but are unable to enter epithelial cells. Therefore, flagellar export machinery
appears to have several roles in the C. jejuni invasion process.
3 Damage of epithelial cell function. The organism perturbs the normal absorptive capacity of
the intestine by damaging epithelial cell function. This is due to direct action, by cell invasion
and/or the production of toxin(s), or indirectly, following the initiation of an inflammatory
response (Figure 4.1). Intracellular survival within host cell may be aided by the production
of catalase to protect against oxidative stress from lysosomes. The organism may also enter
a VBNC state, which may be of importance in the organism’s virulence.
1. Attachment
and engulfment
2. Engulfment
into vacuole
3. Invasion of lamina propria
Figure 4.1 Campylobacter invasion of the gut wall.
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A number of virulence factors have been identified:
1 Heat‐labile enterotoxin (60‐ to 70‐kDa), which increases cyclic AMP levels of intestinal cells
and cross‐reacts with anticholera toxin antibodies. This is also referred to as the ‘cholera‐
like’ toxin. It is iron‐regulated and causes elongation of Chinese hamster ovary cells and
binds to GM1 ganglioside. It has an AB5 domain structure and there is homology between
the B subunit and cholera toxin and E. coli heat‐labile toxin (LT).
2 Cytoskeletal altering toxin that may also cause diarrhoea. This is also known as the cytolethal distending toxin (CDT) and has been the most studied toxin from C. jejuni. This toxin
causes characteristic elongation of cultured mammalian cells followed by distension. It is
different from other toxins produced by enteric bacteria in that it is destroyed by heating at
70°C for 15 minutes and by trypsin.
3 Heat‐labile protein cytotoxin, which is not neutralised by anticholera toxin.
DNA microarray analysis of C. jejuni strains has correlated the CDT and haemolysin with the
organism’s survival under aerobic conditions at room temperature (On et al. 2006). The poorly
surviving strains represented genotypes that have not been reported in human infections,
whereas, the strains with high surviving potential represented genotypes from human disease
cases.
1 Transmigration across the epithelial barrier. Campylobacter jejuni is able to invade underlying tissues such as the lamina propria and bloodstream followed by entering other organs
such as the spleen, mesenteric lymph nodes or liver. However, the molecular mechanism of
this is poorly understood. Campylobacter jejuni may trigger its own transmigration across
polarised intestinal epithelial cells by expressing ganglioside‐like lipooligosaccharides that
can attach to the apical surface of epithelial cells. There is also a family of proteins termed
‘high temperature requirement A’ (HtrA), which are secreted virulence factors with roles in
adhesion, invasion and transmigration. The HtrA family of proteins is widely conserved in
the bacterial kingdom and represents a class of heat‐shock serine proteases with additional
chaperone activity. These proteases act in the periplasm, for the assembly of proteolytically
active HtrA oligomers that control protein quality. These proteases influence the survival
and virulence capabilities of many bacterial pathogens. Additionally, in C. jejuni (and
Helicobacter pylori), HtrA proteins are actively secreted in the extracellular environment,
and proteolytically cleave the 125‐kDa E‐cadherin receptor in the adherens junctional complex. This leads to the opening of the cell‐to‐cell junctions between neighbouring epithelial
cells followed by paracellular transmigration of C. jejuni.
2 Intracellular survival. Campylobacter jejuni can survive for extended periods of time in
intestinal epithelial cells. After invasion, C. jejuni localises in a specific membrane‐
surrounded compartment in the cytoplasm. This compartment is called the C. jejuni‐
containing vacuole (CCV), which appears to be distinct from the conventional cellular
lysosomes. It is able to survive within the CCVs of non‐phagocytic epithelial cells for up to
24 hours and possibly 72 hours. The CCVs are transported from the cell periphery to the
perinuclear space by the vesicle transport system, possibly involving microtubules and the
dynein motor protein. The CCVs develop from the canonical endocytic pathway immediately following epithelial cell entry. This avoids delivery of the bacteria into lysosomes. Only
a few enzymes have been proposed for the CCV process. Also, only a few genes influencing
intracellular survival have been identified: aspAB, spoT (stringent response regular), ppk‐1
and ppk‐2 (polyphosphate kinases), sodB (superoxide dismutase), frdA (fumarate reductase
A), ciaI and cprS (a sensor kinase of a two‐component regulatory module controlling planktonic bacterial growth).
Bacterial foodborne pathogens
145
3 Interaction with immune cells. It is unclear whether C. jejuni can persist in phagocytic
immune cells. In laboratory studies, C. jejuni can survive for several days after uptake within
some cell lines of macrophages from human and mice.
Campylobacter infection is now recognised as the single most identifiable antecedent infection
associated with the development of GBS (see Section 1.9 on chronic sequelae) and as the most
common cause of acute flaccid paralysis (Allos 1998). Campylobacter are associated with several pathological forms of GBS, including the demyelinating (acute inflammatory demyelinating polyneuropathy) and axonal (acute motel axonal neuropathy) forms. GBS is an autoimmune
disorder of the peripheral nervous system. It is characterised by weakness usually symmetrical,
which develops over several days. It occurs worldwide and is the most common cause of
neuromuscular paralysis. Of an estimated annual number of 2628–9575 GBS cases in the USA,
526–3830 were triggered by Campylobacter infection. Typically the gastrointestinal symptoms
occur 1–3 weeks before the neurological symptoms.
GBS is probably due to an autoimmune response to the ganglioside GM1 on peripheral
nerves following infection by C. jejuni O19 (although other serotypes may be involved). The
peripheral nerves may share epitopes in common with surface antigens of C. jejuni lipopolysaccharide (LPS) (molecular mimicry). Cytokines may induce the inflammatory process and
result in nerve demyelination. The complement system may also lead to nerve damage, and an
increase in the permeability of the blood–nerve barrier, which causes inflammation. Estimated
total costs (in US$) of Campylobacter‐associated GBS are ~$1 billion. Risk assessment examples
are given in Section 11.2.
4.2.5 Whole‐genome sequence analysis
Campylobacter jejuni is a major cause of bacterial gastroenteritis, and knowledge of its genome
could help in developing further control measures (Llarena et al. 2017). Parkhill et al. (2000)
published the first C. jejuni sequence. This was of strain NCTC 11168, a human clinical isolate.
The genome is 1.6 Mb in length, and since ~94% encodes for proteins, it is one of the densest
that has been sequenced.
The genome sequences can be compared between different Campylobacter species.
Comparing the genome of C. jejuni with C. coli, C. lari and C. upsaliensis shows that there are
considerable genomic differences amongst the organisms. These are associated with the insertion
of phage‐ and plasmid‐like regions, as well as differences in the lipooligosaccharide complex
(Fouts et al. 2005). Table 4.3 summarises the results.
There were a number of discoveries following the genome sequencing, including the revelation
of a capsular polysaccharide, considerable capacity for phase variable gene expression and also
lipooligosaccharide (LOS) structural phase variation. In general, the Campylobacter genome
has a high %GC content, but sequencing revealed two regions of low %GC content (30.6%),
two unexpected regions of LOS and extracellular polysaccharide (EP) biosynthesis gene clusters. Genes encoding for the CDT, haemolysin and phospholipase were identified, and these
may have a role in pathogenesis. No cholera‐like toxin or type III secretion systems were
found, however plasmid‐encoded components of a putative type IV secretion system were
identified.
Apart from the LOS, EP and flagellar modification, there is little gene organisation into
operons or clusters. Most of the hypervariable sequences are in localised regions of the genome,
close to the clusters of the LOS and EP biosynthesis genes, and flagellar modification genes.
Genome sequencing also revealed variations in the length of polyG:C tracts, which in some
organisms is responsible for phase variation of surface antigenicity. It appears that C. jejuni
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Table 4.3 Comparison of genome features for five Campylobacter species.
Trait
Campylobacter jejuni
NCTC 11168
C. jejuni
RM1221
Campylobacter coli
RM2228
Campylobacter lari
RM2100
Campylobacter upsaliensis
RM3195
Chromosome size (Mb)
GC%
Open reading frames (ORF)
% ORF assigned function
Phage/genomic island regions
Plasmids (kb)
Two‐component systems
Outer membrane proteins
Transmembrane proteins
1.64
30.55
1634
–
0
0
15
14
87
1.78
30.31
1835
61
4
0
15
16
92
~1.68
31.37
1764
74
0
1 (~178)
15
12
94
~1.5
29.64
1554
73
1
1 (~46)
13
10
74
~1.66
34.54
1782
68
1
2 (~3.1, 110)
11
11
118
Source: Adapted from Fouts et al. (2005).
Bacterial foodborne pathogens
147
does not possess many of the adaptive responses, such as RpoS homologues present in other
foodborne pathogens and so does not show a general stress response (see Section 2.9). It also
lacks cold‐shock proteins, though its minimum growth temperature is only ~30°C. However,
it shows considerable genetic diversity, and considerable strain–strain variation in virulence
and tolerance to stresses (Park 2002; Scott et al. 2007). The genome encodes for five iron‐
acquisition systems, including enterochelin, siderophore receptor protein and haemin uptake
operon. The sequences of five C. jejuni genomes are aligned in Plate 2. There are considerable
sequence differences between C. jejuni subsp. dolyei and C. jejuni subsp. jejuni, which account
for the rearrangements shown. The major difference between the two C. jejuni genomes is the
presence of four large integrated elements, or regions. Three of these encode for phage, or
phage‐related genes, and the fourth may be an integrated plasmid.
4.2.6 Sources and control of Campylobacter jejuni
In general, C. jejuni colonises the gut of a large variety of domestic and wild birds, as well
as other food animals as a commensal (Table 1.2). Campylobacter jejuni and C. coli are commensal in cattle, swine and birds. Campylobacter jejuni is often the predominant species in
poultry, whereas C. coli and C. lari predominate in swine and birds, respectively.
Campylobacter upsaliensis has been frequently isolated from domestic cats and dogs.
Therefore, handling and consumption of contaminated poultry and other meat products,
raw milk and untreated drinking water have been recognised as common origins of
C. jejuni infection of humans. The high prevalence of Campylobacter on chicken carcasses
and the potential cross‐contamination that can easily occur during food preparation results
in chickens being important vehicle of transmission. It should be noted however that workers in poultry processing facilities can have higher titers of Campylobacter‐specific IgG
antibodies than the rest of the population and rarely become ill by C. jejuni infection. Also,
asymptomatic Campylobacter infections occur even in individuals with only limited earlier
exposure to Campylobacter.
As given above, the organism does not multiply at room temperature (minimum growth
temperature is 30°C, Table 2.8). Therefore, C. jejuni and C. coli do not multiply in chilled foods,
although they will persist under such conditions. This may be why cases of Campylobacter
gastroenteritis outnumber Salmonella in many countries. There is a notable seasonality to
Campylobacter enteritis, with peak incidences in the summer months (Figures 1.4 and 1.5).
The incidence of Campylobacter infections has been decreasing in some countries.
Source:
• livestock: pigs, cattle and sheep;
• domestic animals: cats and dogs;
• poultry;
• raw milk;
• polluted water.
The routes of infection are via contaminated water, milk and meat. Poultry is the largest potential source of infectious Campylobacter. Consequently most sporadic infections are associated
with improper preparations or consumption of mishandled poultry products. Most C. jejuni
outbreaks, which are far less common than sporadic illnesses, are associated with the consumption of raw milk or unchlorinated water. Campylobacter does not grow at temperatures
below 30°C and is sensitive to acid pH. However, it can survive on cut fruits and vegetables for
sufficient time to be a risk to the consumer, and Campylobacter enteritis has been associated
with the consumption of contaminated raw fruits and vegetables.
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In the European Union (EU) the main source (up to 70%) of campylobacteriosis in humans
is attributed to chicken meat, and it is found that most of the broiler stocks are colonised by
Campylobacter at slaughter (Boysen et al. 2014). Subsequently, the prevention of broiler flock
colonisation has therefore become a food safety priority in the EU.
Direct enumeration of Campylobacter species is rarely possible. Usually an enrichment step
is used to recover low numbers of the organism from processed foods (see Section 6.7.3 for
details). On blood agar plates Campylobacter colonies are non‐haemolytic, flat, about 1–2 mm
in diameter and either spreading with an irregular edge or discrete, circular‐convex. Most
Campylobacter isolates are not speciated in routine analytical laboratories. In contrast, public
health laboratories investigating a food poisoning outbreak will ‘fingerprint’ isolates using a
range of procedures: biotyping, phage typing and serotyping.
Control measures:
• heat treatment (pasteurisation/sterilisation);
• hygienic slaughter and processing procedures;
• prevention of cross‐contamination;
• good personal hygiene;
• water treatment.
Campylobacter can easily cross‐contaminate processed food. A contaminated piece of raw
meat can leave 10 000 Campylobacter cells per cm2 on a work surface. Since the infectious dose
is only ~1000 cells the residual microbial load must be reduced to <2 per cm2. Campylobacter
jejuni is quickly killed during cooking at 55–60°C for several minutes and is not a spore‐
former. Hence the main control mechanisms are adequate cooking regimes and prevention
of cross‐contamination for raw meats and poultry.
Future control measures may include:
1 Competitive exclusion, whereby the chickens are inoculated with a cocktail of non‐
pathogenic bacteria that colonise the intestines and reduce the incidence of Salmonella
and Campylobacter carriage.
2 Vaccination, as has been applied for the control of Salmonella.
3 Bacteriophage treatment of chickens, which will reduce the carriage of Campylobacter.
4.3 Salmonella serovars
4.3.1 General description
Salmonella was one of the first bacteria to be studied when Salmonella Typhi was isolated from
a human sample in 1884. The following year, Daniel Elmer Salmon (whose name was later
given to the Salmonella genus) and Theobald Smith isolated S. Choleraesuis from a swine sample. Salmonella is one of the most frequently reported foodborne diseases worldwide and is a
significant cause of morbidity, mortality and economic loss. The numbers of salmonellosis
cases shows a marked seasonal trend with peak incidences in the summer months. Globally
each year there are an estimated 93.8 million cases, resulting in ~155 000 deaths (Majowicz
et al. 2010).
Salmonella is a genus in the Family Enterobacteriaceae. They are Gram‐negative, facultatively anaerobic, non‐spore‐forming short (1–2 μm) rods, which typically (but not always)
produce H2S and are unable to ferment lactose. The majority of species are motile with peritrichous flagella; S. Gallinarum and S. Pullorum are non‐motile. Salmonellae ferment glucose
with the production of acid and gas but, with a few exceptions, are unable metabolise lactose
and sucrose. Their optimum growth temperature is about 38°C and their minimum is about
Bacterial foodborne pathogens
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Box 4.2
Organism
Salmonella (non‐typhoid), S. Typhi and S. Paratyphi
Food source
Raw poultry, meat, eggs, milk and dairy products, vegetables, fruits, chocolate, coconut, peanuts,
fish, shellfish.
Onset of symptoms
Salmonella (non‐typhoid): 6–48 hours
S. Typhi and S. Paratyphi: 7–28 days
Acute symptoms and chronic complications
Salmonella (non‐typhoid): abdominal pain, bloody stools, cold chills, dehydration, diarrhoea,
exhaustion, fever, headache and sometimes vomiting. Chronic symptoms: reactive arthritis, Reiter
syndrome.
S. Typhi and S. Paratyphi: typhoid‐like fever, malaise, headache, abdominal pain, body aches,
diarrhoea or constipation.
5°C (Table 2.8). Because they do not form spores, they are relatively heat‐sensitive, being killed
at 60°C in 15–20 minutes (D62.8 = 0.06 minutes, Table 2.3). Salmonella pathogenicity islands
(SPIs) are covered in Section 2.5.2 (Table 2.2). The organism is highly diverse and there are
exceptions to the standard definition of the organism, with lactose‐fermenting strains and
H2S‐negative‐producing strains being isolated. This is highly important as standard detection
methods could overlook these strains, which are atypical but still virulent. A number of infant
infections have been attributed to infant formula contaminated with atypical lactose‐fermenting Salmonella strains of S. Tennessee and S. Virchow (Cahill et al. 2008), and H2S‐negative S.
Agona (Section 14.4.5).
Microevolution resulting in new variants of bacterial species can lead to new epidemic
clones. Genomic and phylogenetic analysis of monophasic S. Typhimurium isolates from UK
and Italy during 2005–2012 showed they formed a single clone that was distinct from the
monophasic epidemic clones of North America and Spain. Furthermore, the UK monophasic
epidemic clone had acquired a novel genomic island (~90 genes) encoding heavy metal (merTABCDE and merR) resistance and a composite transposon encoding antimicrobial resistance
genes not present in other S. Typhimurium isolates.
A second example of microevolution is S. Agona, which became a distinct serotype in the
1930s. It entered the US and European food chain in 1960s from South American fish meal. The
serotype has expanded and diversified since then, but still only forms four sequence types. Its
variants include H2S‐negative production (mutation in phsA), which therefore will not give the
characteristic black colony formation on XLD agar (Section 6.7.2). This variant caused a serious
outbreak of salmonellosis amongst infants due to infant formula contamination, as will be considered in the S. Agona outbreak case study (Section 14.4.5). It is postulated that the H2S‐negative
trait is an advantageous trait as it enables the organisms to survive the inflammatory response.
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4.3.2 Salmonella serotypes
There are only two species of Salmonella, S. enterica and S. bongori, which are divided into
eight groups (Boyd et al. 1996). Salmonella enterica is further divided into seven subspecies as
given by the Roman numerals, I, II, IIIa, IIIb, IV, VI and VII. The former subspecies V is now
recognised as the separate species S. bongori, which is not of clinical or foodborne disease
relevance. In order to facilitate epidemiological investigation, S. enterica strains need to be
further differentiated and this is achieved through a serotyping scheme, which was the initial
method of choice given the lack of molecular methods available at the time. In 1934, the first
list of 44 Salmonella serotypes defined using the Kauffmann–White scheme was published.
To date there are over 2500 defined serovars (Grimont and Weill 2007; Guibourdenche et al.
2010; Issenhuth‐Jeanjean et al. 2014). Although all serovars can be considered pathogenic to
humans, only about 200 are associated with human illness. Additionally, some confusion has
arisen in the nomenclature whereby the serovar name is mistaken for a species name. For
example, Salmonella enterica serovar Typhimurium is sometimes given as Salmonella typhimurium. The latter term incorrectly infers that ‘typhimurium’ is a species, whereas in fact it is a
serovar of the species Salmonella enterica.
The Salmonella serovars are distinguished by their O, H and Vi antigens using the Kauffmann–
White scheme. The Kauffmann–White formula gives the O antigens in the order of O, H and Vi
(if present). Colons separate the major antigens and commas are used to separate the components of each antigen. Further details are included using the follow convention:
• Underlining: O antigen is encoded by a lysogenic bacteriophage.
• Square brackets: Factor may or may not present (not phage‐encoded).
• Curly brackets: Indicate the factor does not co‐exist with others (exclusive).
• Round brackets: Refer to the factor being a weakly agglutinable factor.
Example:
• Salmonella enterica serotype Typhimurium 1,4,[5],12:i:1,2 shows that the strain has O antigen factors 1,4, [5] and 12 of which 5 may/not be present, and the H antigen i in Phase 1 with
1 and 2 in Phase 2.
• Salmonella enterica serotype Agona 1,4,[5],12:f,g,s:[1,2] shows that the strain has O antigen
factors 1, 4, [5] and 12 of which 5 may/not be present, and the H antigens f, g, s in Phase 1
and possibly 1 and 2 in Phase 2.
The serotypes are then put into serogroups according to common antigenic factors (Table 4.4).
Table 4.4 Salmonella serotyping.
H antigen
Serotype
Group
O antigen
Phase 1
Phase 2
S. Paratyphi A
S. Typhimurium
S. Paratyphi C
S. Newport
S. Typhi
S. Enteritidis
S. Anatum
S. Newington
S. Minneapolis
A
B
C1
C2
D
D
E1
E2
E3
(1), 2,12
(1), 4, (5), 12
6, 7, Vi
6, 8
9, 12, Vi
(1), 9, 12
3, 10
3, 15
(3), (15), 34
a
i
c
e, h
d
g, m
e, h
–
1,2
1,5
1,2
–
Parenthesis indicate antigen determinant that may be difficult to detect.
Dominant antigenic determinants are underlined.
1,6
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The cell surface of Salmonella contains a complex LPS structure (Figures 2.4 and 2.5;
Mansfield and Forsythe 2001), which gives rise to the O antigen. The number of repeating
units and sugar composition varies considerably in Salmonella LPS and is of vital importance
with regard to epidemiological studies. The sugars are antigenic and therefore can be used
immunologically to identify Salmonella isolates. The Kauffmann–White scheme recognises 46
somatic (O) antigen groups. It is the serotype of the Salmonella isolate that aids epidemiological studies tracing the vector of Salmonella infections. Further characterisation is required for
epidemiological studies and this includes biochemical profiles and phage typing. The majority
of the enzymes involved in O antigen biosynthesis are encoded by the rfb gene cluster. The rfb
gene cluster has been the site of PCR‐probe‐based serotyping, though serotyping is also achievable in silico using WGSs (Section 14.3).
The Salmonella H antigens are primarily encoded by one of two genes, fliC and fljB, which
express the Phase 1 H antigen and the Phase 2 H antigen, respectively. The fliC gene is located
in one of the flagellar biosynthesis operons, and is found in all salmonellae. In contrast, the fljB
gene is only encoded in the genome of four Salmonella enterica subspecies (I, II, IIIb and VI).
The two flagellin loci fliC and fljB are coordinately regulated so that only one antigen is
expressed at a time in a single cell. Since these express two flagellin types they are termed
diphasic, whereas those with only one flagellar antigen type (subspecies IIIa, IV, VII) are
termed monophasic.
Some serotypes were initially named after the place where they were first isolated, e.g. S.
Dublin and S. Heidelberg. Others were named after the disease and affected animal. For example, S. Typhi and the paratyphoid bacteria are normally septicaemic and produce typhoid or
typhoid‐like fever in humans. Whereas S. Typhimurium causes typhoid in mice.
Despite their close relatedness, Salmonella serovars differ in their host range and the
diseases they cause. For example, Salmonella Enteritidis is a serovar typically linked to
eggs, and to a lesser degree to poultry meat. It is a so‐called invasive Salmonella, i.e. a
serovar able to enter the bloodstream of the bird and infect the egg. Salmonella
Typhimurium infects many host species, including humans, poultry and mice. It is often
linked to eggs, but more commonly to poultry meat, whereas S. Typhi only infects
humans. In contrast, S. Pullorum and S. Gallinarum are both specific to poultry, but they
cause distinct diseases. It is plausible that the culling of UK poultry in the early 1970s
that were seropositive for S. Gallinarum and S. Pullorum created a niche that was filled
by the antigenically similar S. Enteritidis, which increased in the 1980s to become the
most common serotype of human isolates.
The dominant serotype causing food poisoning changes, probably reflecting changes in animal husbandry and the dissemination in the food chain of new serotypes from increased world
trade. Current concern is the increase in multiple antibiotic‐resistant serovars, such as S.
Typhimurium DT104, mono‐phasic Salmonella and S. Typhimurium ST313, which has been
associated with severe infections and deaths in humans in sub‐Saharan Africa (Hammarlöf
et al. 2018).
Multidrug‐resistant S. Typhimurium DT104 emerged in the 1970s–1980s and spread rapidly around the world. Its origin and transmission route has been unclear, though generally it
was regarded as being generated by the use of antibiotics in cattle. Table 1.12 shows its increase
in multiple antibiotic resistance over a 6‐year period, from 1990 to 1996. This has been investigated using WGS and the rates of mutation estimated. Salmonella Typhimurium DT104
emerged initially as an antimicrobial‐susceptible variant between 1934 and 1962, and became
multiply‐drug resistant (MDR) around ~1972 through the horizontal transfer of the 13‐kb
Salmonella genomic island 1 (SGI1) MDR region. This was followed by multiple transmission
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events, initially from central Europe and later between several European countries. An independent transmission to the United States and another to Japan also occurred, and from those
countries it was transmitted to Taiwan and Canada. Additionally, an independent acquisition
of resistance genes took place in Thailand in ~1975 (Leekitcharoenphon et al. 2016).
4.3.3 Infections caused by Salmonella serovars
Salmonella typically causes one of three diseases:
• gastroenteritis, S. Enteritidis and S. Typhimurium;
• enteric fever, S. Typhi and S. Paratyphi;
• invasive systemic disease, S. Choleraesuis.
Characteristic symptoms of Salmonella food poisoning:
• diarrhoea;
• nausea;
• abdominal pain;
• mild fever and chills;
• sometimes vomiting, headache and malaise.
The incubation period before illness is between 12 and 36 hours. The illness is usually self‐
limiting, lasting 4–7 days (Tables 1.3 and 1.4). The infected person will be shedding large numbers of salmonellae in the faeces during the period of illness (average of 5 weeks). The numbers
of salmonellae in the faeces will decrease but may persist for up to 3 months, approximately 1%
of cases become chronic carriers. Children excrete up to 106–107 salmonellae per gram faeces
during convalescence. Occasionally systemic infections will occur, often due to S. Dublin and
S. Choleraesuis, which may require fluid and electrolyte replacement treatment. Salmonella
serovars Typhimurium, Dublin and Choleraesuis cause more extraintestinal infections than
other serovars.
Chronic consequences include postenteritis reactive arthritis and Reiter’s syndrome may
follow 3–4 weeks after onset of acute symptoms (see Section 1.9 on chronic sequelae). Reactive
arthritis may occur in 1–2% of cases. Reactive arthritis and Reiter’s syndrome are rheumatoid
diseases caused by a range of bacteria that induce septic arthritis by haematogenous spread to
the synovial space, causing inflammation. Causative organisms include S. Enteritidis, S.
Typhimurium and other serotypes such as S. Agona, S. Montevideo and S. Saint Paul.
Non‐Salmonella organisms causing reactive arthritis include C. jejuni, Shigella flexneri, Shigella
sonnei, Yersinia enterocolitica (in particular O:3 and O:9), Yersinia pseudotuberculosis, E. coli
and Klebsiella pneumoniae. These conditions are related to the major histocompatibility complex (MHC) gene for the Class 1 antigen, HLA‐B27, and cross‐reaction with bacterial antigen
leading to an autoimmune anti‐B27 response. Those who are human leukocyte antigen HLA‐
B27 positive have an 18‐fold greater risk for reactive arthritis, a 37‐fold greater risk for Reiter
syndrome and up to a 126‐fold greater risk for ankylosing spondylitis than persons who are
HLA‐B27 negative and have the same enteric infections. However, a lack of correlation between
reactive arthritis and HLA‐B27 was reported after S. Typhimurium and S. Heidelberg–S.
Hadar outbreaks in Canada (Thomson et al. 1995). The condition is immunological and hence
patients do not benefit from treatment with antibiotics, but are treated with non‐steroid anti‐
inflammatory drugs.
While many Salmonella serovars associated with food poisoning such as S. Typhimurium
and S. Enteritidis are generalist pathogens with broad host specificity, S. Typhi, S. Sendai and
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S. Paratyphi A, B, or C appear to be highly adapted to the human host. These are collectively
referred to as the typhoidal Salmonella serovars, and are the causative agents of enteric fever
(also known as typhoid or paratyphoid fever if caused by the serovars Typhi or Paratyphi,
respectively). This is an invasive, life‐threatening, systemic disease with an estimated global
annual burden of over 27 million cases, resulting in more than 200 000 deaths (Buckle et al.
2012). It is spread by the faecal–oral route and is endemic in regions lacking clean water and
adequate sanitation. As with other Salmonella serovars, there are changes in incidence. In
recent years, the incidence of infections with serovar Paratyphi A has increased and in South‐
East Asia, this serovar is accountable for up to 50% of all enteric fever cases (Meltzer and
Schwartz 2010).
Typhoid and paratyphoid fever is a life‐threatening illness as the organism multiplies in the
submucosal tissue of the ileal epithelium and then spreads throughout the body via macrophages. Subsequently various internal organs such as the spleen and liver become infected.
The bacteria infect the gallbladder from the liver and finally infect the intestines using bile as
the transportation medium. If the organism does not progress past the gallbladder then no
typhoid fever develops. Nevertheless the person may continue to shed the organism in their
faeces. Salmonella Typhi differs from most S. enterica serovars in that it has a capsule and does
not carry the virulence plasmid. Presumably, S. Typhi has additional virulence factors.
The symptoms of typhoid fever are caused by LPS, which induces a local inflammatory
response during invasion of the mucosa. Unlike S. Typhi, it is uncertain if food poisoning
strains of Salmonella (i.e. S. Enteritidis and S. Typhimurium) are inside macrophages of the
liver and spleen. The symptoms of gastroenteritis probably result from the invasion of mucosal
cells. Salmonella Typhi causes a systemic infection, whereas enteric pathogens such as S.
Typhimurium rarely penetrate beyond the submucosal tissues.
Typical symptoms of typhoid fever are:
• sustained fever as high as 39–40°C;
• lethargy;
• abdominal cramps;
• headache;
• loss of appetite;
• rash of flat, rose‐coloured spots may appear.
The fatality rate of typhoid fever is 10% compared with less than 1% for most forms of salmonellosis. A small number of people recover from typhoid fever but continue to shed the bacterium in their faeces. Salmonella Typhi and S. Paratyphi enter the body through food and drinks
that may have been contaminated by a person who is shedding the organism in their faeces.
Salmonella infections in animals differ from the typical gastroenteritis and other sequelae
produced in humans. However, although animal models are limited for studying salmonellosis, unlike most other bacterial pathogens, there is a considerable amount of human data on
the illness.
Sources:
• Wide range of foods (Table 1.2).
• Domestic and wild animals: poultry, pigs, cattle, rodents, cats and dogs.
• Infected humans (especially S. Typhi and S. Paratyphi).
• Initially it was believed that large numbers of Salmonella had to be ingested for infection.
However, outbreaks involving cheddar cheese and chocolate were found to be caused by
low cell numbers: ~10/g cell and 50–100/g cells, respectively. It is now accepted that the
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infective dose varies from 20 cells to 106 according to age and health of the victim, the food
and also the Salmonella strain. See Section 10.5.5 for further discussion on dose–response
relationship, food and vulnerability of host, and the difference between infective and
ingested dose. It should be noted that the first 50 ml of liquid passes straight through the
stomach into the small intestines and is therefore protected from the stomach’s hostile
acidic environment. Likewise it is believed that chocolate can protect Salmonella while
transient in the stomach, hence reducing the infectious dose. Survival of Salmonella serovars through the acidic environment of the human stomach can be enhanced by the induction of acid tolerance due to heat treatment and exposure to short chain fatty acids (cf.
stress responses, Section 2.9).
Infection is caused by the penetration and passage of Salmonella organisms from gut lumen
into epithelium of small intestine where they multiply. Subsequently the bacteria invade the
ileum and even occasionally the colon. The infection elicits an inflammatory response. Because
Salmonella cannot tolerate the low pH of the stomach, the ingested dose is in the order of 105
bacteria, whereas if it is administered intravenously, as few as 10 cells can kill a mouse.
Antibiotic resistance in Salmonella is increasing, and in some Asian countries, more than
90% of Salmonella isolates are resistant to the most commonly used antibiotics. The combination of increased antibiotic resistance and widespread dissemination of the organism has
resulted in strains such as S. Typhimurium DT104 (see Section 1.12 and Table 1.12).
Since antibiotic therapy can prolong the duration of excretion of Salmonella cells, it is only
recommended in cases of Salmonella gastroenteritis for the highly vulnerable: infants, the
elderly and immunocompromised individuals. In contrast, due to its severity, enteric fever is
always immediately treated with antibiotics.
4.3.4 Virulence factors of Salmonella serovars
In summary, Salmonella’s pathogenicity is due to its ability to enter the body through phagocytic intestinal cells, such as antigen‐sampling M cells and dendritic cells, as well as non‐
phagocytic host cells. A major determinant of this invasiveness is a type III secretion system
(T3SS), which is essentially a molecular syringe that injects virulence effector proteins directly
into target host cells. These effector proteins cooperatively hijack the multiple host cell signalling pathways to induce pathogen internalisation. Salmonella cells also use several other T3SS‐
independent mechanisms to gain entry into host cells.
Salmonella have over 200 virulence factors that are encoded in at least five pathogenicity
islands (PAIs). They also have a virulence plasmid and many pathogenicity islets (see
Section 2.5.2 and Table 2.2). Like many other enteric pathogens Salmonella serovars invade
mammalian cells of the lower intestinal tract by inducing actin rearrangements that result in
the formation of pseudopods that engulf the bacteria. The role of adhesins is uncertain, but
invasion of epithelial cells by Salmonella serovars most likely occurs following adhesion to
microvilli via adhesins, such as mannose‐specific type 1 fimbriae. Salmonella invades intestinal epithelial cells. Although these cells are not phagocytic, Salmonella use a T3SS to inject
several bacterial factors into the host cell that affect a number of host cell processes (Ly and
Casanova 2007). Actin rearrangement occurs underneath the adherent Salmonella cell causing
a change in the appearance of the surface of the host cell that resembles a droplet splash. Next
the membrane ruffling results in macropinocytosis, and the engulfment of the bacterium
inside an endocytic vesicle. The effect of the bacteria on host cells is called ruffling because of
the appearance of the deformed host cell membrane (Figure 4.2).
Bacterial foodborne pathogens
Membrane
ruffling
155
Organisms in
phagosome
Uptake into
vacuole
Figure 4.2 Salmonella invasion of the gut wall.
Invasion is enhanced under anaerobic conditions, when the cells are in the stationary phase
and when osmolarity is high. Salmonella serovars have two T3SSs: one for invasion and one for
intracellular survival. A large number of gene loci are required for invasion and many are
located on SPI‐1 (Table 2.2). One of the genes (inv) encodes for the formation of surface structures produced when the bacterium adheres to the host cell. After the bacteria are engulfed in
a vesicle, the host cell surface and actin filament organisation return to normal. Salmonella
avoids lysosomal fusion due to a T3SS that causes the vacuole to diverge from the standard
pathway that would deliver it to a lysosome. The Salmonella remain within the vacuole and
multiply. The vesicles may coalesce and this may be followed by further bacterial multiplication, which may lead to host cell death. The organism can survive in the phagocytes due to its
resistance to oxidative bursts through the production of catalase and superoxide dismutase
and resistance to defensins (toxic peptides) due to produces from the phoP/phoQ operon.
4.3.5 Whole‐genome analysis
Although an organism is identified according to key features, the comparison of bacterial
genomes has revealed that considerable diversity in genes exist within a bacterial ‘species’.
Within the two Salmonella species, there are many clones that are specialised according to
their host and also the disease that they cause. The variation in genes between clones causes
the major genetic diversity within a bacterial species. It is recognised that there can be up to
a 20% difference in the DNA between two strains of the same species. Genes found in most
strains can be regarded as the core set of genes, which characterise the species. In contrast to
the gain in genes through horizontal (or lateral) gene transfer, genes that become deleterious
or are no longer of benefit will be lost following an accumulation of mutations and
deletions.
The ability of Salmonella to cause disease is attributed to specific virulence factors. The
genes encoding these virulence factors are often found, clustered together at specific loci on
large (>30 kb) chromosomal regions or plasmids as PAIs (Table 2.2). Salmonella serovars may
also encode for at least five PAIs (Section 2.5.2). PAIs have been a major area of pathogenicity
research, and in Salmonella are particularly of interest with respect to the virulence and adaptation of the species. Because the G + C ratio of PAIs are often distinct from the rest of the
bacterial DNA G + C ratio, it has been proposed that they may have been acquired in the past
by HGT from other bacterial species. In Salmonella, the distribution of PAIs between serovars
suggests that their acquisition by HGT was essential in the organism becoming a pathogen.
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SPI‐1 is associated with the T3SS and encodes for ~25 genes (Table 2.2). It contains genes
required for the invasion of epithelial cells and multiplying in the lymphoid tissue. As this is
absent in E. coli, it could have enabled Salmonella to occupy different niches to its close relative. Further gene acquisition, such as SPI‐2, enabled Salmonella enterica serovars to survive
macrophage uptake to spread to the bloodstream. SPI‐2 is found in S. enterica serovars and
not S. bongori (non‐foodborne pathogen). The acquisition of SPI‐3 and SPI‐4 resulted in the
ability to multiply within macrophages. SPI‐3 also contains open reading frames similar to the
ToxR regulatory protein of V. cholerae, and another that is similar to an adhesion of
enteropathogenic E. coli (EPEC). SPI‐5 encodes the genes for enteropathogenicity.
This illustrates an application of genomics to the study of bacterial virulence, and pathogen
evolution. These genetic regions usually have a different %GC content of DNA, often have
repetitive ends and are often inserted into or near tRNA genes. They can be located on bacterial
genomes by looking at a plot of the %GC content and noting regions of atypical values.
As covered in more detail in Section 4.3.2, different Salmonella serovars can have very different
host ranges and diseases that they cause. Therefore it is of interest to compare the complete
genomes of Salmonella serovars. Using WebAct to visualise an alignment of S. Typhimurium,
S. Typhi and S. Paratyphi genomes, one can see large regions that have been inverted, as
indicated by the blue triangles in Plate 3. They are all Salmonella, and possess nearly the same
genes, but they are in a different order in different serovars. At a greater resolution one can
determine the regions where prophage DNA remnants can be located, as well as antibiotic
resistance factors.
4.3.6 Sources and control of Salmonella serovars
Ninety‐six percent of salmonellosis cases are estimated to be caused by a wide range of contaminated foods (see Table 1.2). This includes raw meats, raw or undercooked products of poultry,
eggs, products containing raw eggs, milk and dairy products, fish, shrimp, frog legs, yeast, coconut, sauces and salad dressing, cake mixes, cream‐filled desserts and toppings, dried gelatin,
peanut butter, cocoa and chocolate. In addition, fruits and vegetables (sprouts, tomatoes, fruits,
peanuts and spinach) are becoming important sources of salmonellosis. Contamination of the
foods is through poor temperature control, handling practices or cross‐contamination of processed foods from raw ingredients. The organism multiplies on the food to an ‘infectious’ dose.
In addition the organism can be transferred by person‐to‐person contact or from contact with
pets such as cats, dogs, rodents, reptiles or amphibians (Pires et al. 2014).
Salmonella Enteritidis outbreaks in humans are often linked to contaminated foodstuffs
produced by the poultry industry (Harker et al. 2014; Lane et al. 2014). Although the incidence
of S. Enteritidis infections in the UK and in Europe has decreased significantly following the
implementation of a vaccination programme and other control measures in chicken flocks
(Poirier et al. 2008), outbreaks associated with contaminated eggs continue to occur (Hugas
and Beloeil 2014).
Most Salmonella infections are thought to be associated with foodborne transmission from
poultry meat and dairy products. Nevertheless outbreaks of salmonellosis have been linked to
a diversity of fresh produce, fruits and vegetables. Salmonella have been isolated from many
types of raw fruits and vegetables including bean sprouts, melons, unpasteurised orange juice,
apple juice and tomatoes (Bidol et al. 2007). The bacterium can grow on the surface of alfalfa
sprouts, tomatoes and possible other raw fruits and vegetables. Therefore it is essential that
hygienic practices are observed during handling to reduce produce contamination. Salmonella
Bacterial foodborne pathogens
157
can contaminate cocoa pods during harvesting and fermentation. The pods are lightly roasted
(60–80°C) to make chocolate. Salmonella can survive due to the minimal processing, low water
activity and high fat content, which help to protect the organism during transit through the
stomach.
A wide range of accredited methods for detecting Salmonella are available. These usually
comprise the three stages: pre‐enrichment, enrichment and selection (Mansfield and Forsythe
2000a). Hence the organism is not enumerated in the foodstuff, but a detection limit of ‘less
than one Salmonella cell in 25 g of food product’ is set. For more detail, see Section 6.7.2.
Salmonella are zoonotic bacteria with birds as one of the reservoirs. In addition to contaminating egg shells, S. Enteritidis can be isolated from the egg yolk due to transovarian infection.
The organism travels up the anus from the environment and colonises the ovaries. Subsequently,
S. Enteritidis infects the egg before the protective shell is formed. An infected unfertilised egg
will result contaminated egg products, whereas an unfertilised egg results in a chronically ill
chick with systemic infection and hence a contaminated carcass. A risk assessment conducted
by the Food and Agriculture Organisation of the United Nations (FAO) and the World Health
Organisation (WHO) (2002) noted that the human incidence of salmonellosis transmitted
through eggs and poultry meat appeared to have a linear relationship to the observed
Salmonella prevalence in poultry. This means that, when reducing the prevalence of Salmonella
in poultry by 50%, then the incidence of salmonellosis in humans should also fall by 50%,
assuming all other conditions stay constant.
Control:
• heat treatment (pasteurisation, sterilisation);
• refrigeration;
• prevention of cross‐contamination;
• good personal hygiene;
• effective sewage and water treatment processes.
Control of salmonellae is achieved through a number of requirements: the requirement for the
absence (<1 Salmonella cell in 25 g food) in ready‐to‐eat (RTE) foods, temperature control
during storage and a processing step (i.e. cooking) to eliminate salmonellae from raw meats.
After rising in the early 1980s, the number of Salmonella cases has decreased in some
countries (see Figure 1.4). In the UK, there was a notable decline of S. Enteritidis cases that
coincided with the introduction of vaccination of egg‐laying hens against this serovar. It will
be important to ensure other serovars with similar traits do not replace S. Enteritidis in the
poultry population. In fact, S. Enteritidis replaced S. Typhimurium in the 1980s.
Examples of Salmonella risk assessments are given in Section 11.1.
4.3.7 Salmonella serovar outbreaks
Salmonella causes a large number of outbreaks worldwide. Table 11.3 lists a number of
Salmonella outbreaks along with size of population exposed, dose ingested and number of
cases. This section gives details of a few such outbreaks, and Section 14.4 considers more
recent outbreaks that were investigated based on the analysis of the isolates’ genomes.
US Salmonella outbreak associated with ground meat, 2004 (Cronquist et al. 2006)
In September 2004, the New Mexico Department of Health received reports from the New
Mexico Scientific Laboratory Division that eight S. Typhimurium isolates had indistinguishable pulsed‐field gel electrophoresis (PFGE) patterns using both XbaI and BlnI restriction
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enzymes (see Section 6.5.4 for explanation of the typing method). The patients were linked by
place (three New Mexico counties) and time as the onsets of illness were between 18 and 19
August. Subsequently, a case was defined as a person with a S. Typhimurium infection with a
PFGE pattern that was indistinguishable from the outbreak profile.
The microbiological analysis comprising the Salmonella PulseNet database collated a
further 31 indistinguishable patient isolates of S. Typhimurium. These were from nine
states, with an illness onset between 11 August and 2 October 2004. The states were
Colorado, Kansas, Minnesota, New Jersey, New Mexico, New York, Ohio, Tennessee,
Wisconsin and the District of Columbia. One case‐patient had leftover frozen ground
beef. It was analysed for Salmonella, and S. Typhimurium with a PFGE pattern indistinguishable from the outbreak profile was recovered.
For epidemiological analysis, questionnaires were used to collect detailed information on
patient’s history of food consumption before becoming ill. Several patients reported eating
ground beef from the same national chain of supermarkets and therefore this was suspected as
the source of the outbreak. A case–control study was undertaken with 26 of the 31 case‐patients
and 46 controls. The controls were identified by sequential telephone digit dialling. They had
no reported gastrointestinal illness within 7 days before onset of illness of the cases and were
matched with cases by age group (2–10, 11–17, 18–60 and >60 years). Details were collected
for ground beef consumption, brand, location and date of purchase.
Symptoms reported by the 26 cases included diarrhoea (100%), abdominal cramps (92%),
fever (92%), vomiting (65%) and bloody diarrhoea (46%). The median duration of illness was
7.5 days with a range of 2–30 days. A third (35%) of the patients were hospitalised, and there
were no deaths. Of the 21 cases who ate ground beef, 15 (71%) purchased the beef from a
national chain of supermarkets. This compared with nine (24%) of the controls.
The source of ground beef and its production date were determined by using the purchase
receipts, etc. from the cases. The traceback showed that the ground beef had been packaged at
three processing plants, and that one supplier was common to all three plants. The United
States Department of Agriculture’s (USDA) Food Safety and Inspection Service (FSIS;
Section 13.1.2) reviewed the processing plants and concluded that they conformed to current
FSIS production guidelines and so no products were recalled.
US multi‐state outbreaks of S. Tennessee and S. Typhimurium infections associated with peanut
butter and peanut butter‐containing products, 2006–2007 and 2008–2009 (CDC 2007; Medus
et al. 2009)
Beginning in November 2008, there was a small (13 isolates) and a highly dispersed (12 states)
cluster of S. Typhimurium isolates, which consisted of two pulsotypes (PFGE banding pattern
cluster). The first cluster had a unique XbaI restriction pattern and an uncommon BlnI restriction pattern. The second cluster had two closely related XbaI patterns that were similar to the
first cluster and a BlnI pattern that was indistinguishable from the first cluster. Isolates from
both clusters were indistinguishable by multiple‐locus variable number tandem repeat analysis
(MLVA) and were phage type 3. They were also susceptible to the normal range of antimicrobial agents. Subsequently, the isolates were grouped together as a single outbreak strain. The
profile did not occur in the National VetNet database, which contains Salmonella isolates from
raw meat and poultry products.
The illnesses continued to April 2009, when the last CDC report on the outbreak was published. In total there were 714 reported illnesses, 171 of whom were hospitalised and 9 died. A
Bacterial foodborne pathogens
159
case was defined as a laboratory‐confirmed infection of S. Typhimurium with the outbreak
strain in a person with illness onset date (or, if that date was not known, with date of isolation
of Salmonella) on or after 1 September 2008. The median age of patients was 16 years, with an
age range of <1 to 98 years; 21% were aged <5 years; and 15% were aged >59 years. A median
time between the day the illness began to the date the PFGE pattern was uploaded to PulseNet
was 16 days.
The initial epidemiologic investigation used a questionnaire with approximately 300
food items. This indicated a possible association with institutional settings, although
non‐institutionalised patients often reported the consumption of peanut butter of multiple
brands. In the initial investigation, amongst the most frequently reported food exposures in
the 7 days before illness began, 86% of patients interviewed reported they were likely to
have eaten chicken and 77% were likely to have eaten peanut butter. By comparison, the
frequencies in the general public of eating these items were 85% for chicken and 59% for
peanut butter in a 2006–2007 FoodNet food consumption survey.
By December (2008), it was realised that some cases lived or ate meals in one of at least three
institutions (two long‐term care facilities and one elementary school). A review of associated
menus and invoices revealed that the institutions had a common food distributor in North
Dakota, and the only food common to the three institutions was a particular creamy peanut
butter. By January (2009), six additional cases in six other institutions were identified and each
of these had the same peanut butter. An open container of the specific peanut butter was collected from one of the institutions, a long‐term care facility. This contained a strain of S.
Typhimurium that matched the outbreak strain.
Additionally, in January (2009) investigators recovered S. Tennessee from an unopened can
of peanut butter from a distributor, which had a PFGE pattern that was indistinguishable from
a multi‐state outbreak in 2006–2007 caused by contaminated peanut butter (CDC 2007). This
outbreak had caused 628 infections, The median age of patients was 52 years, but ranged
between 2 months and 95 years, 73% of which were female. Symptoms included diarrhoea
(72%), abdominal cramps (65%), fever (43%) and dysuria (45%). Symptom onset dates were
over 9 months, from 1 August 2006 to 23 April 2007.
Interviews with cases of the S. Typhimurium outbreak revealed that many of them did not
eat peanut butter in institutions, but had eaten peanut butter‐containing products including
crackers. Sequential case–control studies showed significant associations between illness and
consumption of any peanut butter (matched odds ratio = 2.53), and specific brands of pre‐
packaged peanut butter crackers (matched odds ratio = 12.25), but no association with national
brand jarred peanut butter sold in grocery stores. Illness also was associated with eating any of
a group of previously frozen chicken products. Illness was not associated with eating roasted
peanuts or national brands of jarred peanut butter sold in grocery stores.
Subsequent epidemiologic and microbiological analysis indicated that peanut butter
and peanut paste produced at one plant were the probable source of the outbreak. Food
and Drug Administration (FDA) investigators reported that the specific production facility produced peanut butter, peanut paste and other peanut products, which were sold to
many food companies for use as an ingredient in peanut butter‐containing foods; these
peanut butter‐containing products are widely distributed in the United States and also are
distributed in at least 23 other countries and non‐US territories. There were at least 431
peanut butter‐containing products recalled by 54 companies. Therefore, the outbreak was
associated with peanut butter and peanut butter‐containing products that were sold to
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institutional settings, and peanut paste, which was sold to a number of food companies for
use as an ingredient. Implicated peanut products were sold widely throughout the USA, 23
countries and non‐US territories. Despite numerous product recalls, the wide dispersement of the peanut products, the long shelf life of these products and the multiple labellings made it impossible to assure that all sources of these contaminated products had been
totally eliminated. Peanut prices and demand for peanut‐based products were little
affected by this outbreak.
This outbreak highlights the complexities of investigating outbreaks that are due to a contaminated ingredient which is used in many products and distributed by many companies. It also, in
2008, demonstrated the relevance of subtyping Salmonella isolates in order to distinguish
outbreak‐related strains from others in circulation. Additionally it showed the same PFGE
profile of S. Tennessee from an earlier outbreak (2006–2007) was still in peanut butter products.
Although the cause of the contamination is uncertain, it is initially surprising that Salmonella
serovars would survive in the peanuts, which would have a roasting step, and therefore could be
assumed to be a kill step. However, Salmonella can persist for long periods of time in high‐fat,
low‐water‐activity foods such as peanut butter, and the food matrix can enable the Salmonella to
withstand temperatures as high as 90°C (194°F) for 50 minutes. Typically, peanuts for peanut butter are roasted at ~180°C (350°F), which should be sufficient to kill Salmonella in a short time
period. However, some temperatures used in processing peanut butter or paste in other products
might be inadequate to eliminate any Salmonella that have entered the product after the initial
roasting step. It is therefore important that appropriate laboratory tests are undertaken to ensure
any Salmonella are killed and that re‐contamination cannot occur, and any hazard analysis critical control point (HACCP) plan is revisited if there are changes in processing procedures.
S. Poona 907 Ill, 204 hospitalised and 6 dead, cucumbers, USA, 2015
One of the most severe outbreaks of Salmonella in the USA lasted from September 2015 to
March 2016. In September (2015) the CDC announced an outbreak of S. Poona linked to consumption of cucumbers imported from Mexico. This is a very unusual cause of infection, and
given its rarity the serovar is often used as a quality control (QC) positive‐control strain for
Salmonella detection methods.
There was a total of 907 cases, from 40 states, infected with the outbreak strain of S. Poona.
Of these, 204 were hospitalised and six deaths were reported, though two were not considered
to be due to Salmonella infection. Epidemiological and microbiological evidence, along with
traceback investigations, identified imported cucumbers from Mexico and distributed by one
company as the likely source of the outbreak.
Note: Salmonella outbreaks due to cucumber are infrequent. However when they occur there are
a large number of cases. There was a multi‐state outbreak in the US due to S. Neport in 2014 with
275 cases. In 2017–2018 there was another outbreak in Europe (five countries) due to S. Agona that
caused 147 cases, these were primarily in UK (129 cases) (EFSA 2018).
4.4 Pathogenic E. coli
4.4.1 General description
Escherichia coli is a Gram‐negative, non‐spore‐forming, facultative anaerobe and is a genus in
the Enterobacteriaceae. Escherichia coli strains can be serotyped according to their O and H
Bacterial foodborne pathogens
161
antigens, of which there are in the order of 180 O antigens and 56 H antigens. This is a convenient means of identifying pathovars. With respect to food poisoning, the serotyping of
Shiga toxin‐producing E. coli (STEC) strains (which are not all O157) can help support epidemiological analysis to reveal the routes, sources, and prevalence of strains during outbreak
investigations as well as in surveillance studies.
4.4.2 E. coli pathovars
Pathogenic strains of E. coli (pathovars) are grouped according to their clinical symptoms and
mechanisms of pathogenesis. There are several recognised groups, which vary in their incubation periods and duration of illness (Tables 1.3, 1.4 and 4.5). There is also a considerable range
of virulence. For example, small doses (10–100 cells) of E. coli O157:H7 can cause severe
illness, whereas ETEC requires an estimated 108–1010 ingested cells to cause a mild illness. The
six recognised pathogenic groups are:
• Enterohaemorrhagic E. coli (EHEC), which causes bloody diarrhoea, haemorrhagic colitis
(HC), HUS and thrombic thrombocytopenia purpura. This group includes the STEC (also
known as verotoxigenic E. coli, VTEC) serotypes O157:H7, O26:H11 and O111:NM – the
former being the main serotype studied in this group.
• ETEC is commonly known as traveller’s diarrhoea. ETEC cause watery diarrhoea (rice
water‐like) and a low‐grade fever. The organism colonises the proximal small intestine.
• EPEC, which causes vomiting, fever and diarrhoea that is watery with mucus but no blood.
The organism colonises the microvilli over the entire intestine to produce the characteristic
‘attaching and effacing’ (A/E) lesion in the brush border microvillus membrane.
Box 4.3
Organism
E. coli O157:H7
Onset of symptoms
1–2 days
Food source
Beef particularly ground beef, poultry, apple cider, raw milk, vegetables, cantaloupe, hot dogs,
mayonnaise, salad bar items.
Acute symptoms and chronic complications
Abdominal pain, diarrhoea, fever, malaise.
Chronic symptoms
Haemolytic‐uraemic syndrome (HUS), chronic kidney disease, thrombotic thrombocytopenic
purpura.
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Table 4.5 Pathogenic strains of Escherichia coli.
Group
Serotypes
Enterotoxigenic (ETEC)
O6, O8, O15, O20, O27, O63,
O78, O80, O85, O115, O128,
O139, O148, O153, O159,
O167
Enteropathogenic
(EPEC)
Adhesion and
invasion characters
Toxins
Disease symptoms
Adhere uniformly
but do not invade
Heat‐labile (LT). Heat‐stable
(ST). LT is similar to cholera
toxin and acts on mucosal cells
Cholera‐like diarrhoea but generally less severe
O18, O44, O55, O86, O111,
O112, O114, O119, O125,
O126, O127, O128, O142
Adhere in clumps.
Invade host cells,
attach and efface
Not apparent
Infantile diarrhoea, vomiting
Enteroinvasive (EIEC)
O124, O143, O152
Invade cells of
colon. Spread
laterally to adjacent
cells
No Shiga‐like toxin has been
detected
Cell‐to‐cell spread and disease is similar to
dysentery
Enterohaemorrhagic
(EHEC)
O6, O26, O46, O48, O91,O98,
O11, O112, O146, O157,
O165
Adhere tightly.
Attach and efface
host cells. Invade
Verocytotoxic Shiga‐like toxin
Bloody diarrhoea. Haemorrhagic colitis. May
progress to haemolytic‐uraemic syndrome (HUS)
and thrombotic thrombocytopenic purpura (TTP)
Enteroaggregative
(EAEC)
Wide range of serotypes,
recent outbreaks O62, O73,
O134
Adhere in clumps
but do not invade
ST‐like toxin. Haemolysin.
Verocytotoxin reported in some
strains
Diarrhoea. Some strains have been reported to
cause HUS
Source: Information kindly supplied by Oxoid, Thermo Fisher Scientific, Basingstoke, UK.
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163
Box 4.4
Organisms
Enterotoxigenic E. coli (ETEC), enteropathogenic (EPEC), enteroinvasive E. coli (EIEC)
Onset of symptoms
ETEC: 24 hours
EPEC: Not known
EIEC: 12–72 hours
Food source
ETEC: foods contaminated by human sewage or infected food handlers.
EPEC: raw chicken and beef, food contaminated by faeces or contaminated water.
EIEC: food contaminated by human faeces or contaminated water, hamburger meat, unpasteurised
milk.
Acute symptoms and chronic complications
ETEC: watery diarrhoea, abdominal cramps, fever, nausea, malaise.
EPEC: watery or bloody diarrhoea.
EIEC: abdominal cramps, vomiting, fever, chills, generalised malaise, HUS.
• Enteroaggregative E. coli (EAEC) causes persistent watery diarrhoea especially in children,
lasting more than 14 days. The EAEC align themselves in parallel rows on either tissue cells
or glass. This aggregation has been described as ‘stacked brick‐like’. They produce a heat‐
labile toxin antigenically related to haemolysin but not haemolytic and plasmid‐encoded
heat‐stable toxin (EAST1) unrelated to the heat‐stable enterotoxin of ETEC. It is thought
that EAEC adhere to the intestinal mucosa and synthesize the enterotoxins and cytotoxins,
which results in secretory diarrhoea and mucosal damage. EAEC is associated with malnutrition and growth retardation in the absence of diarrhoea.
• EIEC causes a fever and profuse diarrhoea containing mucus and streaks of blood. The
organism colonises the colon and carries a 120–140 mD plasmid known as the invasiveness
plasmid, which carries all the genes necessary for virulence.
• Diffusely adherent E. coli (DAEC) have been associated with diarrhoea in some studies but
not consistently.
4.4.3 Infections caused by E. coli pathovars
EHEC were first described in 1970s and recognised as a disease of humans in 1982. The bacteria harbour plasmids of various sizes, the most common being 75–100 kb.
E. coli O157:H7 was first described in 1977. However it was not until 1993, following a large
outbreak with more than 700 cases infected by eating contaminated fast‐food hamburgers, that
it was recognised as a major food safety issue (CDC 1993). Further outbreaks in Japan,
Washington and Scotland (Table 1.8) confirmed the severity of infection and the need for
additional food safety controls.
In 1996, in Japan the E. coli O157:H7 outbreak resulted in ~ 9523 illnesses in the city of
Sakai, and three deaths. The source was contaminated school lunches. Following the outbreak,
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the central government compiled a sanitation management manual for cooking facilities that
supply meals to large numbers of people. The USDA has established a ‘zero‐tolerance’ policy
for E. coli O157:H7 on ground beef. This policy has not resolved the problem, as >70 000 cases
of E. coli O157:H7 infection (food and non‐food related) occur annually in the United States.
It is estimated that globally STEC causes 2 801 000 acute illnesses annually and leads to 3890
cases of HUS, 270 cases of end‐stage renal disease and 230 deaths (Majowicz et al. 2014).
Compared with other pathogens with a foodborne transmission component, STEC appears to
cause more cases than alveolar echinococcosis each year, but less than typhoid fever, foodborne trematodes and non‐typhoidal salmonellosis.
The EHEC belong to many serogroups that can cause very severe forms of food poisoning
resulting in death. It has been postulated that E. coli O157:H7 evolved from E. coli O55 following
the acquisition of toxin genes from Sh. dysenteriae via a bacteriophage, and that the newly
emerging pathogen arrived in Europe from South America (Coghlan 1998) (Figure 4.8). The
reported incidence and serotype varies from country to country.
The incubation period for EHEC diarrhoea is usually 3–4 days, although incubation times
can be as long as 5–8 days or as short as 1–2 days where the patient initially develops diarrhoea,
accompanied by abdominal pain, which, in most cases, aggravates to bloody diarrhoea. The
use of antibiotics is not advised, due to the increased risk of HUS. The risk of developing HUS
is variable and depends on host‐related factors (demographics, immunity, lifestyle) and bacterial factors (serotype, toxin stx type, virulence factors) and exposure dose (Karmali 2017).
Post‐HUS sequelae include chronic renal complications, diabetes mellitus, neurological disorders, colon stenosis, hypertension, urinary abnormalities and bile stones.
The most well studied EHEC serotype is E. coli O157:H7, which predominates in North
America, Japan and the UK, whereas in Central Europe and Australia serotypes O26:H11 and
O111:NM dominate. The ‘O157’ and ‘H7’ refer to the serotyping of the strain’s O and H antigens, respectively (Chapter 2). These are two distinct genetic lineages; see Section 4.4.5 and
Figure 4.10. Although EHEC strains cause dysentery similar to that caused by Shigella species,
they do not invade mucosal cells as readily as Shigella strains. The infectious dose of E. coli
O157:H7 is considered low and it is estimated that less than 100 cells are required to develop
the pathogenesis. The low infectious dose is probably due to several reasons, amongst which
are that E. coli O157:H7 is more acid tolerant than other E. coli strains, and therefore survives
the stomach acidity, and that its virulence is influenced by the rest of the intestinal flora by
quorum sensing (Castro et al. 2017).
Escherichia coli O157:H7 differs from the majority of E. coli strains in that it does not grow
or grows poorly at 44°C and does not ferment sorbitol or produce β‐glucuronidase. The growth
of E. coli O157:H7 in the human intestine produces a large quantity of toxin(s) that cause
severe damage to the lining of the intestine and other organs of the body (Figure 4.3). These
Shiga‐like toxins (SLTs), are very similar, if not identical, to the toxins produced by Sh. dysenteriae. These were formerly referred to as verotoxin. Strains producing Shiga toxins were initially recognised by the cytotoxicity towards vero cells (green monkey kidney cell line) and
subsequently the term ‘verotoxigenic E. coli’ or VTEC arose. However, since the purified and
sequenced verotoxin has been found to be nearly identical to Shiga toxin, the organisms are
more often referred to as STEC. The phage‐encoded toxin consists of one A subunit and five
identical B subunits (cf. Figure 2.10). It should be noted that there are E. coli serotypes other
than O157 that produce Shiga toxins, and conversely, not all E. coli O157 produce Shiga
toxins.
Bacterial foodborne pathogens
Intestinal
epithelial
cell
Attach and
efface cells
Loss of
microvilli
165
Adherence
and some
invasion
Figure 4.3 Route of infection of pathogenic Escherichia coli: Enterohaemorrhagic E. coli (EHEC).
EHEC infections in healthy adults cause thrombic thrombocytopenic purpura (TTP) where
blood platelets surround internal organs leading to kidney damage and central nervous system
damage. The most vulnerable of the population, children and the elderly, however develop
HC, which may lead to HUS. HC is a less severe form of E. coli O157:H7 infection than HUS.
The first symptom of HC is the sudden onset of severe crampy abdominal pains. About
24 hours later non‐bloody (watery) diarrhoea starts. Some cases have a fever of short duration.
Vomiting occurs in about half of the patients during the period of non‐bloody diarrhoea and/
or other times in the illness. After 1 or 2 days, the diarrhoea becomes bloody and the patient
experiences increased abdominal pain. This usually lasts between 4 and 10 days. In severe
cases, faecal specimens are described as ‘all blood and no stool’. In most patients, the bloody
diarrhoea resolves with no long‐term impairment. Unfortunately 2–7% patients (up to 30% in
certain outbreaks) will progress to HUS and subsequent complications.
In HUS the patient suffers from bloody diarrhoea, haemolytic anaemia, kidney disorder,
renal failure and requires dialysis and blood transfusions. Central nervous disease may develop,
which can lead to seizures, coma and death. The mortality rate is 3–17%. Acute renal failure is
the leading cause of death in children, whereas thrombocytopenia is the leading cause of death
in adults.
The SLTs are specific for the glycosphingolipid globotriaosylceramide (Gb3), which is present on renal endothelial cells. Since Gb3 is found in the glomeruli of infants under 2 years of
age but not in the glomeruli of adults, the presence of Gb3 in the paediatric renal glomerulus
may be a risk factor for development of HUS.
According to the FDA of the United States, the infectious dose for E. coli O157:H7 is
unknown. However, a compilation of outbreak data indicates that it may be as low as 10 organisms. The data show that it takes a very low number of micro‐organisms to cause illness in
young children, the elderly and immune‐compromised people.
Most reported outbreaks of EHEC infection have been caused by O157:H7 strains. This suggests that this serotype is more virulent or more transmissible than other serotypes. However,
other serotypes of EHEC have been implicated in outbreaks, and the incidence of disease due
to non‐O157:H7 serotypes seems to be rising. More than 50 of these serotypes have been
associated with bloody diarrhoea or HUS in humans. The most common non‐O157:H7 serotypes associated with human disease include: O26:H11, O103:H2, O111:NM and O113:H21.
Outbreaks due to these organisms have been reported in Japan, Germany, Italy, Australia, the
Czech Republic and the United States. These outbreaks have involved 5–234 people, and for
most of them, the source of infection could not be determined. In many countries such as
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The microbiology of safe food
Adherence
no invasion
LT and ST
produced
Figure 4.4 Enterotoxigenic Escherichia coli (ETEC) infection of gut mucosal cells.
Chile, Argentina and Australia, non‐O157:H7 serotypes have been found to be responsible for
the majority of HUS cases. Non‐bloody diarrhoea has also been associated with some of these
non‐O157:H7 serotypes.
Infants are particularly prone to EPEC infections. The EPEC cause diarrhoea, vomiting,
fever and diarrhoea that is watery with mucus but no blood.
The low E. coli O157:H7 infectious dose (10 cells or less) could be due to several factors:
greater acid tolerance resulting in greater survival through the stomach, quorum sensing and
its virulence factors are very potent.
ETEC strains resemble V. cholerae in that they adhere to the small intestinal mucosa and
produce symptoms not by invading the mucosa but by producing toxins that act on mucosal
cells to cause diarrhoea (Figures 2.3 and 4.4). Unlike E. coli O157:H7, which can cause severe
illness even if low numbers of cells (10 or less) are ingested, ETEC require an estimated 108–109
cells to cause relatively mild symptoms. ETEC strains produce two types of enterotoxin: a
cholera‐like toxin called heat‐labile toxin and a second diarrhoeal toxin called heat‐stable
toxin. Heat‐stable being defined as retaining activity after heat treatment at 100°C for
30 minutes.
There are two main types of heat‐labile toxin: LT‐I and LT‐II. LT‐I shares about 75% amino
acid sequence identity with cholera toxin and has an AB5 structure. The A subunit catalyses the
ADP‐ribosylation of Gs, which raises host cell cAMP levels, identical to the cholera toxin mode
of action. The B subunits of LT‐I interact with the same receptor as cholera toxin (GM1).
However LT‐I is not excreted (as per cholera toxin) but is localised in the periplasm. The toxin
leaks out of the organism on exposure to bile acids and low iron concentrations (as would
occur in the small intestines).
Heat‐stable toxin is a family of small (~2 kDa) toxins that can be divided into two groups:
methanol soluble (STa) and methanol insoluble (STb). STa causes an increase in cGMP (not
cAMP) level in the host cell cytoplasm, which leads to fluid loss. cGMP, like cAMP, is an
important signalling molecule in eucaryotic cells, and changes in cGMP affect a number of
cellular processes, including activities of ion pumps. LT‐I and STa are encoded on plasmids.
The EAEC resemble ETEC strains in that they bind to small intestinal cells, are not invasive
and cause no obvious histological changes in intestinal cells to which they adhere (Figure 4.5).
They differ from ETEC strains primarily in that they do not adhere uniformly over the surface
of the intestinal mucosa but tend to clump in small aggregates. EAEC strains produce a ST‐like
toxin (EAST) and a haemolysin‐like toxin (120 kDa in size). Some strains are reported to produce a Shiga‐like (verocytotoxin) toxin.
Bacterial foodborne pathogens
167
EPEC do not produce any enterotoxins or cytotoxins. They invade, attach and efface epithelial cells. This induces a characteristic A/E lesion (Figure 4.6) in epithelial cells in which microvilli are lost and the underlying cell membrane is raised to form a pedestal that can extend
outward for up to 10 μm. This phenomenon is the result of extensive rearrangement of host cell
actin in the vicinity of the adherent bacteria that results in formation of a cuplike pedestal
structure under the bacteria. The genes encoding for this virulence are encoded on the locus
of enterocyte effacement (LEE) a PAI (Table 2.2; Section 2.5.2). This island encodes for a T3SS,
intimin intestinal colonisation factor and the translocation intimin receptor protein. Contact
with epithelial cells results in the secretion of a number of proteins including EspA (25 kDa)
and EspB (37 kDa), which subsequently trigger a series of responses in the host cell. These
responses include activation of signal transduction pathways, cell depolarisation and the binding of the outer membrane protein intimin (94 kDa). Intimin is encoded by the gene eae.
Intimin probably binds to Tir (translocated intimin receptor) a bacterial protein (78 kDa) that
is secreted by EPEC and binds to the host cell. The characteristic diarrhoea of EPEC infections
is possibly due to an induced efflux of chloride ions due to activation of protein kinase C. The
loss of microvilli would contribute due to the decreased absorption ability (Figures 2.1 and
2.2). The T3SS is used to avoid being engulfed by the host cell and blocks phagocytosis enabling the bacterium to remain attached to the host cell surface.
EIEC strains cause a disease that is indistinguishable at the symptomatic level from the dysentery caused by Shigella species. EIEC strains actively invade colonic cells and spread laterally
Small
intestinal
mucosal cell
Adhere,
do not invade
Adhere in
clumps
ST-like toxins
produces
Figure 4.5 Enteroaggregative Escherichia coli (EAEC) infection of gut mucosal cells.
Intestinal
epithelial
cell
Attach and
efface cells
Loss of
microvilli
Pedestal
formation
Toxin
production
Figure 4.6 Enteropathogenic Escherichia coli (EPEC) infection of gut mucosal cells.
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The microbiology of safe food
Lateral
spread
Colonic cell
Invasion
Figure 4.7 Enteroinvasive Escherichia coli (EIEC) infection of gut mucosal cells.
to adjacent cells (Figure 4.7). The steps in invasion and cell‐to‐cell spread appear to be virtually
identical to Shigella species. However, EIEC do not produce Shiga toxin, which may account
for the lack of HUS as a complication of EIEC dysentery.
4.4.4 Virulence factors
EHEC (including STEC) have two major virulence pathways contributing to disease: the Shiga
toxin expression, and the LEE PAI. The latter is a 38‐kb region of DNA that is inserted into the
bacterial chromosome near a tRNA gene. There are 41 genes located on the LEE PAI, which
are divided into five operons: LEE‐1–LEE‐5. Regions 1, 2 and 3 encode the T3SS that translocates
bacterial protein effectors into the enterocyte (see Section 2.1). LEE‐4 contains the EspADB
gene encoding translocating proteins, forming a channel through which T3SS is able to provide proteins to host cells (A/E). The adhesion genes are located in LEE‐5, including Tir, eaeA
for Intimin and cesT for the Tir chaperone (Elliott et al. 2000). Hence the LEE PAI enables the
organism to adhere to the host’s epithelial cells and form a pedestal on the epithelial surface.
Effacement of the microvilli occurs, producing the same type of A/E phenomenon as EPEC
strains, damaging the microvilli (Figure 2.2). These lesions are characterised by effacement of
the brush border microvilli near to the adhering bacteria. Also intimin‐mediated bacterial
attachment to the plasma membrane of the host cell results in bacterial adherence to the host
cell. Tir is transferred from E. coli to the host cell membrane where it acts as an anchor for
intimin, a 94‐kDa bacterial outer membrane protein. Additionally, Tir recruits host cytoskeletal proteins to cause actin accumulation and pedestal formation. Using the T3SS acting both
as a bridge and syringe between the bacterium and host cell, the E. coli can inject a set of proteins with cytotoxic action into the host epithelial cell.
After binding, STEC strains express the Shiga toxins: stx1 (stx1a, stx1c and stx1d) and stx2
(stx2a, stx2b, stx2c, stx2d, stx2e, stx2f and stx2g). stx2 is the main toxin involved in the most
severe cases of the human disease. The Shiga toxin is formed by a subunit A, which exerts toxic
action and inhibits the protein synthesis of cells, and by another five subunits B, which are
responsible for the binding of the toxin to the host cell globotriacylceramide (Gb3) receptor.
The 32‐kDa A subunit is an RNA N‐glycosidase that removes a specific adenine residue from
28S rRNA. The subunit is non‐covalently associated with a pentamer of 7.7‐kDa B subunit.
The pentamer binds the toxin to plasma membrane globotriaosylceramide (Gb3) present on
susceptible mammalian cells. The toxins destroy the intestinal cells of the human colon and
may cause additional damage to the kidneys, pancreas and brain. The dead cells accumulate
and block the kidneys, causing HUS.
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Another pathogenicity factor of EHEC is the production of enterohaemolysin (Ehx), which
is plasmid‐encoded (plasmid pO157). This results in the destruction of red blood cells due to
insertion into the cell cytoplasm and pore production. The subsequent release of iron may be
an important source of iron for the bacterium’s growth.
4.4.5 Whole‐genome analysis
WGS of E. coli strains has greatly facilitated our understanding of pathogen evolution. This can
also be demonstrated by studying E. coli O157:H7, which is thought to have evolved from
ancestral E. coli by stepwise acquisition or loss of virulence and phenotypic traits (Feng et al.
1998; Rump et al. 2011; Kyle et al. 2012; Figure 4.8). It is believed that E. coli O157:H7 evolved
from the EPEC serotype O55:H7 by the stepwise acquisition of (i) a Shiga toxin 1 (stx1)‐encoding bacteriophage in the EPEC O55:H7 progenitor strain; (ii) substitution of the rfb locus
encoding the somatic O55 antigen with that encoding the O157 antigen; (iii) the acquisition of
the pO157 plasmid; (iv) loss of the ability to ferment sorbitol; and (v) loss of the ability to produce β‐glucuronidase, as well as sequence changes in the beta‐glucuronidase gene (uidA) and
fimA and fimH fimbrial genes (Monday et al. 2001; Shaikh et al. 2007). The stx‐encoding phage
is an unstable evolutionary marker, with frequent acquisition and loss occurring in STEC
O55:H7 and all three lineages of STEC O157 throughout their evolutionary history.
Other E. coli groups that have acquired the stx1 phage from bacteriophages and the stx2
phage by HGT, such as E. coli O104:H4 serotype, are involved in foodborne outbreaks.
Meanwhile, MLST phylogenetic analysis shows a parallel evolution of both EPEC and EHEC
O55:H7 SOR+ GUD+
O55:H7 SOR+ GUD+
Stx2
O157:H7 SOR+ GUD+
Stx2
O157:H7 SOR– GUD+
Stx1 + 2
O157:H– SOR+ GUD+
Stx2
O157:H7 SOR– GUD–
Stx1 + 2
Figure 4.8 Model for Escherichia coli O157 evolution. Source: From Feng et al. (1998).
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Non-pathogenic E. coli K12 (MG1655)
585 7.6%
193 2.5%
Uropathogenic E. coli (CFT073)
1623 21.2%
2996 39.2%
514 6.7%
204 2.6%
Total proteins = 7638
2996 (39.2%) in all 3
1346 17.6%
911 (11.9%) in 2 out of 3
3554 (46.5%) in 1 out of 3
Enterohaemorrhagic E. coli O157:H7 (EDL933)
Figure 4.9 Venn diagram of Escherichia coli genomes.
within related serogroups via multiple acquisitions of the LEE, the large virulence plasmids EAF
and pO157, respectively, and stx‐containing lambda‐like bacteriophages in the case of EHEC.
Comparing the sequenced genomes of E. coli O157:H7 with a non‐pathogenic E. coli
reveals some surprising information. As would be expected, both strains share a backbone
of about 4.1 million similarly arranged base pairs. However, the E. coli O157:H7 genome
contains over 1000 additional genes. The Venn diagram in Figure 4.9 shows a simple
comparison of gene distribution amongst E. coli K12 (non‐pathogenic), E. coli O157:H7
and uropathogenic E. coli. Furthermore, the non‐pathogenic E. coli K12 has >500 genes
that are not found in E. coli O157:H7. Possibly the most significant discovery is that the
additional DNA in the pathogenic E. coli is distributed amongst 177 different regions, each
of which are likely to have been inherited through independent events. Also about 18% of
its current genes were obtained by HGT from other species. It has been concluded that
these two E. coli strains diverged about 4.5 million years ago. This followed divergence from
Salmonella about 100 million years ago.
As shown in Figure 4.8 it is believed that E. coli O55:H7 is ancestral to E. coli O157:H7.
‘Primative’ O157 fermented sorbitol, and was β‐glucuronidase positive, and had the Shiga
toxin 2 gene (stx2). This divided into two lineages. The first lineage has the loss of sorbitol
metabolism, the gain of the stx1 gene and later loss of β‐glucuronidase. The second lineage is
composed of SOR+, GUD+, non‐motile strains. The common virulence genes shared by
EHEC serotypes O157:H7 with O26:H11 and O111:H8 show that the acquisition of the same
virulence gene elements has occurred on multiple occasions.
4.4.6 Sources and control of E. coli pathovars
Source:
• Wide range of foods; Table 1.2.
• Ruminants, and in particular cattle, are considered the primary reservoir of EHEC.
• Various other domestic animals and wildlife (sheep, swine, goats and deer).
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171
• Undercooked ground beef products.
• Dry fermented meats, cooked and fermented sausages.
• Other foodborne sources include milk and dairy products (e.g. unpasteurised milk, cheese
from raw milk), fresh produce (e.g. sprouts, salads), drinks (e.g. apple cider/juice) and water.
• Raw or minimally processed fruits and vegetables.
Because cattle lack the receptor for the Shiga toxin, E. coli O157:H7 and related strains can
persist in cattle without causing disease. As many as half of all cattle carry the bacterium at
some time in their lives, and some are ‘super spreaders’ of the organism. The organism enters
the environment from faeces and manure used as fertiliser, and rainwater runoff can spread
the organism to water reservoirs and wells. In addition, faecal contamination of meat during
the slaughtering process can occur. The bacterium can be carried by goats and sheep, as well
as wild ruminants, such as deer. Following ingestion the organism’s tolerance to acidic pH
may explain the low infectious dose (10–100 cells). This acid tolerance also allows it to survive in low‐acid food, and explains the outbreaks traced to unpasteurised apple juice
(pH 3.5).
Cattle appear to be the main reservoir of E. coli O157:H7. Transmission to humans is principally through the consumption of contaminated foods, such as raw or undercooked meat
products and raw milk. Fresh‐pressed apple juice or cider, yogurt, cheese, salad vegetable and
cooked maize have also been implicated (Figure 4.10), as well as faecal contamination of water
and other foods, and cross‐contamination during food preparation. There is evidence of transmission of this pathogen through direct contact between people. Escherichia coli O157:H7 can
be shed in faeces for a median period of 21 days with a range of 5–124 days.
Control measures:
• Effective sewage and water treatment.
• Prevention of cross‐contamination from raw foods and contaminated water.
• Heat treatment: cooking, pasteurisation.
• Good personal hygiene.
Meat
Cow
Cow
Human
Milk
Water
Manure
Water
Fruits and
vegetables
Deer
(Sheep, caribou,
other ungulates)
Main routes of transmission
Figure 4.10 Escherichia coli O157:H7 transmission.
Human
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4.4.7 Outbreaks caused by E. coli pathovars
E. coli O157:H7, hamburgers, USA, 1993
In January 1993, an uncommonly high incidence of HUS occurred amongst children in the
Seattle area of the USA. Their illness was due to E. coli O157:H7 consumed in hamburgers at a
specific restaurant that was part of a chain. In the following weeks, further cases were reported
in three other states (Idaho, California and Nevada), all of whom had eaten at the same restaurant chain. Over 700 people in 4 states became ill, which led to 171 hospitalisations and 4
deaths. Cases were reported from the states of Washington (602 cases/144 hospitalisations/3
deaths), Idaho (14 cases/4 hospitalisations/no deaths), California (34 cases/14 hospitalisations/1 death) and Nevada (58 cases/9 hospitalisations/no deaths). In total 73 restaurants in
the chain were linked to the E. coli O157:H7 outbreak. Subsequent testing of the hamburger
patties showed the presence of E. coli O157:H7, and matched that from the cases.
The outbreak demonstrated the consequences of a restaurant chain receiving centralised yet
contaminated food. The investigation into the outbreak eventually identified five slaughterhouses in the US and one in Canada as possible sources of the bacteria, but the exact source of
the contaminated meat was never pinpointed. Further investigation revealed that the parent
company of the restaurant chain had been warned by local health departments and its own
employees that its hamburgers were being undercooked. However this had been ignored as
they claimed cooking at the required temperature (155°F) made the meat too tough.
E. coli O157 outbreak in South Wales, UK, 2005 (Salmon 2005)
On 16 September 2005, in Wales (UK) nine cases of bloody diarrhoea were reported by a
hospital to the National Public Health Service for Wales and local authorities. The normal
annual total for Wales was about 30 cases and therefore this was recognised as a probable
outbreak. The number of cases increased over the following days. These were subsequently
confirmed microbiologically as Shiga toxin‐producing E. coli O157. A case was defined as any
person living in South Wales who presented with bloody diarrhoea or had a faecal isolate of
presumptive STEC O157 in September (2005).
The dates of onset of symptoms ranged from 10–20 September. Except for one primary case
(adult), they were all school age children attending 26 different schools. A review of the first
15 cases revealed that all had eaten school meals and the adult case was a school meals
supervisor. The small numbers of cases across a large number of schools suggested the
source of the infection was a centrally distributed product with low levels of contamination
rather than a problem in the individual schools. In addition there was secondary person‐
to‐person spread. Parents were advised to keep children out of school if they developed symptoms of gastroenteritis.
The initial early epidemiological investigation focused on a single main supplier of cooked
meats to the school meals service. Inspection of the supplier’s premises revealed practices that
could result in the contamination of cooked meat. Subsequently local authorities took action
on 19 September, and the Food Standards Agency (Wales) issued a food alert on 21 September.
Other control measures were to remove RTE foods (not foods cooked on the school premises)
and to reduce any educational activities that might facilitate person‐to‐person spread.
A fuller epidemiological analysis, between 16 and 20 September, involved contacting 10 of
the first 18 primary school children cases whose early symptom onset dates were before 17
September. Controls were chosen at random from the school register. It was found that all
cases had eaten lunch in the school canteen. This compared with 8 out of 13 controls. By the
end of the outbreak, 67 males and 90 females had been affected, and 65% of cases (102/157)
Bacterial foodborne pathogens
173
14
12
Number of cases
10
Uncertain
8
Secondary cases
6
Primary cases
4
2
0
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 2 3
Date September–October 2005
Figure 4.11 Cases of verotoxigenic Escherichia coli (VTEC) O157 infection with known date of onset, outbreak
in South Wales, UK (n = 133). Source of data: Salmon (2005).
were children of school age from 42 schools. Dates of onset of symptoms were from 10–30
September (Figure 4.11). One boy aged 5 died.
Ninety‐seven of the cases were microbiologically confirmed as due to E. coli O157 infection. Nearly all of these isolates were phage type (PT) 21/28, and produced Shiga toxin (ST)
2. There was one exception, which was PT32 ST2. In addition four other microbiologically
confirmed cases of E. coli O157 infection were excluded from the outbreak case list. This
was because three were PT1 ST‐negative, and the remainder was PT8 ST1 + 2. These phage
types were not associated with the outbreak and there were alternative reasons for their
infection.
Escherichia coli O157 was isolated from three samples of sliced cooked meat from the supplier. These isolates were typed and confirmed as PT 21/28 and ST2, the same as the isolates
from the patients. The PFGE profiles of food and patient isolates were indistinguishable.
E. coli O157 outbreak from spinach, USA, 2006
In September 2006, an E. coli O157:H7 outbreak in the USA totalled 205 cases. There were 104
hospitalisations, with 31 cases of kidney failure and 3 deaths. The cause was traced back to
contaminated fresh, bagged spinach from one company in California. The product was
distributed directly to three further countries. An International Food Safety Authorities
Network (INFOSAN; see Section 13.1.1) Emergency Alert was issued to all INFOSAN members because another country received the product through secondary distribution. This
outbreak significantly differed to the previous example in South Wales (UK) due to the wider
distribution of the food product, and serves as an example of the need for international surveillance and cooperation.
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On 8 September 2006, the Centers for Disease Control and Prevention (CDC) were notified
of three cluster of E. coli O157:H7 infections in separate states, which were not all in close
proximity to each other. On 12 September, CDC’s PulseNet (Section 13.1.3) confirmed that
matching E. coli O157:H7 strains had been recovered from all the infected patients. On 13
September, the state public health officials notified the CDC that their epidemiological investigations suggested the infections were associated with the consumption of fresh spinach. The
following day, the FDA issued an alert about the multi‐state outbreak of E. coli O157:H7, and
advised consumers to avoid this product. Canada and Mexico were also notified due to the
large number of people who cross those borders daily and because many of the initial cases
came from states on the border with Canada and Mexico. The advice to avoid spinach was
revised on 22 September since the FDA had concluded that the contaminated spinach was only
from counties in California. By 18 September it was apparent that the contaminated spinach
had been distributed to Canada, Mexico and Taiwan. The relevant public health authorities
were notified. Initially INFOSAN sent Emergency Alerts to the INFOSAN Emergency Contact
Points in the affected countries. However, on 22 September the information was sent to the
entire INFOSAN network, as it became apparent that it was not possible to trace the full
distribution chain.
Based on epidemiological and laboratory evidence, the FDA on 29 September determined
that all spinach implicated in the outbreak could be traced back to one company. The spinach
had been grown in three California counties. Four fields on four different ranches were identified as the possible source of contamination. Escherichia coli O157:H7 was found in environmental samples collected near each of the four fields that provided spinach for the product.
However, only E. coli O157:H7 isolates from one of the four fields had a PFGE pattern indistinguishable from the outbreak strain. The PFGE pattern was identified in river water, cattle
faeces and wild pig faeces in the same area, the closest of which was less than 1 mile from the
spinach field. Subsequently the company recalled all spinach products, and farmers in the
affected area stopped growing spinach and stopped producing RTE spinach.
PFGE profiles of E. coli O157:H7 isolates were analysed around the country, as part of
PulseNet and were shown to have the same DNA pattern. In total there were 204 cases, from
26 states. These comprised 104 hospitalisations, of which 31 cases had HUS, and 3 deaths: 2
elderly women and a 2‐year‐old child. There was one confirmed case in Canada.
Comment: Control of E. coli in fresh produce is considered in Section 1.6.3.
E. coli O157:H7, cookie dough, 2009, USA, multi‐state outbreak (Neil et al. 2012)
In 2009 there was a STEC O157:H7 multi‐state outbreak in the US, which resulted in a total of
77 illnesses. This was linked to the consumption of contaminated commercial, pre‐packaged,
ready‐to‐bake cookie dough that contained contaminated raw flour.
The epidemiological investigation used a matched case–control study to identify exposures
associated with illness. Controls being age, sex and state‐matched to the range of cases. Isolates
of E. coli were typed using PFGE and MLVA. In total 77 cases from 30 states were identified for
the period 16 March – 8 July 2009. Almost half the cases (35/77) were hospitalised. Ten cases
developed HUS, but fortunately none died. Sixty‐six percent of patients were less than 19 years in
age, and 71% were female. In the case–control study, 33/35 (94%) of the cases had consumed
ready‐to‐bake commercial pre‐packaged cookie dough without cooking it, compared with only
4 out of 36 controls (11%). No other reported exposures were significantly associated with illness.
Most (94%) of the cases reported eating the same brand of uncooked cookie dough. Although no
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175
strains of E. coli O157:H7 matching the outbreak strain were isolated from unopened packages
of cookie dough, three non‐outbreak STEC strains (E. coli O8:H119 and E. coli O60:H7) were
isolated from the same brand. The investigation led to a recall of 3.6 million packages of cookie
dough and a product reformulation. It should be noted that the manufacturer’s instructions
stated that the cookie dough should be cooked before eating as it contained raw flour.
EIEC linked outbreaks, UK, 2014 (Newitt et al. 2016)
Although EIEC outbreaks are uncommon in Europe, in June 2014, two EIEC outbreaks
occurred within 2 days that were within less than a mile of each other, in Nottingham (UK).
The first outbreak (A) was linked to a takeaway restaurant, whereas outbreak B was a wedding
party. Given the differences in locations, a case–control study was undertaken for outbreak A,
and a cohort study for outbreak B (Section 13.2.3). Microbiological and environmental samples were taken and isolates of E. coli were whole‐genome sequenced.
In total there were 157 probable cases of whom 27 were laboratory‐confirmed as EIEC serotype O96:H19. Twenty percent of cases in outbreak A were hospitalised compared with none for
outbreak B, indicating a more severe illness. Although combined epidemiological, microbiological and environmental investigations implicated lettuce as the vehicle of infection in the takeaway
restaurant outbreak (A), the source of the organism was unproven. Nine of the 12 food handlers
associated with outbreak A tested positive for EIEC, but most reported they were asymptomatic.
However, one food handler who claimed to be asymptomatic at the time of the outbreaks but
tested positive for EIEC reported becoming ill with gastrointestinal symptoms on return from
Pakistan in May (2014). It is plausible that this food handler was still shedding EIEC, and this has
been reported to occur for up to 1 year after infection. Consequently, this food handler through
poor hygienic practices and cross‐contamination may have introduced the organism into the
takeaway restaurant. With regard to outbreak B, only 68% of the guests agreed to participate in
the investigation. Nevertheless, the same strain (differing by one single‐nucleotide polymorphism [SNP]) was isolated from both outbreaks (including the recovered food handler) according to whole‐genome analysis. Despite the close proximity of both outbreaks, no epidemiological
link was found. This could in part have been due to the non‐participation by 32% of the wedding
guests (Outbreak B). Nevertheless, these outbreaks illustrate that EIEC can cause severe outbreaks and should be considered as a potential pathogen in foodborne outbreaks.
E. coli O157:H7 romaine lettuce outbreaks, USA, 2017 and 2018 (CDC 2018)
In 2017, an outbreak of E. coli O157:H7 linked to romaine lettuce started between 15 November
and 8 December. At the same time, the Public Health Agency of Canada was investigating an
outbreak of E. coli O157:H7 infections in several provinces. In the USA there were 25 E. coli
O157:H7 illnesses across 15 states and another 42 illnesses in Canada. The outbreak caused
two deaths, one each in the US and Canada. Twenty‐six people in the two countries required
hospitalisation. Neither country found a common supplier, distributor or retailer of the contaminated romaine lettuce.
Another outbreak of E. coli O157:H7 linked to romaine lettuce grown in Arizona (USA)
occurred in 2018. This resulted in 5 deaths, and 210 illnesses. Almost half (96) of the cases
were hospitalised, including 27 people with HUS. The illnesses started between 13 March
(2018) and 12 May (2018). The age of the cases ranged from 1 to 88 years, with a median age of
29, and 68% were female. The same strain also caused six infections in Canada.
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Since it takes 2–3 weeks from the time a person becomes ill to when the illness is reported
to CDC, there is a delay before any attributable food produce can be recalled. Subsequently,
further people can become ill as the produce is likely to be still available in stores, restaurants
or in peoples’ homes. In this outbreak, some cases did not report eating romaine lettuce, but
had close contact with someone else who got sick from eating romaine lettuce.
The initial traceback investigation indicated that the illnesses could not be attributable to a
specific grower, harvester, processor or distributor. However, several weeks later, the causative
strain was found in the canal water used for irrigation. Why it took over a month before the
water was tested has not been explained.
See Section 13.3 for a complicated legal case involving an outbreak of STEC associated with
cheese made from raw milk, and crowd funding. Also, Section 14.4 has examples of E. coli
outbreaks investigated using genomic epidemiology.
4.5 Sh. dysenteriae and Sh. sonnei
4.5.1 General description
Shigella is a highly contagious bacterium that infects the intestinal tract. It is closely related to
E. coli but can be differentiated from E. coli by the lack of gas production from carbohydrates
(anaerogenic) and negative lactose fermentation. Essentially it can be regarded as a pathotype
of E. coli with the ability to invade the human gut mucosa and cause dysentery. However, for
historic and practical reasons the genus name Shigella remains in use.
The genus Shigella consists of four species: Sh. dysenteriae (serotype A), Sh. flexneri (serotype B),
Sh. boydii (serotype C) and Sh. sonnei (serotype D). In general Sh. dysenteriae, Sh. flexneri and
Sh. boydii predominate in developing countries, whereas, Sh. sonnei is most common and
Sh. dysenteriae is less common in developed countries. Shigella is spread by direct and indirect
contact with infected individuals. Most cases of shigellosis result from the ingestion of food or
water contaminated with human faeces. Several large outbreaks have been due to the
consumption of contaminated raw fruits and vegetables. Food or water may be contaminated
Box 4.5
Organism
Shigella species
Food source
Salads, raw vegetables, bakery products, sandwich fillings, milk, and dairy products, poultry.
Onset of symptoms
12–50 hours.
Acute symptoms and chronic complications
Abdominal pain and cramps, diarrhoea, fever, vomiting, blood, pus or mucus in stools.
Bacterial foodborne pathogens
177
by direct contact with faecal material from infected people. Shigella often causes outbreaks in
day care centres.
4.5.2 Shigellosis
The main symptoms of shigellosis are:
• diarrhoea, mild or severe, may be watery or bloody;
• fever and nausea;
• vomiting and abdominal cramping may also occur.
The symptoms appear within 12–96 hours after exposure to Shigella; the incubation period is
typically 1 week for Sh. dysenteriae (see Tables 1.3 and 1.4). The symptoms from Sh. sonnei are
generally less severe than the other Shigella species. Shigella dysenteriae may be associated with
serious disease, including toxic megacolon and HUS. Shigella cells are shed in the faeces for
1–2 weeks of infection.
4.5.3 Virulence factors
Probably because the organism is not readily killed by the acidity of the stomach, Sh. dysenteriae has a low infectious dose (Table 4.1). The organism then colonises the colon and enters the
mucosal cells where it multiplies rapidly. Once inside the mucosal cells, the bacterium moves
laterally to infect adjacent mucosal cells (Figure 4.12). It provokes an intense inflammatory
response in the lamina propria and the mucosal layer, and the inflammatory response causes
the blood and mucus to be found in the victim’s faeces.
The organism produces Shiga toxin, an exotoxin, with AB5 structure (Figure 2.10; A subunit
is 32 kDa, B subunit 7.7 kDa) and a CDT. The AB5 toxin is structurally similar to cholera toxin
although there is little similarity in amino acid sequences. The B subunits of Shiga toxin, like
those of cholera toxin, recognise a host cell surface glycolipid (Gb3), but the carbohydrate
moiety on this lipid is Gal α‐1,4‐Gal, not sialic acid as for cholera toxin receptor GM1. The Shiga
toxin first binds to the surface of mammalian cells and is then internalised by endocytosis.
Nicking to activate and translocate the A subunit takes place inside the host cell. In contrast to
other AB toxins, the A subunit of Shiga toxin does not ADP‐ribosylate a host cell protein, but
stops host cell protein synthesis. It inactivates the 60S subunit of host cell ribosomes by cleaving the N‐glycosidic bond of a specific adenosine residue in 28S rRNA, a component of the 60S
ribosomal subunit. Cleavage of 23S rRNA at this site prevents binding of aminoacyl‐tRNAs to
the ribosome and stops elongation of proteins.
Engulfment
into vacuole
Escape and
multiplication
Colonic cell
Figure 4.12 Shigella species infection of gut mucosal cells.
Invasion of
adjacent cell
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The microbiology of safe food
Shigella sonnei has for a long time been a primary cause of dysentery in developed countries,
and is increasingly causing cases in the developing world. WGS analysis shows that the current
Sh. sonnei population is derived from a most recent common ancestor less than 500 years ago.
In Europe, the species has diversified into four distinct lineages, and this was followed by the
spread and establishment of a single, rapidly evolving, multi‐drug‐resistant lineage into Asia,
Africa and America, termed ‘pandemic lineage III’. This lineage is now a dominant cause of
dysentery in many endemic areas of the world.
It is plausible that the emergence of Sh. sonnei was due to the acquisition of the virulence
plasmid pINV B, encoding the Plesiomonas shigelloides (Section 4.11) related O antigen.
Alternatively, there is cross‐protection due to prior exposure to P. shigelloides with indistinguishable O antigens. Consequently, the increased incidence in Sh. sonnei infections following
improvements in water quality may be ironically due to the reduced passive cross‐protection
from exposure to P. shigelloides.
4.5.4 Sh. sonnei outbreak
Sh. sonnei outbreak linked to fresh parsley, USA, 1998
In August 1998, multiple reports of Shigella infection were received from people who had eaten
from two restaurants that were in different cities of Minnesota. These had separate water supplies, and there were no employees in common (CDC 1999). Initial expectations were that the
ill food handlers contaminated ice and fresh produce. However molecular characterisation
using PFGE revealed that both outbreaks were caused by the same strain of Sh. sonnei. This
strain had not previously been isolated in the state. Since the two outbreaks had a common
source, the food ingredients were considered as the likely cause. Further analysis showed an
association of illness with those who had eaten chopped parsley. Further matching isolates
were identified using PFGE. In total there were six other outbreaks from July to August: two in
California, and one each in the states of Massachusetts, Florida, and the provinces of Alberta
and Ontario. Shigella sonnei isolates were recovered from five of the six outbreaks. Their PFGE
patterns matched the Minnesota outbreak pattern. In each outbreak, chopped parsley was
sprinkled on the food implicated by a high proportion of cases.
Subsequent traceback identified a farm in Baja California, Mexico as the most likely source
of the parsley in six out of seven outbreaks. Further investigation found that municipal water
was used to make the ice that was packed with the parsley. This water was both unchlorinated
and susceptible to contamination. The preparation of the parsley in the restaurants further
enhanced the transmission of Sh. sonnei. The parsley was usually chopped in the morning, and
then left at room temperature until required. Under these conditions the bacterium could
increase by 1000‐fold in 24 hours. Additionally food handlers became infected and contributed
to the ongoing transmission of the bacterium. Therefore, the food ingredient was contaminated
by ice and this was amplified through handling practices, contaminating other RTE foods.
4.6 Cronobacter species
4.6.1 General description
Cronobacter is possibly the archetypal emergent bacterial pathogen that has been associated
with foodborne infection, albeit via one particular food source: powdered infant formula. The
considerable progress in better understanding and control of this organism is undoubtedly due
to improved international policies for infant health.
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179
Box 4.6
Organism
Cronobacter genus; seven species
Food source
Powdered infant formula, plant‐based ingredients, vegetables and salads.
Onset of symptoms
Days.
Acute symptoms and chronic complications
Infections in all age groups, particularly infants <6 months in age, and the elderly. Life‐threatening
symptoms in infants <6 months in age include meningitis, necrotising enterocolitis and respiratory
infections. Adults, gastroenteritis, conjunctivitis, biliary sepsis, urosepsis, appendicitis, wound
infections, and pneumonia.
The genus Cronobacter is composed of seven species: C. condimenti, C. dublinensis, C.
malonaticus, C. muytjensii, C. sakazakii, C. turicensis and C. universalis. However, probably
only C. sakazakii and C. malonaticus are of clinical significance, with C. sakazakii and C.
malonaticus causing severe infections in neonates and adults, respectively (Forsythe 2018a, b).
Using multi‐locus sequence analysis the closer relatedness of C. sakazakii and C. malonaticus
compared with the other five species can be shown (Figure 4.13). According to phylogenetic
analysis these major divisions formed about 41 million years ago and further host adaptation
has occurred as will be considered later with the specific case of the C. sakazakii sequence type
4 pathovar (Joseph et al. 2012).
The Cronobacter genus has undergone a number of taxonomic revisions since its original
description in 2007 (Forsythe 2018a, b). Essentially, the genus encompasses strains previously
known as the species Enterobacter sakazakii, which in turn had been previously referred to as
‘yellow‐pigmented Ent. cloacae’. It is inevitable that when a previously understudied group of
bacteria is investigated taxonomic revisions will occur. However, the difficulty arises for regulatory authorities and manufacturers to ensure that the appropriate control measures and
detection methods are implemented to protect human health. The taxonomic revisions directly
affect the reliability of some current detection methods, especially those based on commercially available phenotyping kits. In addition, the yellow pigment description used in the early
isolation methods of the FDA and ISO is now recognised as inaccurate as the trait is only
carried by ~80% of strains and expressed at room temperature, and even fewer strains show it
at 37°C (Fanning and Forsythe 2008).
4.6.2 Infections due to Cronobacter species
Cronobacter infections can occur in all age groups, but of particular significance are those in neonates, infants <6 months in age and the elderly. Life‐threatening symptoms in neonates and infants
<6 months in age include meningitis, necrotising enterocolitis and respiratory infections. They
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99
C. sakazakii ATCC29544T
C. malonaticus LMG23826T
100
C. turicensis LMG23827T
87
100
C. universalis NCTC9529T
78
C. dublinensis LMG23823T
C. muytjensii ATCC51329T
97
100
C. condimenti LMG26250T
F. pulveris LMG24059
F.helveticus LMG23732T
S. turicensis LMG23730T
0.01
Figure 4.13 Maximum likelihood tree of ribosomal‐MLST (53 loci) analysis for members of the Cronobacter
genus, and closely related genera of Franconibacter and Siccibacter. The tree was drawn using MEGA6 with 1000
bootstrap replicates.
have a fatality rate of 50% (Townsend et al. 2007b, 2008). Bowen and Braden (2006) considered 46
neonatal cases and reported that the symptoms of very low birth weight neonates tend to be bacteraemia, whereas those of birth weight ~2000 g tended to suffer from meningitis. The primary
identified source of infection in neonates is contaminated reconstituted powdered infant formula.
The organism is ubiquitous in nature, particularly plant material, and there is human carriage.
Reconstituted powdered infant formula has been implicated in some outbreaks and sporadic cases of Cronobacter infection. It can survive in the desiccated state for over 2 years
(Caubilla‐Barron and Forsythe 2007). The organism causes infections in adults, especially
those who are immunocompromised, though one outbreak of gastroenteritis has been report
amongst university students (Yong et al. 2018). However, it is the infection of neonates which
has raised the profile of this bacterium.
4.6.3 Identification and typing methods for Cronobacter species
The most accurate means of identification and typing Cronobacter isolates is by DNA sequencing, primarily the fusA gene, as part of the standardised seven‐loci MLST scheme (Section 6.6.1).
An open access MLST database is available with a centralised database (www.pubMLST.org/
cronobacter) and protocols, and also whole genomes can be accessed. The MLST scheme
revealed the high level of clonality in the organism, particularly C. sakazakii and C. malonaticus, and that there are pathovars associated with the major clinical presentations: C. sakazakii
CC ST4 with neonatal meningitis, C. sakazakii ST12 with necrotising enterocolitis and C.
malonaticus ST7 with adult infections (Joseph and Forsythe 2011; Forsythe et al. 2014; Forsythe
2018a, b).
Historically serotyping has been a useful means of typing isolates, before more robust and reliable
methods were developed. Similarly serotyping was initially attempted for Cronobacter but has severe
limitations. It only differentiates C. sakazakii strains, the main species of concern with neonatal
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and infant infections into five types, while even just seven‐loci MLST has >500 defined types
(Forsythe 2018a, b). In addition some serotypes of Cronobacter are shared across different species,
and also with E. coli and Shigella. Therefore, it has no usefulness compared to more modern
methods.
Whole‐genome analysis has led to methods of typing that are far more discriminatory than
PFGE. These include CRISPR‐cas array profiling, ribosomal‐ and core genome‐MLST, and
capsule profiling (Ogrodzki and Forsythe 2015, 2016, 2017) (Section 6.6). The recognition by
seven‐loci MLST of strong clonality within the Cronobacter has been useful in both describing
the diversity of the genus, and the recognition of pathovars. However, it also restricts the ability
to distinguish between unrelated strains during microbial source tracking. This is because
unrelated strains may still be indistinguishable by PFGE and conventional MLST since, by
definition, clonal organisms have nearly identical genomes (Forsythe et al. 2014). In order
to address this issue, Ogrodzki and Forsythe (2015, 2017) developed ‘clustered regularly
interspaced short palindromic repeats’ (CRISPRs) and CRISPR‐associated genes (cas)
protein‐coding genes (CRISPR‐cas) array profiling (Section 6.6) (Plate 18).
4.6.4 Virulence factors
WGS has revealed a large number of plausible virulence factors in Cronobacter, though many
of these await laboratory confirmation. Due to the increasing number of Cronobacter genomes
being sequenced, for up‐to‐date information the reader should consult the Cronobacter
BIGSdb, which is a searchable (BLAST) repository of all published Cronobacter genomes
(>500) (www.pubMLST.org/cronobacter).
Cronobacter can invade human intestinal cells, replicate in macrophages and pass through the
blood–brain barrier. The route of infection is probably through attachment and invasion of the
intestinal cells. A number of fimbriae clusters have been identified in the genomes of Cronobacter
species. However, C. sakazakii is the only Cronobacter species that encodes for β‐fimbriae and
lacks curli fimbriae. The organism has a number of iron assimilation mechanisms, which might
enable the organism to utilise iron from breast milk and formula. Whole‐genome analysis has
revealed various type VI secretion system (T6SS) clusters, which may be involved in adherence,
cytotoxicity, host cell invasion, growth inside macrophages and survival within the host. It has
been proposed that the outer membrane proteins OmpA and OmpX have roles in Cronobacter
penetrating the blood–brain barrier, similar to meningitic E. coli K1. The organism also encodes
for a number of haemolysins. Nevertheless, mechanisms leading to abscess formation in the
brain cavity are unknown and could in part be a over stimulated host immune response.
Cronobacter can produce copious amounts of capsular material, which is composed of colanic
acid (CA), K antigen, cellulose and Enterobacteriaceae common antigen. This probably contributes
to the organism’s ability to survival desiccation, spray drying and biofilm formation. There is also a
strong association between the possession of the K2:CA2 capsular profile and neonatal meningitis.
Essentially the K2:CA2 capsule profile is nearly unique to strains isolated from destructive meningitis cases (C. sakazakii ST4 and exceptional C. malonaticus meningitis cases) (Ogrodzki and Forsythe
2015, 2017). However the chemical composition of this capsule has not been determined.
Cronobacter sakazakii is nearly unique in the Cronobacter genus in its utilisation of exogenous sialic acid. The ability to utilise sialic acid could be a major evolutionary host adaptation
since the compound is found in mucin, breast milk and gangliosides. Given the clinical presentations of necrotising enterocolitis, and meningitis this could be highly significant, especially since C. sakazakii is also able to grow on the ganglioside GM1 as a sole carbon source
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(Joseph et al. 2013). Additionally, sialic acid is an ingredient in powdered infant formula due
to its association with brain development. The property is also possessed by a few strains in
one branch of C. turicensis, however this species is not associated with neonatal meningitis.
Levels of endotoxin due to the presence of heat‐stable LPS have been measured in infant formula
(Townsend et al. 2007a). In rat pups, LPS enhances the translocation of Cronobacter across both the
intestines and the blood–brain barrier, and therefore indicates its presence in infant formula could
increase the risk of bacteraemia in neonates. It has been speculated that frequent LPS contamination
of PIF (known to disrupt tight junctions) might contribute to the invasiveness of Cronobacter across
the blood–brain barrier. The organism also has a number of heavy metal resistance factors and biofilm formation, which might enable it to resist disinfectants in food production environments.
4.6.5 Sources and control of Cronobacter species
Despite earlier sporadic cases of neonatal and infant infections, the organism was brought to
regulatory attention in 2002 following an outbreak in a university hospital in Tennessee (USA).
One neonate died from meningitis, there were two suspected infections (tracheal aspirate positive) and seven were colonised (six faecal positive and one urine positive) with the same strain
according to PFGE profiling. The source was attributed to powdered formula (Himelright
et al. 2002), which has been misinterpreted as powdered infant formula (see Section 4.6.6 for
details). Since such neonates only have a limited number of exposure routes the FAO/WHO
instigated the first risk assessment for a foodborne pathogen (FAO/WHO 2004), which was
followed up by two further ones (2006 and 2008) (see Section 11.7). These led to revisions of
both Codex Alimentarius Commission microbiological specifications of PIF as well WHO
guidelines for the preparation of powdered infant formula.
Prior to this the number of Enterobacteriaceae (except for Salmonella) permitted in
powdered infant formula was <100 cfu/g (CAC 1979). These specifications had not been
revised since 1979. Subsequently the microbiological criteria for these products have been
revised (CAC 2008), and stricter microbiological criteria have been adopted. The microbiological criteria changed such that Salmonella serovars and Cronobacter should not be detectable in 25 and 10 g test volume quantities of powdered infant formula, respectively.
Cronobacter has been isolated from 0 to 12% dried infant formula samples (FAO/WHO
2006a), but has never been reported at levels greater than 1 cell/gram. Therefore an increased
risk of neonatal infection from contaminated reconstituted feeds may be attributed to temperature abuse. The organism’s minimum growth temperature is ~ 5°C, and the doubling time
is ~40 minutes at room temperature and 5 hours at 10°C.
In 2007, the WHO released the ‘Safe preparation, storage and handling of powdered infant
formula guidelines’ and specific documents for different care settings (WHO 2007). Essentially
these guidelines reflect the FAO/WHO recommendations that these powders are reconstituted
at 70°C to reduce the number of any enteric pathogens to an acceptable number; that the
reconstituted feed should be consumed as quickly as possible; and the storage of partially used
feeds should be minimised.
However, this raised temperature of reconstitution can cause vitamin losses, and clumping.
Temperatures of ~55°C or less are frequently practised in neonatal units and at home, which
do not result in any significant loss in bacterial viability. Subsequent incubation at room temperature, or prolonged storage in refrigerators can result in significant bacterial multiplication
and contribute to infant infections.
It should be noted that the past emphasis on controlling Cronobacter in powdered infant formula
has given the false impression that this is the only route of infection. In fact infections have been
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183
attributed to the water used for the reconstitution of powdered infant formula (Hariri et al. 2013).
Also, the organism has been isolated from the nasogastric feeding tubes of neonates not receiving
reconstituted infant formula, and infections have been reported in infant exclusively breastfed,
which could be due to contamination of equipment used for expressed breast milk preparation.
Furthermore, the C. malonaticus species type strain has been isolated from breast abscesses, there is
human carriage and the organism is recovered from a wide range of foods (Table 1.2).
According to the FAO/WHO risk assessments (2004 and 2006a) other Enterobacteriaceae and
Acinetobacter species have been categorised as ‘Causality plausible, but not yet demonstrated’
with respect to causing neonatal infection through contaminated formula powder, and further
monitoring has been advised. Additionally, the FAO/WHO also produced a third category of
‘Organism’s causality less plausible, or not yet demonstrated’. This covers B. cereus, Cl. botulinum, Cl. difficile, Cl. perfringens, Listeria monocytogenes, St. aureus and coagulase‐negative
staphylococci. For a more extensive coverage of Cronobacter, the reader should refer to the
author’s web page (www.foodmicrobe.com/publications.htm) and the ASM Press publication
(Fanning and Forsythe 2008). Detection methods and typing schemes are covered in Section 6.7.7.
4.6.6 Cronobacter outbreaks
Neonatal intensive care unit, Tennessee, USA, 2001 (Himelright et al. 2002)
Sometimes a single outbreak can be a turning point with regard to the relative importance of
an organism, and can lead to a review of detection methods and production methods. With
respect to Cronobacter it was an outbreak in a hospital in Tennessee, USA (Himelright et al.
2002) that led to the WHO for the first time taking action for a foodborne infection. A neonate
aged 11 days old developed a fever, tachycardia and meningitis. Cronobacter sakazakii was
recovered from the baby’s cerebrospinal fluid. Despite antimicrobial treatment the baby died
9 days later. Further case surveillance on the intensive care unit of 49 infants revealed further
C. sakazakii infections or colonisation. Two infants had suspected infections (culture positive
from tracheal aspirate) and seven colonisation (six culture positive from stools and one from
urine). The risk factor identified was the consumption of reconstituted powdered formula. This
was a product for target age >1 year. However it was misreported as ‘powdered infant formula’,
which is a product with target age <1 year. Cronobacter sakazakii with matching PFGE profile
as the CSF isolate was recovered from a previously unopened can of the powdered formula.
The considerable publicity of this outbreak led to the WHO revisions of the microbiological
criteria for powdered infant formula and guidelines for its preparation. Given the C. sakazakii
was previously ‘permissible’ as an Enterobacteriaceae instead of being a named specific pathogen with ‘zero tolerance’ means this change has considerably reduced the risk of neonatal
infections (Sections 4.6.5). This is despite the mistake in reporting the attributed source of the
outbreak to powdered infant formula, not powdered formula. However, the microbiological
criteria and microbial safety of powdered formula which caused the outbreak have not been
revised. Finally, we now know that due to the high clonal nature of C. sakazakii, PFGE cannot
discriminate unrelated strains, and therefore the fatal strain could have originated from a
source other than the formula. These days more discriminatory methods would be used to
attribute source, such as CRISPR‐cas array profiling and SNP analysis.
A more detailed analysis of a triple outbreak in the same neonatal intensive unit is covered
in detail in Section 14.4.6, and includes progressive analysis from PFGE, seven‐loci MLST,
core genome multi‐locus sequence typing (cg‐MLST), CRISPR‐cas array profiling and SNP
analysis.
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4.7 Vibrio cholerae, V. parahaemolyticus and V. vulnificus
4.7.1 General description
Vibrio species are frequently isolated from estuarine waters and are therefore associated with
fish and various seafoods. Although there are 12 human pathogenic Vibrio species, only
V. cholerae, V. parahaemolyticus and V. vulnificus are of principal concern to human infection.
Vibrio cholerae causes cholera and is the best‐known Vibrio infection. Carriage of V. cholerae
by infected humans is important in the disease transmission, as water used for drinking or
washing food can become contaminated by faecal matter. Genomic analysis has revealed the
three organisms possess two chromosomes, a large chromosome encoding for key cellular
functions, and a smaller chromosome, which may originally have been a megaplasmid, which
has acquired increasing greater number of genes from organisms outside the γ‐proteobacteria
(Enterobacteriaceae, Vibrionaceae and Pseudomonadaceae).
4.7.2 Infections due to Vibrio species
Vibrio cholerae has been a cause of human disease since antiquity, and has resulted in at least
eight pandemics. It is normally recognised as a waterborne disease, but can also be foodborne
especially for countries who consume seafood as a large portion of their diet (Table 1.2). There
are over 200 serogroups of V. cholerae, and classic Asiatic cholera is caused by V. cholerae serogroups O1 and O129. These produce the cholera toxin (Figure 2.11). Serogroup O1 has two
biotypes, classic and El Tor, and three serotypes, Inaba, Ogawa and Hikojima. The incubation
period varies between 6 hours and 3 days (Table 1.3). The initial symptoms can be mild, and
Box 4.7
Organism
V. cholerae, V. parahaemolyticus, V. vulnificus
Onset of symptoms
V. cholerae: 1–3 days.
V. parahaemolyticus: 9–25 hours.
V. vulnificus: 12 hours to 3 days.
Food source
V. cholerae: seafood, vegetables, cooked rice, ice.
V. parahaemolyticus: raw or undercooked fish and fishery products.
V. vulnificus: seafood, particularly raw oysters.
Acute symptoms and chronic complications
V. cholerae: profuse watery diarrhoea.
V. parahaemolyticus: profuse watery diarrhoea free from blood or mucus, abdominal pain, vomiting
and fever.
V. vulnificus: profuse diarrhoea with blood in stools.
Bacterial foodborne pathogens
185
then progress to copious diarrhoea, with associated loss of body fluids of ~1 l/h. This results in
dehydration, hypertension and salt imbalance. Without treatment, death may be rapid.
Infections due to other serotypes that lack the cholera toxin genes do occur. This may be
milder, with nausea, vomiting and diarrhoea, but can also in ~25% include bloody diarrhoea.
Vibrio parahaemolyticus means ‘dissolving blood’ and the organism was first isolated in
1951. The organism is not isolated in the absence of additional NaCl (2–3%) and was therefore
not cultivated in early studies of gastroenteritis. Vibrio parahaemolyticus is a major cause of
foodborne gastroenteritis in Japan. This is because the organism is associated with the consumption of seafood, which is a significant part of the average diet in Japan.
Typical symptoms of V. parahaemolyticus food poisoning:
• diarrhoea;
• abdominal cramps;
• nausea;
• vomiting;
• headaches;
• fever and chills.
The incubation period is 4–96 hours after the ingestion of the organism, with a mean of
15 hours (Tables 1.3 and 1.4). The illness is usually mild or moderate, although some cases may
require hospitalisation. On average the illness lasts about 3 days. The infective dose is possibly
greater than 1 million organisms. Virulence is associated with the production of a thermostable direct haemolysin, the ability to invade enterocytes and possibly the production of an
enterotoxin (possibly Shiga‐like). The production of the tdh gene is the only reliable trait that
currently distinguishes between pathogenic and non‐pathogenic strains. Although the demonstration of the Kanagawa haemolysin was initially regarded as indicative of pathogenicity,
this is now uncertain.
Vibrio vulnificus was first isolated by the CDC (USA) in 1964. ‘Vulnificus’ means ‘wound
inflicting’, which reflects the organism’s ability to invade and destroy tissue. The organism is
recovered in high numbers (>105 cfu/g) from molluscan shellfish and estuarine water, especially in the warmer (summer) months (Baker‐Austin and Oliver 2018). At temperatures
below 13°C, the organism can enter the VNBC state (Section 6.2.3).
Human infections are due to both the consumption of contaminated seafood produce (primary septicaemia) and water exposure (wound infections). The organism has the highest
death rate of any foodborne disease agent equating to anthrax and Ebola virus (Todd 1989b).
It causes 95% of all seafood‐related deaths in the United States. Reported infections disproportionately occur in males (~85% of cases) and the > 40 years age group, especially those with
underlying conditions such as liver diseases, diabetes and immune disorders. Non‐lethal infection nevertheless can be life‐changing through tissue damage such as the loss of fingers.
Typical symptoms of V. vulnificus food poisoning are:
• fever;
• chills;
• nausea;
• skin lesions.
The onset of symptoms takes about 24 hours (range 12 hours to several days) after ingestion of
contaminated raw shellfish (especially oysters) by vulnerable people. Individuals most susceptible to infection include the elderly, the immunocompromised, and those suffering with
chronic liver disease and chronic alcoholism. The organism differs from other pathogenic
vibrios in that it invades and multiplies in the blood stream.
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There are three biotypes and two genotypes of V. vulnificus. Biotype 1 is responsible for both
the ingestion cases (‘primary septicaemia’) and most wound infections. Biotype 2 is the causative agent of a rapidly fatal septicaemia in farmed eels, but only rarely of human infections.
Biotype 3 was discovered in 1996 after an outbreak of V. vulnificus wound infections in an
Israeli fish market. This is a hybrid of biotypes 1 and 2, and is primarily found in Israel, with
an exceptional report in Japan. The two genotypes are based on the variation, according to
RAPD of the vcg (virulence correlated gene) (Rosche et al. 2005). The clinical (‘C’) genotype is
responsible for virtually all septicaemia cases, and the environmental (‘E’) genotype causes
virtually all of the wound infections. Approximately 90% of human clinical isolates are the C
genotype, whereas the E genotype is recovered from 85–90% of environmental isolates from
shellfish and water. WGS studies have not yet determined which genes are essential for human
virulence or environmental fitness genes for persistence in estuarine environments (Morrison
et al. 2012).
4.7.3 Virulence factors
In the small intestine, V. cholerae attaches via cell‐associated adhesins to the mucosal surface
of the small intestine and produces an exotoxin, cholera toxin, that acts on intestinal mucosal
cells. The toxin is 84 kDa in size and is composed of A1 subunit (21 kDa) and A2 subunit
(7 kDa) covalently linked to five B subunits (10 kDa each). The B subunit binds to a receptor
ganglioside on the mucosal cells and the A subunit enters the cell activating adenylate cyclase
and subsequently increasing the concentration of cAMP (Figures 2.3 and 2.11).
Mucosal cells have a set of ion transport pumps (for Na+, Cl−, HCO3− and K+) that normally
maintain a tight control over ion fluxes across the intestinal mucosa; Section 2.1. Because water
can pass freely through membranes, the only way to control the flow of water into and out of tissue is to control the concentration of ions in different body compartments. Under normal conditions, the net flow of ions is from lumen to tissue (Figure 2.3) resulting in a net uptake of water
from the lumen. The effect of cholera toxin on mucosal cells is to alter this balance. Cholera toxin
causes no apparent damage to the mucosa, but the increased level of cAMP decreases the net flow
of sodium into tissue and produces a net flow of chloride (and water) out of tissue and into the
lumen, resulting in massive diarrhoea and electrolyte imbalance (Figure 2.11).
The V. cholerae genome is unusual for Enterobacteriaceae in that it consists of two circular
chromosomes of ~2.9 and ~1.1 Mb, which together encode 3885 open reading frames. The
majority of genes for essential cell functions (such as DNA replication, transcription, translation) and virulence (toxins, surface antigens and adhesins) are on the larger chromosome.
The smaller chromosome proportionally contains more genes than the larger chromosome,
which originate from outside the γ‐Proteobacteria (Enterobacteriaceae, Vibrionaceae and
Pseudomonadaceae). The small chromosome also encodes an integron island, which may
function as a gene capture system. It is plausible that the small chromosome may have originally been a megaplasmid that was captured by an ancestral Vibrio species.
The V. parahaemolyticus genome also consists of two circular chromosomes (~3.3 and
~1.9 Mb) that encode for ~4800 genes. Comparison of the V. parahaemolyticus genome with
that of V. cholerae shows many rearrangements within and between the two chromosomes and
therefore possible common origins. Vibrio parahaemolyticus does additionally encode for
the T3SS, which V. cholerae lacks. This secretion system is a major virulence factor of
diarrhoea‐causing bacteria such as Salmonella, and EPEC. Enabling the organisms to cause
gastroenteritis by invading or interacting with intestinal epithelial cells. This may explain why
Bacterial foodborne pathogens
187
V. parahaemolyticus infections commonly include inflammatory diarrhoea, while those of V.
cholerae are generally associated with non‐inflammatory diarrhoea.
Vibrio vulnificus has two chromosomes. The larger chromosome is ~3.3 Mb in size, encoding for ~2900 genes, while the smaller chromosome is ~1.9 Mb and encodes for ~1600 genes.
Vibrio vulnificus is highly invasive and produces various factors that protect it from the host
immune system, including a serum resistance factor, capsular polysaccharide and the ability to
acquire iron from iron‐saturated transferrin. It produces a range of exoenzymes including a
heat‐labile haemolysin/cytolysin and an elastolytic protease, which probably causes the cellular damage. Since a large amount of shellfish is consumed each year and only relatively small
numbers of cases of V. vulnificus food poisoning are reported, it seems reasonable to predict
that not all strains are pathogenic. However, no definitive virulence genes have been identified
that distinguish between virulent and non‐virulent strains. The closest may be capsule production, which is an essential virulence trait since non‐encapsulated cells are readily
phagocytosed.
Analysis of the V. vulnificus genome has identified a range of genes that are possibly associated with pathogenicity: haemolysin (vvhA), rtx gene cluster for MARTX, three complete
secretion systems (type I, II and VI) and iron uptake‐related genes. HGT has influenced the
evolution of the V. vulnificus genome as shown by insertion events, integrons and conjugative elements. Genes specific to the clinical strains include sialic acid catabolism, Flp pili,
GGDEF proteins, ‘genomic island XII’, mannitol fermentation and a component of a type IV
secretory pathway (VirB4). Genomic analysis also indicates that V. vulnificus biotype 3 may
have evolved from environmental populations and formed a genetically distinct group
(Koton et al. 2015).
4.7.4 Sources and control
There are usually fewer than 103 cfu/g of V. parahaemolyticus on fish and shellfish, except in
warm waters where the count may increase to 106 cfu/g. Infections with this organism have
been associated with the consumption of raw, improperly cooked or cooked, recontaminated
fish and shellfish. A correlation exists between the probability of infection and warmer months
of the year. Improper refrigeration of seafood contaminated with this organism will allow
its proliferation, which increases the possibility of infection. The organism is very sensitive
to heat and outbreaks are therefore frequently due to improper handling procedures and
temperature abuse. Control of the organism is therefore through prevention of the organism’s
multiplication after harvesting by chilling (<5°C) and cooking to an internal temperature of
>65°C. Isolation of any Vibrio species from cooked food indicates poor hygienic practice since
the organism is rapidly killed by heat.
Vibrio vulnificus is isolated from shellfish and coastal water. The organism is rarely isolated from seawater at <10–15°C, but numbers rise when the water temperature is >21°C.
The principal routes of infection are through wounds and septicaemia after ingestion. It is
not a significant cause of food poisoning amongst healthy adults. Therefore, the main means
of prevention is for immunocompromised individuals to avoid eating raw shellfish, in particular oysters. Control of the organism is primarily by ceasing oyster harvesting if the water
temperatures exceed 25°C, and by chilling and holding oysters at a temperature of <15°C
post‐harvesting. See Section 11.6 for a risk assessment of V. parahaemolyticus in molluscan
shellfish, and Section 1.14 for concern over increasing Vibrio infections due to global
warming.
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4.8 Brucella melitensis, Br. abortus and Br. suis
4.8.1 General description
Brucella is a strictly aerobic, Gram‐negative coccobacillus that causes brucellosis. This organism is carried by animals and causes incidental infections in humans. The four species that
infect humans are named after the animal they are commonly isolated from: Br. abortus (cattle), Br. suis (swine), Br. melitensis (goats) and Brucella canis (dogs). Cattle and dairy products
are the prime source of infection.
4.8.2 Brucellosis
Brucella can enter the body via the skin, respiratory tract or the digestive tract. Once there the
intracellular organism can enter the blood and the lymphatics where it multiplies inside phagocytes and eventually causes bacteraemia (bacterial infection of blood). Symptoms vary from
patient to patient but can include high fever, chills and sweating.
Worldwide brucellosis remains a major source of disease in humans and domesticated
animals. The incidence of brucellosis has decreased in North America and Western Europe.
However, it remains an important health problem in a number of other countries: the Middle
East, the Mediterranean, Mexico, Peru, some regions of China, the former USSR and India.
Some countries in the Middle East are experiencing an increasing incidence.
In humans, Br. melitensis is the most important clinically apparent disease. Pathogenicity is
related to the production of LPSs containing poly N‐formyl perosamine O chain, Cu─Zn
superoxide dismutase, erythrulose phosphate dehydrogenase, stress‐induced proteins related
to intracellular survival, and adenine and guanine monophosphate inhibitors of phagocyte
functions.
Prevention of brucellosis depends on the eradication or control of the disease in animal
hosts, hygienic precautions to limit exposure to infection through occupational activities and
the heat treatment of dairy and other potentially contaminated foods.
Box 4.8
Organism
Brucella species
Food source
Raw or unheated processed foods of animal origin, e.g. milk, milk products, cream, cheese, butter.
Onset of symptoms
Days to weeks.
Acute symptoms and chronic complications
Sweating, headache, lack of appetite, fatigue, fever.
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189
4.9 Yersinia enterocolitica
4.9.1 General description
There are three pathogenic species in the genus Yersinia, but only Y. enterocolitica and Y. pseudotuberculosis cause gastroenteritis. Yersinia pestis, the causative agent of ‘the plague’, is genetically very similar to Y. pseudotuberculosis but infects humans by routes other than food.
Yersinia enterocolitica, a small (1–3.5 × 0.5–1.3 μm) rod‐shaped, Gram‐negative bacterium,
is often isolated from clinical specimens such as wounds, faeces, sputum and mesenteric lymph
nodes. Young cultures are oval or coccoid cells. The organism produces peritrichous flagella
when it is grown at 25°C but not when grown at 35°C. The organism has an optimal growth
temperature of 30–37°C, however it is also able to grow on food at refrigeration temperatures
(8°C). Yersinia pseudotuberculosis has been isolated from the diseased appendix of humans.
Both organisms have often been isolated from such animals as pigs, birds, beavers, cats and
dogs. Only Y. enterocolitica has been detected in environmental and food sources, such as
ponds, lakes, meats, ice cream and milk. Most isolates have been found not to be pathogenic.
However pigs frequently carry serotypes that are capable of causing human disease.
4.9.2 Yersiniosis
Typical symptoms of foodborne yersiniosis:
• abdominal pain;
• fever;
• diarrhoea (lasting several weeks);
• other symptoms may include sore throat, bloody stools, rash, nausea, headache, malaise,
joint pain and vomiting.
Yersiniosis is frequently characterised by such symptoms as gastroenteritis with diarrhoea
and/or vomiting; however, fever and abdominal pain are the characteristic symptoms
(Tables 1.3 and 1.4). Yersinia infections mimic appendicitis and mesenteric lymphadenitis, but
the bacteria may also cause infections of other sites such as wounds, joints and the urinary
tract. The minimum infectious dose is unknown. Illness onset is usually between 24 and
Box 4.9
Organism
Y. enterocolitica
Food source
Pork products, cured or uncured, milk and dairy products.
Onset of symptoms
24–36 hours.
Acute symptoms and chronic complications
Abdominal pain, diarrhoea, mild fever, vomiting.
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48 hours after ingestion, although the maximum incubation period can be as long as 11 days.
Yersiniosis has been misdiagnosed as Crohn’s disease (regional enteritis) as well as
appendicitis.
There are four serotypes of Y. enterocolitica associated with pathogenicity O:3, O:5, O:8 and
O:9. The genes (inv and ail) encoding for invasion of mammalian cells are located on the chromosome, while a 40–50MDa plasmid encodes most of the other virulence‐associated phenotypes. The 40–50MDa plasmid is present in almost all the pathogenic Yersinia species and the
plasmids appear to be homologous. A heat‐stable enterotoxin has been isolated from most
clinical isolates; however, it is uncertain if this toxin has a role in the pathogenicity of the
organism.
Yersiniosis does not occur frequently. It is rare unless a breakdown occurs in food processing techniques. Yersiniosis is a far more common disease in Northern Europe,
Scandinavia and Japan than the USA. The major complication with the disease is the performance of unnecessary appendectomies, since one of the main symptoms of infections is
abdominal pain of the lower right quadrant. Both Y. enterocolitica and Y. pseudotuberculosis have been associated with reactive arthritis, which may occur even in the absence of
obvious symptoms. The frequency of such postenteritis arthritic conditions is about 2–3%.
Another complication is bacteraemia (entrance of organisms into the blood stream), in
which case the possibility of a disseminating disease may occur. This is rare, however, and
fatalities are also extremely rare.
The organism is resistant to adverse storage conditions (such as freezing for 16 months).
4.9.3 Sources and control
Yersinia enterocolitica is ubiquitous. It can be found in meats (pork, beef, lamb, etc.), oysters,
fish and raw milk. The exact cause of the food contamination is unknown. However, the prevalence of this organism in the soil and water and in animals such as beavers, pigs and squirrels
offers ample opportunities for it to enter the food supply. Infection by Y. enterocolitica is often
associated with ingestion of pork because pigs commonly harbour the pathogenic serotypes
O:3 and O:9. Recent foodborne outbreaks have been associated with pork products and pasteurised milk.
Poor sanitation and improper sterilisation techniques by food handlers, including improper
storage, cannot be overlooked as contributing to contamination. Therefore, primary control of
the organism would require changes to current slaughtering practice. Since the organism is
able to grow at refrigeration temperatures this is not an effective means of control unless
combined with the addition of preservatives. The low temperature growth and its presence on
raw produce does indicate that there is the potential for salad vegetables to act as vehicles of
yersiniosis in humans.
4.9.4 Outbreaks due to Y. enterocolitica
Y. enterocolitica O:9 outbreak, RTE salad, Norway, 2011 (MacDonald et al. 2012)
In 2011, an outbreak of Y. enterocolitica O:9 in Norway was linked to a RTE salad mix. As given
above, this is an unusual vehicle for this pathogen but plausible due to the organism’s growth
at low temperature and presence on raw produce.
Yersiniosis is a notifiable disease in Norway, and is the fourth most common cause of acute
bacterial enteritis with ~30 domestic cases reported annually (2010 incidence rate 0.5
cases/100 000 population). The majority (>98%) of cases are due to Y. enterocolitica serotype
O:3, which is also the dominant serotype in Europe, Japan and parts of North America.
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In the investigation, a confirmed case‐patient was defined as a person who had
a laboratory‐confirmed Y. enterocolitica O:9 infection that matched the MLVA
(Section 6.5.10) profile of the outbreak strain. The authorities identified 21 outbreak
cases, of whom 15 were female, and were geographically dispersed. Most cases reported
becoming ill between 7 February and 20 March. Using a case–control study the suspect
food was identified as a salad mix. This was traced to a single Norwegian company who
were then the subject of an environmental and traceback investigation, plus a review of
production and cleaning procedures.
The suspected salad mix contained four salad green types: arugula, radicchio rosso, iceberg
lettuce and endive. These ingredients were received unprocessed from 12 suppliers in two
European countries. Upon receipt, the greens were washed in two cold water baths, cut and
packaged. Radicchio rosso, a leaf chicory, was regarded as the most probable source of infection because it is stored for several months and was the only ingredient included in the suspected salad mix for which delivery, production and storage dates were consistent with the
outbreak period. The radicchio rosso was traced back to one of three possible growers in one
European country but the source of contamination could not be identified. The Norwegian
company voluntarily withdrew all salad mixes containing radicchio rosso from the market,
after which no new outbreak cases were reported.
4.10 Aeromonas hydrophila, A. caviae and A. sobria
4.10.1 General description
The genus Aeromonas was proposed in 1936 for rod‐shaped Enterobacteriaceae possessing a
polar flagellum. Since then there have been many taxonomic revisions and currently it forms
the family Aeromonadaceae. They are Gram‐negative, rod‐shaped, facultative anaerobic, non‐
spore‐forming bacteria, which are widely distributed in the soil and aquatic environments.
The Aeromonas genus includes psychrophiles and mesophiles, and is associated with various
diseases of warm‐ and cold‐blooded animals. Members of the genus are divided into three
Box 4.10
Organism
A. hydrophila
Food source
Seafood (fish, shrimp, oysters), snails, drinking water.
Onset of symptoms
24–48 hours.
Acute symptoms and chronic complications
Watery stools, stomach cramps, mild fever and vomiting.
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phenotypically differentiated groups: A. hydrophila, A. caviae and A. sobria. Currently, the
genus comprises 17 DNA hybridisation groups or genomospecies and 14 phenospecies. It is
associated with traveller’s diarrhoea.
4.10.2 A. hydrophila gastroenteritis
There is controversy as to whether A. hydrophila is a cause of human gastroenteritis. The
uncertainty is because volunteer human feeding studies (1011cell dose) have failed to demonstrate any associated human illness. However, its presence in the stools of individuals with
diarrhoea, in the absence of other known enteric pathogens, suggests that it has some role in
disease and has been included in this survey of foodborne pathogens. Similarly A. caviae and
A. sobria are putative pathogens associated with diarrhoeal disease, but as of yet they are
unproven causative agents.
General symptoms of A. hydrophilia gastroenteritis are:
• diarrhoea;
• abdominal pain;
• nausea;
• chills and headache;
• dysentery‐like illness;
• colitis;
• additional symptoms include: septicaemia, meningitis, endocarditis and corneal ulcers.
Two distinguishable types of gastroenteritis have been associated with A. hydrophila: a
cholera‐like illness with a watery (rice water‐like) diarrhoea and a dysenteric illness characterised by loose stools containing blood and mucus. The infectious dose of this organism
is unknown. Aeromonas hydrophila may spread throughout the body in the bloodstream
and cause a general infection in persons with impaired immune systems. Those at risk are
individuals suffering from leukaemia, carcinoma and cirrhosis, and those treated with
immunosuppressive drugs or who are undergoing cancer chemotherapy. Aeromonas
hydrophila produces a cytotonic enterotoxin(s), haemolysins, acetyl transferase and a phospholipase. Together these virulence factors may account for the organism’s pathogenicity.
The detection of genes responsible for Aeromonas virulence is a vital tool in establishing
the potential pathogenicity of the bacteria, as these virulence genes may act alone or in
synergy in the establishment of infections.
4.10.3 Sources and control
Aeromonas species have been isolated from fish, shellfish, meats, dairy products and fresh
vegetables. However, only a few foodborne outbreaks have been documented. Some studies
have shown that some motile Aeromonas species are becoming food and waterborne pathogens of increasing importance. They have been associated with several foodborne outbreaks
and are progressively being isolated from patients with traveller’s diarrhoea.
Aeromonas hydrophilia is present in all freshwater environments and in brackish water. It
has frequently been found in fish and shellfish and in market samples of red meats (beef, pork,
lamb) and poultry. The organism is able to grow slowly at 0°C. It is presumed that, given the
ubiquity of the organisms, not all strains are pathogenic. Some strains of A. hydrophila are
capable of causing illness in fish and amphibians as well as in humans, who may acquire infections through open wounds or by ingestion of a sufficient number of the organisms in food or
water. Aeromonas hydrophila may cause gastroenteritis in healthy individuals or septicaemia in
Bacterial foodborne pathogens
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individuals with impaired immune systems or various malignancies. Aeromonas caviae and
A. sobria also may cause enteritis in anyone or septicaemia in immunocompromised persons
or those with malignancies.
4.11 Plesiomonas shigelloides
4.11.1 General description
The Plesiomonas genus comprises a single species, Pl. shigelloides, which is classified in the
Family Plesiomonadaceae. Plesiomonas shigelloides is a facultatively anaerobic, rod‐shaped
Gram‐negative bacterium. Plesiomonas shares characteristics with both Vibrio and Aeromonas.
It also contains the Enterobacteriaceae common antigen.
4.11.2 Plesiomonas infections
Typical symptoms of Pl. shigelloides gastroenteritis:
• diarrhoea;
• abdominal pain;
• nausea;
• chills;
• low‐grade fever, headaches and vomiting.
The symptoms may begin 20–24 hours after consumption of contaminated food or water
and last from 1 to 9 days (Tables 1.3 and 1.4). Diarrhoea is watery, non‐mucoid and
non‐bloody. In severe cases, however, diarrhoea may be greenish‐yellow, foamy and
blood‐tinged.
The infectious dose is presumed to be quite high, at least greater than 1 million organisms.
The pathogenesis of Pl. shigelloides infection is not known. The organism produces a heat‐
stable cytotonic enterotoxin and possibly haemolysins, proteases and endotoxins. Its significance
as an enteric (intestinal) pathogen is presumed because of its predominant isolation from stools
of patients with diarrhoea.
Most Pl. shigelloides strains associated with human gastrointestinal disease have been from
stools of diarrhoeic patients living in tropical and subtropical areas. Such infections are rarely
reported in the US or Europe because of the self‐limiting nature of the disease. Subsequently it
may be included in the group of diarrhoeal diseases ‘of unknown aetiology’ which are treated
with and respond to broad spectrum antibiotics.
4.11.3 Sources and control
It has been isolated from freshwater, freshwater fish and shellfish, and from many types of animals including cattle, goats, swine, cats, dogs, monkeys, vultures, snakes and toads. Most human
Pl. shigelloides infections are suspected to be waterborne. The organism may be present in contaminated or untreated water that has been used as drinking water, and recreational water.
Plesiomonas shigelloides does not always cause illness after ingestion but may reside temporarily
as a transient, non‐infectious member of the intestinal flora. It has been isolated from the stools
of patients with diarrhoea, but is also sometimes isolated from healthy individuals (0.2–3.2%
of population). As with A. hydrophila, Pl. shigelloides is not a proven foodborne pathogen but
nevertheless has been included in this survey as a few studies have linked water and food
contamination with Pl. shigelloides gastroenteritis outbreaks (Claesson et al. 1994).
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The organism is ubiquitous in the environment. Most Pl. shigelloides infections occur in the
summer months and correlate with environmental contamination of freshwater (rivers,
streams, ponds, etc.). The usual route of transmission of the organism in sporadic or epidemic
cases is by ingestion of contaminated water or raw shellfish. Since the organism is heat‐sensitive,
the main means of control is the proper cooking of shellfish before ingestion.
4.12 Listeria monocytogenes
4.12.1 General description
Listeria are Gram‐positive, non‐spore‐forming bacteria. The genus is divided into 17 species, of
which L. monocytogenes is the species of primary concern with regard to food poisoning. Listeria
monocytogenes is classified into four major evolutionary lineages, 13 agglutination serotypes and
five molecular serotypes. They are motile by means of flagella. The organism has a growth range of
between 0–42°C. Therefore, L. monocytogenes can multiply slowly at refrigeration temperatures, in
contrast to most other recognised foodborne pathogens (see Table 2.8). They are less sensitive to
heat compared with Salmonella, and hence pasteurisation is sufficient to kill the organism.
Listeria monocytogenes has been found in at least 37 mammalian species, both domestic and
feral, as well as at least 17 species of birds and possibly some species of fish and shellfish. It is
plausible that 1–10% of humans may be intestinal carriers of L. monocytogenes. The majority
of those who succumb to severe listeriosis are individuals with underlying conditions that suppress their T‐cell‐mediated immunity. Another factor related to susceptibility is reduced gastric acidity as occurs on ageing, especially in those more than 50 years old. This may explain
the age distribution of listeriosis (Figure 4.14).
Phylogenetic analysis based on WGS of Listeria species has shown that the Listeria genus has
two main branches. One is composed of L. monocytogenes, L. innocua and L. welshimeri.
Whereas L. seeligeri and L. ivanovii form a second branch, with L. grayii distant from both
Box 4.11
Organism
L. monocytogenes
Food source
Soft‐ripened cheese, pâté, ground meat, poultry, dairy products, hot dogs and bologna-like sausages,
potato salad, chicken, seafood, vegetables.
Onset of symptoms
Few days to 3 weeks.
Acute symptoms and chronic complications
Influenza‐like symptoms, fever, severe headache, vomiting, nausea, sometimes delirium or coma.
Chronic symptoms: septicaemia in pregnant women, foetuses or neonates, internal or external
abscesses, meningitis, sepsis, septicaemia.
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Cases per 100 000
10
1
0.1
0.01
<1
1–10
11–
21–
31–
41–
51–
61–
20
30
40
50
60
70
Age (years)
Figure 4.14 Distribution of listeriosis with age. Source: Buchanan and Linqvist (2000).
branches. The natural habitat of the organism is probably soil and decaying plant material, and
it is transferred to humans and animals via ingestion of contaminated food. Those at particular
risk are immunocompromised individuals, pregnant women, neonates and the elderly. Only
two species are recognised as pathogenic: L. monocytogenes and L. ivanovii. They are both
facultative intracellular parasites, multiplying in macrophages and other normally non‐phagocytic
cells (epithelial and endothelial cells and hepatocytes). The organisms cause listeriosis, which
is an opportunistic infection of humans and animals with severe clinical symptoms such as
meningoencephalitis, abortion and septicaemia. Listeria monocytogenes has a host range of
mammals and birds. Whereas L. ivanovii is mostly pathogenic to ruminants. It is questionable
whether all strains of L. monocytogenes are able to cause human disease as epidemiological studies
have revealed that the 13 L. monocytogenes serovars vary in their ability to cause infections. About
98% of human cases are due to serovars 1/2a, 1/2b, 1/2c and 4b, with the latter causing >50% of
cases worldwide especially foeto‐maternal cases.
4.12.2 Listeriosis
Symptoms of listeriosis are:
• meningitis, encephalitis or septicaemia;
• when pregnant women are infected in the second and third trimester, it can lead to abortion,
stillbirth or premature birth.
The infective dose of L. monocytogenes is contentious. Listeria monocytogenes only rarely
infects healthy individuals. The majority of infections are of immunocompromised individuals,
and it has a high mortality rate (~20%). Whether there is an ingested dose that can be tolerated
by the healthy majority of the population is controversial.
There have been an increased number of reported cases of listeriosis in the EU. For example, in 2014 there were 0.52 cases per 100 000 persons, which corresponds to a 30% increase
compared with the previous year (EFSA 2016). Also the number of deaths increased to 210
(EFSA 2016). In contrast, in the US, the number of reported listeriosis cases was 0.26 and
0.24 cases per 100 000 for 2013 and 2014, respectively (Jackson et al. 2015; Pohl et al. 2019)
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(www.cdc.gov/listeria/outbreaks/index.html). In Canada, it is estimated that there are ~180
cases/year caused by L. monocytogenes. In 2008, 57 cases of listeriosis and 24 were linked to
contaminated delicatessen meat from one meat processing plant. Costs associated with the
cases (including medical costs, non‐medical costs and productivity losses) and those incurred
by the implicated plant and federal agencies responding to the outbreak were estimated to be
nearly CA$242 million (CA$ 2008). Case costs alone were estimated at approximately $2.8 million (CA$ 2008) including loss of life (Thomas et al. 2015).
There has been considerable debate with regard to whether all strains of L. monocytogenes
should be considered to be human pathogens and of equal public health relevance, or whether
just certain serovars should be controlled (Hof and Rocourt 1992). Similarly, different governmental agencies have different permissive levels of the organism in food, varying between
absence in RTE foods or <100 cfu/g. A more informed decision will be achievable through the
increasing application of high‐throughput sequencing, which is leading to improved typing
methods, identification of virulence determinants and determination of the organism’s mechanisms of pathogenesis and host–pathogen interactions. WGS is also being applied in surveillance and outbreak investigations (Sections 4.12.7 and 14.4.7).
The epidemiologically important serotypes are 1/2a (15–25% of cases), 1/2b (10–35% of
cases) and 4b (37–64% of cases). Outbreaks due to serotype 4b are significantly greater in
pregnancy cases, whereas serovar 1/2b is more common with non‐pregnant cases. Those at
greatest risk of listeriosis after consuming foods contaminated with L. monocytogenes are foetuses and neonates of an infected mother during pregnancy, the elderly and persons with
weakened immune systems. Invasive listeriosis is characterised by a high case‐fatality rate of
between 20 and 30%.
Listeria monocytogenes has one of the highest mortality rates amongst foodborne pathogens,
though fortunately its incidence is relatively low (Lomonaco et al. 2015). However, from 2008
to 2013, there was a significant increase (8.6%) in the incidence of listeriosis in Europe. In
2015, >2200 cases were reported in Europe. Then in 2017 the largest outbreak of L. monocytogenes occurred in South Africa, resulting in 1060 cases and 216 deaths (Section 14.4.7).
Consequently, L. monocytogenes is a serious re‐emergent pathogen of increasing public health
concern (de Noordhout et al. 2014; Lomonaco et al. 2015).
4.12.3 Lineages and typing L. monocytogenes
Many DNA sequence‐based typing approaches have been applied to L. monocytogenes. These
will be of increasing use as they will replace the PFGE method that has been the standard technique since 1996 and the establishment of PulseNet (Section 13.1.3). These have included
MLST and various expansions such as multi‐virulence locus sequence typing (MVLST), MLVA
and multi‐locus genotyping (MLGT) based on detection of a large array of SNPs on the chromosome
(Henri et al. 2017).
The DNA sequence‐based approach enables strains to be assigned to phylogenomic groups,
commonly referred to as ‘lineages’, which are in general congruent with strain clusters based
on serotype‐based approaches. Of the two major lineages that account for most strains implicated in human listeriosis, lineage I includes strains of serotype 1/2b, 3b 4b, 4d, 4e and 7,
whereas lineage II includes serotype 1/2a, 1/2c, 3a and 3c strains. Strains in the less common
lineage III have a propensity for animal infections and include serotypes 4a, 4c and certain
serotype 4b strains, while lineage IV (formerly designated as lineage IIIB) is even less common. Strains from foodborne epidemics and sporadic cases are in lineage I. Lineage II contains
human and animal cases and no foodborne epidemic strains, and lineage III only contains
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animal pathogens (Hain et al. 2007). There is a high degree of synteny in gene organisation and
content between Listeria species. A low occurrence of transposons and insertion sequence elements in the genomes are the reason for a lack of inversions and genome plasticity (Hain et al.
2007). Nelson et al. (2004) reported that 83 genes were unique to L. monocytogenes serotype
1/2a. This included three gene clusters encoding for carbohydrate transport and metabolism,
and an operon for the antigenic rhamnose substituents that are located in the serotype 1/2a cell
wall‐associated teichoic acid polymer. There were 51 genes unique to serotype 4b, and it lacked
insertion sequence elements. These differences probably contribute to the differences in pathogenicity and environmental survival. In general, the L. monocytogenes genomes encode for
intact glycolysis and pentose phosphate pathways, transportation and utilisation of a number
of simple and complex sugars. These traits are associated with the ability to grow in the natural
environment, and utilise a wide variety of carbohydrates.
MLST has been a popular genotyping method for L. monocytogenes and has revealed
associations between sequence type and source (Section 6.6.1). A major study of >6000
strains of clinical and food origin collected in France over a 9‐year period (2005–2013),
revealed 63 different CCs. Some of these STs were disproportionately represented amongst
clinical vs. food isolates (Maury et al. 2016). For instance, the serotype 4b (lineage I) CCs
1–4 (CC1, CC2, CC4 and CC6) were significantly more common amongst human clinical
isolates than amongst those from food, whereas the opposite was observed with the
most numerous CC, CC121, of serotype 1/2a (lineage II), which was significantly over‐
represented amongst food isolates. Furthermore, in CC4 71.3% of the isolates were of clinical
origin, whereas CC121 strains were primarily (93%) of food isolates (Maury et al. 2016). It
is therefore plausible that CC1, CC2, CC4 and CC6 have higher virulence for humans and
may be regarded as hypervirulent. In contrast, CC121, CC8/CC16 and CC9 may be
hypovirulent.
Listeria monocytogenes attaches to the intestinal mucosa, possibly α‐D‐galactose residues on
the bacterial surface bind to α‐D‐galactose receptors on the intestinal cells, and invades the
mucosal cells. This occurs in particular in the small intestine, either through the M cells overlaying the Peyer’s patches or through non‐specialised enterocytes. The bacteria are taken up by
induced phagocytosis, whereby the organism is engulfed by pseudopodia on the epithelial cells
resulting in vesicle formation. Listeria monocytogenes is encased in a vesicle membrane, which
it disrupts using listeriolysin O (responsible for the β haemolysis zone surrounding isolates on
blood agar plates). The organism also produces catalase and superoxide dismutase, which may
protect it from oxidative burst in the phagosome. Listeria monocytogenes also produces two
phospholipase C enzymes, which disrupt host cell membranes by hydrolysing membrane
lipids such as phosphatidylinositol and phosphatidylcholine. In the host cell cytoplasm the
bacterium multiplies rapidly (possibly doubling every 50 minutes). The organism moves
through the cytoplasm to invade adjacent cells by polymerising actin to form long tails
(Figure 4.15). This form of motility enables it to move at about 1.5 μm/second. The bacterium
produces protrusions into adjacent cells, enters its cytoplasm and repeats the cycle of escaping
the vacuole and multiplying.
Once the bacterium enters the host’s monocytes, macrophages or polymorphonuclear leukocytes it is bloodborne (septicaemic) and can grow. Its presence intracellularly in phagocytic
cells also permits access to the brain and probably transplacental migration to the foetus in
pregnant women. The pathogenesis of L. monocytogenes centres on its ability to survive and
multiply in phagocytic host cells. Listeriosis has a very high mortality rate. When listeric meningitis occurs, the overall mortality may be as high as 70%. Cases of septicaemia have a 50%
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The microbiology of safe food
Engulfment
into vacuole
Actin tail
formation
Invasion of
adjacent cell
Figure 4.15 Listeria monocytogenes infection of gut mucosal cells.
fatality rate, whereas in perinatal–neonatal infections the rate is greater than 80%. In infections
during pregnancy, the mother usually survives. Infection can be symptomless resulting in faecal excretors of infectious Listeria. Consequently ~1% of faecal samples are positive for L.
monocytogenes and ~94% of sewage samples.
4.12.4 Virulence factors
All virulence determinants identified so far are chromosomally located and not plasmid‐
borne. The virulence genes are localised on genetic islands (Section 2.5.2; Table 2.2). A 9‐kb
gene cassette associated with intracellular survival and cell‐to‐cell spread is known as the
Listeria pathogenicity island 1 (LIPI‐1) (Vazquez‐Boland et al. 2001). This was previously
known as the hly‐ and prfA‐virulence gene cluster. This region is found in all evolutionary
branches of Listeria, and is conserved in the core Listeria genome due to strong selective pressure. LIPI‐1 encodes for four genes. First, Hly, which is a pore‐forming toxin, and is also
known as listeriolysin O in L. monocytogenes. This toxin is in the cholesterol‐binding
‘thiol‐activated’ family. The PAI also encodes for ActA a surface protein causing the actin
polymerisation and protrusion into the adjacent cell; PlcB, a phospholipase C; and Mpl, a zinc‐
metalloenzyme. Mpl and PlcB are involved in the bacterium escaping from the vacuole following engulfment into a phagosome. Other virulence determinants are Clp stress tolerance
mediators (intraphagosomal survival), the Ami protein (cell attachment), a hexose phosphate
transporter (intracellular proliferation) and internalin proteins (internalisation of epithelial
cells). The latter contains a domain with a variable number of leucine‐rich repeats (LRRs),
which form a right‐handed helix called a parallel β‐helix. These are mostly found in eucaryotes
and mediate protein–protein interactions. In procaryotes they are associated with virulence
proteins: IpaH of Sh. flexneri and SspH1 and H2 of S. Typhimurium. Thirteen of the 25 L.
monocytogenes‐specific surface proteins (including all but two internalin proteins) are absent
in lineage III serovars 4a and 4c, which are animal and not human pathogens. Therefore, surface protein diversity may be linked to host range.
A second large (22‐kb) virulence gene cluster, LIPI‐2, has been found in L. ivanovii that is
not found in L. monocytogenes. It contains a sphingomyelinase gene and a large number of inl
genes. Since internalin proteins may be involved in cell and host tropism, their encoding in
this gene cluster may account for the more restricted host range of L. ivanovii to ruminants
compared with L. monocytogenes. The LIPI‐2 region is flanked by the tRNAarg and ydeI genes.
In contrast, L. welshimeri has a prophage inserted between these same two genes. Therefore,
this region may be a hot spot for genome alterations. Listeria welshimeri has a smaller genome
than other Listeria species, and has 482 fewer genes than L. monocytogenes. This is probably
Bacterial foodborne pathogens
199
the result of the loss of genes involved in virulence, intracellular survival and carbohydrate
metabolism.
There is generally high conservation of L. monocytogenes genes encoding known virulence
determinants amongst different strains, serotypes and lineages (Maury et al. 2016). Sequence
polymorphisms, while of subtyping potential, have generally not been correlated with differences in virulence. However, there are certain notable exceptions, which include (i) virulence‐
related sequences harboured by some, but not all strains and (ii) virulence‐associated
polymorphisms in conserved genes. Such differences in gene content can be determined from
WGS. For example:
1 The listeriolysin S Listeria pathogenicity island (Listeria pathogenicity island 3, LIPI‐3). In
L. monocytogenes, LIPI‐3 is present in the chromosome of strains in serotypes 1/2b and 4b,
but not other lineage I strains, and is not carried by other lineages.
2 The CC4‐specific Listeria pathogenicity island (Listeria pathogenicity island 4, LIPI‐4).
Listeria monocytogenes CC4 is regarded as one of the human‐hypervirulent clones due to
human clinical isolates being more frequently recovered (71.3%) than any other clones
(Maury et al. 2016). LIPI‐4 appears to be unique to CC4.
3 Genes encoding certain members of the large internalin protein family have strain‐specific
distribution.
4 Integrative chromosomal elements (ICEs) includes genes associated with the cadmium‐
resistance cadAC cassette are only found in relatively few L. monocytogenes genomes. The
fact that in at least certain lineage I strains the integration site of the ICE is occupied by
LIPI‐3 may partially contribute to the relative scarcity of the Tn916‐like ICE in L.
monocytogenes.
5 Prophage sequence content and prophage–chromosome junction sequences are variable
amongst different strains and this may affect virulence since prophage excision is induced
intracellularly, leading to enhanced escape from the vacuole and virulence.
6 Studies with CRISPRs revealed an ‘orphan’ CRISPR, rliB, which lacked a CRISPR‐associated
protein (cas gene) (Section 6.6.3). In the presence of type I A CRISPR‐cas, rliB, conferred
protection against invading phage DNA. However, type I A CRISPR‐cas only carried some
strains of L. monocytogenes.
7 In L. monocytogenes, the composition of cell wall teichoic acid (WTA) varies between the
different serotypes. In serogroup 1/2, phospho‐ribitol phosphate is glycosylated with rhamnose and N‐acetyl‐glucosamine, whereas serotype 4b, 4d and 4e the N‐acetyl‐glucosamine
is part of the backbone and is decorated with glucose and galactose moieties. The composition of the WTA appears to be linked to virulence, susceptibility to antimicrobial peptides
(AMPs) and phage.
Many naturally occurring L. monocytogenes strains used in animal studies to determine risk
potential are now recognised as encoding mutations in virulence‐associated genes. The main
gene of interest has been inlA, which encodes for the enterocyte invasion determinant
Internalin A, and the occurrence of premature stop codons (PMSCs). Internalin A encoded by
such alleles is truncated and does not locate at the organism’s cell surface as it lacks the terminal LPXTG motif required for anchoring into the cell wall. The absence of surface‐associated
InlA prevents the adherence of L. monocytogenes to the InlA receptor E‐cadherin. Known inlA
PMSCs have been incorporated in MLGT schemes, allowing simultaneous subtyping and inlA
PMSC detection (Ward et al. 2010). There the prevalence of mutations in virulence genes can
be determined from analysis of WGS data, and by sequence polymorphism analysis in MLGT
and other high‐throughput subtyping schemes.
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The microbiology of safe food
InlA alleles with PMSCs are often (>30%) found in serotype 1/2a, 1/2b and 1/2c (i.e. serogroup 1/2) isolates from foods and food processing environments, whereas most clinical isolates of the same serotypes expressed full‐length internalin A, thus indicating that PMSC
strains have impaired virulence. In contrast, PMSCs are very uncommon amongst serotype 4b
isolates, regardless of source.
Naturally occurring mutations inactivating genes in the PAI LIPI‐1 have been occasionally
found in isolates from foods and food processing plants. These mutations can result in altered
phenotypic traits such as non‐haemolytic or hyper‐haemolytic and constitutively over‐
producing LLO and lecithinase (PrfA‐controlled determinants). Again, these may affect the
strain’s virulence. For example, non‐haemolytic strains (due to mutations in hly or prfA)
are generally not implicated in invasive listeriosis. For an unknown reason, possibly linked
to fitness and survival in processing environment, clinical isolates are generally not
hyper‐haemolytic strains.
In L. monocytogenes iap (invasion‐associated protein) is a conserved gene encoding for a
60‐kDa extracellular protein (P60), which is essential for cell division. Mutations in this gene
result in rough (filamentous) variants that are considered attenuated in their virulence. Rough
mutants are infrequently detected in foods or food processing plants, and are not typically
recovered from invasive human listeriosis.
The above analysis of changes in strain phenotype has led to the proposal that food‐derived
strains with PMSCs in genes such as inlA should not be subjected to the same restrictions by
regulatory agencies as other L. monocytogenes strains. However, isolates with inlA PMSCs are
isolated, albeit rarely, from clinical cases of listeriosis and, from a practical viewpoint for
industry, controlling a species is more feasible than needing specialist typing facilities. The
detection of such mutant strains indicates the potential presence of other L. monocytogenes
strains and a general lack of control in the manufacturing process. Multiple L. monocytogenes
strains have been implicated in several common‐source listeriosis outbreaks: the 2011 cantaloupe‐associated outbreak, with three distinct clones of two different serotypes (1/2a and
1/2b), the 2014 caramel apple‐associated outbreak, with two distinct clones of the same serotype (4b) and the polony 2017 outbreak (serotype 4b, ST6) in South Africa (Section 14.4.7)
(Smith et al. 2019). In the caramel apple‐associated outbreak, evidence for coinfection was
obtained, albeit inadvertently (Chen et al. 2017).
4.12.5 Whole‐genome analysis of L. monocytogenes
Since 2013 there has been a considerable increase in sequencing of L. monocytogenes genomes
and there are now thousands of strains that have been whole‐genome sequenced. In the US,
the CDC validated the use of WGS in routine L. monocytogenes surveillance in illness, foods
and food processing plants as well as in outbreak detection and investigation. Now, in the US,
all L. monocytogenes isolates from patients, foods and other sources are subjected to WGS in
real time for surveillance purposes (Section 14.3.2).
Various DNA sequence‐based typing methods are used by different laboratories, both based
on conventional laboratory loci sequencing and WGS‐based typing schemes. These include
seven‐loci MLST, cg‐MLST, whole‐genome multi‐locus sequence typing (wgMLST), and
multi‐locus predicted protein sequence typing (MLPPST) and SNP. These methods are largely
congruent to each other, though the choice of reference strain is important in SNP analysis
(Henri et al. 2017).
Early whole‐genome studies analysed strains from different outbreaks (Nelson et al. 2004),
and also strains of the same epidemic clone obtained at different times from the same processing
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facility and from food–patient pairs. The studies confirmed the presence of recognised virulence genes in L. monocytogenes of different serotypes (1/2a, 4b) and clonal lineages. L.
monocytogenes strains may harbour islands with different sequence content at the same chromosomal locus, which appears to constitute a hotspot for the acquisition of new genes.
Different virulence‐associated genes were detected on some of these hotspot‐associated
islands.
Studies of outbreak‐related strains also revealed the presence of an accessory genome portion composed of unique genes and strain‐specific gene clusters. These included prophage
sequences, plasmids and unique chromosomal genes or gene cassettes of variable size (from
a few kb to almost 50 kb), such as the large (~50 kb) Listeria genome island, LGI1, of the
Canadian outbreak strain (CC8) (Cheng et al. 2010; Gilmour et al. 2010; den Bakker et al.
2013; Kuenne et al. 2013).
The persistence of L. monocytogenes in food processing environments increases the risk of
food contamination and listeriosis cases. The accessory genome included a few genes with
potential functions in virulence or strain persistence in a manufacturing environment. These
included (i) Tn916‐like ICEs with a cadAC cadmium resistance cassette; (ii) gene islands mediating resistance to chemical stressors or phage, such as resistance to cadmium (cadAC), quaternary ammonium disinfectant (e.g. benzalkonium chloride) (bcrABC) and triphenylmethane
dye (e.g. crystal violet, malachite green) (tmpA); and (iii) a novel, thermoregulated restriction‐
modification system that is mainly expressed at low temperature (≤30°C), which protects the
organism to phage when growing a low temperature.
In addition to bcrABC, there are at least two other unrelated genomic islands that are associated with quaternary ammonium disinfectant resistance in L. monocytogenes (Müller et al.
2014; Kovacevic et al. 2015). Such disinfectant‐resistant strains may be under selective pressure in food processing plants, and exposure to disinfectants may induce the expression of
virulence genes. Listeria genomic island 2 (LGI2) harbours multiple genes with putative heavy
metal (arsenic and cadmium) resistance functions.
The ability of L. monocytogenes ST121 to persist in the manufacturing environment may be
in part due to its carriage of a stress survival islet (SSI‐2). This may help the organism survive
alkaline and oxidative stresses that occur during food processing (Harter et al. 2017).
4.12.6 Sources and control of L. monocytogenes
Although the range of food products that may be contaminated by L. monocytogenes is broad,
human listeriosis cases are most strongly associated with RTE foods (Table 1.2). A zero‐
tolerance policy for the presence of L. monocytogenes in RTE foods has been mandated in the
US by the USDA and the FDA. While in the EU the zero‐tolerance criterion is only applied to
RTE to be consumed by infants or that is for particular medical purposes. Instead for RTE
foods, for those that can support the growth of the pathogen, a criterion of <100 cfu/g is given
during their shelf life or that it is absent in 25 g immediately before the product is delivered
for distribution. Furthermore, for RTE foods that do not support the growth of L. monocytogenes, the limit is 100 cfu/g during their shelf life. The Codex Alimentarius guidelines
provide analogous criteria on the application of general principles of food hygiene to the
control of L. monocytogenes in RTE foods – CAC/GL 61–2007 (CAC 2007, www.fao.org/
input/download/standards/10740/CXG_061e.pdf).
This ubiquitous bacterium has been isolated from various environments, including decaying vegetation, soil, animal feed, sewage and water. It is present in the intestinal tract of many
animals, including humans, and therefore can be found in faeces, sewage, soil and on plants
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that grow in these soils. The organism also grows on decaying plant materials, and can be
isolated from raw fruits and vegetables including cabbages, cucumbers, potatoes and radishes,
RTE salads, tomatoes and cucumbers, and bean sprouts, sliced cucumbers and leafy
vegetables.
Listeria monocytogenes is resistant to diverse environmental conditions and can grow at
temperatures as low as 3°C. It is found in a wide variety of foods, both raw and processed,
where it can survive and multiply rapidly during storage. These foods include supposedly pasteurised milk and cheese (particularly soft‐ripened varieties), meat (including poultry) and
meat products, raw vegetables, fermented raw‐meat sausages as well as seafood and fish products. Listeria monocytogenes is quite hardy and resists the deleterious effects of freezing, drying
and heat remarkably well for a bacterium that does not form spores. Its ability to grow at
temperatures as low as 3°C permits multiplication in refrigerated foods. The foods that pose
the highest risk are those which support the growth of L. monocytogenes, whereas foods that
pose the lowest risk of listeriosis are processed or have intrinsic or extrinsic factors that prevent
the growth of L. monocytogenes. For example, the pH of the food is ≤4.4, the water activity
≤0.92, or it is frozen. Listeria monocytogenes survives adverse environmental conditions longer
than many other non‐spore‐forming foodborne pathogens. It is more resistant to nitrite and
acidity, tolerates high salt concentrations and survives frozen storage for extended periods.
After ingestion, L. monocytogenes will be exposed to various stresses, but due to the food
processing and the manufacturing environment it may already have induced stress response
genes, which will include cross‐adaptation. Therefore, the organism may already be pre‐
adapted and expressing virulence‐related traits.
Listeria monocytogenes is responsible for opportunistic infections, preferentially affecting
individuals whose immune system is perturbed, including pregnant women, newborns and
the elderly. Listeriosis is clinically defined when the organism is isolated from blood, cerebrospinal fluid or an otherwise sterile site, i.e. placenta and foetus.
The CCFH (1999b; Section 12.4) has stated that a concentration of L. monocytogenes not
exceeding 100 organisms per gram of food at point of consumption is of low risk to the consumers. From cases contracted through raw or supposedly pasteurised milk, it is evident that
fewer than 1000 total organisms may cause disease. The incubation period is extremely wide
at 1–90 days.
The stomach acidity will reduce the viable number of cells, but it requires exposure times of
between 15–30 minutes to reduce L. monocytogenes numbers by 5‐log orders. Additionally,
ingested small liquid volumes of <50 ml may pass through the stomach because the pyloric
sphincter will not be stimulated to contract. Another factor affecting survival in the stomach
is the food matrix, especially the presence of fatty material.
Control measures:
• Heat treatment of milk (pasteurisation, sterilisation).
• Avoidance of cross‐contamination.
• Refrigeration (limited period) followed by thorough reheating.
• Avoidance of high‐risk products (e.g. raw milk) by high‐risk populations (e.g. pregnant
women).
Most cases of human listeriosis occur sporadically, without any apparent pattern. However
there are a number of foods that can support the growth of L. monocytogenes and are RTE and
have been associated with outbreaks or sporadic cases of listeriosis. These include soft cheese
made from unpasteurised milk, coleslaw and pâté. Outbreaks of listeriosis are often associated
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with a processing or production failure as illustrated below. A number of risk assessments for
L. monocytogenes are given in Section 11.3.
4.12.7 L. monocytogenes outbreaks
A large number of L. monocytogenes outbreaks are described here as they illustrate our
advances in understanding this foodborne pathogen, which emerged in the 1980s. There are
two additional outbreaks described in Section 14.4, which emphasise the application of high‐
throughput sequencing to outbreak investigations.
L. monocytogenes outbreak linked to cheese, Switzerland, 1983–1984
The reader may think this outbreak is rather ‘dated’ to be in this book, however it is of considerable significance due to the considerably raised public reaction (a.k.a. Listeria hysteria),
which brought Listeria very much to the fore as a foodborne pathogen for which greater control measures were required. Not only was this outbreak due to a food they had not normally
associated with food poisoning, but the link to infant deaths added to the very strong public
reaction.
Between January 1983 and March 1984, a cluster of 25 listeriosis cases were reported in the
same medical facility in Switzerland. This consisted of 14 adult and 11 maternal–foetal cases.
Fifteen other cases were reported in nearby hospitals. The epidemic was unusual as the patients
were otherwise healthy, and immunocompetent, yet there was high rate of encephalitis and the
mortality rate was 45%. Listeria monocytogenes serotype 4b was isolated for 92% of cases, and
there were two unique phage types. In the previous 6 years, only 44% were of these phage types.
This indicated the probability of a single source of infection. A further 16 cases were reported
the following November to April (1985).
Following the linking of a listeriosis outbreak in California to the consumption of a Mexican‐
style cheese, the Swiss health authorities surveyed a variety of dairy products for L. monocytogenes. The organism was isolated from 5/25 surface samples of a soft smear‐ripened cheese
called Vacherin Mont d’Or. This cheese was manufactured from October to March and was
primarily consumed in the outbreak area. The five isolates were serotype 4b, and two of the
phage types were identical to most of the clinical L. monocytogenes strains for the 1983–1986
period. Between 1983 and 1987, there were a total of 122 cases of listeriosis including 34 deaths
recorded in Switzerland. The bacterium was traced to the cellars, and wooden shelves that the
cheeses had been ripened in. After the cellars had been cleaned and the wooden shelves
replaced with metal ones, the number of L. monocytogenes in the cheese was considerably
reduced.
Chocolate milk, febrile gastroenteritis outbreak, US, 1994
In 1994, in the US, chocolate milk drunk at a summer picnic was contaminated with L.
monocytogenes serotype 1/2b, CC3, and resulted in febrile gastroenteritis. Later analysis
determined the levels of L. monocytogenes in the milk had grown to a very high level
(~109 cfu/ml) due to temperature abuse, following product contamination at the dairy.
The calculated dose of L. monocytogenes/person would have been in the order of 1011
cells. This is termed a febrile gastroenteritis outbreak, which typically occurs amongst
previously healthy adults due to foods with unusually high levels of L. monocytogenes.
Surprisingly, despite the wide distribution of the contaminated product, only three other
cases involving this strain were epidemiologically traced to the contaminated chocolate
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milk, two of whom were children aged 2 and 5. This possibly indicates the strain had low
pathogenicity.
Turkey deli meats outbreak (2002) and karoun cheese outbreak (2014)
In 2002, in the US a multi‐state outbreak of invasive listeriosis was traced to turkey deli meat
products contaminated with L. monocytogenes serotype 4b. MLST analysis showed the strains
were in CC6, meaning they have five or more loci in common with sequence type 6. Of particular note in this outbreak was that seven of the 54 cases (13%) lacked known predisposing
conditions. This CC6 clone is one of four that are regarded as hypervirulent for invasive human
invasive listeriosis based on epidemiological data from a large collection of strains in France,
as well as animal model data (Maury et al. 2016).
The CC6 was first identified in a hot dog‐associated outbreak in the US (1998–1999) and is
attributed to a significant portion of human listeriosis cases in the US, France and, more
recently, South Africa. Details of the 2002 turkey deli meat‐associated outbreak did not match
those of the later US outbreak of L. monocytogenes CC6, which was due to contaminated soft
cheese (Lomonaco et al. 2015). Further investigation using WGS retrospectively identified several earlier cases giving a total of 30 cases due to L. monocytogenes CC6 over a 5‐year (2010–
2015) period. It is plausible that these results indicate a low incidence of illness during the
long‐term release of contaminated product. Therefore, the CC6 strains may be a diversified
bacterial population with lower virulence than observed with previous CC6‐associated outbreaks before.
Delicatessen meat slicer, Canada, 2008 (Currie et al. 2015)
Beginning in the summer of 2008, the deaths of two Toronto nursing home residents were
attributed to listeriosis infections. In total, 57 cases of illness, across many provinces, were
detected, and there were 24 (42%) deaths. The outbreak was attributed to three similar strains
of L. monocytogenes based on PFGE. Forty‐one (72%) of 57 individuals were residents of long‐
term care facilities or hospital inpatients during their exposure period. PFGE analysis matched
strains from the cases with those from contaminated deli meat from a single production site.
This led to product recall, closure of the production facility and advice to the general public to
avoid serving or consuming certain brands of deli meat due to possible contamination with L.
monocytogenes. The source was traced back to the meat slicing equipment that had been inadequately cleaned and the residual material facilitated the colonisation and persistence of
Listeria.
Inspections revealed several aspects of concern with the parts of the production site especially those containing the RTE meat product: structural damage and poor maintenance with
water condensation dripping onto the unpackaged finished product in a common refrigerated
storage room. Prior to the outbreak, Listeria had been detected on environmental swabs of
food contact surfaces, and production equipment. The areas were sanitised inadequately, and
the source of the contamination was not traced. There was also employee movement between
areas, which could enable the cross‐contamination of finished product.
As given in Chapter 1, there is a considerable economic burden associated with foodborne disease and foodborne outbreaks in particular. The costs associated with this outbreak were estimated to be ~CA$242 million. This estimate includes medical and
non‐medical costs, and productivity losses, as well as costs incurred by the implicated plant
and federal agencies.
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Cantaloupe outbreak, USA, 2011
This US multi‐state outbreak of L. monocytogenes was attributed to five distinct strains and
resulted in a high number of deaths. This was the largest listeriosis outbreak investigated, with
147 cases and 33 deaths, prior to the outbreak in South Africa in 2017 (Section 14.4.7). Ninety‐
nine percent of the cases were hospitalised. Seven cases were related to pregnancy, being three
newborns and four pregnant women, and there was one miscarriage.
The route of infection was the consumption of cantaloupe grown at a farm in Colorado,
USA. Source tracing of the cantaloupes indicated that they came from a particular farm, and
were marketed from one region. These cantaloupes were distributed to at least 24 states.
Despite the CDC and FDA naming the source of the outbreak, and national news of a voluntary recall of this product, the outbreak continued and cantaloupes continued to cause illnesses and deaths for 47 days after the announcement of the likely source of the outbreak.
A second unusual aspect of this outbreak was that the outbreak was due to multiple strains
of serotypes 1/2a (CC7) and 1/2b (CC5), including members of two new clonal groups.
Commonly 12–66% of the cases in an outbreak are pregnancy‐related yet in this outbreak only
5% of the cantaloupe‐associated outbreak cases involved pregnancy. Additionally those
>60 years of age constituted an unusually high proportion (86%) of cases in this outbreak.
Together this suggests that the strains had limited invasive ability. CC7 is infrequent isolated
from either food (0.9%) or clinical isolates (2.9%).
L. monocytogenes 4b (CC1 and ST382), caramel apples, stone fruit, and packaged leafy green
salad, USA, 2014–2016 (Chen et al. 2017)
Three outbreaks in the US between 2014 and 2016, involving case‐patients in and outside the
United States, were linked to stone fruit, caramel apples and packaged leafy green salad.
Caramel apples, a vehicle not previously identified in listeriosis or any other foodborne
disease, were associated with 35 cases of listeriosis; 3 of those with meningitis were children
(5–15 years old) without known predisposing conditions whereas approximately one‐third (11
of the 35 illnesses) were pregnancy‐related.
The outbreak was due to two genetically distinct clones of serotype 4b. One was CC1, which
is well known for its frequent involvement in outbreaks and sporadic listeriosis and is regarded
as hypervirulent. The second was a previously rare genotype, ST382, and has limited genomic
divergence. However, from 2014 and 2016 there were also outbreaks of listeriosis due to L.
monocytogenes ST382 linked to stone fruit and packaged leafy green salad. Furthermore, the
ST382 strains were indistinguishable by PFGE.
The ST382 isolates were analysed by WGS. SNPs analysis clustered food, environmental and
clinical isolates within each outbreak, and also differentiated amongst the three outbreak
strains and epidemiologically unrelated ST382 isolates, which were indistinguishable by PFGE.
Listeria monocytogenes ST382 appears to be an emerging clone that began to diverge from its
ancestor in the 1980s.
Leafy vegetables, USA, 2016
A L. monocytogenes outbreak in 2016 that resulted in 19 hospitalisations and one death in the
USA was traced for the first time to leafy vegetables. The production facility temporarily suspended operations for 4 months. During this time health officials tried to find the source of L.
monocytogenes at the facility. The company suffered a $25 million financial loss, which was due
to the cost of recalling the products, and stopping production for 4 months.
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Long‐term multinational outbreak L. monocytogenes ST6 serogroup 4b, frozen raw vegetables,
2015–2018 (EFSA and ECDC 2018b)
This outbreak is believed to have begun in 2015 and lasted until it was detected in 2018. In total
the outbreak resulted in 47 cases, of which 18 were in 2018. Confirmed cases were in five
European countries (Austria, Denmark, Finland, Sweden, UK), and one in Australia. There
were 10 attributed deaths. For various reasons not all cases could be traced to the consumption
of raw vegetables, which were initially distributed frozen.
The outbreak was not detected until 2018 when comparisons were made of WGSs of clinical
L. monocytogenes strains that had been collected within the EU. The source of the outbreak
was traced back to a vegetable processing plant in Hungary, which was owned by a French
company. The produce was distributed to at least 107 countries across the EU and other countries including Australia, Canada and USA. The traceback was very complicated as some countries had reprocessed the original products into other products under different brands and
exported to other countries. Due to the scale of the situation, the investigation involved the
INFOSAN, the Early Warning and Response System (EWRS) and the Rapid Alert System for
Food and Feed (RASFF) (Section 13.1.6).
Products recalled were those produced between August 2016 and June 2018. The estimated
cost of the recall was $35 million (€30 million), which includes the costs for the product, transportation, handling, storage, destruction, subcontracting, lower cost absorption of the factory
and loss of margin. The outbreak was expected to continue past the recall date as the symptoms of listeriosis can take up to 70 days after ingestion of L. monocytogenes to develop. Also,
given many of the cases were identified retrospectively years after the event, the cases could
not recall what they had eaten, or had died before the investigation began.
The investigation began in November 2017, when Finland launched an urgent inquiry through
ECDC (Section 13.1.4) having identified three WGS‐confirmed clusters of L. monocytogenes
cases from different parts of the country. The largest WGS cluster was associated with L. monocytogenes serogroup IVb (which includes 4b), ST6, with 14 cases detected between January 2016
and January 2018. Furthermore, two of the cases had died due to or with the infection.
The ECDC and the members of the outbreak investigation team in the affected countries
agreed on a harmonised European outbreak case definition that took into account the different
molecular typing systems (cg‐MLST, wg‐MLST, SNP‐based analysis) for surveillance across
Member States. A confirmed outbreak case was defined as either:
1 A laboratory‐confirmed listeriosis patient with symptom onset on or after 1 January 2015 (date of
sampling or date of receipt by the reference laboratory if date of onset is not available) and fulfilling
the additional laboratory criterion with L. monocytogenes having less than seven core genome
MLST (cg‐MLST) allelic differences from the outbreak isolate based on cg‐MLST analysis, or
2 Fulfilled the additional laboratory criterion with L. monocytogenes within a five‐SNP cluster
from the outbreak isolate based on SNP analysis.
For both cg‐MLST and SNP analysis, the reference assembly was uploaded to ECDC.
By June (2018), a multi‐country foodborne outbreak has been verified in five countries,
involving 47 confirmed cases and nine deaths due to or with the infection. Cases were identified in Finland (23 cases), the UK (11 cases), Sweden (7 cases), Denmark (4 cases) and Austria
(2 cases). The median age of cases was 72 years, and 26 (55%) cases were female. In July (2018),
a fatal case in Australia was identified.
Listeria monocytogenes isolates from food, including those from the fridges of known cases,
were whole‐genome sequenced for comparison with the human outbreak strain. In total 29 L.
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monocytogenes isolates matched the multi‐country human cluster of L. monocytogenes 4b ST6
outbreak strains, and were from frozen raw vegetables (especially sweetcorn) that had originated
in Hungary. Also, L. monocytogenes strains matching the outbreak strain were isolated at the
Hungarian plant. The majority of the factory isolates were from 2017 season products: frozen
sweetcorn, frozen vegetable mixes including sweetcorn, frozen spinach and frozen green beans.
There was also one isolate from a frozen vegetable mix produced in 2016, and three isolates from
spinach products produced in 2018. In addition, two isolates were from two environmental samples (i.e. a floor drain at the packaging area) collected at different plants that were freezing and
handling frozen vegetables in France and Hungary during the 2017 and the 2018 production
seasons, respectively. Therefore, there was produce and environmental contamination. Isolating
indistinguishable strains over a 3‐year period indicates it was probably persisting in the environment of the processing plant after standard cleaning and disinfection procedures. Additionally,
cross‐contamination of several products could occur due to using contaminated production
lines for more than one product. Microbiological analysis showed contaminated frozen vegetables contained the outbreak‐related L. monocytogenes strain at ~50 cfu/g.
It should be noted that the producer considered the frozen raw vegetables as ‘non‐RTE’
food. Listeria monocytogenes is not a spore‐former. Therefore, had the contaminated frozen
raw vegetables been cooked (70°C, 2 minutes) before consumption, the Listeria would have
been killed. However, they may be eaten raw without any cooking by using the thawed vegetables in salads. It is known that L. monocytogenes can grow on thawed vegetables at refrigeration
temperatures therefore increasing the ingested dose (Kataoka et al. 2017). Other routes of
infection could be through making smoothie drinks, or inadequate cooking due to cold spots
during microwave cooking.
The large 2017 polony sausage outbreak in South Africa with >200 deaths is considered in
detail in Section 14.4.7 (Smith et al. 2019).
4.13 Staphylococcus aureus
4.13.1 General description
Staphylococcus aureus is a Gram‐positive spherical bacterium (coccus), which occurs in pairs,
short chains or bunched, grape‐like clusters. The organism was first described in 1879. The
organism is a facultative anaerobe and is divided into a number of biotypes on the basis of
biochemical tests and antibiotic resistance patterns. The biotypes are then further divided
according to phage typing, serotyping, plasmid analysis and ribotyping. Staphylococcus aureus
produces a wide range of pathogenicity and virulence factors: staphylokinase, hyaluronidases,
phophatases, coagulases and haemolysins. Food poisoning is due to the consumption of staphylococcal enterotoxins.
4.13.2 Infections associated with St. aureus
Symptoms of staphylococcal food poisoning are a rapid onset of:
• nausea;
• vomiting;
• abdominal cramps.
The onset of symptoms in staphylococcal food poisoning is usually rapid within hours
of ingestion (Tables 1.3 and 1.4). The symptoms can be very acute, depending on individual
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Box 4.12
Organism
St. aureus
Food source
Workers handling foods, meat (especially sliced meat) poultry, fish, canned mushrooms, dairy
products, prepared salad dressing, ham, salami, bakery items, custards, cheese.
Onset of symptoms
1–7 hours.
Acute symptoms and chronic complications
Severe nausea, abdominal cramps, vomiting, retching, prostration, often with diarrhoea.
susceptibility to the toxin, the amount of contaminated food eaten, the amount of toxin in the
food ingested and the general health of the victim. The most common symptoms are nausea,
vomiting and abdominal cramping. Some individuals may not always demonstrate all the
symptoms associated with the illness. In severe cases, headache, muscle cramping, and transient changes in blood pressure and pulse rate may occur. The illness is usually self‐limiting
and generally takes 2–3 days to recover. Severe cases will take longer.
4.13.3 Virulence factors
Food poisoning is specifically caused by enterotoxins. The enterotoxins are low molecular weight
proteins (26000–34000 Da), which can be differentiated by serology into a number of antigenic
types (SEA to SEE, and SEG to SEQ), with three variants of SEC. A toxin previously designated
enterotoxin F is now recognised as being responsible for toxic shock syndrome and not enteritis.
Staphylococcal enterotoxins are heat‐stable and are able to withstanding boiling for many hours,
and therefore they present a health risk as they are not denatured during cooking. Bioinformatic
analysis of their protein sequences reveals a close phylogenetic relationship between the enterotoxins. The sequences can also be used to search databases (BLAST searching) for similar toxin
sequences in other organisms. As shown in Figure 2.6, there are similarities between the enterotoxins
of St. aureus and the streptococci PTs. Phylogenetic analysis reveals three main groups: one group is
composed of SEA, SEE, SEP and more distantly related SEJ, with SED, and SEN and SEO, with SEH
as an outlier to the group. The second group contains SEB, SEC and SEG, as well as streptococcal PT
A and Streptococcus pyogenes superantigen SSA. The third group includes SEI, SEK, SEL, SEM
andSEQ, with streptococcal pyrogenic exotoxin C as an outliner to the group.
SEA is the most common toxin associated with staphylococcal food poisoning (~77% of outbreaks), and is carried by a temperate bacteriophage. The second most common is SED (38%) and
the third is SEB (10%). These toxins are highly heat‐stable (D98.9 ≥2 hours), resistant to cooking
and proteolytic enzymes. They are gastrointestinal toxins, as well as superantigenic, and stimulate
monocytes and macrophages to produce cytokines. These two functions are localised on separate
domains of the toxin. They share a common sequence (and hence phylogenetic relationship) with
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streptococcal pyrogenic exotoxins (see Section 2.5.1). These toxins have been associated with toxic
shock syndromes and food poisoning, as well as allergenic and autoimmune diseases.
4.13.4 Sources and control
Staphylococci exist in air, dust, sewage, water, milk and food, or on food equipment, environmental surfaces, humans and animals (Table 1.2). Humans and animals are the primary reservoirs. Staphylococci are present in the nasal passages and throats and on the
hair and skin of 50% or more of healthy individuals. This incidence is even higher for
those who associate with or who come into contact with sick individuals and hospital
environments. Although food handlers are usually the main source of food contamination
in food poisoning outbreaks, equipment and environmental surfaces can also be sources
of contamination with St. aureus.
Human intoxication is caused by ingesting enterotoxins produced in food by some strains of
St. aureus, usually because the food has not been kept hot enough (60°C, 140°F, or above) or
cold enough (7.2°C, 45°F, or below). Foods that are frequently incriminated in staphylococcal
food poisoning include meat and meat products; poultry and egg products; salads such as egg,
tuna, chicken, potato, and macaroni; bakery products such as cream‐filled pastries, cream pies,
and chocolate éclairs; sandwich fillings; and milk and dairy products.
Foods that require considerable handling during preparation and that are kept at slightly
elevated temperatures after preparation are frequently involved in staphylococcal food
poisoning.
The organism competes poorly with other bacteria and therefore rarely causes food poisoning in a raw product. Similarly, St. aureus can be isolated from fresh produce, and RTE vegetable salads, but because it does not compete well with other micro‐organisms present, spoilage
will normally occur before the development of sufficiently high populations of St. aureus
needed for production of staphylococcal enterotoxin.
Since the staphylococcal toxin is very heat‐stable it cannot be inactivated by standard cooking regimes. Therefore, avoiding contamination of food by the organism and maintaining low
temperatures is used to eliminate the microbial load.
A toxin dose of <1.0 μg/kg (300–500 ng) in contaminated food will produce symptoms
of staphylococcal intoxication. This amount of toxin is produced by 105 organisms per
gram. The resistance to heat and proteolysis in the intestinal tract means that it is important that foods which may have supported the growth of St. aureus are tested for toxin
after heat processing (and subsequent bacterial cell death). A comparison of characteristics for St. aureus growth and toxin production is given in Table 4.6. The organism is
quickly killed by heat (D65.5 = 0.2–2.0 minutes) but is resistant to drying and is salt‐tolerant
(see Tables 2.3 and 2.8).
Table 4.6 Conditions for Staphylococcus aureus growth and toxin production.
Parameter
Growth
Toxin production
Temperature (°C)
pH
Water activity
7–48
4–10
0.83–0.99
10–48
4.5–9.6
0.87–0.99
Note: To convert to °F use the equation °F = (9/5) °C + 32.
As a guidance: 0 °C = 32 °F, 4.4 °C = 40 °F, 60 °C = 140 °F.
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Box 4.13
Organism
Cl. perfringens and Cl. botulinum
Onset of symptoms
Cl. perfringens: 8–22 hours.
Cl. botulinum: 18–36 hours.
Food source
Cl. perfringens: meat, meat stews, meat pies, and beef, turkey and chicken gravies, beans, seafood.
Cl. botulinum: improperly canned or fermented goods.
Acute symptoms and chronic complications
Intense abdominal cramps, diarrhoea, nausea. Chronic symptoms: gas gangrene, necrotising
enteritis.
4.14 Clostridium perfringens
4.14.1 General description
There are four clinically important Clostridium species: Cl. botulinum, Cl. perfringens, Cl. difficile and Cl. tetani. However, only Cl. botulinum and Cl. perfringens cause food poisoning.
Clostridium perfringens is an anaerobic, Gram‐positive spore‐forming rod. ‘Anaerobic’ means
the organism is unable to grow in the presence of free oxygen. It was first associated with
diarrhoea in 1895, but the first reports of the organism causing food poisoning were in 1943.
It is widely distributed in the environment and frequently occurs in the intestines of humans
and animals. Spores of the organism persist in soil, sediments and areas subject to human or
animal faecal pollution.
4.14.2 Cl. perfringens infections
Clostridium perfringens causes two very different types foodborne diseases due to the production of one or more toxins. The organism can produce over 13 different toxins, but each strain
only produces a subset. There are five types (A–E) of Cl. perfringens, which are divided according to the presence of the major lethal toxins of which three are plasmid‐borne (Table 4.7).
Clostridium perfringens types A, C and D are human pathogens, whereas types B, C, D and E
are animal pathogens. The acute diarrhoea caused by Cl. perfringens is due to the production
of α‐toxin, an enterotoxin (Sakurai et al. 2004). A more serious but rare illness is also caused
by ingesting food contaminated with type C strains. The latter illness is known as enteritis
necroticans jejunitis or ‘pig‐bel disease’ and is due to the β‐exotoxin.
Characteristics of perfringens food poisoning are:
• abdominal pain;
• nausea;
• acute diarrhoea;
• symptoms appear 8–12 hours after ingestion of organism.
Bacterial foodborne pathogens
211
Table 4.7 Typing of Clostridium perfringens according to the presence of toxins and enterotoxin.
Cl. perfringens type
α‐toxin
β‐toxin
ε‐toxin
l‐toxin
Enterotoxin
A
B
C
D
E
Location
+
+
+
+
+
Chromosome
−
+
+
−
−
Plasmid
−
+
−
+
−
Plasmid
−
−
−
−
+
Plasmid
+
+
+
+
+
Chromosome/plasmid
The common form of Cl. perfringens poisoning is characterised by intense abdominal cramps
and diarrhoea, which begin 8–12 hours after consumption of foods containing large numbers
of those Cl. perfringens bacteria capable of producing the food poisoning toxin (Tables 1.3 and
1.4). The illness is usually over within 24 hours but less severe symptoms may persist in some
individuals for 1 or 2 weeks. A few deaths have been reported as a result of dehydration and
other complications. In most instances, the actual cause of poisoning by Cl. perfringens is
temperature abuse of prepared foods. Meats, meat products and gravy are the foods most
frequently implicated (Table 1.2). Small numbers of the organisms are often present as spores
after cooking. The spores germinate and the clostridia multiply to food poisoning levels during
the cooling period and storage. The cooking process drives off oxygen hence creating an
anaerobic environment favourable to clostridial growth. After ingestion the enterotoxin is produced in the intestine, after the organism has passed through the stomach. The enterotoxin is
associated with sporulation, possibly induced due to the acidic environment of the stomach.
The enterotoxin is a heat‐sensitive protein 36 000 Da in size. It is destroyed by heat (D90 value
is 4 minutes) and a few cases of food poisoning due to ingestion of the toxin have been reported.
Necrotic enteritis caused by Cl. perfringens is often fatal. This disease also begins as a result
of ingesting large numbers (>108) of Cl. perfringens type C in contaminated foods. Deaths from
necrotic enteritis (pig‐bel syndrome) are caused by infection and necrosis of the intestines and
from resulting septicaemia.
4.14.3 Sources and control
The ubiquitous nature of Cl. perfringens and its spores make it a common problem in food production. The isolation of low numbers of Cl. perfringens from food does not necessarily mean that a food
poisoning danger exists. Only when large numbers are present is there a definite hazard and therefore enumeration techniques are essential for this organism. Although the Cl. perfringens vegetative
cell is killed by chilling and freezing, the spore form may survive. Further details on the detection of
clostridia and growth characteristics are given in Tables 2.3 and 2.8. Control of the organism is
mainly achieved through the cooking and cooling steps. Rapid cooling through the temperature
range 55–15°C reduces the opportunity for any surviving clostridia spores to germinate. Thorough
reheating of food to 70°C immediately before consumption will kill any vegetative cells present.
4.15 Clostridium botulinum
4.15.1 General description
Clostridium botulinum is a Gram‐positive rod‐shaped strict anaerobe (0.3–0.7 × 3.4–7.5 μm)
with peritrichous flagella. It causes the foodborne illness called ‘botulism’. This is a food intoxication due to the ingestion of preformed neurotoxins. The organism is ubiquitous in nature,
including soil, fish, raw fruits and vegetables.
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Table 4.8 Distinguishing characteristics of Clostridium botulinum.
Group
Toxin produced
Proteolysis
Lipolysis
Glucose fermentation
Mannose fermentation
Minimum growth temp. (°C)
Salt inhibition (%)
Volatile fatty acids produceda
I
II
III
IV
A, B, F
+
+
+
−
10–12
10
Ac, iB, B, iV, Ph
B, E, F
−
+
+
+
3.3
5
A, B
C1, C2, D
+ or −
+
+
+
15
3
A, P, B
G
+
−
−
−
12
>3
A, iB, iV, Pa
Ac, acetic acid; iB, isobutyric acid; B, butyric acid; iV, isovaleric acid; Ph, phenylpropionic acid; Pa,
phenylacetic acid.
a
4.15.2 Cl. botulinum intoxication
There are seven types of Cl. botulinum: A, B, C, D, E, F and G. These are differentiated on the basis
of toxin antigenicity (Table 4.8). Types A, B, E and F are the main causes of human botulism (types
C and D in animals). Eight serologically distinct neurotoxins (BoNTA to BoNTG) have been
identified and are amongst the most potent toxins known to man. The toxin is made of two proteins, fragment A (light chain, LC, 50 kDa) and fragment B (heavy chain, HC, 100 kDa), which are
linked by a disulphide bridge (Figures 2.8 and 2.9). The LC is responsible for the toxin’s effect on
nerve cells. The HC contains the membrane translocation domain and the toxin receptor‐binding
moiety. The organism forms spores, which may become airborne and contaminate open jars or
cans. Once sealed the anaerobic conditions favour spore outgrowth and the production of toxins.
Symptoms of botulism are:
• double vision;
• nausea;
• vomiting;
• fatigue;
• dizziness;
• headache;
• dryness in the throat and nose;
• respiratory failure.
The onset of the symptoms is from 12 to 36 hours after ingestion of the bacterial toxins.
Botulinum toxins block the release of the neurotransmitter acetylcholine, which results in
muscle weakness and subsequently paralysis. The illness may last from 2 hours to 14 days
depending upon dose and vulnerability of host. The fatality rate is ~10%.
4.15.3 Sources and control
Botulism is associated with canned (especially home canned) low‐acid foods, vegetables,
fish and meat products. It is also associated with honey and hence honey should not be given
to children under 1 year old. Infant botulism is milder than the adult version. The spores
germinates in the intestinal tract and the bacterium produces the toxins causing ‘floppy baby
syndrome’. A comparison of foodborne botulism and infant botulism is shown in Figure 4.16.
Heat‐treating low‐acid canned foods to 121°C for 3 minutes or equivalent will eliminate the
Cl. botulinum spores. Clostridium botulinum cannot grow in acid or acidified foods with a pH
<4.6 (Tables 2.3 and 2.8). Botulism has been linked to coleslaw prepared from packaged, shredded
Bacterial foodborne pathogens
Foodborne botulism
213
Infant botulism
Cl. botulinum in food spores
Toxin produced
Infant ingestion of Cl. botulinum
Cl. botulinum multiplies in the colon
Toxin ingested
Toxin produced
Absorbed quickly from stomach
Absorbed slowly from colon
Toxin in bloodstream
Attacks peripheral neurons causing flaccid paralysis
Nausea
Headache
Vomiting
Double vision
Headache
Slurred speech
Double vision
Lacks muscle rigour
Slurred speech
Constipation
Possible death
Figure 4.16 Clostridium botulinum intoxication.
cabbage and chopped garlic in oil. The continued metabolism of packed salad vegetables can
result in an anaerobic environment supporting the growth of Cl. botulinum and toxin production. Therefore, the permeability packaging films must minimise the possible development of
anaerobic conditions. An additional control measure is storage at <3 °C.
4.16 B. cereus group
4.16.1 General description
Bacillus cereus is a Gram‐positive, facultatively aerobic spore‐former that was first isolated in
1887. It is ubiquitous in nature, being isolated from soil, vegetation and fresh water. The spores
can survive many cooking processes. The organism grows well in cooked food because of the
lack of a competing microflora. While it is commonly found at low levels in food (<102 cfu/g),
which is considered acceptable, food poisoning outbreaks occur when the food has been subjected to time–temperature abuse sufficient for the low level of organisms to multiply to a
significant (intoxication) level (>105 cfu/g).
The B. cereus group, also known as B. cereus sensu lato, consists of Gram‐positive, rod‐
shaped, spore‐forming aerobic bacteria that are widespread in natural environments. It
comprises at least 11 closely related species: B. anthracis, B. cereus, B. thuringiensis,
B. mycoides, B. pseudomycoides, B. weihenstephanensis, B. cytotoxicus, B. toyonensis,
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Box 4.14
Organism
B. cereus
Onset of symptoms
Diarrhoeal: 6–15 hours.
Emetic: 0.5–6 hours.
Food source
Diarrhoeal: meats, milk, vegetables and fish.
Emetic: rice products, starchy foods (e.g. potato, pasta and cheese products).
Acute symptoms and chronic complications
Diarrhoeal: watery diarrhoea, abdominal cramps and pain.
Emetic: nausea and vomiting.
B. gaemokensis, B. manliponensis and B. bingmayongensis – the latter five species being
recently described. Members of the B. cereus group have a significant impact on human
health, agriculture and the food industry. For example, B. anthracis is the aetiological
agent of anthrax – its virulence being due to the presence of two large plasmids, pXO1 and
pXO2. The pXO1 plasmid controls the production of the three anthrax oedema and lethal
toxins: the oedema factor, the protective antigen and the lethal factor. The pXO2 plasmid
encodes for the capsule, which protects the organism from the host’s immune system.
Bacillus thuringiensis strains usually have plasmid‐encoded cry genes for the large insecticidal crystal protein Cry. Bacillus cereus is an opportunistic pathogen that often causes
two forms of food poisoning, characterised by either nausea and vomiting or abdominal
pain and diarrhoea depending upon the toxigenic strain.
Bacillus cereus is widespread in the environment, being found on inert as well as on living surfaces. It is also able to persist in the environment of food production plants. Its
ability to form biofilms is highly likely to contribute to its ubiquitous distribution and
persistence. Bacillus cereus produces a variety of biofilms, which differ in their architecture
and mechanism of formation. The variation is possibly an adaptation to the various
environments where it occurs. Depending on the strain, B. cereus has the ability to grow
as immersed or floating biofilms. It can secrete within the biofilm a range of metabolites,
surfactants, bacteriocins, enzymes and toxins. The biofilm may contain vegetative cells
and spores that, along with the EP capsule in the biofilm, will increase its resistance to
antimicrobials and to cleaning procedures.
4.16.2 B. cereus foodborne infections
There are two recognised types of B. cereus food poisoning: diarrhoeal and emetic (Table 4.9).
Both types of food poisoning are self‐limiting and recovery is usually within 24 hours. Bacillus
cereus produces the diarrhoeal toxins during growth in the human small intestines, whereas
the emetic toxins are preformed on the food.
Bacterial foodborne pathogens
215
Table 4.9 Characteristics of food poisoning caused by Bacillus cereus.
Emetic syndrome
Diarrhoeal syndrome
Infective dose
Toxin produced
Type of toxin
105–108 cells/g
Preformed
Cyclic peptide (1.2 kDa)
105–107 total
Produced in the small intestine
Three protein subunits (L1, L2, B; 37–105 kDa)
Toxin stability
Very stable (126°C, 90 minutes;
pH 2–11)
0.5–6 hours
6–24 hours
Abdominal pain, watery
diarrhoea, nausea
Inactivated at 56°C, 30 minutes
Fried and cooked rice, pasta,
noodles and potatoes
Meat products, soups, vegetables, fish,
puddings, sauces, and milk and dairy products
Incubation period
Duration of illness
Symptoms
Foods most frequently
implicated
8–24 hours
12–24 hours
Nausea, vomiting and malaise, watery
diarrhoea
Source: Adapted from Granum and Lund (1997).
Symptoms of B. cereus diarrhoeal food poisoning are:
• watery diarrhoea;
• abdominal cramps and pain;
• nausea, rarely vomiting.
The symptoms of B. cereus diarrhoeal type food poisoning mimic those of Cl. perfringens food
poisoning. The onset of watery diarrhoea, abdominal cramps and pain occurs 8–24 hours after
consumption of contaminated food. Nausea may accompany diarrhoea, but vomiting (emesis)
rarely occurs. Symptoms persist for 24 hours in most instances during which time the organism is excreted in large numbers.
Symptoms of B. cereus emetic food poisoning are:
• nausea;
• vomiting;
• abdominal cramps and diarrhoea may occur.
The emetic type of food poisoning is characterised by nausea and vomiting within 0.5–6 hours
after consumption of contaminated foods. Occasionally, abdominal cramps and/or diarrhoea
may also occur. Duration of symptoms is generally less than 24 hours. The symptoms of this
type of food poisoning resemble those caused by St. aureus foodborne intoxication. Some
strains of B. subtilis and B. licheniformis have been isolated from lamb and chicken incriminated in food poisoning episodes. These organisms demonstrate the production of a highly
heat‐stable toxin, which may be similar to the vomiting type toxin produced by B. cereus.
4.16.3 Virulence traits
A wide variety of toxins have been identified:
• diarrhoeal enterotoxin;
• emetic toxin;
• haemolysin I;
• haemolysin II;
• phosphatase C.
The diarrhoeal type of illness is caused by a large molecular weight protein composed of three
subunits (L1, L2 and B; 37–105 kDa) (Table 4.9). This toxin is inactivated at 56°C for 30 minutes. The vomiting (emetic) type of illness is caused by a low molecular weight (1.2 kDa),
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The microbiology of safe food
heat‐stable cyclic peptide. It is similar to the potassium ionophore valinomycin in that it is
ring‐shaped with three repeating units of the amino and/or oxy acids ‘‐D‐O‐leucine‐D‐alanine‐
O‐valine‐L‐valine‐’. It is very resistant to heat (126°C for 90 minutes) and pH values 2–11. It is
produced in the stationary phase of growth, but it is uncertain if its production is linked with
spore formation.
Bacillus cereus can secret three enterotoxins (Hbl, Nhe and CytK), several other toxins (haemolysins HlyI and HlyII) and degradative enzymes (phospholipases and proteases). These are
either secreted or directed to the cell surface. Their expression is primarily controlled by the
PlcR transcriptional activator, which is one of the numerous B. cereus quorum‐sensing systems, which enable the bacterium to adapt to environmental changes. The adaptive properties
of B. cereus is also a consequence of the presence, within the bacterium, of a number of plasmids (2–500 kb range).
4.16.4 Sources and control
Because of their clinical and commercial importance, the identification and taxonomy of the
isolates within the B. cereus group is very important, and has been studied for many years using
both phenotyping and genotyping techniques. The principal approach has been a mixture of
16S rRNA gene sequencing along with the presence or absence of virulence plasmids, colonial
morphology, psychrophilic or thermotolerant ability, and clinical symptoms (B. cereus, vomiting‐ and diarrhoeal‐type food poisoning). However, the group has been strikingly resistant to
any type of satisfactory classification. The identification and phylogenetic relationships of bacteria within the B. cereus group are controversial. The pXO plasmids and cry genes were widely
distributed, suggesting little correlation with the phylogenetic positions of the host bacteria.
Hence the presence of plasmids such as pXO1 and pXO2, and the cry encoding plasmids, cannot
serve as definitive traits for B. anthracis or B. thuringiensis. This might explain why classifications based on virulence characteristics have proved unsatisfactory in the past.
Bacillus cereus cells are large rods and the spores do not swell the sporangium. These and
other characteristics, including biochemical features, have been used to differentiate and
confirm the presence of B. cereus. However, these characteristics are shared with B. cereus var.
mycoides, B. thuringiensis and B. anthracis. Differentiation of these organisms depends upon
determination of motility (most B. cereus are motile), presence of toxin crystals (B. thuringiensis), haemolytic activity (B. cereus and others are β‐haemolytic whereas B. anthracis is usually
non‐haemolytic) and rhizoid growth, which is characteristic of B. cereus var. mycoides. Bacillus
subtilis and B. licheniformis have been proposed as food poisoning organisms but the evidence
to date is not complete. Nevertheless the UK HPA RTE guidelines do include them in its sampling plan (Section 7.10).
Characteristics of temperature and water activity growth range and D values are given in
Tables 2.3 and 2.8. Isolation methods are covered in Section 6.7.13.
Sources:
• ubiquitous: soil, vegetation, meat, milk, water, rice, fish.
A wide variety of foods including meats, milk, vegetables and fish have been associated with
the diarrhoeal type food poisoning (Table 1.2). The vomiting type outbreaks have generally
been associated with rice products; however, other starchy foods such as potato, pasta and
cheese products have also been implicated. Food mixtures such as sauces, puddings, soups,
casseroles, pastries and salads have frequently been incriminated in food poisoning outbreaks.
The presence of large numbers of B. cereus (>106 organisms/g) in a food is indicative of active
growth and proliferation of the organism and is consistent with a potential hazard to health.
Bacterial foodborne pathogens
217
Since the organism is ubiquitous in the environment low numbers commonly occur in food.
Therefore, the main control mechanism is to prevent spore germination and multiplication in
cooked, RTE foods. Storage of foods below 10°C will inhibit B. cereus growth.
Control measures:
• Temperature control to prevent spore germination and outgrowth.
• Storage temperature either >60°C or <10°C, unless other parameters (i.e. pH, aw) prevent
bacterial growth.
• Avoid storage of pre‐cooked foods.
4.17 Enterococcus and Streptococcus species
4.17.1 General description
The Enterococcus and Streptococcus genera are composed of Gram‐positive, microaerophilic
cocci (round), catalase negative, which are non‐motile and occur in chains or pairs. They do
not form spores. They undergo homofermentative lactic acid metabolism with L(+)‐lactic acid
as the main end‐product. They are found in intestinal tract of humans and animals, food and
the environment. The Enterococcus genus is primarily composed of organisms formerly known
as faecal streptococci. They are also used in the production of fermented meat and milk
products. However, they are also opportunistic pathogens.
4.17.2 E. faecalis and E. faecium
Enterococcus faecalis and E. faecium can contaminate meat at the time of slaughter, and is a major
isolate on beef and pork. They are also associated with processed meats and can survive mild cooking temperatures and nitrite levels that kill other non‐spore‐forming organisms. This may result in
spoilage of cured meat products. Strains of E. faecium have been used as probiotics. However, there
is concern regarding the use of Enterococcus species as probiotics as they are ingested in large doses,
and may acquire virulence traits and antibiotic resistance in the intestinal tract.
Box 4.15
Organism
Group A Streptococcus spp. (S. pyogenes)
Food source
Temperature‐abused milk, ice cream, eggs, steamed lobster, ground ham, potato salad, egg salad,
custard, rice pudding, shrimp salad.
Onset of symptoms
2–36 hours.
Acute symptoms and chronic complications
Sore, red throat, pain on swallowing, tonsillitis, high fever, headache, nausea, vomiting, malaise,
rhinorrhoea.
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The microbiology of safe food
General symptoms of enterococci infection are:
• diarrhoea;
• abdominal cramps;
• nausea and vomiting;
• fever and chills;
• dizziness.
Symptoms occur within 2–36 hours after ingestion of suspect food. The infectious dose is
probably >107 organisms. The diarrhoeal illness is poorly characterised, but is acute and
self‐limiting. Food sources include sausage, evaporated milk, cheese, meat croquettes, meat
pie, pudding, raw milk and pasteurised milk. Entrance into the food chain is due to underprocessing and/or unhygienic practices during food preparation.
4.17.3 Streptococcus pyogenes, group A streptococci
The link between scarlet fever and septic sore throat was linked to the consumption of contaminated milk almost 100 years ago. Outbreaks of septic sore throat and scarlet fever were
numerous before the advent of milk pasteurisation.
Symptoms of Group A streptococcal infection are:
• sore and red throat;
• pain on swallowing;
• tonsillitis;
• high fever and headache;
• nausea and vomiting;
• malaise;
• runny nose;
• rash.
Group A streptococci cause septic sore throat and scarlet fever as well as other pyogenic and
septicaemic infections. The organism may also cause toxic shock syndrome (Cone et al.
1987). The time until onset of illness is 1–3 days. The infectious dose is probably quite low at
<1000 organisms. Food sources include milk, ice cream, eggs, steamed lobster, ground ham,
potato salad, egg salad, custard, rice pudding and shrimp salad. In almost all food poisoning
cases, the foodstuffs had been subjected to temperature abuse between preparation and
consumption. Contamination of the food is often due to poor hygiene, ill food handlers or the
use of unpasteurised milk. Streptococcal sore throat is very common, especially in children.
Usually it is successfully treated with antibiotics. Complications are rare and the fatality rate
is low. Most current outbreaks have involved complex foods (i.e. salads) that were infected
by a food handler with a septic sore throat. One ill food handler may subsequently infect
hundreds of individuals.
Streptococcus parasanguinis is an unconfirmed, potential foodborne pathogen. This organism was isolated from two sheep in Spain during a bacteriological survey for determining the
prevalence of subclinical mastitis. Since the organism has been associated with the development of experimental endocarditis, its presence at relatively high concentrations in apparently
healthy sheep milk may pose a health risk in persons with predisposing heart lesions.
4.17.4 Virulence traits
Enterococcus faecalis and E. faecium cause infections in the immunocompromised, and are
commonly associated with hospital‐acquired infections: bloodstream and urinary tract infections
and endocarditis. Enterococcus faecalis and E. faecium encode for various virulence traits.
Bacterial foodborne pathogens
219
These include adhesins (aggregation substance, enterococcal surface protein), cytolysin, gelatinase
and capsule formation. They are also intrinsically resistant to cephalosporins, β‐lactams, sulphonamides and low levels of clindamycin and aminoglycosides. They can also acquire resistance to chloramphenicol, erythromycin, high levels of clindamycin and aminoglycosides, and
vancomycin. The emergence of vancomycin‐resistant enterococci is a serious medical concern
as infections by these strains cannot be treated by conventional antibiotic therapy.
The pathogenicity of Group A streptococci is partially due to the presence of M‐proteins
in the fibrillae on the cell surface. These adherence factors enable the organism to adhere
to epithelial cells and evade phagocytosis. The organism produces haemolysin(s) as evidenced by the β‐type haemolysis on blood agar. Control of foodborne streptococcal infections is by strict control of personnel hygiene and excluding staff with sore throats from the
production area.
4.18 Emerging and uncommon foodborne pathogens
Despite considerable efforts in surveillance and improvements in isolation methods, only about
half of the reported intestinal infectious cases are attributable to a named organism (de Wit et al.
2001). Not all of these are due to a lack of thorough prompt investigation, instead they may be
due to unrecognised (emergent) organisms and this emphasises the point that food microbiology still has many areas of research yet to be investigated. Studying emerging, and possibly
emergent foodborne pathogens is essential to recognise the scale of their importance and their
subsequent control. However, to publicise the emergence of a pathogen based on limited information can be regarded as alarmist, and can lead to unnecessary additional testing by industry
and regulatory bodies. There is a problem that the link may not be established without adequate
surveillance, but no financial support for surveillance would be undertaken without evidence of
a link. It is hard to break this circle. Nevertheless the example already covered for Cronobacter
illustrates how certain cases can result in global changes in test methods, microbiological criteria and food preparation guidance (Section 4.6; Forsythe 2018a, b).
Although the word ‘emerging’ implies the emergence de novo of the organism, the phrase
‘recently recognised’ may be more appropriate as the organism will have already been described,
but the link with foodborne illness may be new, as occurred with E. coli O157:H7. Some organisms in this chapter are ‘emergent’ or ‘recently recognised’ pathogens for which food has been
established as a vector, but some will not be so strongly associated but could be foodborne.
Some, such as Cronobacter, which were ‘emerging’ in the second edition of this book have
already been moved to the main section of recognised foodborne pathogens. It may be argued
that some are too speculative to be included – however this begs the question of how will we
ever know unless we look? Previously our ability to look was severely hampered by the use of
selective and differential agars, which were designed for previously recognised pathogens.
However, the application of high‐throughput sequencing to identification without cultivation
is highly likely to reveal hitherto unrecognised pathogens.
Emerging (and re‐emerging) infections have been defined as ‘new, recurring, or drug‐resistant infections whose incidence in humans has increased in the last decades or whose incidence
threatens to increase in the near future’ (NRC 1993). For various reasons the number of identified foodborne pathogens has increased (Tauxe 2002). Some emergent foodborne disease are
well characterised, but are considered ‘emerging’ because the reporting of them has become
more common.
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The microbiology of safe food
The (re‐)emergence of certain foodborne pathogens and toxins is due to a number of causes:
1 Weakened or collapsed public health infrastructure for epidemic disease control due
to economic problems, changing health policies, civil strife and war.
2 Poverty, uncontrolled urbanisation and population displacements.
3 Environmental degradation and water and food source contamination.
4 Ineffective infectious disease control programmes.
5 Newly appeared in the microbial population, such as the rise of antimicrobial resistance resulting from inappropriate use of antibiotics, including those used in animal
production.
6 Diseases crossing from animal to human populations with increasing frequency especially as humans exploit new ecological zones and as intensification of animal food
production (including fish) and industrialisation of food processing and distribution
become global practices.
7 Increased potential for spread of disease through globalisation of travel and trade
including that of processed and raw foodstuffs of vegetal and animal origin.
8 Dispersed to new vehicles of transmission.
9 Recently identified due to increased knowledge or methods of identification,
though previously widespread.
(Lindsay 1997)
The factors that can affect the epidemiology and recognition of emergent food pathogens are
given in Table 4.10.
Micro‐organisms have evolved many adaptation mechanisms to survive and persist in
otherwise ‘unfavourable’ growth conditions (Lederberg 1997). They can exchange genetic
material (e.g. conjugation, transduction and transformation) and hence acquire new gene
sequences. HGT is now recognised as one route by which toxin genes can be distributed to new
bacterial strains (i.e. origin of E. coli O157:H7). Gene sequences called ‘pathogenicity islands’,
which encode for specific virulence factors can be recognised by their GC% content, which
differs from the rest of the bacterial genome. Likewise, though less well understood, bacteriophages
Table 4.10 Factors that can affect the epidemiology and recognition of emergent food pathogens.
Reason
Example
1
Microbial adaptation through natural selection; selection of antibiotic‐resistant strains, i.e.
S. Typhimurium DT104 due to antibiotic usage
New foods and food preparation technologies, i.e. BSE and vCJD
Changes in host susceptibility, i.e. increase in population age
Changes in lifestyle such as an increased consumption of ‘convenience food’ and subsequent risk to
Listeria monocytogenes
Increasing international trade and travel, enabling the rapid spread of pathogens worldwide,
i.e. Escherichia coli O157:H7
New food vehicles of transmission being recognised, i.e. Mycobacterium paratuberculosis
(plausible)
High publicity of infections in high‐risk group, i.e. Cronobacter sakazakii in powdered infant
formula
Microevolution. Salmonella serovars’ loss of H2S production leading to greater resistance to
inflammatory response
2
3
4
5
6
7
8
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221
may interact with host genomes and emerge in new susceptible populations and vehicles, with
less than predictable outcomes. Foodborne pathogens often have an animal reservoir from
which they can spread to humans, although they frequently do not cause illness in the primary
host. Because of the considerable increase in international travel and trade, foodborne pathogens can be spread rapidly worldwide.
There has been considerable concern over the emergence of antibiotic resistance within
foodborne pathogens such as S. Typhimurium DT104 and C. jejuni. Highly publicised concerns are the plasmid‐mediated colistin resistance (mcr‐1 and variants) in E. coli and other
Enterobacteriaceae, and the use of clinically important antibiotics in veterinary practice.
The emergence of certain food pathogens are due to a number of causes:
• Newly appeared in the microbial population.
• Dispersed through new vehicles of transmission.
• Rapidly increasing incidence or geographic range (e.g. V. cholerae in southern USA
coastal waters in 1991).
• Recently identified due to increased knowledge or methods of identification, though
previously widespread.
(Adapted from Van de Venter 1999)
4.18.1 Arcobacter genus
General description
Campylobacter jejuni and C. coli are well recognised as a major cause of human gastroenteritis.
However, a number of other Campylobacter species such as C. concisus (Section 4.2) and the
closely related Arcobacter species have also been recognised as causing animal if not human
cases of gastroenteritis. While there are relatively (compared with Campylobacter species) few
reported cases of infection due to Arcobacter, this is probably due in part to the lack of routine
use of appropriate isolation media (Figueras et al. 2014). Raw or minimally processed foods are
probably the main source of human Arcobacter infection, with the cause being faecal contamination during the various stages of production.
Arcobacter genera
The Arcobacter genus was formerly known as aerotolerant campylobacters and campylobacter‐like organisms (CLOs). But improved methods of taxonomic evaluation have led to the
Box 4.16
Organism
Arcobacter butzleri, A. cryaerophilus and A. skirrowii
Food source
Contaminated drinking water and food.
Acute symptoms and chronic complications
Persistent and watery diarrhoea.
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recognition of the genus Arcobacter. There are currently 18 recognised Arcobacter species, and
these have been isolated from various sources. Of particular interest are A. butzleri, A. cryaerophilus and A. skirrowii, as these have been associated with human cases of diarrhoea, the
probable transmission routes being through the ingestion of contaminated drinking water and
food. These three species are also veterinary pathogens causing porcine abortions. Arcobacter
butzleri serotypes 1 and 5 are regarded as the primary human pathogens, however no epidemiological studies have yet shown the transmission of the organism through the food chain to
humans. The situation is, however, reminiscent of C. jejuni and L. monocytogenes. These
organisms were recognised as veterinary pathogens many years before the medical microbiologists used suitable isolation media for samples from patients suffering from gastroenteritis,
and later food microbiologists started to use the media and isolation techniques. Arcobacter
species have been isolated from a range of food sources (Table 1.2) using a range of methods,
some of which may favour certain species more than others. Water may also be a vector of
Arcobacter transmission to animals and humans.
Virulence aspects
It is plausible that A. butzleri and A. cryaerophilus, which were first isolated from aborted
bovine foetuses and later from porcine foetuses, will in the future be more fully recognised as
of significant human importance. Currently there is increasing awareness of their role as
veterinary pathogens, but relatively few human cases. The occurrence of Arcobacter‐related
diseases may be underestimated due to the lack of surveillance and optimised detection
procedures.
Examination of human and veterinary clinical specimens for the presence of Arcobacter
species is rarely performed, and in most cases suboptimal procedures are used (Houf
et al. 2001). In addition, little is known about the risk factors for human infection. An
extensive study was conducted by Vandenberg et al. (2004), who studied a total of
67 599 stool samples over an 8‐year period. Arcobacter butzleri was the fourth most common CLO isolated. It was more frequently associated with symptoms of a persistent,
watery diarrhoea than C. jejuni.
Arcobacter species appear resistant to antimicrobial agents typically used in the treatment of
diarrhoeal illness caused by Campylobacter species; for example, erythromycin, other macrolide antibiotics, tetracycline and chloramphenicol.
The pathogenicity and virulence mechanisms of Arcobacter species are still poorly understood and have only been studied in four Arcobacter species: A. butzleri, A. cryaerophilus, A.
skirrowii and Arcobacter cibarius. WGS has enabled several putative virulence genes to be identified, such as ciaB, cj1349 and cadF. These are homologous to genes associated with pathogenicity in other closely related organisms. The ciaB gene encodes an invasion protein injected
directly into the cytoplasm of the host cells through a secretion system. The cj1349 gene
encodes for proteins that enable adhesion to host cells by binding specifically to fibronectin,
and the CadF protein also induces the internalisation of bacterial cells by the activation of
GTPases.
Twelve pathotypes of A. butzleri have been proposed based on the occurrence of possible
virulence genes cadF, cj1349, ciaB, pldA, tlyA, hecA, hecB, mviN, irgA and IroE. The most
frequently occurring genes were ciaB, mviN, tlyA, cj1349, pldA and cadF, while the least
common genes were iroE, hecA, hecB and irgA. The genes tlyA, irgA, hecA, hecB and iroE are
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223
more frequent in isolates from industrial dairy plants. The occurrences of the most frequently
detected P‐types (1, 2, 3 and 5) differ with respect to both the environmental site and geographical area of isolation.
Isolation of arcobacters requires selective media such as mCCDA and CAT (Forsythe 2006).
Identification can subsequently be achieved using 16S rRNA gene probes (Mansfield and
Forsythe 2000b). For a more detailed consideration of Arcobacter, the reader should consult
Corry et al. (2002), Forsythe (2006) and Ferreira et al. (2015).
4.18.2 Campylobacter concisus
While a large number of cases are related to C. jejuni and C. coli infections, there is evidence
that other Campylobacter species may also be causative agents. Epidemiological evidence is
poor but it is reasonable to assume that more fastidious Campylobacter species, such as
C. concisus, will not be recovered as efficiently as C. jejuni for which the Campylobacter isolation methods have been designed. In common with other campylobacters, C. concisus is a
Gram‐negative, curved, microaerophilic bacterium. It can be isolated from the human oral
cavity and faecal samples from healthy and diarrhoeic patients, as well as contaminated food
and water. As a consequence, its primary pathogenic potential is uncertain. In many diarrhoeal
cases, C. concisus is isolated as the only potential intestinal pathogen, and hence the need to
determine its role in human enteric disease is evident. Unfortunately, to the author’s knowledge, there is no specific method available to date.
The C. concisus species is composed of various genotypes, and these could vary in their
pathogenic potential. However, further work will be necessary to assess the risk of C. concisus
to human health and identify specific vehicles of infection. Given the habitat of the organism
as being in the intestinal tract of healthy individuals, it is highly plausible that contaminated
food and water are sources of infection. The organism has been included in this chapter to
raise awareness of this emerging pathogen and its possible contribution to foodborne
infections.
4.18.3 EAEC, E. coli O55 and E. coli O26
General description
Escherichia coli includes a number of pathotypes that are defined according to their clinical
presentation or adherence pattern to cell lines such as the intestinal mucosa cells Hep‐2
(Section 4.4). Enteroaggregative E. coli (EAEC) have a ‘stacked‐brick’ adherence phenotype
in vitro on Hep‐2 cells. It should be noted that the EAEC definition is based on a phenotype
rather than genotype, and therefore the EAEC is a heterogeneous cluster of E. coli strains. No
specific isolation procedures are available for this variant of E. coli.
Virulence aspects of EAEC
Clinical symptoms are described as watery diarrhoea with or without blood and mucus,
abdominal pain, nausea, vomiting and low‐grade fever, can be persistent. These generally
describe traveller’s diarrhoea. EAEC is estimated to be the second most common cause of
traveller’s diarrhoea, which is an important cause worldwide of acute or persistent diarrhoea in
children and adults. The reason for its inclusion in this chapter is that since the late 1990s
EAEC has received increasing attention as a cause of acute, often persistent, watery diarrhoea
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Box 4.17
Organism
The enteroaggregative E. coli (EAEC) are a pathotype within the E. coli species and are Gram‐negative,
facultative rods. The species is a member of the Enterobacteriaceae family
Food source
Contaminated food.
Clinical presentations
Watery diarrhoea with or without blood and mucus, abdominal pain, nausea, vomiting and low‐
grade fever, can be persistent.
and malnutrition, in children and HIV‐infected persons living in developed countries. The
first EAEC infection case was described in 1987 in a child with acute diarrhoea in Lima, Peru.
EAEC outbreaks have been described in children and adults in UK and France.
There has been an increasing rise in the proportion of childhood diarrhoeal cases in which
EAEC are implicated, and this indicates that EAEC are important emerging agents of paediatric diarrhoea. The carriage of the organism by children <5 years of age is reportedly higher in
those with a history of diarrhoea. Unconfirmed reports have linked EAEC with the development of irritable bowel syndrome.
EAEC may not only be causing acute and persistent diarrhoeal disease but may also persist
in the human intestine subclinically, inducing chronic inflammation in the absence of dysentery. This persistent infection could result in chronic disruption of gut function resulting in
malnutrition and restricted childhood development.
The EAEC route of transmission can be through contaminated food. In Italy, two consecutive EAEC outbreaks (affecting 24 individuals) were linked to contaminated unpasteurised cheese. A study of Mexican tabletop sauces identified 44% of sauces from
Guadalajara (Mexico) contained viable EAEC cells, compared with 0% of sauces in restaurants in Houston (USA). In the largest reported outbreak so far, 2697 (40.6%) Japanese
children who consumed infected school lunches had severe diarrhoea, and EAEC was
found in 10% of cases.
In the UK, 97 EAEC strains were serotyped to 40 different O‐types and in another study, 93
out of 143 EAEC strains could be serotyped to 47 different serotypes. Finally, many of the
EAEC strains auto‐agglutinate, and so are described as non‐typable or O‐rough.
Although the extent of foodborne illness is uncertain, and no specific detection methods are
available, the pathogenesis of EAEC is well‐described. It involves three stages: (i) adherence
to the intestinal mucosa by aggregative adherence fimbriae (AAF) and adherence factors;
(ii) increased production of mucus that enhances EAEC adherence to the surface of enterocytes;
and (iii) the release of toxins and elicitation of an inflammatory response, mucosal toxicity and
intestinal secretion. The best‐studied virulence factor is AggR. This is a transcription activator
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225
carried on pAA, a large 60‐MDa plasmid. AggR controls the expression of fimbriae (adherence
factors), a dispersin protein and at least two PAIs on the EAEC chromosome. Dispersin is an
antigenic antiaggregative protein that is encoded by the aap gene in the pAA plasmid. It is
regulated by aggR, modulates fimbrial adhesion and facilitates penetration of the micro‐organism through intestinal mucus by binding to LPS and altering the electrostatic properties of the
EAEC outer membrane surface. Although several other virulence factors are detectable using
PCR probes, none exhibit 100% specificity to EAEC strains, though it should be noted that
EAEC are a heterogenous cluster of E. coli strains defined by their attachment to Hep2
cells in vitro, and not genotype. Other putative virulence factors include a yersiniabactin system, a complex carbohydrate specific lectin, enterotoxins and cytotoxins. The large E. coli
O104 outbreak in 2011 was due to a hybrid EAEC (Section 14.4.2).
E. coli O55
E. coli O157:H7 is the STEC most often associated with epidemics of STEC infections worldwide, and can cause severe infections with systemic complications such as HUS. Nonetheless,
STEC belonging to non‐O157 serogroups raise public health concern in many countries by
displaying the same pathogenic potential as O157:H7. These include STEC E. coli serotypes
O55 and O26.
A stepwise evolutionary model for the emergence of E. coli O55:H7 (STEC) is the acquisition of stx2 by a strain of EPEC serotype O55:H7, resulting in emergence of a strain of E. coli
O55:H7, which was β‐glucuronidase positive and sorbitol‐positive (see Figure 4.8). This would
be closely related but ancestral to the STEC E. coli O157:H7, which was β‐glucuronidase‐positive
and sorbitol‐positive. The evolutionary history of the UK outbreak strain starts with an EPEC
O55:H7 progenitor strain, followed by the acquisition of a shiga toxin (stx2a)‐encoding phage.
The loss of the sorbitol‐positive phenotype has also occurred in the evolution of E. coli O157,
albeit by an alternative mechanism.
The curious convergent evolutionary history of both STEC serotypes O157:H7 and O55:H7
may demonstrate a common driver in bacterial evolution. The loss of the sorbitol‐positive
phenotype may coincide with the new ability to colonise a new animal host or transfer across
animal hosts without the need to survive in the environment for long periods.
In July 2014, the first outbreak of STEC O55:H7 in England was reported. It involved 31
patients, 13 (42%) of whom had HUS. This is a higher rate than the normal value of ~5% for
E. coli O157:H7 infections. The strains was not detected at the local hospital level using the
standard cefixime and tellurite sorbitol MacConkey agar, because the strain was sensitivity to
tellurite. Isolates were sequenced and core genome phylogeny revealed that the most parsimonious model was a progenitor EPEC O55:H7 sorbitol‐fermenting strain, lysogenised by an
stx2a‐encoding phage that is strongly associated with HUS clinical symptoms, followed by loss
of the ability to ferment sorbitol because of a non‐sense mutation in srlA (Schutz et al. 2017).
The E. coli O55:H7 UK outbreak strain shared characteristics with the common E. coli
O157:H7 clone, specifically the acquisition of an stx2a‐encoding phage and the sorbitol‐
negative phenotype. Key differences between them are the rfb gene cluster encoding for the
O antigen, plasmid content, β‐glucuronidase phenotype and the absence of the ter gene cluster
encoding for resistance to tellurite in the E. coli O55:H7 outbreak strain. The acquisition of the
stx2a‐encoding phage may explain the emergence of E. coli O157:H7 as a clinically significant
pathogen.
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The parallel, convergent evolutionary histories of STEC O157:H7 and STEC O55:H7 may
indicate a common driver in the evolutionary process. Because emergence of STEC O157:H7
as a clinically significant pathogen was associated with acquisition of the stx2a‐encoding
phage, the emergence of STEC E. coli serotype O55:H7 harbouring the stx2a gene is of public
health concern.
E. coli O26
STEC E. coli O26:H11/H‐ (non‐motile) poses a significant threat to human health causing
diarrhoea and HUS as well as potential outbreaks. They accounted for 5–7% of all human
EHEC isolates and 15–19% of HUS‐associated EHEC isolates reported to the European
Surveillance System of the ECDC (Section 13.1.4) between 2008 and 2010. This serogroup is
considered emerging in Europe and, in the past decade, has been the most frequently isolated
non‐O157 STEC serogroup in human sporadic cases of infection, including those developing
HUS in Europe and the United States. It has also been increasingly isolated from patients in
Asia, South America and Australia. Severe outbreaks of STEC O26 infection have been
reported both in community and childcare settings. Strains harbouring the stx1a gene prevail,
but strains with stx2a as the sole Shiga toxin‐encoding gene have emerged.
In 2013, a highly virulent clone of STEC O26 strongly associated with HUS in Europe was
recognised (Bielaszewska et al. 2013). The study used 272 EHEC O26 strains isolated in seven
European countries between 1996 and 2012 with disease phenotypes. Out of the 272 isolates, 107
(39.3%), 139 (51.1%) and 26 (9.6%) possessed stx1a, stx2a or both genes, respectively. Strains
harbouring stx2a only were significantly associated with HUS compared with other stx genotypes. The stx2a‐harbouring strains consist of two phylogenetically distinct MLST sequence
types ST21 and ST29. These two sequence types form a CC as they share six of the seven MLST
loci, along with five single locus variants (SLVs). Almost all strains harbouring stx1a only, and all
strains harbouring stx1a and stx2a, belonged to ST21. In contrast, strains containing stx2a but
not stx1a were equally distributed between ST21 and ST29. This new clone occurred in six of the
seven EU countries and represented approximately 50% of all stx2a‐harbouring EHEC O26
strains isolated between 1996 and 2012. This study showed that stx2a‐harbouring EHEC E. coli
O26 strains consist of two major phylogenetically distinct subgroups (ST21 and ST29), each of
which has a particular plasmid gene profile. ST29 strains represent a highly virulent clone of
EHEC E. coli O26:H11/H−, which emerged in Germany in the mid‐1990s.
4.18.4 Escherichia albertii
General description
Escherichia albertii are Gram‐negative, facultative non‐motile rods that cause diarrhoea. It is
closely related to E. coli, and the genus is a member of the Enterobacteriaceae family. The
source of the organisms is widespread: human faeces, birds, animals and the environment.
Escherichia albertii is carried by ~1% of wild birds and is associated with mass mortality events
amongst birds in the northern hemisphere, and is the cause of mortality in captive birds and
poultry. The organism has previously been misidentified by routine diagnostic protocols as
eae‐positive Hafnia alvei, as well as strains of eae‐positive E. coli, E. coli serotype O86, EPEC,
and EHEC. There are no specific isolation procedures available.
E. albertii strains are non‐motile, fermented D‐glucose (with gas), D‐mannitol and D‐mannose,
but do not ferment lactose or other sugars. A large number of MLST sequence types have been
defined. Strains carry the wzx and wzy genes and can be divided into seven serotypes. Strains with
identical sequence types are clustered in the same serotype group demonstrating congruence with
phylogeny.
Bacterial foodborne pathogens
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Box 4.18
Organism
E. albertii, species closely related to E. coli. Gram‐negative, facultative non‐motile rods. Genus is a
member of the Enterobacteriaceae family.
Source
Human faeces, birds, animals and environment.
Clinical presentations
Diarrhoea.
Virulence traits
The recognition of E. albertii as an emerging human enteric pathogen typifies the value in re‐
evaluating previous identification schemes, and anomalies. In 1991 clinical isolates of H. alvei
were found to differ in phenotypic and genotypic assays from representative H. alvei strains.
This variation included the carriage of an intimin gene homologous to the eae gene encoding
for the A/E phenotype of EPEC. Following the use of 16S rDNA sequence analysis and DNA–
DNA hybridisation, E. albertii was proposed as a new Escherichia species for the strains previously regarded as eae‐positive H. alvei.
Escherichia albertii strains have a similarity to EPEC strains, as they harbour a PAI called the
LEE and multiple effector proteins. These effectors are injected into the host cell by a T3SS
encoded by the LEE. In addition to the possession of intimin, E. albertii also produces a CDT.
Based on MLST and virulence gene sequences (eae and cdt) it is proposed that the E. albertii
lineage also includes Sh. boydii (serotype 13) and other previously non‐typable clinical isolates.
This lineage shared a common ancestor with E. coli and Shigella pathogenic groups ~28 million
years ago (mya). However the E. albertii lineage was established before the radiation of pathogenic E. coli and Shigella. Essentially, E. albertii is not a newly emerged pathogenic variant of E.
coli‐Shigella, but a previously unrecognised pathogen that has been confused with its more
well‐known close relatives.
The organism is similar to EPEC strains, as they harbour the PAI LEE and multiple effector
proteins. These effectors are injected into the host cell cytosol by a T3SS encoded by the LEE.
All strains are positive for the eaeA gene, but the presence of other virulence‐related genes
(cdtB, phoE, ehxA and stx2f) is variable. Therefore, there is variability within this lineage, which
may cause confusion and hinder accurately distinguishing E. albertii from E. coli. Although the
number of accurately recorded outbreaks due to E. albertii is uncertain, it is plausible that
some outbreaks have been misattributed to E. coli.
Antibiotic resistance
Escherichia albertii does encode for some antibiotic resistance. Tetracycline resistance has the
highest prevalence (62.7%), followed by resistance to nalidixic acid and streptomycin at 56.9
and 51.0%, respectively. There is some carriage (~30%) of extended‐spectrum β‐lactamase
(ESBL) production. The main β‐lactamase gene groups detected have been blaTEM, blaSHV and
blaCTX‐M. Some E. albertii isolates in this study demonstrated resistance to four antimicrobials
identified by the WHO as being of critical importance in the treatment of human infectious
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diseases, including piperacillin, ampicillin, cefotaxime and cefepime. Furthermore, one‐third
of isolates have demonstrated resistance to cephalothin that was identified by the WHO as
highly important in human disease treatment.
Colistin‐resistant isolates with minimum inhibitory concentrations of 8 mg/l have been
identified. The colistin‐resistance genes mcr‐1 and blaCTX‐M‐55 were carried on two different
plasmids. Colistin is an antibiotic of last resort for the treatment of infections due to extensively drug‐resistant Gram‐negative bacteria. Hence the colistin resistance is more transferable
than if it were chromosomal and of concern for public health.
The author does not know of any confirmed cases of foodborne infections due to this organism, or even isolation from food. Nevertheless the organism has been included in this chapter
as an emerging foodborne pathogen based on its association with poultry and misidentification with EPEC and EHEC. It is hoped this will raise awareness and encourage future detailed
surveillance.
4.18.5 Providencia alcalifaciens
Providencia alcalifaciens is a Gram‐negative rod, and the genus is a member of the
Enterobacteriaceae family. It is primarily recognised as a possible cause of traveller’s diarrhoea
in developing countries due to contaminated food and water. In 1996, there was a large outbreak of foodborne infection causing acute gastroenteritis, involving 290 patients, which
occurred in Fukui, Japan. No previously recognised enteropathogens were detected in the faecal samples of the patients. However, PFGE‐indistinguishable P. alcalifaciens strains were
recovered from seven out of 18 samples. Additionally a specific antibody against the isolated
strain was found to be elevated in the patients’ sera. In vitro virulence studies of the strains
using the Caco‐2 cell line showed strains could invade human intestinal cells, and fluid accumulation in rabbit ileal loop experiments. Together these results indicate that P. alcalifaciens
was probably the causative agent of the outbreak.
A selective medium for the recovery of the organism from faeces has been published. But to
the author’s knowledge no large‐scale trials of method evaluations have been undertaken.
4.18.6 Clostridium difficile
General description
Clostridium botulinum and Cl. perfringens are already well‐recognised agents of foodborne
illness. The organisms are Gram‐positive spore‐formers and therefore are more persistent in
the manufacturing environment. In contrast, Cl. difficile is primarily recognised as a severe,
life‐threatening clinical pathogen and is not normally considered in food microbiology.
Virulence aspects
Clostridium difficile produces two toxins A (TcdA) and B (TcdB) as its main virulence factors.
The majority of strains isolated from animals produce an additional binary toxin (Cl. difficile
transferase), which is associated with increased virulence in human disease. Some strains also
encode for a toxin regulatory gene, tcdC, which may result in an increased toxin production
depending upon sequence variation. Some strains of Cl. difficile recovered from different animal species and humans are indistinguishable by conventional molecular typing techniques,
including ribotyping, MLST and MLVA. WGS with SNP analysis has shown that pigs and pig
farmers were colonised by indistinguishable strains of Cl. difficile. Lund and Peck (2015)
pointed out aspects such as the carriage of Cl. difficile, and similarities between Cl. difficile and
Bacterial foodborne pathogens
229
Cl. perfringens, which indicate a need to further consider the possible transference of this
severe pathogen to vulnerable individuals by food.
Sources and control
Clostridium difficile has been recovered from the intestinal tract of many animals, including pets (cats and dogs) and those used in food production: cattle, pigs, sheep and poultry.
Therefore, it is of relevance to consider the incidence of Cl. difficile in retail meat. High
prevalence rates have been reported in North America for uncooked meat products: beef
(42%), pork (41%) and turkey (44%). Values for RTE braunschweiger and summer sausage
were 63% and 14%, respectively. Lower prevalence rates have been found in Europe: 4.3%
in ground beef/pork and 2.7% in chicken meat. In a Canadian study, Cl. difficile was isolated from 28 of 230 (12%) of samples of retail ground beef and ground pork. This study is
very useful as it gives values for direct enumeration as well as presence/absence following
enrichment. Regarding the 28 positive samples, 20 were positive by enrichment and not by
direct plating. In four ground beef samples that were positive by direct culture,
20–240 spores/g were found and in four ground pork samples that were positive by direct
culture, 20–60 spores/g were detected. Clostridium difficile was detected in 12.8% of chicken
meat samples. These were only detected by enrichment, indicating that the numbers of
spores in the samples were <10 spores/g. Together these reports show that Cl. difficile can
be recovered from meat products, however they are usually at a low level and may need
enrichment to be detectable.
Ribotyping of isolates from cattle, pigs and poultry includes those causing disease in
humans. For example, ribotypes (RT) 027 and 078, which are found commonly in human
infection, have been detected. Most Cl. difficile strains isolated from foods have a genotype
identical to those of human and animal isolates. RT 027 is a fluoroquinolone‐resistant hypervirulent variety of the organism. RT 078 is a virulent predominantly animal strain, and is
increasingly responsible for human infection in Europe. Clostridium difficile RT 027 and RT
078 both produce all three toxins, TcdA, TcdB and CDT.
Clostridium difficile can be recovered from raw vegetables, RTE organic and non‐organic
salads, lettuce, green peppers and aubergine. The overall prevalence of Cl. difficile in vegetables
is ~7.5%. The reason for the prevalence in vegetables is unclear, but it is possible that the use
of animal effluent on crops could contaminate vegetables.
The concern is that cases of Cl. difficile infection could be through zoonotic transmission,
which has not been previously considered and therefore not monitored or specifically controlled. Transmission could occur by direct contact with live animals or their environment,
during or after slaughter, and also via retail meat.
Clostridium difficile and Cl. perfringens prevalence in meat is similar. Faecal levels of Cl. difficile are of the order of 104 cfu/g, and ~17% of carcass samples have been contaminated with
~7 cfu/cm2, supporting the possibility the abattoir environment is contributing to meat contamination. In addition, contamination of root vegetables could be a potential source of the
organism.
Both Cl. difficile and Cl. perfringens produce heat‐resistant spores that will survive normal
cooking practices, and germinate if the food is subsequently kept between 12 and 50°C. The
optimum temperature for growth of Cl. difficile is 30–37°C, with a growth range of ~25–45°C.
The D values for Cl. difficile spores in gravy are in the order of D71 30–71 minutes. Therefore,
the organism will survive the standard core cooking temperature regime of 70°C for 2 minutes.
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This is very significant given the accepted association of Cl. perfringens food poisoning through
cooked meat and poultry dishes and is therefore a plausible scenario for Cl. difficile food transmission (Section 6.7.12).
Detection methods for Cl. difficile are designed for both the germination of spores and
growth of vegetative bacteria, though further optimisation is still needed. Currently isolation
procedures may use brain–heart infusion broth for initial enrichment, followed by plating on
blood agar or similar media containing sodium thioglycolate (support anaerobiosis), lysozyme
(increase spore germination) and sometimes sodium cholate (selective agent), incubation
under strict anaerobic conditions at 37°C being a prerequisite for the growth of vegetative cells.
The detection limit is ~10 spores/g following enrichment.
Also of significance considering the possible role of food in the transmission of Cl. difficile
is that often Cl. difficile cases cannot be matched with previous symptomatic cases. Therefore,
other sources need to be considered as routes of transmission. Clostridium difficile can be carried asymptomatically (~3–4%) following colonisation of healthy individuals. This may be
transient or persistent, but nevertheless is an exposure route given the common issues of
hygienic practices (i.e. lack of hand washing after going to the toilet). The spores of Cl. difficile
can survive on contaminated surfaces for long periods of time (~5 months), which will increase
exposure risk.
A key issue of this topic is the need for more rapid and reliable isolation and genotyping
methods. These can then be used for real‐time surveillance, combining the genotyping of isolates from clinical (symptomatic), contacts (asymptomatic) and food.
4.18.7 Mycobacterium paratuberculosis
Johne’s disease
Mycobacterium paratuberculosis (commonly referred to as ‘MparaTB’) is a subspecies of M.
avium. It causes the chronic enteritis in cattle known as Johne’s disease. In North America and
Europe, the organism is highly prevalent in a subclinical form in dairy herds and domestic
livestock such as sheep and goat. It can also infect a range of wild animals such as rabbits and
deer. The symptoms are diarrhoea, weight loss, debilitation and, since it is incurable, death.
The prevalence of Johne’s disease in the USA is 2.6% of the dairy herd; this is comparable with
the 2% of cattle being clinically infected in England (Çetinkaya et al. 1996).
Mycobacterium paratuberculosis is excreted at 108 cfu/g and has been isolated from milk of
asymptomatic carriers at a level of 2–8 cfu/50 ml milk (Sweeney et al. 1992). It has been
reported that the organism can survive pasteurisation conditions of 72°C and 15 seconds
(Chiodini and Hermon‐Taylor 1993; Grant et al. 1996; Stabel et al. 1997). Hence it has been
proposed that the organism is the causative agent of the human equivalent called ‘Crohn’s disease’ (Hermon‐Taylor et al. 2000; Acheson 2001; FSA 2001; Hermon‐Taylor 2001, 2009; Behr
and Kapur 2008).
Crohn’s disease
Crohn’s disease is a highly debilitating chronic inflammation of the gastrointestinal tract in
humans. Most commonly the distal ileum and colon are affected. It is a lifelong disease with no
cure and usually affects young people. The highest incidence rate is in the age group 15–24.
Genetic and immunologic factors may have an important role in the occurrence of the
disease.
Bacterial foodborne pathogens
231
The proposed link between Crohn’s disease and My. paratuberculosis is controversial because
(i) the organism has not been detected in commercial pasteurised milk sources, and (ii) it is
not the consensus of opinion that Crohn’s disease is caused by My. paratuberculosis. If it is
proven that My. paratuberculosis is transferred from infected cattle to humans, resulting in
Crohn’s disease via pasteurised milk, then the standard pasteurisation time and temperature
will have to be re‐evaluated. Milk and water are considered as potential sources of exposure.
Other dairy products, e.g. cheese as well as meat are also considered potential vehicles for this
organism. Another feature of this organism that makes its control difficult is its ability to survive in the environment as well as methods of culturing partly due to its slow growth. The
problem with studying this organism is that it is very difficult to grow in the laboratory. Colony
formation is only just visible after 4 weeks’ incubation and requires confirmatory tests. Hence
large‐scale experiments are extremely time‐consuming. Surveys carried out in the UK have
shown the presence of the organism in a small proportion of raw as well as commercially available pasteurised milk samples (FSA 2001).
4.18.8 Acinetobacter species
Acinetobacter baumannii and A. calcoaceticus are opportunistic pathogens causing urinary
tract infections, bacteraemia and wound infections. They are also well known for their carriage
of multiple antibiotic resistance, and are very resistant to desiccation. The organism is detectable in the air of milk powder manufacturing plants and is highly persistent in infant formula
(Mullane et al. 2008; Juma et al. 2016; Wu et al. 2018). The organism is included here as it is
recognised by FAO/WHO (2004, 2006a) as a plausible causative agent of infant infection
through the ingestion of contaminated powdered infant formula. However, to the best of the
author’s knowledge, to date no cases of Acinetobacter have been traced to the ingestion of contaminated infant formula.
4.18.9 Nanobacteria
Nanobacteria are the smallest bacteria that have been described. They have been found in
marine limestone, freshwater streams, springs, water pipes and caves, as well as human and
cow’s blood (Folk 1999). During their growth, nanobacteria form carbonate apatite on their
cell envelope, which resemble the smallest apatite units in the kidney stone. In a study of
Finnish patients with kidney stones 97.25% of cases were positive for nanobacteria (Ciftcioglu
et al. 1999; Hjelle et al. 2000), hence the indication that the organism may be linked with the
formation of kidney stones. However, this is highly controversial with alternative explanations
proposed (Cisar et al. 2000). Further studies are needed to test this hypothesis and the ecology
and route of transmission of these organisms, which could conceivably include food and water
transmission.
5 Foodborne pathogens: viruses, toxins,
parasites and prions
5.1 Foodborne viruses
Box 5.1
Organism
Viral gastroenteritis; norovirus, adenovirus, rotavirus.
Viral hepatitis A
Food source
Gastroenteritis: food and drinking water contamination, filter‐feeding shellfish.
Hepatitis A: shellfish, raw fruit and vegetables, bakery products.
Onset of symptoms
Gastroenteritis: 15–50 hours
Hepatitis A: 2–6 weeks
Acute symptoms and chronic complications
Gastroenteritis: diarrhoea and vomiting, often severe and projectile.
Hepatitis A: loss of appetite, fever, malaise, nausea, vomiting, dark urine, pale stools and jaundice.
Essentially there are two types of viruses in food microbiology: bacteriophages and viruses,
which can directly cause human food poisoning. Bacteriophages can contribute to the dissemination of virulence traits, alter O antigen and infect industrially important production
strains such as lactic acid bacteria in yogurt manufacture. Foodborne infectious viruses are
transmissible through foods, and must be environmentally fit to retain their infectivity over
time and within the food matrix. As viruses are unable to replicate in the food matrix they are
presumed to have a low infectious dose. However, they are shed in large amounts in faeces and
viral contamination of food is primarily via human faecal contamination.
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
233
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Non‐bacterial gastroenteritis due to enteric viruses has been established since the first discoveries of norovirus (formerly Norwalk virus) in 1972 and rotavirus in 1973. Viruses can be
excreted in large numbers by infected individuals. Viruses cannot grow in or on foods; however, they serve as vehicles for infection. Sentinel studies (Section 1.10) have estimated that in
the US approximately 30.9 million (80%) of the 38.6 million total foodborne illnesses per year
can be attributed to viruses. Previously these infections had been grossly underestimated due
to under‐reporting of mild gastroenteritis and a lack of reliable detection methods. Fortunately
molecular biology is greatly helping in the development of analytical procedures to analyse
food and aid epidemiological studies. The advent and implementation of accessible high‐
throughput sequencing has greatly increased our ability to investigate foodborne viruses
(Ronholm et al. 2016; Sekse et al. 2017).
Viral gastroenteritis is usually characterised by:
1 Onset after a 24–36‐hour incubation period.
2 Vomiting and/or diarrhoea lasting a few days.
3 A high attack rate (average 45%).
4 A high number of secondary cases.
The infectious dose is not known but is presumed to be low (100–102) (Tables 1.3 and 4.1).
Viruses are transmitted by the faecal–oral route via person‐to‐person contact or ingestion
of contaminated foods and water. Ill food handlers may contaminate foods that are not
further cooked before consumption. Enteric adenovirus may also be transmitted by the
respiratory route.
There is a very wide range of viruses causing foodborne disease (Table 5.1). Their size ranges
from 15 to 400 nm. As obligate intracellular parasites they require mammalian (even as specific
as human) cells to replicate in and have properties to protect the genome when outside the cell
and aid transmission. Most food‐ and waterborne viruses are non‐enveloped and are relatively
resistant to heat, disinfection and pH changes. They can be transmitted in different ways; for
example, inhalation of water droplets (aerosol) from a cough and faecal contamination of a
work surface. Therefore, contamination can occur anywhere in the farm to fork sequence.
Unfortunately little work has been done on the thermal inactivation of enteric viruses in foods
other than shellfish.
General features of foodborne viral infections are:
• Only a few particles are needed to produce an illness.
• High numbers of viral particles are shed in the faeces from infected persons (up to 1011 particles/g
faeces reported for rotaviruses). Raw sewage can contain 103–105 infectious particles/l.
Table 5.1 Viral foodborne pathogens.
Symptoms
Gastroenteritis
Hepatitis
Other illnesses
Adenovirus
Aichi virus
Astrovirus
Enteric adenovirus types 40 and 41
Norovirus
Rotavirus groups A to C
Sapporo viruses
Small round viruses
Hepatitis A
Hepatitis E
Coronavirus
Coxsackie virus groups A and B
Cytomegalovirus
Echovirus serotypes 68–71
Parvovirus
Poliovirus
Foodborne pathogens: viruses, toxins, parasites and prions
235
• Viruses do not replicate in food or water.
• Foodborne viruses typically are quite stable outside the host and are acid resistant.
Current food hygiene procedures have been developed to prevent bacterial foodborne pathogens and therefore are probably inadequate for the control of viral pathogens present before
processing. An additional problem with foodborne viral pathogens is that the most common
ones (i.e. noroviruses) grow poorly, or not at all in cell culture.
Viral foodborne pathogens can be divided into three groups:
1 Viruses that cause gastroenteritis: rotavirus (groups A, B and C), enteric adenovirus, noroviruses and Sapporo‐like viruses (both caliciviruses), adenovirus (types 40 and 41) and
astrovirus (serotypes 1–8).
2 Faecal–orally transmitted hepatitis viruses: hepatitis A virus (HAV) and hepatitis E virus
(HEV).
3 Those that cause other illnesses: cytomegalovirus, parvo‐like viruses, coronavirus and the
enteroviruses (polio 1–3, Coxsackie A and B, echo 68–71).
After Koopmans and Duizer (2002) and Koopmans et al. (2002), see Table 5.1.
The most common causes of viral foodborne illness are noroviruses and HAV. In the USA,
an estimated 32–42% of foodborne infections are caused by viruses. These viruses are
principally transmitted via human‐to‐human contact and no zoonotic (animal‐to‐human)
transfer is recognised. Noroviruses have been found in a large proportion of cattle herds and
some pigs but are genetically distinct from those infecting humans (van der Poel et al. 2000).
Routes by which foods can be contaminated with pathogenic viruses are:
1 Shellfish contaminated by faecally polluted marine water.
2 Human sewage pollution of drinking and irrigation water.
3 Ready‐to‐eat and prepared foods contaminated as a result of poor personal hygiene in
infected food handlers.
4 Aerosolisation of vomit.
5 Contact with contaminated surfaces (fomite).
Viruses have a strict intracellular replication requirement and cannot replicate in food or
water. Hence their numbers do not increase during processing, transport or storage.
Additionally they are more resistant to heat, disinfection and pH changes than bacterial
pathogens.
Although there is no correlation between the presence of viruses and indicator bacteria (i.e.
coliforms, Escherichia coli), no specific microbiological criteria for enteric viruses are included
in statutory sanitary control measures for shellfish. This is of concern since depuration does
not reduce the levels of viral contaminants as effectively as bacterial contaminants.
Detection methods are either based on enzyme‐linked immunosorbent assay (ELISA) based
kits or molecular probes (PCR of specific gene sequences) and are used in public health
laboratories rather than food microbiology laboratories (Atmar and Estes 2001). There is a
Foodborne Virus Network as a rapid alert system for the European Union (EU) (Section 13.1.5).
5.1.1 Norovirus
General description
Norovirus infects all age groups, with clinical symptoms commonly characterised by diarrhoea,
projectile vomiting, fever and abdominal cramps. It has a positive strand RNA genome of
7.3–7.6 kb encoding for a set of non‐structural proteins at the 5′‐end and the major structural
protein at the 3′‐end. The 28–35nm viral particles have a buoyant density of 1.39–1.40 g/ml in
CsCl, and the capsid is composed of 180 copies of a single structural protein. These viruses
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cannot be grown in cell culture. The noroviruses were formerly known as ‘Norwalk‐like virus’
(NLV) and ‘small round structured viruses’ (SRSV).
Noroviruses are the leading cause of human viral gastroenteritis globally and are responsible
for more than half of the gastroenteritis outbreaks that occur annually and approximately one‐
fifth of all diarrhoea cases (Patel et al. 2009). It is an important public health issue with a
substantial socioeconomic burden (Hoffmann et al. 2012). The World Health Organisation’s
global estimates of the burden of foodborne disease (for 2010) gives noroviruses as the most
common cause of cases of and deaths from foodborne diarrhoea disease, and the fourth
greatest burden in terms of disability‐adjusted life years (DALYs) (Kirk et al. 2015; Pires et al.
2015). Noroviruses were estimated to cause in the order of 684 million episodes of diarrhoeal
disease and 212 000 deaths (annually) for all age groups and from all modes of transmission.
Globally, norovirus infections cause ~$4.2 billion in direct health system costs (Bartsch et al.
2016). The total cost to society per year is ~$60.3 billion, of which infections in children
<5 years in age cost society ~$39.8 billion. Productivity losses accounted for 84–99% of total
costs and varied according to region. The incidence of norovirus was ~10 000 per 100 000
persons.
In developing countries, it is estimated to kill over 200 000 people annually, primarily children under 5 years old (Ahmed et al. 2014). Due to its low infectious dose and environmental
stability, it is easily transmitted from person to person, through the faecal–oral route and vomitus spread. It commonly causes outbreaks in semi‐enclosed institutions such as nursing
homes, schools, hospitals and cruise ships.
Norovirus genera and genotypes
Early descriptions of epidemic non‐bacterial gastroenteritis or ‘winter vomiting disease’ can be
traced back to 1929, but the causative agent was not identified until an outbreak in 1968 at an
elementary school in Norwalk (Ohio, USA) when immune electron microscopy was used on
faecal samples. The non‐enveloped virus was the first virus to be associated with acute gastroenteritis outbreaks and was named after the location of the outbreak (Kapikan et al. 1972). The
practice of naming the virus after the outbreak area continued until recently and consequently
the serologically distinct groups of viruses had location names such as Hawaii virus, Snow
Mountain virus and Toronto virus. This practice has now ceased since the geographic names
might be disputed because of national and/or local sensitivities.
The taxonomy of the noroviruses has changed frequently, but it is generally agreed that they
belong within the Caliciviridae family, which is formed of four genera (van Regenmortel et al.
2000):
1 vesiviruses: feline calicivirus;
2 lagoviruses: rabbit haemorrhagic disease virus;
3 Norwalk virus;
4 Sapporo‐like viruses (SLV): Sapporo virus.
The genus Norovirus is classified into six genogroups (GI–GVI) according to phylogenetic
clustering of the capsid gene, and an additional genogroup (GVII) that infects dogs has been
proposed. To date, only GI, GII and GIV are known to infect humans, with norovirus GII
strains predominating in epidemiological investigations. Each genogroup can be further classified into genotypes, with more than 36 genotypes infecting humans currently described
(Kroneman et al. 2013).
Genogroup II, genotype 4 (GII.4) is of particular importance as it is the only genotype that
has been associated with norovirus pandemics since the mid‐1990s. The emergence and global
Foodborne pathogens: viruses, toxins, parasites and prions
237
spread of novel GII.4 variants are responsible for each of the six global epidemics that have
occurred over the past two decades: (i) US 1995/96 in the late 1990s; (ii) Farmington Hills
virus in 2002; (iii) Hunter virus in 2004; (iv) Den Haag 2006b virus in late 2007; (v) New
Orleans virus in 2009; and (vi) the current predominant GII.4 strain in circulation, Sydney
2012. The Eacg GII.4 variant has replaced the previous one in circulation globally. The
GII.4‐2006b strain has two mutations in region A (part of the polymerase gene) and one in
region C (part of the capsid gene). Unfortunately, there is a need for international standardisation
in the nomenclature of the variant types. The GII.4‐2006b variant is known as Minerva in the
USA, Kobe034 in Japan and v6 in UK.
Unfortunately noroviruses cannot be cultivated in the laboratory, which until the development of molecular studies severely hampered our understanding and detection of this virus.
For genotyping, the common sequences used for multiple alignments are region A, which is
part of the polymerase gene, and region C, which is part of the capsid gene.
Norovirus gastroenteritis
Norovirus gastroenteritis is self‐limiting and mild. The characteristics of norovirus
gastroenteritis are:
• low‐grade fever;
• projectile vomiting;
• diarrhoea;
• headache;
• chills, muscle aches and weakness may also occur.
The illness is considered mild and self‐limiting. The infectious dose is unknown but presumed
to be low. A mild and brief illness usually develops 24–48 hours after contaminated food or
water is consumed and lasts for 24–60 hours (Tables 1.3 and 1.4).
Noroviruses account for 67% of foodborne associated gastroenteritis cases, 33% of
hospitalisations and 7% of deaths (Mead et al. 1999). Noroviruses cause diarrhoea and vomiting
and are the single most common cause of gastroenteritis in all age groups. Sapporo virus
predominantly causes illness in children.
There are 36 distinct norovirus genotypes due to genetic differences and differences in
protein composition. Immunity is developed to one genotype and is short lived. Hence multiple
norovirus infections can occur.
Norovirus is as common as rotavirus in patients who visit general practitioners (Wheeler
et al. 1999; Koopmans et al. 2002; see Section 1.10 for sentinel studies), and is second to the
common cold in reported cases in the USA. The incidence is highest in young children, though
illness does also occur in adults and of relevance to hygienic food production in the home and
factory is that asymptomatic infections are common. Outbreaks occur associated with schools,
hospitals, restaurants and nursing homes. The proportion of infections that are due to the
ingestion of contaminated food is unknown though it is expected to be common. The virus is
typically spread by direct person‐to‐person contact; the secondary (indirect) route is via
contaminated food, water or environments. It should be noted that the virus does not multiply
on food or in water and hence cold storage cannot be used to control its presence.
The virus invades and damages the gastrointestinal tract, resulting in mucosal lesions of the
small intestinal tract. The inflammatory response in the lamina propria (Figure 2.2) is similar
to that caused by rotavirus. Severe illness or hospitalisation is very rare. The virus is shed in
faeces (as high as 108 virus particles/g faeces) and vomit, starting during the incubation period
and lasting up to 10 days or longer. Thirty percent of cases shed viruses for up to 3 weeks after
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The microbiology of safe food
infection. Norovirus infections are highly contagious with over 45% attack rate. Many different
norovirus genotypes circulate in the general population causing sporadic cases and outbreaks.
The strain sequence of different isolates within an outbreak is nearly identical, unless there has
been a common sewage‐contaminated source. Immunity to the specific infecting genotype
only lasts for a short period and hence the development of a long‐lasting vaccine may not be
possible.
Sources and control
Routes of transmission include:
• Water (most common source of outbreaks): municipal supplies, wells, recreational lakes,
swimming pools and water stored aboard cruise ships.
• Contaminated food: directly by food handler or by contaminated washing and irrigation
water.
• Projectile vomiting (common feature of norovirus infection) and aerosolised vomit is a
vehicle of transmission via environment contamination and airborne transmission (Marks
et al. 2000).
Noroviruses can survive outside the host, and are more resistant to common disinfectants than
bacteria. Norovirus is reported to be resistant to pH values as low as 2.7, heating (60°C, 30 minutes) and free chlorine (up to 1 mg free chlorine/l, 30 minutes of exposure time). The virus is
inactivated at higher concentrations (>2 mg/l free chlorine). Only limited studies on the effect
of other disinfectants on norovirus have been undertaken due to the lack of in vitro cultivation
methods. Drinking water processing can reduce the amount of norovirus by four log orders.
Filter‐feeding shellfish and salad ingredients are the foods most often implicated in norovirus outbreaks. Shellfish can filter up to 10 gal (38 l) of water/hour and hence concentrate
viruses from the surrounding water. Unfortunately depuration is about 100 times less effective
at removing viral pathogens as bacterial pathogens (Power and Collins 1989). Due to heat
resistance even steaming may not prevent norovirus gastroenteritis, although feline caliciviruses
(a model for norovirus, though from a different genera) are completely inactivated in shellfish
after a heat treatment of 70°C for 5 minutes or boiling for 1 minute. Ingestion of raw or
insufficiently steamed clams and oysters poses a high risk of infection with norovirus.
The inability to grow the virus in the laboratory severely hinders studies of inactivation and
detection. Nevertheless control of the norovirus in food is the same as for HAV. It is achieved
through avoidance of food contamination from contaminated water and infectious personnel.
Outbreaks associated with noroviruses
Berg et al. (2000) reported a multi‐state outbreak associated with oysters that was traced to a
sick oyster harvester whose vomit had been disposed of overboard in the oyster bed area.
Foods other than shellfish are contaminated by ill food handlers. Unfortunately, little work has
been done on the thermal inactivation of enteric viruses in foods other than shellfish.
Frozen raspberries have been the source of several other norovirus outbreaks in recent
years. Hjertqvist et al. (2006) reported on four outbreaks in Sweden where contaminated
raspberries were the source of infection (Table 5.2). All of the suspected raspberries were from
the same brand, from the same distributor, being imported from China. A high percentage of
the outbreaks with ‘unknown aetiology’ are probably outbreaks of viral gastroenteritis. One
retrospective study confirmed the presence of noroviruses in 90% of non‐bacterial
gastroenteritis outbreaks (Fankhauser et al. 1998). In another retrospective review of 712
foodborne outbreaks from 1982 to 1989 that had been reported to the Centers for Disease
Foodborne pathogens: viruses, toxins, parasites and prions
239
Table 5.2 Four norovirus outbreaks in Sweden associated with raspberry deserts.
Outbreak (2006)
Description
Incidence and symptoms
Laboratory analysis
23 June
15 people at a
private party
Ate homemade cake
containing cream
and raspberries
11 people at a family
gathering
Cheesecake and
raspberries eaten by
everyone
1–2 days after the party, 12
people were ill with
gastroenteritis
Stool samples from two
patients were positive for
norovirus by PCR
Following day, 10 people were
ill with signs of norovirus
infection
There were also two secondary
cases
24 August
School class, 30
pupils aged 13
Drinks prepared with
raspberries
25 August
Meeting with nine
participants. Guests
ate a homemade
raspberry parfait
26 or 27 August, parent
reported ill child
Cohort study showed 12
children had been ill
Incubation period 24–36 hours,
symptoms of vomiting, fever,
diarrhoea and headache.
Duration of illness 1–3 days
Eight people became ill
No faecal samples due to
significant time before
authorities notified
Raspberries were of the same
brand as the first outbreak, and
were imported from China
Faecal samples from two
children were positive for
norovirus. Raspberries were the
same brand as the previous
outbreaks
2 August
One stool sample was tested,
and found positive for norovirus.
The berries were the same
brand as in previous outbreaks
Control and Prevention (CDC), 48% met the epidemiologic criteria for outbreaks of noroviruses. Recently the Foodborne viruses in Europe network was established (Section 13.1.5),
which monitors norovirus activity in 10 countries, and reports on strain variations.
5.1.2 Hepatitis A
General description
HAV is classified with the genus Hepatovirus and is in the Picornaviridae family (Cuthbert
2001). Many other picornaviruses cause human disease, including polioviruses, coxsackieviruses, echoviruses, and rhinoviruses (cold viruses). HAV is a non‐enveloped spherical virus
composed of a single molecule of RNA (7.5 kb) surrounded by a small (27 nm diameter) protein capsid and a buoyant density in CsCl of 1.33 g/ml. A large polyprotein is encoded by the
RNA and is processed into four structural and seven non‐structural proteins by proteases. The
genome encodes the structural proteins at the 5′‐end, and non‐structural proteins at the 3′‐
end. Seven genotypes have been recognised, four of which occur in humans. Genetic diversity
has been used to study food‐ and waterborne outbreaks.
Virulence aspects
The infectious dose is unknown but is presumed to be 10–100 virus particles. The incubation
period is dependent upon the number of infectious particles consumed and varies from 10 to
50 days (mean 30 days) with virus shedding starting 10–14 days before the onset of symptoms.
Typical symptoms of hepatitis A are:
• fever;
• headache;
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The microbiology of safe food
• chills;
• malaise;
• loss of appetite;
• nausea;
• jaundice;
• dark urine;
• light‐coloured stools;
• abdominal pain in liver area.
The signs of hepatitis start 1–2 weeks after the general symptoms of fever, headache and
malaise (Tables 1.3 and 1.4). The virus can be spread from early in the incubation period to
about a week after jaundice develops, especially in the middle of the incubation period, which
is before the symptoms develop. The virus enters the body through the intestinal tract and is
transported to the liver where it replicates in the hepatocytes and may be shed in the bile,
though it has also been isolated from spleen, kidneys, tonsils and saliva. Diagnosis of acute
hepatitis A is by the detection of IgM antibody to the capsid proteins. Only one serotype has
been observed amongst HAV isolates collected from various parts of the world, though the
incidence varies considerably amongst and within countries.
HAV has a worldwide distribution occurring in both epidemic and sporadic fashions. HAV
is primarily transmitted by person‐to‐person contact through faecal contamination, but
common‐source epidemics from contaminated food and water also occur. Poor sanitation and
crowding facilitate transmission. Outbreaks of HAV are common in institutions, crowded
house projects, prisons and in military forces in adverse situations. In developing countries,
the incidence of disease in adults is relatively low because of exposure to the virus in childhood.
Outbreaks under these conditions are rare since young children generally remain asymptomatic.
Most individuals of 18 and older demonstrate an immunity (IgG anti‐HAV antibodies) that
provides lifelong protection against reinfection.
Many infections with HAV do not result in clinical disease, especially in children. When
disease does occur, it is usually mild, self‐limiting and recovery is complete in 1–2 weeks.
Occasionally, the symptoms are severe and convalescence can take up to 6 months. Patients
suffer from feeling chronically tired during convalescence, and their inability to work can
cause financial loss. Approximately 15% of patients require hospitalisation and up to 20% may
have a relapse and be impaired for as long as 15 months. The fatality rate is 0.5–3% in adults
15–40 years old, and >1.8% in persons of >59 years. There is an unusually high fatality rate in
pregnant women (15–20%). Whilst HAV infection is regarded as one of the most severe foodborne illnesses, in most cases recovery is complete and lifelong immunity is acquired.
Sources and control
HAV is excreted in the faeces (up to 109 particles/g) of infected people and can produce clinical
disease when susceptible individuals consume contaminated water or foods. Cold cuts and
sandwiches, fruits and fruit juices, milk and milk products, vegetables, salads, shellfish and
iced drinks are commonly implicated in outbreaks. Water, shellfish and salads are the most
frequent sources. Since shellfish can filter up to 10 gal (38 l) water/hour, they can concentrate
the virus 100‐fold from contaminated water and depuration is about 100‐fold less effective at
removing viral pathogens as it is for bacterial pathogens. Consequently the use of indicator
bacteria for faecal bacteria in food and water is unreliable as an indicator for viral contamination.
Heating shellfish to >85°C for 1 minute will result in a 4 log decrease in infectious HAV (Lees
2000). Although heat inactivation of viruses has been studied in few foods other than shellfish,
Foodborne pathogens: viruses, toxins, parasites and prions
241
it is known that a heat treatment for milk of <0.5 minutes at 85°C is sufficient to cause a 5 log
drop in infectious HAV particles.
HAV is resistant to pH values as low as 1, survives at 60°C for 1 hour and is relatively resistant to free chlorine when organic matter is present. It is more resistant to heat and drying than
most other human enteric viruses. It can survive for long periods (weeks) in seawater, water
and on work surfaces. For example, only a 2 log decrease was detected after 50 days at 4°C in
water. Similarly, the virus infectivity at 4°C on an aluminium surface only decreased by 2 log
orders after 60 days. Consequently, contamination of foods by infected workers in food processing plants and restaurants is common. More than 1000 virus particles can easily be transferred from faecally contaminated fingers to foods and surfaces (Bidawid et al. 2000). Viruses
do not multiply on food – it is simply the vehicle of transmission. HAV outbreaks can be large.
The largest reported outbreak was in Shanghai when 250 000 people were infected with HAV
after consuming contaminated clams (Halliday et al. 1991). A smaller outbreak in the USA was
due to contaminated frozen strawberries distributed in school lunches. These caused 213 people to develop hepatitis A (Hutin et al. 1999). Hepatitis A infection has also been linked to the
consumption of lettuce, diced tomatoes and raspberries. The efficacy of disinfectants to kill
HAV and other viruses on the surface of fruits and vegetables is poorly studied due to the
greater technical difficulties in laboratory procedures compared with those for bacteria.
A vaccine is available for HAV and contacts can be treated within 2 weeks of exposure; however there is no consensus as to whether all food handlers should be vaccinated, instead personal hygiene is emphasised.
A fundamental problem with investigating HAV, and other viral cases of foodborne
infection, is that because of the long incubation period, any suspected food is unlikely still to
be available for analysis. In addition there are no methods available for the routine analysis of
food for viruses. Molecular methods involving PCR are being developed for the detection of
HAV in water and clinical specimens. These could also be applicable to food samples.
The largest hepatitis A outbreak to date occurred in October 2003. All but one of the initial cases
had eaten at the same restaurant in Pennsylvania, USA. In total 565 cases were confirmed, of whom
130 were hospitalised, and 3 died. The victims included at least 13 employees of the restaurant. It
was determined that >9000 people had either eaten at the restaurant, or had been exposed to cases,
and were given a post‐exposure vaccine against hepatitis A. A case–control study indicated fresh,
green onions that had been grown in Mexico were the probable source of this outbreak.
5.1.3 Hepatitis E
HEV is the major aetiological agent of enterically transmitted non‐A, non‐B hepatitis
worldwide. There are approximately 2 million cases of acute hepatitis E annually, most of
which are contracted in developing countries via contaminated water. The virus is spherical,
non‐enveloped, single‐stranded RNA that is ~32–34 nm in diameter. HEV has provisionally
been classified in the Caliciviridae family. This virus enters the body through water or food,
especially raw shellfish that has been contaminated by sewage. Anti‐HEV activity has been
determined in the sera of a number of domestic animals such as pigs in areas with a high
endemicity of human infection, indicating that this may be an emerging zoonosis (Meng et al.
1997). Previously infections in developed countries were primarily attributed to travel to
endemic regions such as South Asia, India and Africa. However, the number of cases not
linked to travel is rising and this may be linked to the consumption of pork products,
particularly if raw or undercooked. As with most other micro‐organisms, high temperatures
such as roasting or boiling should inactivate the virus.
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There are seven genotypes of which four are associated with human infection. Genotypes 1
and 2 are only found in humans. These are the genotypes that are endemic in parts of the
world. Genotypes 3 and 4 can infect a variety of animals, including humans, the latter being
found in Asia. Genotype 3 has been increasing in non‐travel‐related infection, and the main
risk group are males >55 years of age. The underlying reason for this is not known. Genotype
5 has only been associated with one human case.
5.1.4 Rotaviruses
General description
Rotaviruses are classified with the Reoviridae family. They have a genome consisting of 11
double‐stranded RNA segments surrounded by a distinctive two‐layered protein capsid.
Particles are 70 nm in diameter and have a buoyant density of 1.36 g/ml in CsCl. Six serological groups have been identified, three of which (groups A, B and C) infect humans
(Desselberger 1998).
Virulence aspects
Rotavirus gastroenteritis in the developed world is usually a self‐limiting, mild to severe disease characterised by vomiting, watery diarrhoea and low‐grade fever (Hart and Cunliffe 1999;
Ciarlet and Estes 2001). However, worldwide rotavirus is one of the worst infectious organisms
and kills up to 2000 children a day; 20–40 deaths/year in the USA compared with 15 000–
30 000/year in Bangladesh. Rotavirus kills one in 200–250 Indian children before they are
5 years old.
The infective dose is presumed to be 10–100 infectious viral particles (Shaw 2000; Lundgren
and Svensson 2001). Because a person with rotavirus diarrhoea often excretes large numbers
of virus (108–1010 infectious particles/ml of faeces) infectious doses can be readily acquired
through contaminated hands, objects or utensils (Ponka et al. 1999). Asymptomatic rotavirus
excretion has been well documented and may play a role in perpetuating endemic disease.
Sources and control
Rotaviruses are transmitted by the faecal–oral route. Person‐to‐person spread through contaminated hands is probably the most important means by which rotaviruses are transmitted
in close communities such as paediatric and geriatric wards, day care centres and family
homes. Infected food handlers may contaminate foods that require handling and no further
cooking, such as salads, fruits and hors d’oeuvres (Richards 2001). Rotaviruses are quite stable
in the environment and have been found in estuary samples at levels as high as 1–5 infectious
particles/gal. Sanitary measures adequate for bacteria and parasites seem to be ineffective in
endemic control of rotavirus, as similar incidence of rotavirus infection is observed in countries with both high and low health standards (Mead et al. 1999; Fleet et al. 2000; Inouye et al.
2000; Sethi et al. 2001). Rotaviruses survive in aerosols for up to 9 days at 20°C, and persist on
surfaces (aluminium, china, polystyrene) for 1–60 days with a 100‐fold reduction in infectivity
over 1 year in mineral water at 4°C (Beuret et al. 2000).
Group A rotavirus is endemic worldwide. It is the leading cause of severe diarrhoea
amongst infants and children, and accounts for about half of the cases requiring hospitalisation. Almost all children acquire serum antibodies by 5 years of age. Over 3 million cases
of rotavirus gastroenteritis occur annually in the US. In temperate areas, it occurs primarily
in the winter, but in the tropics it occurs throughout the year. The number of cases attributable to food contamination is unknown. Group B rotavirus, also called adult diarrhoea
Foodborne pathogens: viruses, toxins, parasites and prions
243
rotavirus or ADRV, has caused major epidemics of severe diarrhoea affecting thousands of
persons of all ages in China. Group C rotavirus has been associated with rare and sporadic
cases of diarrhoea in children in many countries, and the first outbreaks were reported
from Japan and England. The incubation period ranges from 1–3 days. Symptoms often
start with vomiting followed by 4–8 days of diarrhoea. Temporary lactose intolerance may
occur. Recovery is usually complete. However, severe diarrhoea without fluid and electrolyte replacement may result in severe dehydration and death. Childhood mortality caused
by rotavirus is relatively low in the US, with an estimated 100 cases/year, but this reaches
almost 1 million cases/year worldwide. Association with other enteric pathogens may play
a role in the severity of the disease.
The virus has not been isolated from any food associated with an outbreak, and no satisfactory method is available for routine analysis of food. Control of the organism is the same as for
hepatitis A and norovirus; that is, the prevention of food contamination by polluted water and/
or an infected food handler.
5.1.5 Small round viruses, astroviruses, sapporo‐like viruses, adenoviruses
and parvoviruses
Although the rotaviruses and noroviruses are the major causes of viral gastroenteritis, a
number of other viruses have been implicated in outbreaks, including astroviruses, enteric
adenoviruses and parvovirus. Viruses with smooth edges and no discernible surface structure
are designated ‘featureless viruses’ or ‘small round viruses’ (SRVs). These agents resemble
enterovirus or parvovirus and may be related to them.
Astroviruses cause sporadic gastroenteritis in children <4 years of age and account for
about 4% of the cases hospitalised for diarrhoea. Most American and British children over
10 years of age have antibodies to the virus. Astroviruses are unclassified viruses that contain
a single positive strand of RNA of about 7.5 kb surrounded by a protein capsid of 28–30 nm
in diameter. A five‐ or six‐pointed star shape can be observed on the particles under the electron microscope. Mature virions contain two major coat proteins of about 33 kDa each and
have a buoyant density in CsCl of 1.38–1.40 g/ml. At least five human serotypes have been
identified in England. The Marin County agent found in the USA is serologically related to
astrovirus type 5.
Sapporo viruses infect children between 6 and 24 months of age and account for about 3%
of hospital admissions for diarrhoea. By 6 years of age, more than 90% of all children have
developed immunity to the illness. Sapporo viruses are classified in the family Caliciviridae.
They are sometimes termed ‘typical caliciviruses’ to separate them from the other foodborne
infectious caliciviruses (noroviruses). They contain a single strand of RNA surrounded by a
protein capsid of 31–40 nm in diameter. Mature virions have cup‐shaped indentations that
give them a ‘Star of David’ appearance in the electron microscope. The particle contains a
single major coat protein of 60 kDa and has a buoyant density in CsCl of 1.36–1.39 g/ml. Four
serotypes have been identified in England.
The enteric adenovirus causes 5–20% of gastroenteritis cases in young children, and is the
second most common cause of gastroenteritis in this age group. The virus may be transmitted
by the respiratory route as well as oral–faecal, person–person and contaminated food. By
4 years of age, 85% of all children have developed immunity to the disease. Enteric adenoviruses
represent serotypes 40 and 41 of the family Adenoviridae. These viruses contain a double‐
stranded DNA surrounded by a distinctive protein capsid of about 70 nm in diameter. Mature
virions have a buoyant density in CsCl of about 1.345 g/ml.
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Parvoviruses belong to the family Parvoviridae, the only group of animal viruses to contain
linear single‐stranded DNA. The DNA genome is surrounded by a protein capsid of about
22 nm in diameter. The buoyant density of the particle in CsCl is 1.39–1.42 g/ml. The Ditchling,
Wollan, Paramatta and cockle agents are candidate parvoviruses associated with human
gastroenteritis. Shellfish have been implicated in illness caused by a parvo‐like virus. Parvo‐
like viruses have been implicated in a number of shellfish‐associated outbreaks, but the
frequency of disease is unknown. A mild, self‐limiting illness usually develops 10–70 hours
after contaminated food or water is consumed and lasts for 2–9 days. The clinical features are
milder but otherwise indistinguishable from rotavirus gastroenteritis. Co‐infections with
other enteric agents may result in more severe illness lasting a longer period of time. Only a
parvovirus‐like agent (cockle) has been isolated from seafood associated with an outbreak.
5.1.6 Human enteroviruses
The human enteroviruses are classified within the Picornaviridae and can be found in human
faeces and hence sewage. They include the polioviruses, group A and B coxsackieviruses,
echoviruses and enterovirus serotypes 68–71. The virus is a smooth, round, non‐enveloped
particle ~27 nm diameter with a positive sense, single‐stranded non‐segmented RNA genome.
Poliovirus can be transmitted by contaminated water and unpasteurised milk. Human
enteroviruses are the most common virus detected in shellfish. A small number of outbreaks
have been associated with coxsackie and echoviruses. Unfortunately, as previously stated, there
is no correlation between the presence of coliforms (indicator organisms) and human
enteroviruses. Poliovirus has been proposed as a suitable viral pathogen indicator since it is
more easily detected than other human enteroviruses, because of techniques developed
alongside vaccine production.
5.2 Seafood and shellfish poisoning
There are a number of causes of food poisoning originating from seafood and shellfish
(Tables 1.2 and 5.3). Ciguatera poisoning can be caused by a number of microalgae toxins
which have accumulated in fish flesh. It used to be believed that scombroid poisoning was due
to the consumption of fish flesh containing high levels of histamine from bacterial histidine
dehydrogenase activity on mackerel and similar fish. Incriminated bacteria are Morganella
morganii, Proteus species, Hafnia alvei and Klebsiella pneumoniae. However, this has not been
conclusively proven since human volunteers ingesting histamine do not always produce the
characteristic scombroid poisoning symptoms. Possibly there are other biogenic amines
present. Shellfish poisoning is caused by a group of toxins produced by planktonic algae
(dinoflagellates, in most cases) upon which the shellfish feed. The toxins are accumulated and
sometimes metabolised by the shellfish. Ingestion of contaminated shellfish results in a wide
variety of symptoms, depending upon the toxins(s) present, their concentrations in the
shellfish and the amount of contaminated shellfish consumed.
Paralytic shellfish poisoning is better characterised than the symptoms associated with
diarrhoeic shellfish poisoning, neurotoxic shellfish poisoning and amnesic shellfish poisoning.
All shellfish (filter‐feeding molluscs) are potentially toxic. Paralytic shellfish poisoning is generally associated with a range of shellfish: mussels, clams, cockles and scallops. Neurotoxic
shellfish poisoning is associated with shellfish harvested along the Florida coast and the Gulf
of Mexico. Diarrhoeic shellfish poisoning is associated with mussels, clams, oysters and scallops, whereas amnesic shellfish poisoning is only associated with mussels.
Foodborne pathogens: viruses, toxins, parasites and prions
245
Table 5.3 Micro‐organisms and toxins associated with seafood and shellfish poisoning.
Disease
Micro‐organism
Toxin
Incriminated seafood
Paralytic
shellfish
poisoning
Alexandrium catenella
Saxitoxin
Mussels, oysters, clams,
planktonivorous fish
Alexandrium tamarensis
Other Alexandrium spp.
Pyrodinium bahamense
Cymnodinium catenatum
Dinophysis fortii
Neosaxi toxin
Gonyautoxins
Other saxitoxin
derivatives
Okadaic acid
Dinophysis acuminata
Dinophysis acuta
Dinophysis mitra
Dinophysis norvegica
Dinophysis sacculus
Prorocentrum lima
Other Prorocentrum spp.
Cymnodinium breve
Dinophysis toxin
Pectenotoxin
Yessotoxin
Brevetoxins
Oysters, mussels,
clams, scallops
Pseudonitzschia pungens
Domoic acid
Mussels
Cambierdiscus toxicus
Ostroepsis lenticularis
Ciguatera toxin
Maitotoxin,
scaritoxin
Histamine and
other biogenic
amines
Reef‐associated fish
Diarrhoeic
shellfish
poisoning
Neurotoxic
shellfish
poisoning
Amnesic
shellfish
poisoning
Ciguatera
Scombroid
poisoning
Morganella morganii, Proteus spp., Hafnia
alvei, Klebsiella pneumoniae and other
bacteria capable of decarboxylating
amino acids to biogenic amines
Mussels, scallops,
clams, oysters
Scombroid fish species,
mahi mahi, bluefish,
tuna, sardines
Source: Adapted from ICMSF (1988).
5.2.1 Ciguatera poisoning
Ciguatera poisoning is characterised by:
• prickling of the lips, tongue and throat;
• headache;
• severe pain in arms, legs and eyes;
• impaired vision;
• skin disorders: blisters, stinging sensation and erythema.
The majority of cases recover within days to weeks and mortality is low. Ciguatera poisoning
is primarily caused by the lipid‐soluble ciguatera toxin (Figure 5.1; Murata et al. 1990). Other
toxins associated with the ciguatera cases are scaritoxin and maitotoxin. This polyether is similar in structure to the brevetoxins and is known to affect thermoregulation and sensory, motor,
autonomic and muscular activities. Scaritoxin is less potent than ciguatera toxin and may actually be a derivative of it. A third toxin has been implicated in ciguatera poisoning called maitotoxin. It activates Ca2+ channels, releases neurotransmitters and increases the contraction of
smooth, cardiac and skeletal muscles. Since there are a variety of symptoms it is possible there
are a range of toxins involved in the illness.
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CH3
CH3
CH3
O
OH
O
O
O
OH
OH
OH
O
O
O
O
O
OH
O
O
O
O
CH3
CH3
Figure 5.1 Ciguatera toxin structure.
5.2.2 Scombroid poisoning
Scombroid poisoning symptoms are:
• metallic, sharp or peppery taste in the mouth;
• intense headache;
• dizziness;
• nausea and vomiting;
• facial swelling and flushing;
• epigastric pain;
• rapid and weak pulse;
• itching skin;
• burning throat and difficulty in swallowing.
Usually recovery is within 12 hours. Fatalities are rare, and are usually due to other predisposing factors. Initially it was believed that the symptoms were caused by histamine intoxication – the histamine being bacterially produced during storage. However, studies on human
volunteers have failed to show a correlation between amounts of histamine in fish flesh and
scombrotoxicosis. Therefore, the causative agent is still unknown.
5.2.3 Paralytic shellfish poisoning
Paralytic shellfish poisoning symptoms are primarily neurological and include tingling, burning, numbness, drowsiness, incoherent speech and respiratory paralysis. Paralytic shellfish
poisoning is due to 20 toxins that are all derived from saxitoxin produced by dinoflagellates
(Figure 5.2).
5.2.4 Diarrhoeic shellfish poisoning
Diarrhoeic shellfish poisoning is normally a mild gastrointestinal disorder, i.e. nausea, vomiting, diarrhoea and abdominal pain accompanied by chills, headache and fever. Onset of diarrhoeic shellfish poisoning may be as little as 30 minutes to 3 hours depending on the dose of
toxin ingested. The symptoms may last as long as 2–3 days. Recovery is complete with no
aftereffects and the disease is generally not life‐threatening. It is probably caused by high
molecular weight polyethers, including okadaic acid, the dinophysis toxins, the pectenotoxins
and yessotoxin produced by dinoflagellates.
5.2.5 Neurotoxic shellfish poisoning
Neurotoxic shellfish poisoning causes both gastrointestinal and neurological symptoms,
including tingling and numbness of the lips, tongue and throat, muscular aches, dizziness,
reversal of the sensations of hot and cold, diarrhoea and vomiting. Onset of neurotoxic shellfish
poisoning occurs within a few minutes to a few hours. The illness duration is fairly short, from
Foodborne pathogens: viruses, toxins, parasites and prions
H2N
247
O
H
O
NH
NH
NH2+
NH
N
NH2+
OH
OH
H2N
O
H
O
NH
NH2+
NH2+
NH
N
OH
OH
Figure 5.2 The structure of saxitoxin (upper) and neosaxitoxin (lower).
a few hours to several days. Recovery is complete with few aftereffects; no fatalities have been
reported. The poisoning is due to exposure to a group of polyethers called brevetoxins produced by dinoflagellates.
5.2.6 Amnesic shellfish poisoning
Amnesic shellfish poisoning is characterised by gastrointestinal disorders (vomiting, diarrhoea,
abdominal pain) and neurological problems (confusion, memory loss, disorientation, seizure,
coma). The gastroenteritis symptoms occur within 24 hours, whereas neurological symptoms
occur within 48 hours. The toxicosis is particularly serious in elderly patients, and includes
symptoms reminiscent of Alzheimer’s disease. All fatalities to date have involved elderly patients.
It is caused by the presence of an unusual amino acid, domoic acid, as the contaminant of shellfish from diatoms (Figure 5.3). Hence it is also known as domoic acid poisoning.
O
O
O
O
NH
CH3
H
O
Figure 5.3 The structure of domoic acid.
CH3
O
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5.3 Foodborne parasites: eucaryotes
Box 5.2
Organism
Toxoplasma gondii, Trichinella spiralis
Food source
T. gondii: raw or undercooked meat, vegetables, goat’s milk, food and water contaminated with cat
faeces.
T. spiralis: pork, horse, wild boar, game.
Onset of symptoms
T. gondii: 5–23 days.
T. spiralis: 8–21 days.
Acute symptoms and chronic complications
T. gondii: abortion or stillbirth, brain damage.
T. spiralis: nausea, vomiting, diarrhoea, fever.
Box 5.3
Organism
Anisakis species, Taenia solium, T. saginata
Food source
Anisakis species: raw fish dishes; sushi, sashimi, herring, ceviche.
T. solium: raw or undercooked beef.
T. saginata: raw or undercooked pork.
Onset of symptoms
Anisakis spp.: days to weeks.
T. solium, T. saginata: days to years.
Acute symptoms and chronic complications
Anisakis species: ulceration of stomach wall, nausea, vomiting.
T. solium, T. saginata: nervousness, insomnia, anorexia, weight loss, abdominal pain.
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249
There are a number of protozoans and other eucaryotic organisms that are of major significance to human health. Their principal modes of transmission include ingestion of contaminated water and food, as well as person‐to‐person contact.
Foodborne parasites are increasingly recognised as a cause of human health problems. Two
well‐known examples that are significant causes of morbidity or mortality are T. gondii, a
particular hazard to pregnant women and the foetus, causing congenital toxoplasmosis; and T.
solium, the cause of neurocysticercosis. The disease burden of 11 foodborne parasites was
estimated to be 12 DALYs per 100 000 population, which is nearly 900 000 DALY when
extrapolated to the estimated European population of 740 million for 2015. The protozoans
Giardia lamblia, Cryptosporidium species and Entamoeba histolytica cause persistent diarrhoea. As usual those most at risk are young children, and those with immune deficiency.
The ranking of foodborne parasites varies amongst different regions of the world. For example, T. solium is ranked 10th in Europe, whereas it is first in world ranking. The reason for this
is T. solium is almost absent in Europe, but remains common in many Asian, South American
and African countries. The parasites ranking second (Echinococcus granulosus), third
(Echinococcus multilocularis) and fourth (T. gondii) in world ranking are also amongst the top
four in European ranking. Overall, E. multilocularis and T. gondii are considered the most
important foodborne parasites in terms of public health for Europe as a whole, but there is
some regional variation.
The epidemiology of infections by Cyclospora, Toxoplasma and Cryptosporidium is not fully
understood. However, although their life cycles are known to differ, a common feature is that
they all require passage through an animal or human intestinal tract. Cysts or spores are dispersed via faeces, which can contaminate water. Subsequently raw fruits and vegetables can
become contaminated during irrigation, washing or handling.
5.3.1 Toxoplasma gondii
Toxoplasma gondii is the causative agent of toxoplasmosis, and can be found in undercooked
and raw meats such as pork, lamb, beef and poultry. The primary hosts are cats, and human
infection takes place when contact is made with their faeces. This can also take place by the
ingestion of raw or undercooked meat from intermediate hosts, such as rodents, swine, cattle,
goats, chicken and birds. Raw or undercooked meat and raw vegetables contaminated with cat
faeces are recognised routes of infection.
Toxoplasmosis in humans often produces mononucleosis‐type symptoms, but transplacental infection can result in foetal death if it occurs early in pregnancy. The organism
causes hydrocephalus and blindness in children, the symptoms being less severe in adults.
In immunocompromised individuals it can cause pneumonitis, myocarditis, meningoencephalitis, hepatitis or chorioretinitis, or combinations of these. Cerebral toxoplasmosis is
often seen in AIDS patients. Proper cooking of meat will kill the organism. The incidence
of the disease worldwide is unknown but it is reported to be the most common parasitic
infection in the UK.
5.3.2 Taenia saginata and T. solium
Tapeworm (cestodes) infections in man are caused by the beef tapeworm (T. saginata) and
pork tapeworm (T. solium) through the consumption of raw or undercooked pork and beef,
respectively, which is infected with the parasite larvae. Both tapeworms are obligate parasites
of the human intestine. The organisms have a complex life cycle. The larval form is ingested in
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infected beef or pork meat and develops into the adult form (several metres in length), which
attaches to the intestinal wall and produces hundreds of proglottids, which are shed in the
faeces. The proglottids produce eggs in the environment and in the intestine, which are the
main vector in cattle and pig infection. In the otherwise healthy adult, taeniasis is not severe
and may not show any symptoms. However, people infected with T. solium are also potential
transmitters of cysticercosis. Cerebral lesions due to infection can lead to neurological and
mental symptoms. Taeniasis is endemic in some countries such as Ethiopia, Kenya, Zaire, former Yugoslavia and Central Asia. Breaking the life cycle of the organism is the main control
measure, through thorough meat inspection and adequate cooking (>60°C).
5.3.3 Echinococcus multilocularis and E. granulosus
Echinococcus multilocularis and E. granulosus are tapeworms that produce diseases known as
echinococcosis. This refers to a disease complex caused by the metacestodes of the parasite.
Echinococcus granulosus parasitises the small intestine of canids as an adult, but has important
intermediate hosts such as livestock and humans. Echinococcus multilocularis produces many
small cysts (also known as locules) that spread throughout the internal organs of the infected
animal. Humans are intermediate hosts, being infected by the larval stage of the worms through
ingestion of the parasite’s eggs. Oncospheres, which hatch from the eggs, are activated in the
small intestine and are released into the bloodstream where they mostly accumulate in the
liver. The parasites then grow into unilocular and multilocular cystic masses that result in
cystic echinococcosis and alveolar echinococcosis. Characteristically it can take 10–15 years
for the alveolar echinococcosis to develop in humans. This is characterised by liver failure and
can ultimately be fatal.
Echinococcus granulosus and E. multilocularis are the nearest phylogenetic neighbours in the
Taeniidae family. They share many aspects of growth and developmental plasticity as well as
similarities in their intermediate and definitive hosts. The genomes of these two parasites are
~115 Mb with 96% sequence identity within the coding regions. They both have an expansion
of similar gene families that specialise in nutrient uptake from the host and protection from
the host defensive system. Nevertheless, they differ in biological features, such as morphological characteristics during growth and development, and invasion into adjacent tissues within
the intermediate hosts. The E. granulosus metacestode grows slowly to form unilocular cyst
that cluster in the affected organs and tissues. In contrast, E. multilocularis metacestodes form
a multi‐vesiculated cystic mass with peripheral infiltration with central necrosis. This can
resemble an invasive malignant tumour. The intermediate hosts of the parasites differ: ungulates and humans for cystic echinococcosis, and rodents and humans for alveolar
echinococcosis.
5.3.4 Cyclospora cayetanensis
This coccidian parasite occurs in tropical waters worldwide and causes a watery and sometimes explosive diarrhoea in humans. The first known human cases were reported in 1979. It
was initially associated with waterborne transmission but has also been linked to the consumption of raspberries, lettuce and basil or basil‐containing products. Cyclospora infects the
small intestine. The incubation period is 1 week after the ingestion of the contaminated food
and the agent is shed in the faeces for >3 weeks. Cyclospora is spread by people who ingest
contaminated water or food. Direct person‐to‐person transmission is unlikely because excreted
oocysts require time (days to weeks) under favourable environmental conditions before they
become infectious (i.e. sporulate). The natural host for this parasite is unknown. Nevertheless,
contaminated water that is used for irrigation and pesticide application, as well as poor worker
hygiene, are the most likely routes of contamination.
Foodborne pathogens: viruses, toxins, parasites and prions
251
Typical symptoms of cyclosporiasis are:
• watery diarrhoea;
• frequent, sometimes explosive bowel movements;
• loss of appetite;
• substantial weight loss;
• abdominal bloating;
• increased gas and abdominal cramps;
• nausea;
• vomiting;
• muscular aches;
• low‐grade fever;
• fatigue.
The illness lasts from a few days to a month or longer. Relapses may occur one or more times
and asymptomatic infections do occur.
Multi‐state USA Cyclospora outbreak due to vegetable dip trays and salads, 2018
In 2018 the CDC identified two similar yet separate Cyclospora outbreaks across the USA.
There were a total of at least 400 cases and 10 hospitalisations, but no reported deaths. The
number of cases was expected to increase after the alert as it can take up to 2 weeks or longer
for infected people to develop symptoms. There is an additional delay of up to 6 weeks in
cyclosporiasis cases between when a person is initially diagnosed and when laboratory confirmation is reported to the CDC. The source of the parasitic infections was epidemiologically
traced to the salads and vegetable trays at major fast food chains. These are not cooked before
consumption. However, the specific ingredient was not identified.
There were 163 cases, with three hospitalisations, across 10 US states, all of whom had been
infected through salads. The onset date of illness was on or after 1 May through to 10 July.
Their ages ranged from 16 to 87 years old, and two‐thirds were female.
At least 237 cases, with seven hospitalisations were linked to pre‐cut vegetable trays. The
onset of symptoms was from 14 May to 13 June. The age range was 13–79 years old, and 53%
were female.
5.3.5 Cryptosporidium parvum
Box 5.4
Organism
C. parvum
Food source
Raw milk, drinking water, apple cider.
Onset of symptoms
2–14 days.
Acute symptoms and chronic complications
Diarrhoea, nausea, vomiting, abdominal pain, sometimes influenza‐like illness and fever.
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Cryptosporidium was first described in the early 1900s. However it was not considered to be
medically important until the 1970s when it was linked to diarrhoea in calves. The first human
case was in 1976, in a person who had been receiving immunosuppressive chemotherapy.
Further human cases were also immunosuppressed or immunodeficient. In the 1980s the first
cases of cryptosporidiosis in people with normal functioning immune systems and exposure
to calves were reported. Also outbreaks in day care centres and waterborne cryptosporidiosis
were recorded. In 1993 a massive waterborne outbreak in Milwaukee due to contaminated
water caused more than 400 000 illnesses.
Symptoms of cryptosporidiosis include fever, diarrhoea, abdominal pain and anorexia. The
disease usually lasts <30 days but may be prolonged in immunodeficient individuals and can
cause death. Genotyping can distinguish between human and bovine strains, although humans
are susceptible to bovine strains. The mode of transmission is faecal–oral via water and foods.
Reservoirs include man and domestic animals, including cattle. Oocysts can survive and
remain infective in the environment for long periods of time. Although they are resistant to
chemicals used to purify drinking water, they are removed by filtration.
Outbreak of C. parvum due to contaminated pre‐cut salad leaves, UK, 2012
(McKerr et al. 2015)
In 2012 a widespread foodborne outbreak of C. parvum occurred, which included cases in
England and Scotland. Cases were more common in female adults, none of whom had a history
of foreign travel. Over 300 cases were identified during the outbreak period. A case–control
study of 154 participants (74 cases and 74 controls) indicated a strong association with the
consumption of pre‐cut mixed salad leaves sold by a single retailer. Speciation and microbiological typing (real‐time PCR) showed the outbreak strain to be C. parvum gp60 subtype
IIaA15G2R1. This is the largest documented outbreak of cryptosporidiosis attributed to a food
vehicle.
5.3.6 Anisakis simplex
Anisakiasis is an infection of the human intestinal tract caused by the ingestion of raw or
undercooked fish containing larval stages of the nematodes A. simplex or Pseudoterranova
decipiens. Infections caused by the latter roundworm are not a serious threat to human health,
but those caused by A. simplex are more serious since it penetrates the gastrointestinal tissue
and causes symptoms that are difficult to diagnose. The primary hosts are warmblooded
marine mammals such as seals, walruses and porpoises. Their larvae pass via krill to fish such
as cod, pollock, halibut, rockfish, flat fish, mackerel, salmon and herring.
5.3.7 Trichinella spiralis
Trichinella spiralis is a nematode worm that is transmitted principally through raw or undercooked pork, as well as game (e.g. bear, wild boar). It causes trichinosis, also known as trichiniasis and trichinelliasis. It is mainly associated with the ingestion of contaminated pork. The
organism is a roundworm (nematode) that lives in the upper two‐thirds of the small intestine.
The female is viviparous, giving birth to living larvae that are deposited into the mucosa. About
1500 larvae are produced before the adult is expelled due to the host’s immune system. The
larvae are spread around the body via the bloodstream. Those that invade striated muscle (other
than cardiac muscle) continue to develop. The larvae are digested by humans and subsequently
invade the duodenal mucosa and become adult in 3–4 days, and so the life cycle continues.
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253
The main symptoms of trichinosis:
• First week: enteritis.
• Second week: irregular fever (39–41°C), muscle pain, difficulty in breathing, talking or
moving.
• Third week: high fever, swollen eyelids, muscle pain.
• Fourth week: fever and muscle pains subside.
The larvae can be killed by a number of methods: heating to 65.5°C (150°F), freezing at −15°C
(5°F) for 3 weeks or at −30°C (−22°F) for 1 day.
5.4 Mycotoxins
Mycotoxins are secondary metabolites produced by fungi. They have acute toxicity, and potential carcinogenicity to humans and animals, and have caused major epidemics in man and
animals. The toxic effect of mycotoxins on animal and human health is referred to as mycotoxicosis. Our initial awareness of mycotoxins started in 1960 when it was found that Turkey
X disease, which killed more than 100 000 turkeys, was caused by aflatoxins (produced by
Aspergillus species). Subsequently, it was found that aflatoxins are carcinogenic and cause
hepatocellular carcinoma in animals and humans. Contamination of feedstuffs as well as food
commodities by fungi occurs frequently in a natural manner and is accompanied by the presence of mycotoxins (Table 5.4). It has been estimated that 25% of the world’s crops such as nuts,
cereals and rice are contaminated by mould and fungal growth, as reviewed by the United
Nations Food and Agriculture Organisation and the World Health Organisation (Pandya and
Arade 2016). Consequently they are ubiquitous and widespread at all levels of the food chain.
Hundreds of mycotoxins have been identified and are produced by some 200 varieties of
fungi. Those of particular interest in food microbiology are the genera Aspergillus, Fusarium
and Penicillium. These fungi are ubiquitous and are part of the normal flora of plants. Annually,
over 1000 million tonnes of cereals are at risk of mycotoxin contamination.
The aflatoxins range from single heterocyclic rings to six‐ or eight‐membered rings
(Figure 5.4). Penicillium produces a range of 27 mycotoxins, such as patulin (an unsaturated
lactone) and penitrem A (nine adjacent rings composed of four to eight atoms). Ergotism,
alimentary toxic aleukia, stachybotryotoxicosis and aflatoxicosis have killed thousands of
humans and animals in the past century.
Table 5.4 Toxicity of mycotoxins.
Mycotoxin
Food
Fungus species
Biological affect
LD50 (mg/kg)
Aflatoxins
Maize, peanuts,
milk
Cheese, maize,
peanuts
Maize
Aspergillus flavus,
Aspergillus parasiticus
A. flavus, Penicillium
aurantiogriseum
Fusarium moniliforme
Hepatotoxin, carcinogen
0.5 (dog),
9.0 (mouse)
36 (rat)
Maize, cereals,
coffee beans
Maize, barley,
wheat
Penicillium verrucosum,
Aspergillus ochraceus
Fusarium graminearum
Cyclopiazonic acid
Fumonisin
Ochratoxin
Zearalenone
Source: Adapted from Adams and Motarjemi (1999).
Convulsions
Equine encephalomalacia,
pulmonary oedema in
pigs
Nephrotoxin
Oestrogenic
Unknown
20–30 (rat)
Not acutely
toxic
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The microbiology of safe food
O
O
O
O
O
OCH3
O
O
O
Aflatoxin B1
OCH3
O
O
Aflatoxin B2
O
O
O
O
O
OCH3
O
Aflatoxin G1
O
O
O
O
O
O
OCH3
Aflatoxin G2
O
O
O
O
OH
O
O
OCH3
Aflatoxin M1
Figure 5.4 The structure of aflatoxins.
Control of mycotoxins is very difficult as their spread is due to preharvest invasion by the
fungi through seeds, soil or even air. Adequate drying and storage are useful provided there are
good farm management practices beforehand. UV screening procedures (for fluorescence of
the aflatoxins) are of use in maize, cottonseed and figs, but not peanuts since they
autofluoresce.
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255
There are four types of toxicity:
• acute, resulting in liver or kidney damage;
• chronic, resulting in liver cancer;
• mutagenic, causing DNA damage;
• teratogenic, causing cancer in the unborn child.
5.4.1 Aflatoxins
The aflatoxins have been studied in more detail than other mycotoxins (Figure 5.4 and
Table 5.4). The aflatoxins are a group of structurally related toxic compounds produced by
certain strains of the fungi Aspergillus flavus and A. parasiticus under favourable conditions of
temperature and humidity. These fungi grow on certain foods and feeds, resulting in the production of aflatoxins. The most pronounced contamination has been encountered in tree nuts,
peanuts and other oilseeds, including maize and cottonseed. The major aflatoxins of concern
are designated B1, B2, G1 and G2 by the blue (B) or green (G) fluorescence given off when
viewed under a UV lamp. These toxins are usually found together in various foods and feeds
in various proportions. However, aflatoxin B1 is usually predominant and is the most toxic.
Aflatoxin M is a major metabolic product of aflatoxin B1 in animals. It is usually excreted in
the milk and urine of dairy cattle and other mammalian species that have consumed aflatoxin‐
contaminated food or feed. Lifetime exposure to aflatoxins in some parts of the world, commencing in utero, has been confirmed by biomonitoring.
Aflatoxins produce acute necrosis, cirrhosis and carcinoma of the liver in a number of animal species. No animal species is resistant to the acute toxic effects of aflatoxins, hence it is
logical to assume that humans may be similarly affected. A wide variation in LD50 values has
been obtained in animal species tested with single doses of aflatoxins. For most species, the
LD50 value ranges from 0.5–10 mg/kg body weight. Animal species respond differently in their
susceptibility to the chronic and acute toxicity of aflatoxins. The toxicity can be influenced by
environmental factors, exposure level and duration of exposure, age, health and nutritional
status of diet. Aflatoxin B1 is a very potent carcinogen in many species, including non‐human
primates, birds, fish and rodents. In each species, the liver is the primary target organ of acute
injury. Metabolism plays a major role in determining the toxicity of aflatoxin B1. This aflatoxin
requires metabolic activation to exert its carcinogenic effect and these effects can be modified
by induction or inhibition of the mixed function oxidase system.
The discovery of aflatoxins in the 1960s led to extensive surveying of koji moulds for mycotoxin production. Although under laboratory conditions mycotoxins can be produced by
A. oryzae, A. sojae and A. tamarii, no aflatoxins have been demonstrated in commercial
production strains (Tables 3.16 and 3.17). The moulds used in cheese manufacture have also
been tested for toxin production. Penicillium roqueforti produces trace amounts of patulin,
roquefortine C, whereas P. camemberti produces low levels of cyclopiazonic acid. These toxins
are only produced under laboratory‐induced stress conditions and it is reported that levels in
cheese are ‘extremely low’.
In developed countries, aflatoxin contamination of food rarely occurs at levels that could
cause acute aflatoxicosis. Instead human toxicity studies have focused on their carcinogenic
potential. Studies in Africa and South East Asia have shown an association between the incidence of liver cancer and dietary aflatoxin intake. Bowers et al. (1993) studied the possible link
between aflatoxin exposure, hepatitis B prevalence and primary liver cancer in China. This
included the data of Yeh et al. (1989) for almost 8000 men and aimed to construct a model for
extrapolation for the US. The best estimates of lifetime cancer potency of aflatoxin in the US
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The microbiology of safe food
O
O
O
OH
O
O
NH
CH3
H
Cl
O
O
O
NH
OH
O
O
CH3
H
Ochratoxin A (upper) and B (lower) structure
Figure 5.5 The structure of ochratoxins.
were 9 and 230 (mg/kg/day) for hepatitis B negative and positive populations, respectively. This
is lower than the 75 (mg/kg/day) estimate for Africa and South East Asia due to the greater
prevalence of hepatitis B.
5.4.2 Ochratoxins
Ochratoxins are produced by Aspergillus ochraceus, Penicillium verrucosum and P. viridicatum.
Ochratoxin A is the most potent of these toxins; Figure 5.5. The main dietary sources are cereals but significant levels of contamination may be found in grape juice and red wine, coffee,
cocoa, nuts, spices and dried fruits. Contamination may also carry over into pork and pig
blood products and into beer. Ochratoxin is potentially nephrotoxic and carcinogenic, the
potency varying markedly between species and sexes. It is also tetratogenic and
immunotoxic.
5.4.3 Fumonisins
Fumonisins are a group of Fusarium mycotoxins occurring worldwide in maize and maize‐
based products. Their casual role in several animal diseases has been established. Available
epidemiological evidence has suggested a link between dietary fumonisin exposure and human
oesophageal cancer in some locations with high disease rates. Fumonisins are mostly stable
during food processing.
5.4.4 Zearalenone
Zearalenone is a fungal metabolite mainly produced by Fusarium graminearum and F. culmorum, which are known to colonise maize, barley, wheat, oats and sorghum. These compounds
can cause hyperoestrogenism and severe reproductive and infertility problems in animals,
especially in swine, but their impact in public health is hard to evaluate.
5.4.5 Trichothecenes
Trichothecenes are produced by many species of the genus Fusarium. They occur worldwide
and infect many different plants, notable amongst which are the cereal grains, especially wheat,
barley and maize. There are over 40 different trichothecenes but the most well‐known are
deoxynivalenol and nivalenol. In animals they cause vomiting and feed refusal, as well as
Foodborne pathogens: viruses, toxins, parasites and prions
257
affecting the immune system. In humans they cause vomiting, headache, fever and nausea. A
large number of deoxynivalenol poisoning cases have occurred in China and India.
5.4.6 Prions and transmissible spongiform encephalopathies
Scrapie was the first recognised neurological disorder now known as zoonotic transmissible
spongiform encephalopathies (TSEs). The name scrapie comes from observations in the
eighteenth century of Merino sheep showing abnormal behaviour such as altered gaits,
excessive licking and intense itching that led them to pathologically scrape against fences
(Zabel and Reid 2015). Other TSEs are bovine spongiform encephalopathy (BSE) (‘mad cow
disease’) in cattle and Creutzfeld–Jakob disease (CJD) in humans. These are now known to
be caused by prions.
Prusiner and colleagues in 1982 purified infectious particles from scrapie‐infected hamster
brains, and demonstrated that the particles did not consist of nucleic acids (DNA or RNA), but
of a specific protein. This was called a ‘prion’, a term derived from the phrase ‘proteinaceous
infectious particle’. The infectious prion pathogen is derived from its endogenous cellular form
in the central nervous system. Instead of being genetically encoded, the prion traits are encoded
within the conformational structure and post‐translational modifications of the proteins (Das
and Zou 2016).
The EU BSE epidemic lasted from 1986 to 1998. It is commonly accepted that BSE originated in Britain when cattle were fed carcass meal from scrapie‐infected sheep. This resulted
in >180 000 cattle being infected, requiring an eradication programme that led to the destruction of 4.4 million cows.
Human cases of a non‐classic form of CJD called variant CJD (vCJD) are attributed to the
consumption of cattle meat, in particular nerve tissue. Evidence that the infectious agent was
a prion came from the studies of Collinge et al. (1996), Bruce et al. (1997) and Hill et al. (1997).
Prions are modified forms of a normal protein called PrPc, which is referred to as PrP* or PrPSc.
The proteins accumulate in the brain causing holes or plaques and the subsequent clinical
symptoms leading to death.
The average age at death from vCJD is 28.5 years (range 14–74 years). The median period
between onset and diagnosis is 328 days, and death in 413 days. It has also been proposed that
BSE‐contaminated milk may cause sporadic CJD. The link between BSE and vCJD led to significant changes in food safety policy.
On 20 March 1996 the Secretary of State for Health in the British Government announced
the most likely cause of 10 new cases in humans was the ingestion of meat from cattle suffering
from BSE (Will et al. 1996). This resulted in the Specified Offal Ban, which stopped the recycling of potentially infectious material (such as the spinal cord) to cattle through food supplements, and more stringent inspections of abattoirs. These restrictions and the decrease in BSE
cases mean that there should now be almost no exposure of the UK public to the infectious
agent. The number of BSE cases has decreased significantly in the EU, from 554 cases reported
in 2005 to just two in 2015 (both animals born after the ban). However, the incubation period
for vCJD of 2–5 years meant new cases continued after the bans were imposed.
The expected number of vCJD cases in the UK became a matter of controversy and was difficult to predict due to the uncertain incubation period and host–dose response. Some groups
claimed the number could not be estimated (Ferguson et al. 1999), whilst Thomas and Newby
(1999) estimate that the value will not exceed ‘a few hundred, and is most likely to be a hundred or less’, whereas Cousens et al. (1997) gave a value of 80 000. In total across Europe there
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The microbiology of safe food
30
25
20
15
10
5
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Figure 5.6 Number of vCJD deaths in the UK. Histogram of number of vCJD cases diagnosed (left‐hand bars),
and deaths (right‐hand bars) over the period 1995–2007. Please note that one death in 2003 and two deaths in
2006 were secondary cases linked to blood transfusions. Source: www.cjd.ed.ac.uk/sites/default/files/report26.
pdf, accessed on 17 December 2018.
were 229 deaths: 177 in the UK and 52 in other EU countries that were supplied with British
beef or beef products. Figure 5.6 gives the epidemic curve for vCJD cases in the UK during the
peak of the crisis from 1995 to 2007.
6 Methods of detection and characterisation
6.1 Prologue
There are an ever‐increasing number of detection methods for foodborne pathogens. These
may be conventional culturing methods, molecular techniques (often PCR‐based), as well as
immunological techniques (e.g. immunomagnetic capture and enzyme‐linked immunosorbent assay [ELISA]). Rapid screening methods are acceptable alternatives to conventional
culture methods when comparative studies establish that they are at least equivalent to the
approved standard cultural methods.
Initially microbial analysis of food was primarily end‐product testing, which screened
finished products before release. Negative test batches went into distribution, whereas the positive test batches were reprocessed or discarded. Although this approach reduced the release of
contaminated products onto the market, it did not help in preventing product contamination
or improving production efficiency. These days, the more effective food safety approaches aim
to eliminate foodborne pathogens by proactive screening from ingredients to finished product
with the Hazard Analysis and Critical Control Point (HACCP) approach (Chapter 9). By preventing pathogens from entering the production process or reducing them to acceptable levels,
and having critical microbial controls in place, the finished product should be within design
specifications. Therefore, current food safety focus is on prevention and process control, and
not retrospective control following the detection of processing failure.
Nevertheless detection methods are prolifically used in the food industry. Alocilja and Radke
(2003) estimate that the pathogen‐detecting biosensor market value was $563 million with
annual growth of 4.5%, of which the food industry accounted for $192 million. According to
Tom Weschler of Strategic Consultants (www.strategic‐consult.com), the worldwide food microbiology market in 2005 represented over 629 million tests with a market value in excess of $1.65
billion and a rate of growth of ~7–9%. In 2008 the number of tests was about 738 million, with
80% being general routine tests (i.e. total viable counts), and 138 million for specific pathogens
(market value ~$1 billion). Salmonella is the most frequently tested pathogen, followed by
Listeria, Escherichia coli O157 and Campylobacter. In 2010, the microbial testing of food represented a market worth >$2.4 billion with 822.8 million tests, with molecular and immunological‐based methods accounting for about 35% of the total number of tests. Although they are more
expensive per test, by definition they offer a faster throughput than conventional methods.
The choice of test varies per organism. For example conventional methods predominate for
Campylobacter species, whereas the opposite is true for E. coli O157. Around 68.5 million
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
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Salmonella tests are carried out annually, but the results may take several days. Hence there is
still a need for even more rapid testing, which would benefit both food producers and consumers. This chapter reviews the various methods available to detect the major foodborne
pathogens.
Analysing food and environmental samples for the presence of food poisoning and food
spoilage bacteria, fungi and toxins is standard practice for ensuring food safety and quality.
Despite the considerable collection of detection methods that have been developed, the interpretation of results in food microbiology is far more difficult than is normally appreciated. It
is not only the specificity and sensitivity of the method that needs to be appreciated, but also
how representative was the sample that was analysed. This chapter considers the major
groups of detection and characterisation methods available to the food microbiologist, and
the issues of sampling plans and statistical representation of samples are covered in Chapter 7.
The various reasons for caution in interpreting microbiological results include:
• Micro‐organisms are in a dynamic environment in which multiplication and death of different species occur at differing rates. This means that the result of a test is only valid for the
time of sampling.
• Viable counts by plating out dilutions of food homogenate onto agar media can be misleading if no micro‐organisms are cultivated yet preformed toxins or viruses are present. For
example, staphylococcal enterotoxin is very heat‐stable and will persist through the drying
process in the manufacture of powdered milk.
• Homogeneity of food is rare, especially with solid foods. Therefore, the results for one sample may not necessarily be representative of the whole batch. However, it is not possible to
subject a whole batch of the food to such examination for micro‐organisms as there would
be no product left to sell.
• Colony counts are only valid within certain ranges and have confidence limits (Table 6.1).
For of the reasons above, microbiological counts obtained through random sampling can only
form part of the overall assessment of the product.
There are a number of issues related to the recovery of micro‐organisms from food that
must be addressed in any isolation procedure:
1 If solid food, then a liquidised homogenate is necessary for dilution purposes.
2 The target organism is normally in the minority of the microbial population.
Table 6.1 Confidence limits associated with numbers
of colonies on plates.
95% confidence intervals
for the count
Colony count
Lower
Upper
3
5
10
12
15
30
50
100
200
320
<1
2
5
6
8
19
36
80
172
285
9
12
18
21
25
41
64
120
228
355
Source: Cowell and Morisetti (1969).
Methods of detection and characterisation
261
3 The target organism is present at low levels.
4 The target organism may be physically and metabolically injured.
5 The target organism may not be uniformly distributed in the food.
6 The food may not be of a homogenous composition.
Plate counts are obtained for three purposes and groups of organisms:
1 The basic aerobic plate count (APC) indicates the general microbial load and hence the shelf
life of the product. The APC is very useful in the food industry as the technique is easy to
perform and can provide a threshold for acceptance or rejection decisions for samples taken
regularly at the same point under the same conditions.
2 The presence of faecal organisms (i.e. Enterobacteriaceae) to indicate if the food has been
inadequately heat processed or has been mishandled and contaminated post‐processing.
3 Specific pathogens associated with the raw ingredients of processed food.
A degree of assurance is only obtained when tests on uniform quantities of representative samples of the food by standard methods prove negative. The methods therefore must be reliable,
robust and accredited. These aspects are considered in the following sections. Only representative
examples of detection methods can be covered here, and fuller details can be found in various
sources, such as those listed below. The reader should consult the most recent edition of these
for up‐to‐date protocols.
It is best to use validated methods to detect a target organism, especially since the results
may be of industrial, regulatory and even legal significance. There are national and international organisations for the standardisation and validation of methods. For example, the
International Organisation for Standardization (ISO) and the Association of Official Analytical
Chemists (AOAC) International’s Official Methods of Analysis.
Useful sources of approved protocols include:
• AOAC International;
• ISO;
• Food and Drug Administration (FDA) Bacteriological Analytical Manual;
• USDA Microbiology Laboratory Guidebook;
• Compendium of Methods for the Microbiological Examination of Foods.
The URLs for most of these organisations and laboratory manuals are given in the ‘Food Safety
Resources’ section.
The validity of a method can be defined as the ability of the test to do what it is intended to
do. This involves determining the ‘sensitivity’ and ‘specificity’ of the method. Sensitivity is the
probability of a sample testing positive if it is contaminated. Specificity is the probability of a
sample testing negative if the organism is truly absent. For many methods available for
foodborne pathogens, the sensitivity and specificity are both in the order of 95%.
New detection methods are constantly being announced, but their acceptance by industry
depends upon three criteria: speed, accuracy and ease of use. Industry requires testing with the
shortest time possible between sample availability and a test result. The accuracy of a method
includes its sensitivity, specificity and limit of detection, whereas ease of use refers to the level
of technical expertise and equipment. Essentially microbial detection methods can be divided
into conventional cell cultivation, and more rapid methods based on immunological and
molecular methods (Table 6.2). However, this is a very simplified categorisation as frequently
immunological and molecular methods require pre‐cultivation to enrich and amplify the
target organism to a detectable level.
Conventional cell culture methods normally require several days before a colony of the
target organism is visible and therefore an actionable test result is obtained. Despite this limitation many conventional methods are recognised as approved for international use by ISO, or
FDA, and are the gold standard procedure to which all others are compared. Conventional
Table 6.2 Selection of detection methods for major foodborne pathogens.
Organism
Method
Technique
Manufacturer
Campylobacter
spp.
Simplate Campylobacter CI
Biochemical assay
BioControl
O.B.I.S. campy
Phenotyping profile
Oxoid Thermo Fisher Scientific
Dryspot Campylobacter
Latex agglutination
Oxoid Thermo Fischer Scientific
Pathatrix
IMS (sample circulation)
Matrix Microscience
Campylobacter VIA
ELISA
TECRA/Biotrace
VIDAS Campylobacter
Automated ELFA
bioMérieux
Accuprobe Campylobacter
DNA hybridisation
Gen‐Probe
BAX
PCR
DuPont Qualicon
Hybridisation
Sigma‐Aldrich®
Bactiflow Salmonella spp.
Automated immunoassay
AES Chemunex
FastrAK™
IMS + bioluminescence +
phage capture
Alaska
S.P.R.I.N.T. Salmonella
Culture media
Oxoid Thermo Fisher Scientific
Brilliance™ Salmonella
Chromogenic agar
Oxoid Thermo Fisher Scientific
BBL CHROMagar
Chromogenic agar
BBL CHROMagar
ISO‐GRID Salmonella spp.
Hydrophobic grid
membrane
Neogen Corp.
API 20E, ID32 E
Biochemical test kits
bioMérieux
O.B.I.S. Salmonella
Phenotyping profile
Oxoid Thermo Fisher Scientific
Assurance Salmonella
Immunoassay
BioControl
Anti‐Salmonella Dynabeads
IMS
In Vitrogen
Pathatrix
IMS (sample circulation)
Matrix Microscience
Salmonella Unique
Immunoassay
TECRA/Biotrace
VIDAS Salmonella
Automated ELFA
bioMérieux
GENE‐TRAK Salmonella
DNA hybridisation
Neogen Corporation
MicroSeq
DNA sequence
Applied Biosystems
PROBELIA Protocol
PCR
Bio‐Rad Laboratories
BAX
PCR
DuPont Qualicon
Hybriscan
Hybridisation
Sigma‐Aldrich
DuPont™ Lateral Flow
System
Lateral flow system
DuPont Qualicon
Brilliance agar
Chromogenic agar
Oxoid Thermo Fisher Scientific
TEMPO EC
MPN culture
bioMérieux
Harlequin™
Chromogenic agar
LabM
®
Hybriscan
Salmonella
serovars
Escherichia coli
®
®
E. coli O157
VIDAS UP E. coli O157
bioMérieux
Anti‐E. coli O157
Dynabeads
IMS
In Vitrogen
Captivate™
IMS
LabM
FastrAK
IMS + bioluminescence +
phage capture
Alaska
Foodproof
PCR
Merck KgaA
BAX
PCR
DuPont Qualicon
DuPont Lateral Flow
System
Lateral flow system
DuPont Qualicon
Methods of detection and characterisation
263
Table 6.2 (Continued)
Organism
Method
Technique
Manufacturer
Staphylococcus
aureus
TEMPO STA
MPN culture
bioMérieux
CHROMagar St. aureus
Chromogenic agar
BBL
VITEK® Gram‐positive
Phenotyping profile
bioMérieux
RapID™ STAPH PLUS
Phenotyping profile
Oxoid Thermo Fisher
Scientific
BAX
PCR
DuPont Qualicon
St. aureus
toxins
TST‐RPLA & SET‐RPLA
RPLA
Oxoid Thermo Fisher Scientific
Listeria
monocytogenes
BAX
PCR
DuPont Qualicon
DuPont Lateral Flow
System
Lateral flow system
DuPont Qualicon
ALOA®
Chromogenic agar
AES Chemunex
GENE‐TRAK Listeria
DNA hybridisation
Neogen Corporation
VITEK Gram‐positive
Phenotyping profile
bioMérieux
O.B.I.S. mono
Phenotyping profile
Oxoid Thermo Fisher Scientific
Hybriscan
Hybridisation
Sigma‐Aldrich
Duopath® cereus
enterotoxins
Lateral flow device
Merck KGaA
Bacillus‐ID
Phenotyping profile
Microgen Bioproducts Ltd
Phenotype Microarray™
Phenotyping profile
Biolog Inc
CP ChromoSelect agar
Chromogenic agar
Sigma‐Aldrich
m‐CP
Chromogenic agar
Oxoid Thermo Fisher Scientific
PET‐RPLA
RPLA enterotoxin
Oxoid Thermo Fisher Scientific
Bacillus cereus
Clostridium
perfringens
methods are relatively easy to use, and require an appropriately trained laboratory staff for
sample preparation and interpretation of results. Good Laboratory Practices (GLPs) are necessary for sample and media preparation, and most of the materials required are disposable
consumables. There are a large number of companies that produce dehydrated media, and
pre‐poured, sample‐ready plates.
Immunological methods are mostly based on the antigen/antibody‐binding affinity using
the ELISA technology. Antibodies with high specificity to an antigen of the target organism
are anchored to a solid surface, such as the wells of a microtitre tray. These can be stored for a
long period of time until required for use. If the target antigen is present in the sample, it will
bind to antibody, and non‐target organisms will be removed by subsequent washing steps.
A second antibody conjugated to an enzyme (i.e. horseradish peroxidase) is then added that
will bind to the pre‐existing cell–antibody–surface complex, forming what is known as an
‘antibody–antigen–antibody sandwich’. The presence of target cells is visualised by adding the
enzyme’s substrate resulting in a colorimetric or fluorescent reaction, the intensity of which
determines the presence or absence of the target organism in the original sample. The accuracy of the method depends upon the specificity of the antibodies, and false‐positive and
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The microbiology of safe food
false‐negative results may occur due to cross‐reactivity with related non‐target organisms, or
the absence of the target antigen in some strains of the target organism. The detection limit of
the ELISA method is ~104–106 cells and therefore the sample must be enriched in a growth
medium (a time‐consuming step) to amplify the target organism to a detectable level beforehand. Therefore, the speed of ELISA technology is determined by the target and the duration of
the sample enrichment. Immunological kits for various pathogens are commercially available.
The cost per test for consumables, including enrichments and reagents, is in the $4–6 range.
Molecular methods are frequently based on the PCR reaction. Being DNA‐based the methods can be highly accurate and are not subject to variation in protein expression as can occur
with immunological methods targeting cell surface structures. Nevertheless, the detection is
commonly after a time‐consuming sample enrichment step in order to increase the number of
target organisms to ~104. As for the other methods, trained laboratory staff are required for
sample analysis and interpretation. The average test cost is in the $5–10 range. Although this
is more expensive than conventional and immunological tests, since multiple samples can be
processed simultaneously using automated procedures, sample analysis productivity is greater.
Other emerging rapid methods are being developed using laser‐based technologies such as
flow cytometry and Raman spectroscopy in which unique, target‐specific spectral signals are
developed. In flow cytometry, the laser may excite specific nucleic acid sequences or proteins
in the target organism and offers very short detection times. Being able to detect multiple targets simultaneously, giving the desirable speed, accuracy and ease of use of reliable real‐time
results may be achievable due to current developments in biosensors. In the future multiple
organisms and toxins could be analysed for in a single test, and the unit could be reusable.
Currently the closest real‐time result‐based analysis is probably adenosine triphosphate (ATP)
testing for hygienic monitoring. Even though this method does not detect any specific pathogens, it is normal practice for >37% of all food processing plants, and over 30 million ATP
monitoring tests are performed annually (Weschler, Strategic Consulting). One can only imagine
the market for a real‐time test that covers at least the major foodborne pathogens.
6.2 Conventional methods
A number of steps are required in order to successfully isolate target organisms from food.
• Choose representative samples to test the batch of ingredients/food.
• Where practical, homogenise the food before sampling. Otherwise take representative samples from the different phases (liquid/solid). Volumes of food analysed are often 1 g when
direct enumeration is used; or 25 g when a large sample size is required for presence/absence
testing. Multiple numbers of samples may be required from each batch of food, depending
on the appropriate microbiological criteria (Chapter 7).
• Homogenise solid ingredients/food using a Stomacher™ or Pulsifier® machine.
• A pre‐enrichment step may be required to allow any injured cells to repair their damaged
membranes and metabolic pathways. Injury may have occurred during processing (cooking,
desiccation, etc.).
• Enrich the target organisms from within the mixed flora using a medium that encourages
the growth of the target organisms and suppresses the growth of other micro‐organisms.
Conventional methods are frequently plate counts obtained from homogenising the food sample, diluting and inoculating specific media to detect the target organism (Figure 6.1). The first
step is normally preparing a 1:10 dilution of the food. The sample is usually homogenised in
order to release attached micro‐organisms from the food surface. The methods are very sensitive and relatively inexpensive (compared with rapid methods), but require incubation periods
of at least 18–24 hours for visible colony formation.
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Pre-enrichment
Recovery of injured cells
1–25 g of sample
1:10 dilution in pre-enrichment broth
Enrichment
Suppress growth of non-target organisms
Subculture on selective agar
Differential media to distinguish target from non-target isolates
Subculture on non-selective media
(check isolate purity)
Biochemical and serological tests as appropriate
Figure 6.1 General sequence of isolation of foodborne pathogens: presence/absence testing.
The target organism, however, is often in the minority of the food microbial flora and may
be sublethally injured due to processing (cooking, etc.). Therefore, the above procedure is frequently modified to allow a recovery stage for sublethally injured cells, or to enrich for the
target organism. For example, the recovery of Salmonella serovars from ready‐to‐eat foods
occurs in the stages pre‐enrichment, enrichment, selection and detection, and uses a large
sample size (25 g). The procedure is covered in more detail in Section 6.7.2. As referred to
above, this approach is ‘bacteriological’ rather than ‘microbiological’ in that the presence of
toxins, protozoa and viruses will not be revealed.
Specific examples of methods for the detection of key target organisms are given in later sections.
6.2.1 Culture media
Conventional food microbiology requires the use of broths and agar plates to cultivate the
target organism(s). These media must meet the organism’s nutritional and physiological requirements. Hence the media must be designed with sufficient protein, carbohydrates and minerals
as well as a suitable pH, and incubated under favourable conditions of temperature and oxygen
availability for an adequate length of time. In general terms, media whether as a broth or in a
solid agar form may be (i) non‐selective and able to grow most organisms in a sample, (ii)
selective to favour the growth of a target organism or (iii) semi‐selective and differential where
the target organism is presumptively identified based on colony morphology including colour
in the presence of other organisms. Such presumptive isolates require further confirmatory
tests, which are frequently phenotypic (biochemical profiles). Selective media may be designed
to suppress the growth of non‐target organisms while enabling the differential growth of the
target organism. If the target organism outgrows the non‐target organism by >100‐fold in broth
culture, there is a good chance that it will be isolated as a pure culture on plating out. Ideally
selective media will be non‐inhibitory to the target organism. This is not always achieved, but
preferably the media will recover more than 50% of the initial population.
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E. coli
β-glucuronidase
β -D-glucuronide 4-methyl-umbelliferyl
Coliforms
4-methyl-umbelliferone
(fluorescence, UV 365 nm)
β-galactosidase
β-D-galactopyranoside o-nitrophenyl
o-nitrophenol
(bright yellow)
Enterococci
β-glucosidase
β -D-glucoside-4-methyl-umbelliferyl
4-methyl-umbelliferone
(fluorescence, UV 365 nm)
Figure 6.2 Fluorogenic substrates for specific detection of food pathogens.
Fermentation of carbohydrates is frequently used in differential agar. Violet red bile lactose
agar (VRBA) contains the indicator neutral red causing lactose‐fermenting organisms (commonly
referred to as ‘coliforms’) to acquire a pink‐red colour. This differentiates them from other
bile‐resistant Gram‐negative organisms. Although pH indicators have a long history of use,
they suffer in that the surrounding medium may change colour and the observer may be unable to select the target organism when large numbers of colonies have grown on the plate.
The advantage of incorporating fluorogenic and chromogenic substrates into growth media
is that they generate brightly coloured or fluorescent compounds after bacterial metabolism
(Plate 5) (Manafi 2000). Therefore, colonies of the target organism can be spotted on a mixed
flora plate, even when considerably outnumbered. The main fluorogenic enzymes substrates
in use are based on 4‐methylumbelliferone, such as 4‐methylumbelliferyl‐β‐D‐glucuronide
(MUG) (Figure 6.2). Although these compounds are very specific for the distinguishing enzyme
activity, they can diffuse into the medium making the target colony less noticeable in a mixed
flora. In addition, they require the medium to be slightly alkaline, and require a UV light source
for visualisation. Consequently, the application of MUG subtrates has been limited. Chromogenic
substrates commonly used are indoxyl substrates, for example 5‐bromo‐4‐chloro‐3‐indolyl‐β‐D‐
glucuronic acid (BCIG), which in the presence of oxygen form coloured aglycones; examples
are shown in Plate 4. In contrast to MUG substrates, these do not diffuse into the agar. TBX agar
(Oxoid Thermo Fisher, Merck and LabM) is an example of a chromogenic agar for the detection
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267
of E. coli, which is based on the splitting of BCIG by β‐D‐glucuronidase enzyme activity to
form blue‐green colonies. Unlike the majority of E. coli strains, those in the serovar group
O157:H7 do not ferment sorbitol or rhamnose in the presence of sorbitol. They are β‐D‐
glucuronidase negative and do not grow at 45.5°C. This has enabled the design of specific
chromogenic agars such as CHROMagar O157 (CHROMagar) and Fluorocult E. coli O157:H7
(Merck), which can differentiate between the two types of E. coli based on sugar fermentation
by colony colour.
Although very popular with media manufacturers, the indoxyl substrates require the presence of oxygen or other oxidants for colour formation, and may produce toxic intermediates.
Chromogens and fluorogens (ALDOL™) that do not require oxidation have been developed by
Biosynth AG (Switzerland). These undergo intramolecular aldol condensation to form insoluble dyes. Consequently they can be incorporated into media for use under both aerobic and
anaerobic incubation conditions, which was not feasible with indoxyl substrates.
Media such as the modified semi‐solid Rappaport–Vassiliadis medium and Diagnostic
Semi Solid Salmonella (DIASALM) agar have used bacterial motility as a means to enrich for
the target organism. This principle has been applied to the improved detection of Salmonella
serovars (as per above examples), Campylobacter and Arcobacter species. The semi‐solid
Rappaport medium isolates motile Salmonella as they migrate through the medium ahead of
competing organisms. This medium however will not isolate non‐motile Salmonella strains.
Compact Dry and the Petrifilm® system (manufactured by 3M) are alternatives to the conventional agar plate. The Petrifilm system uses a dehydrated mixture of nutrients and gelling agent
on a film. The addition of 1 ml of sample rehydrates the gel, which enables the colony formation
of the target organism. Colony counts are performed as per the standard agar plate method. The
throughput of samples is estimated to be double that of conventional agar plates. Petrifilm systems are available for various applications including APCs, yeast, coliforms and E. coli (Plate 6).
6.2.2 Sublethally injured cells
Sublethal injury implies damage to structures within the cells that causes some loss or alteration of cellular functions, the leakage of intracellular material and making them susceptible to
selective agents. Changes in cell wall permeability can be demonstrated by the leakage of compounds from the cytoplasm (increase absorbance at 260 nm of culture supernatants) and the
influx of compounds such as ethidium bromide and propidium iodide.
Conditions that can generate sublethally injured cells include:
• moderate heat: pasteurisation;
• low temperature: refrigeration;
• low water activity: dehydration;
• radiation: gamma rays;
• low pH: organic and inorganic acids;
• preservatives: sorbate inclusion;
• sanitisers: quaternary ammonium compounds;
• pressure: high hydrostatic pressure;
• nutrient deficiencies: clean surfaces.
Cells in the exponential phase of growth are generally less resistant than cells in the stationary
phase due to the synthesis of stress resistance proteins.
‘Metabolic’ injury is often taken as the inability to form colonies on minimal salt media
while retaining colony‐forming ability on complex nutrient media, whereas ‘sublethal’ injury
can be taken as the inability to proliferate or survive in media containing selective agents that
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have no apparent inhibitory action upon non‐stressed cells. Injury is reversible by repair but
only if the cells are exposed to favourable resuscitation conditions such as a non‐selective
nutrient‐rich medium under optimal growth conditions.
In practical analytical food microbiology the phenomenon of injury may present considerable problems as many of the physical treatments including heat, cold, drying, freezing, osmotic
activity and chemicals (disinfectants, etc.) may generate injured cells causing variations in plate
counts. The injured cells may remain undetected as selective media usually contain stressing
ingredients such as increasing salt concentrations, deoxycholate lauryl sulphate, bile salts,
detergents and antibiotics. The injured cells are ‘viable’ but are not metabolically active enough
to achieve cell division. Subsequently microbiological examination for quality control can indicate low plate counts, when in fact the sample contains a high number of injured cells. An
example of the difference between plate counts on selective and non‐selective agar can be seen
in Figure 3.7 where food pathogens have been exposed to high pressure.
In food and beverage products, once the stress‐causing injury is removed, these injured cells
are often able to recover. The cells regain all of their normal capabilities, which include pathogenic and enterotoxin properties. Therefore, important food poisoning organisms may be
undetected by analytical testing, but may cause a major food poisoning outbreak. For these
reasons, substantial efforts need to be made to develop improved analytical procedures that
will detect both injured and uninjured cells.
In Salmonella detection (Section 6.7.2) the sample is incubated overnight in buffered peptone water (BPW) or lactose broth to allow injured Salmonella cells to recover and multiply to
detectable levels. However, it is uncertain if BPW is the best recovery medium since other
organisms can suppress the growth of low numbers of salmonellae and also there is the problem of ‘how do you know if injured Salmonella were present in the sample if you do not detect
a colony on a plate?’.
For other organisms that might be sublethally injured it has been recommended that food
samples should be resuscitated in a non‐inhibitory medium for an hour or two, allowing injured
cells to resuscitate yet prevent the population size increasing. This generalised approach is far
from optimised and leaves plenty of opportunity for oversight in the detection of potentially pathogenic food poisoning organisms. Hence such techniques need to be appropriately validated.
Extreme environments usually kill the majority of the bacterial population, and can result in
the selection of resistant mutants. It is possible that stress induces hypermutability and leads to
the greater chance of survivors. The cross‐protection effect in which exposure to one stress
induces the resistance to another stress is of particular concern for food processing. For example, acid‐adapted E. coli O157:H7 is more heat tolerant. Similarly, heat‐shocked Listeria monocytogenes increases its resistance to ethanol and salt.
6.2.3 Viable but non‐culturable bacteria (VBNC)
It has been proposed that many foodborne bacterial pathogens are able enter a dormant state
(Zhao et al. 2017). Such cells are not culturable by conventional methods, but remain viable (as
demonstrated by substrate uptake) and virulent. Hence the term ‘viable but non‐culturable’ or
VBNC was derived. This phenomenon has been shown in Salmonella serovars, Campylobacter
jejuni, E. coli, Vibrio vulnificus and V. cholerae. For example, in the human intestine previously
non‐culturable vibrios were shown to regain their ability to multiply (Colwell et al. 1996).
Therefore, VBNC bacterial pathogens pose a potential threat to health and are of considerable
concern in food microbiology since a batch of food might be released due to the apparent
negative presence of pathogens, yet contain infectious cells.
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VBNC bacterial cells maintain their cell integrity but exhibit dwarfing and have coccoid
morphology. The VBNC state may be induced due to a number of extrinsic factors such as
temperature changes, low nutrient level, osmotic pressure, water activity and pH. Therefore,
foodborne pathogens may enter the VBNC state during food processing techniques, such as
high temperature, high pressure, disinfectant, preservation and low temperature storage.
Consequently there will be a food safety risk as the organisms will not be detectable by the
standard accredited detection methods. Hence current methods may not be recovering all
the pathogens from foods and water. Therefore alternative end‐detection methods need to be
further developed, such as those based on immunology and DNA sequences.
The VBNC concept is not accepted by all microbiologists. Some argue that it is only a matter
of time until we design the most appropriate recovery media and others that the cells have
self‐destructed due to an oxidative burst causing DNA damage (Barer 1997; Barer et al. 1998;
Bloomfield et al. 1998).
6.3 Rapid sampling methods
New pathogen identification technologies are faster than conventional methods, and increasingly automated. No single method is appropriate for all circumstances, so the selection of the
most appropriate method is necessary. Conventional procedures are by nature labour‐intensive
and time‐consuming. Therefore, a plethora of alternative, rapid methods have been developed
to shorten the time between taking a food sample and obtaining results. These methods aim to
either replace the conventional enrichment step with a concentration step (i.e. immunomagnetic separation [IMS]) or to replace the end‐detection method with one that requires a shorter
time period (i.e. ATP bioluminescence).
Major improvements have been in three areas:
1 sample preparation;
2 separation and concentration of target cell, toxins or viruses;
3 end‐detection.
Sometimes a rapid technique will involve one or more of the above aspects, i.e. the hydrophobic
grid membrane filter (HGMF) method both concentrates the organisms and enumerates on
specific detection agar media.
6.3.1 Sample preparation
Agar slides containing selective or non‐selective agar can be pressed against the surface to be
examined and directly incubated. This obviates the need for sampling and the errors inherent
in releasing organisms from cotton wool swabs. Samples can be put onto agar surfaces in a
spiral format allowing several effective dilutions to be countable on one plate (Plate 7).
Another improvement in recent years in sample preparation is the automatic diluter, which
simply enables the operator to take a food sample of ~10 g, and then an appropriate volume of
diluent is added to give an accurate 1:10 dilution factor.
6.3.2 Separation and concentration of target
Separation and concentration of target organisms, toxin or viruses can shorten the detection
time and improve specificity of a test procedure. Common methods include:
• IMS;
• Direct Epifluorescent Filter Technique (DEFT);
• HGMF.
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Immunomagnetic separation
IMS is increasingly being used as it significantly reduces the detection period due to the elimination of a culture‐enrichment step. It uses superparamagnetic particles (3–5 μm diameter)
that contain γ‐Fe2O3 and are coated with antibodies against the target organism. Hence the
target organism is ‘captured’ in the presence of a mixed population due to the antigen–antibody specificity. This has removed the need for an overnight enrichment broth incubation
period in Salmonella isolation, and for E. coli O157 the enrichment step is only 6 hours (see
Section 6.7.4). A generalised procedure is given in Figure 6.3, and Plate 8. Commercially
available IMS kits target key food and water pathogens: Salmonella serovars, E. coli O157:H7,
Mixed microbial culture, for example overnight
pre-enrichment broth
Addition of antibody-coated paramagnetic
particles
Incubate ca. 10 minutes
Antibody beads bind to target organism
Placement of magnet temporarily immobilises
target organism, facilitating removal of non-target
cells, via pipetting, and so on
Resuspension and washing of antibody-bead
bound target cells
Pipetted onto selective media, ELISA, DNA techniques, and so on
Figure 6.3 Immunomagnetic separation (IMS) technique.
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271
Table 6.3 Applications of immunomagnetic separations (IMS).
Organism
Application
Escherichia coli O157
Salmonella serovars
Listeria monocytogenes
Staphylococcus aureus
Cryptosporidium parvum
Legionella species
Yersinia pestis
Chlamydia trachomatis
HIV
Erwinia chrysanthemi
Erwinia carotovora
Saccharomyces cerevisiae
Mycobacterium species
Food and water microbiology
Clinical microbiology
Plant pathogen detection
Biotechnology
Source: Adapted from Safarik et al. (1995).
L. monocytogenes and Cryptosporidium (Table 6.3). IMS can enrich for sublethally injured
micro‐organisms that would otherwise be missed using the standard enrichment broth and
plating procedures. These organisms might be killed in the enrichment broth due to changes
in cell wall permeability. Dead cells can be detected using a combined IMS and PCR procedure. IMS can be combined with almost any end‐detection method: culture media, ELISA and
DNA probe.
The IMS Salmonella detection method is as efficient as the enrichment broth selection stage,
which is the most efficient of the ISO procedures (Mansfield and Forsythe 1996, 2000a;
Section 6.7.2). The selective enrichment step (overnight incubation) is replaced with the IMS
(10 minutes). Hence the technique reduces the total time required for sampling and detection
by 1 day. In addition IMS can have a greater recovery of stressed Salmonella cells than ISO
protocols.
Commonly the first step in isolating a pathogen is pre‐enrichment to aid the recovery of
damaged cells, followed by enrichment to encourage the growth of the target organism and
suppress non‐target cells. Yet at each stage only a small aliquot is taken, leaving the bulk of the
microbial culture to be discarded. To increase sensitivity, a variation on the IMS technique is
to circulate the total volume over the magnet during incubation. This approach has been demonstrated by Pathatrix (Matrix MicroScience) to be very effective and rapid for detecting the
presence of Salmonella and E. coli O157 from a variety of food samples.
Direct epifluorescent technique (DEFT) and hydrophobic grid membrane filters (HGMF)
Membrane filters can be used to shorten the overall detection time because:
1 They can concentration the target organism from a large volume to improve detection
limits.
2 They remove growth inhibitors.
3 They transfer organisms to a different growth media without physical injury through centrifugation and resuspension.
The membranes can be made from nitrocellulose, cellulose acetate esters, nylon, polyvinyl
chloride and polyester. Because they are only 10 μm in thickness they can be directly mounted
on a microscope and the cells visualised.
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Milk, 2 ml
Add trypsin, 0.5 ml
+ Triton ×100, 2 ml
Incubate 50°C, 20 minutes
Filter through Nuclepore MF
Add acridine orange, 2 minutes
Wash + air dry
Observe under epifluorescence microscope
Dead cells fluoresce green
Living cells fluoresce red
Figure 6.4 Direct Epifluorescent Filter Technique (DEFT) for the detection of bacteria in milk.
The DEFT method concentrates cells on a membrane before staining with acridine orange
(Figure 6.4). Acridine orange fluoresces red when interchelated with RNA and green with
DNA. Subsequently viable cells fluoresce orange‐red, whereas dead cells fluoresce green.
The DEFT count has gained acceptance as a rapid, sensitive method for enumerating viable
bacteria in milk and milk products. The count is completed in 25–30 minutes and detects as
few as 6 × 103 bacteria per ml in raw milk and other dairy products, which is three to four
orders of magnitude better than direct microscopy. Because it is a microscopic technique one
is able to distinguish whether the micro‐organisms present are yeasts, moulds or bacteria.
HGMF is a filtration method that is applicable to a wide range of micro‐organisms (Entis
and Lerner 1996, 2000). The pre‐filtered food sample (to remove particulate matter >5 μm) is
filtered through a membrane filter, which traps micro‐organisms on a membrane in a grid of
1600 compartments, due to hydrophobicity effects. The membrane is then placed on an appropriate agar surface and the colony count determined after a suitable incubation period.
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6.4 Rapid end‐detection methods
Improvements in end‐detection methods include:
• immunoassays; ELISA, latex agglutination;
• ATP bioluminescence;
• gene probes linked to PCR.
6.4.1 ELISA and antibody‐based detection systems
ELISAs are widely used in food microbiology. ELISA is most commonly performed using
mono‐ and polyclonal antibody‐coated microtitre trays to capture the target antigen (Figure 6.5;
Plate 9). The captured antigen is then detected using a second antibody (usually monoclonal
for specificity) that is conjugated to an enzyme. The addition of the enzyme substrate enables
the presence of the target antigen to be visualised. ELISA methods offer considerable specificity
and can be automated.
Tray coated with monoclonal antibodies
specific against target organism
Add sample
Target organism binds to antibodies
Washing procedure to remove nontarget
organisms
Secondary antibody labelled with horse
radish peroxidase or alkaline phosphatase
to give colorimetric reaction upon addition
of substrate
Figure 6.5 Enzyme‐linked immunosorbent assay (ELISA).
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A wide range of ELISA methods are commercially available, especially for Campylobacter,
Salmonella serovars and L. monocytogenes. The technique generally requires the target organism to be 106 cfu/ml, although a few tests report a sensitivity limit of 104. Hence the conventional pre‐enrichment and even selective enrichment might be required prior to testing. The
VIDAS system (bioMérieux) has pre‐dispensed disposable reagent strips. The target organism
is captured in a solid phase receptacle coated with primary antibodies and then transferred to
the appropriate reagents (wash solution, conjugate and substrate) automatically. The end‐
detection method is fluorescence, which is measured using an optical scanner. The VIDAS
system can be used to detect most major food poisoning organisms. The bioMérieux VIDAS®
UP E. coli O157 uses bacteriophage‐binding sites for specific capture and detection of the
target organism.
6.4.2 Reversed passive latex agglutination
Reversed passive latex agglutination (RPLA) is used for the detection of microbial toxins such
as the Shiga toxins (from Shigella dysenteriae and enterohaemorrhagic E. coli), E. coli heat‐labile
(LT) and heat‐stable (ST) toxins (Figure 6.6). Latex particles are coated with rabbit antiserum,
Latex particles coated with
V-shaped well microtitre plate well
antibodies against target
antigen (e.g. bacterial toxin).
Absence of antigen
Particles settle to form dense dot
Presence of antigen
Particles remain dispersed in
solution
Appearance viewed from above microtitre plate:
Figure 6.6 The principle of reversed passive latex agglutination (RPLA).
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275
which is reactive towards the target antigen. Therefore, the particles will agglutinate in the
presence of the antigen forming a lattice structure. This settles to the bottom of a V‐bottom
microtitre well and has a diffuse appearance. If no antigen is present then a tight dot will
appear.
6.4.3 ATP bioluminescence techniques and hygiene monitoring
The molecule ATP is found in all living cells (eucaryotic and procaryotic). Therefore, the presence of ATP indicates that living cells are present. The limit of detection is ~1 pg ATP, which is
equivalent to approximately 1000 bacterial cells based on the assumption of 10−15 g ATP per
cell. Since a sample is analysed in seconds–minutes it is considerably faster than conventional
colony counts for the detection of bacteria, yeasts and fungi. Additionally food residues that
act as the loci of microbial growth will also be detected rapidly. Hence ATP bioluminescence is
primarily used as a hygiene monitoring method and not for the detection of bacteria per se. In
fact, in a food factory, there will not necessarily be a correlation between plate counts and ATP
values for identical samples, since the latter will additionally detect food residues (Plate 11).
ATP is detected using the luciferase–luciferin reaction:
ATP luciferin Mg 2
oxyluciferin ADP light 562 nm
The firefly (Photinus pyralis) is the source of the luciferase and the reagents are formulated
such that a constant yellow‐green light (max. 562 nm) is emitted.
ATP bioluminescence measurement requires a series of steps to sample an area (usually
10 cm2). Many instruments currently have the extractants and luciferase–luciferin reagents
encased with the swab in a ‘single‐shot’ device. This saves the preparation of a series of reagents and the associated pipetting errors.
ATP bioluminescence can be used as a means of monitoring the cleaning regime especially
at a Critical Control Point of a HACCP procedure (Section 9.5). See Table 6.4 for a list of examples of ATP bioluminescence applications. There are three food production processes that are
not amenable to ATP bioluminescence. These are milk powder production, flour mixes and
sugar because the cleaning procedures do not remove all food residues.
It has been noted that the luciferase–luciferin reaction can be affected by residues containing sanitisers (free chlorine), detergents, metal ions, acid and alkali pH, strong colours, many
salts and alcohol (Calvert et al. 2000). Hence the commercially available ATP bioluminescence
Table 6.4 Application of ATP bioluminescence
in the food industry.
1 Hygiene monitoring
2 Dairy industry
• Raw milk assessment
• Pasteurised milk, shelf life prediction
• Detection of antibiotics in milk
• Detection of bacterial proteases in milk
3 Assessing microbial load
• Poultry carcasses
• Beef carcasses
• Mince meat
• Fish
• Beer
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kits may contain detergent neutralisers such as lecithin, Tween 80 and cyclodextrin.
Enhancement and inhibition of the luciferase–luciferin reaction can lead to errors of decision
and hence an ATP standard should be used to test the activity of the luciferase. An improvement has been the use of caged ATP as an internal ATP standard, whereby a known quantity
of ATP is released into a solution upon exposing the swab to high intensity blue light (Calvert
et al. 2000).
6.4.4 Protein detection
An alternative to ATP detection for hygiene monitoring is the detection of protein residues.
The method uses the Biuret reaction (Figure 6.7). There are many simple kits available that are
able to detect ~50 μg protein on a work surface within 10 minutes. The surface is sampled
either by swabbing or a dipstick and reagents added. The development of a green colour indicates a clean, hygienic surface, grey is caution and purple is ‘dirty’. The technique is more rapid
than conventional microbiology and less expensive than ATP bioluminescence since no capital
equipment is required. It is however less sensitive than ATP bioluminescence.
6.4.5 Flow cytometry
Flow cytometry is based on light scattering by cells and fluorescent labels that discriminate the
micro‐organisms from background material such as food debris (Figure 6.8). Fluorescence‐
labelled antibodies have been produced for the major food poisoning organisms such as
Salmonella serovars, L. monocytogenes, C. jejuni and Bacillus cereus. The level of detection of
bacteria is limited to approximately 104 cfu/ml due to interference and autofluorescence by
food particles. Fluorescent labels include fluorescein isothiocyanate (FITC), rhodamine isothiocyanate and phycobiliproteins such as phycoerythrin and phycocyanin. These emit light at
530 nm, 615 nm, 590 nm and 630 nm, respectively. Viable counts are obtained using carboxyfluorescein diacetate, which intracellular enzymes will hydrolysis releasing a fluorochrome.
Fluorescent‐labelled nucleic acid probes, designed from 16S rRNA gene sequences, enable a
mixed population to be identified at genus, species or even strain level. However, as the organism might be non‐culturable, it is uncertain whether the organism was viable in the test sample
and this throws into doubt whether its detection is of any significance. The method has been
used for the detection of viruses in seawater (Marie et al. 1999).
6.4.6 Biosensors
Biosensors are analytical devices that integrate biological material for target recognition with
a physicochemical transducer. They are currently the fastest growing pathogen detection technology and have the promise of multiple sample analysis, in real time with high specificity and
Protein chain – N
Protein + Cu2+ + nitrate
N – Protein chain
Cu+
OH–
Protein chain – N
Purple colour
Figure 6.7 The Biuret reaction.
N – Protein chain
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277
Sample
Laser
Fluorescence detector
Deflection plates
+
–
Left collection tube
Right collection tube
Waste
Figure 6.8 Flow cytometry with cell sorting.
sensitivity (Vanegas et al. 2017). The advantages of small‐scale devices are reduced cost per
unit, small sample volume requirement, shorter analysis times and possible multitarget analysis. Currently many biosensor systems use either DNA probes or specific antibodies to give the
high specificity. A greater variety of end‐detection methods are used: optical, electrochemical
and piezoelectric. Optical biosensors are very sensitive and specific, with methods based on
fluorescence and the more recent technology of surface plasmon resonance (SPR) (refractive
index measurement) being developed. Although optical systems may be more sensitive, electrochemical‐based biosensors detecting current or impedance changes may be preferable for
turbid samples. Cell‐based biosensors based on mammalian and higher eucaryotic cells or cell
components for the detection of bacterial pathogens and toxins are emerging (Banerjee and
Bhunia 2009). Mammalian cells generate the initial response, which is converted via an electrochemical or optical system to a detectable signal. Examples include gangliosides to detect E.
coli LT‐II toxin, E‐cadherin for the detection of L. monocytogenes and β1 integrins for Yersinia
enterocolitica. Cell receptors can be the ligands for a number of pathogens and toxins and are
therefore used as the detector.
There is a demand by industry for affordable high‐throughput detection methods (Hyytiä‐
Trees et al. 2007). However, only a few biosensors have been developed for foodborne pathogens
that demonstrate high specificity, quantitative sensitivity and rapid response time in complex
matrices (Valderrama et al. 2016). Few, if any, have been validated by international accreditation
organisations such as AOAC International. Early examples include a conductometric biosensor
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to detect both E. coli O157:H7 and Salmonella serovars, and a disposable immunosensing
amperometric strip for the quantitative detection of E. coli O157:H7 (Muhammad‐Tahir and
Alocilja 2003; Lin et al. 2008).
The most common techniques for the development of handheld quantitative biosensors for
pathogens are SPR, quartz crystal microbalance (QCM), cantilever‐based sensors and electrochemical impedance spectroscopy (EIS). They are comparable in that the target binds to
immobilised antibodies on the sensor surface and this causes a direct measurable signal.
In SPR, when the target molecule binds to the gold sensor surface it causes a change in the
angle of reflected light. A SPR sensor can simultaneously detect E. coli O157:H7, Salmonella
Typhimurium, L. monocytogenes and C. jejuni (Taylor et al. 2006). QCM sensors are composed
of a thin quartz disc with electrodes. The key aspect is that an oscillating electric field is applied
to the disc, which induces an acoustic wave with a specific resonance frequency. Consequently,
by coating the disc with a capture layer (antibodies, nucleic acids, etc.) it will then respond to
the presence of the target by a change in the resonance frequency. These have been developed
for S. Typhimurium, B. cereus and L. monocytogenes. Cantilever‐based sensors using antibodies are also being developed. There are essentially two modes of cantilever. In the static mode,
the cantilever bending of the cantilever on binding the target is measured. Whereas the
dynamic mode is similar to QCM sensors in that resonance frequency changes are monitored
to determine when target molecules bind. There is considerable interest in using cantilevers
for detection of pathogenic micro‐organisms. For example, Campbell and Mutharasan (2007)
detected E. coli O157:H7 at 1 cell/ml without the conventional requirement of cultivation to
increase target cell numbers. Detection times of 10 minutes for 10 E. coli O157:H7 cfu/ml have
been given. It should be noted that these experiment are under ideal laboratory conditions in
the absence of an interfering food matrix.
Antibody microarrays can analyse many samples in parallel for foodborne pathogenic bacteria and biomolecules (Gehring et al. 2008; Karoonuthaisiri et al. 2009). However, with a few
exceptions, most current methods do not have particularly low detection limits and may only
equate to a conventional ELISA method: 105–107 cfu/ml of target organism. Hence, in general
biosensors are not yet comparable with conventional methods for detection limit. One SRP
sensor that has been commercialised is Spreeta™. These small (15 cm × 8 cm) sensors are very
portable due to their low weight (600 g) and power source (9 V battery). They have been used
for Campylobacter, E. coli and L. monocytogenes detection (Nanduri et al. 2007; Wei et al. 2007).
Quantum dots are semiconductor nanomaterials, and therefore only nanometres in size.
Specific antibodies can be conjugated to them to detect specific bacteria. Quantum dots characteristically have high fluorescence efficiency and sensitivity along with wide and continuous
absorption spectra and narrow emission spectra. Highly fluorescent quantum dots (i.e. CdSe/
ZnS) have been used for the simultaneous detection of E. coli O157:H7 and S. Typhimurium.
This is achievable as the two organisms have different emission wavelengths but the same
excitation wavelength. They have also been used for the detection of mycotoxins. Such devices
can be incorporated into a rapid lateral flow device and have a potential application in smart
food packaging indicating the presence of specific microbial pathogens and toxins.
6.4.7 Impedance (Conductance) microbiology
Impedance microbiology is also known as conductance microbiology: impedance is the reciprocal of conductance and capacitance. It can rapidly detect the growth of micro‐organisms by
two different methods (Silley and Forsythe 1996; Plate 10).
1 Directly due to the production of charged end‐products.
2 Indirectly from carbon dioxide liberation.
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In the direct method, the production of ionic end‐products (organic acids and ammonium
ions) in the growth medium causes changes in the conductivity of the medium. These changes
are measured at regular intervals (usually every 6 minutes) and the time taken for the impedance value to change is referred to as the ‘time to detection’. The greater the number of organisms, the shorter the detection time. Hence a calibration curve is constructed and then the
equipment can automatically determine the number of organisms in a sample.
The indirect technique is a more versatile method in which a potassium hydroxide bridge
(solidified in agar) is formed across the electrodes. The test sample is separated from the potassium hydroxide bridge by a headspace. During microbial growth carbon dioxide accumulates
in the headspace and subsequently dissolves in the potassium hydroxide. The resultant potassium carbonate is less conductive and it is this decrease in conductance that is monitored. The
indirect technique is applicable to a wide range of organisms including Staphylococcus aureus,
L. monocytogenes, Enterococcus faecalis, Bacillus subtilis, E. coli, Pseudomonas aeruginosa,
Aeromonas hydrophila and Salmonella serovars. Standard selective media or even an agar slant
can be used for fungal cultures.
The time taken for a conductance change to be detectable (‘time to detection’) is dependent
upon the inoculum size. Essentially the equipment has algorithms that determine when the rate
of conductance change is greater than the preset threshold. Initially the reference calibration
curve is constructed using known numbers of the target organism. The microbial load of subsequent samples will be automatically determined. The limit of detection is a single viable cell since,
by definition, the viable cell will multiply and eventually cause a detectable conductance change.
Microbes frequently colonise an inert surface by forming a biofilm; for more detail see
Section 8.5. Biofilms can be 10‐ to 100‐fold more resistant to disinfectants than suspended cultures and therefore the efficacy of disinfectants for their removal is very important. Impedance
microbiology can be used to monitor microbial colonisation and efficacy of biocides.
6.5 DNA‐based molecular typing and proteomic methods
Typing micro‐organisms is an important tool in outbreak investigations and surveillance both
at national and international levels. At any given time there may be several strains of a foodborne pathogen, plus non‐pathogenic variants circulating. Therefore, typing methods must
have high discriminatory power in order to distinguish between related and unrelated isolates.
Please note the term ‘related’ here is used in the context of relevance, and not in the phylogenetic context. A standardised method should be used that enables results to be comparable
between national and international laboratories. Therefore, it can be used for international
surveillance purposes. Until recently, determining the relatedness between bacteria relied on
phenotyping and chemotyping methods. However, these are limited to well‐studied organisms, and growth conditions etc. must be carefully standardised to ensure reproducible and
reliable results. Despite serotyping and phage typing being well‐recognised methods for
Salmonella and E. coli, they have not been developed for many other organisms. Instead DNA‐
based methods of genotyping are more appropriate, being applicable across the microbial
world. The major advantages of genotyping are:
1 DNA can be extracted from all organisms, including those that cannot be cultivated.
2 It is not dependent upon growth conditions.
3 Closely related strains can be distinguished.
4 Identical methods can be applied to different bacterial species.
5 DNA profiles can be digitised, and easily distributed.
6 DNA profiles can be used for comparative analysis.
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The molecular typing techniques can be designed to target different areas of the genome.
However, the stability of the target areas must be considered in case there is too much variability
for typing purposes. The most common genotyping methods include:
• pulsed‐field gel electrophoresis (PFGE);
• DNA probe‐based hybridisations such as ribotyping;
• PCR‐based methods, such as random‐amplified polymorphic DNA (RAPD);
• sequence‐based methods, including multi‐locus sequence typing (MLST) and multiple‐
locus variable number tandem repeat analysis (MLVA).
6.5.1 Polymerase chain reaction (PCR)
PCR and qPCR (real‐time, quantitative PCR) offer the obvious advantages of a quick turnaround time to obtain a result, as well as high sensitivity and specificity of detection. However,
there are some disadvantages that also need to be considered. These include the purchase and
maintenance of specialised, expensive equipment; the need for trained personnel along with
the use of extensive DNA clean‐up chemistries before addition to the PCR/qPCR reaction; and
the need to avoid cross‐contamination. There is also still the need to pre‐incubate the samples
as the target organism may be below the limit of detection (~100 cells) threshold. This will also
reduce the issue of the inability of PCR to distinguish between live and dead cells, which is why
it is not directly applied to the food.
DNA probes for selected target organisms are commonly used in the food industry. However,
the presence of a pathogen’s DNA in the food does not demonstrate the presence of a viable
organism that is capable of multiplying to an infectious level. The PCR amplifies DNA to levels
that can be detected (Figure 6.9). Specificity is obtained by the design of appropriate DNA probes
to flanking regions unique to the target organism. The PCR technique uses a heat‐stable DNA
polymerase, Taq or Pfu, in a repetitive cycle of heating and cooling to amplify the target DNA.
The procedure is essentially:
1 The sample is mixed with the PCR buffer, Taq or Pfu polymerase, deoxyribonucleoside
triphosphates and two primer DNA sequences (~20–30 nucleotides long).
2 The reaction mixture is heated to 94°C for 5 minutes to separate the double‐stranded target
DNA.
3 The mixture is cooled to approximately 55°C for 30 seconds. During this time the primers
anneal to the complementary sequence on the target DNA.
4 The reaction temperature is raised to 72°C for 2 minutes and the DNA polymerase extends
the primers, using the complementary strand as a template.
5 The double‐stranded DNA is separated by reheating to 94°C.
6 The replicated target sites act as new templates for the next cycle of DNA copying.
7 The cycle of heating and cooling is repeated 30–40 times. The PCR will have amplified the
target DNA to a theoretical maximum of 109 copies, though usually the true amount is less
due to enzyme denaturation. The amount of amplified DNA is approximately 100 μg.
8 The DNA is stained with ethidium bromide or preferably for safety SYBR® Safe (In Vitrogen™)
and visualised by agarose gel electrophoresis with UV transillumination at 312 nm.Negative
control samples omitting DNA must be used in order to check for contamination of the PCR
reaction by extraneous DNA.
PCR is not usually directly performed on food samples for several reasons:
• The technique would not distinguish between viable and non‐viable cells in the sample.
• The reaction is inhibited by some food components.
• The target cell number may be too low for detection.
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PCR cycle
281
Copies of
target gene
Target gene
0
1
5ʹ
3ʹ
3ʹ
5ʹ
DNA polymerase
Two primer
sequences
Heat 94°C, strand separation
Primer extension, 72°C
1
2
+
Heat 94°C, strand separation
Primer extension, 72°C
2
4
3
8
4
16
5
32
Repeat cycle of heating and primer extension
for ca. 20 cycles
Results in ca. 106 copies of the gene
Figure 6.9 The polymerase chain reaction (PCR).
Therefore, a major limitation of PCR is its inability to differentiate the DNA from dead and
viable cells, hence the time‐consuming step of (pre‐)enrichment is used to recover viable organisms from food samples. One means of overcoming this limitation is using ethidium monoazide
and propidium monoazide (PMA) to pretreat samples before DNA extraction to intercalate the
DNA of dead cells in food samples, and then proceed with regular DNA preparation and qPCR.
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By combining PMA treatment with qPCR (PMA‐qPCR), it is possible to directly detect viable
cells of various bacterial pathogens in food samples. The basis of the method is that EMA and
PMA dyes can only enter bacterial cells with damaged cell membranes. The internalised dyes
will intercalate with nucleic acids, and also cross‐link to DNA after exposure to strong visible
light. This intercalation to the DNA of dead bacterial cells will prevent subsequent DNA amplification by PCR, hence obtaining a positive PCR result can be interpreted as indicating the
presence of viable target organisms.
Apart from the principal method of amplifying a single target site, there are three other
main PCR methods. In multiplex PCR different primers are used to amplify different DNA
regions simultaneously. Whereas the previous methods give presence/absence for the target
cell in a sample, real‐time PCR is quantitative. It uses a fluorescent tag on the amplicon.
Consequently the increase in fluorescence is proportional to the number of target organisms
in the sample; various methods have been developed including the molecular beacon and
TaqMan™. Reverse transcriptase PCR (RT‐PCR) can be used to ensure only viable cells are
detected. Certain genes are specifically expressed in the growth phases and these are the targets for the reverse transcriptase enzyme, which transcribes the mRNA to single‐stranded
DNA, which can be amplified by PCR and subsequently detected.
In common with other detection methods, results based on PCR techniques may not be
comparable with results from other laboratories due to different protocols. Therefore, inter‐
laboratory proficiency tests, collaborative trials and standardised protocols are needed.
6.5.2 Microarrays
Microarrays were originally used to simultaneously measure multiple gene expression.
However, oligonucleotide DNA microarrays can be used to detect foodborne pathogens.
Microarrays consist of hundreds to thousands of specific oligonucleotides on a solid support.
The oligonucleotides are short DNA sequences (25–80 bp) that have been generated by the
PCR amplification of specific parts of genes within the selected genome (Plate 12; Schena et al.
1998; Graves 1999). In general, they are prepared by one of two methods:
1 Growing oligonucleotides on the surface, base by base. This is called a Genechip™.
2 Linking presynthesised oligonucleotides or PCR products to a surface.
The DNA sequences are “spotted” onto the chips by a robot and act as the reference for comparison. The spots are positioned in a grid pattern, where each spot contains many identical
copies of an individual gene. The positions of the DNA sequence are recorded by spot location,
so that the appropriate gene sequence can be identified any time a probe hybridises with, or
binds to, its complementary DNA strand on the chip.
DNA array technology can also simultaneously detect different sequences in mixed DNA
samples. Consequently, it is possible to detect and genotype different bacterial species in a
single food sample. Multipathogen microarrays have been reported for food and biodefence
analysis. The FDA‐1 microarray was designed for the simultaneous detection of (i) four
Campylobacter species (C. jejuni, C. coli, C. lari and C. upsaliensis) using glyA and fur genes; (ii)
six Listeria species were distinguishable by using the iap gene; (iii) 16 different St. aureus set
genes encoding SEA‐SEE and SEG‐SEQ; and (iv) six Clostridium perfringens toxin genes (cpb1,
cpb2, etxD, cpe, cpa, Iota). The reported sensitivity was 30–200 colony‐forming units.
However since whole‐genome sequencing continues to become more affordable and accessible, the use of microarrays for bacterial detection and typing will diminish (Section 2.9).
Nevertheless, having the whole genome sequence does not always inform the user regarding
the conditions affecting the expression of key genes such as those involved in pathogenicity.
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Genomic DNA
283
Genes amplified on 96-well microtitre plate
DNA sequences transferred to slide
Hybridisation
Comparison of gene
expression or presence
Intrinsic effects (gene mutations)
Bacterial cDNA
Extrinsic effects (different growth conditions)
Figure 6.10 Applications of bacterial microarrays.
Therefore, there is still a continuing application for microarrays in transcriptomics in which
the mRNA expression is measured under the given conditions (Figure 6.10). Cells are grown
under two different conditions: the experimental condition and the reference (control) condition. The mRNA from the bacteria grown under the two conditions are extracted (separately),
and the enzyme reverse transcriptase is used to convert the mRNA into complementary DNA
(cDNA). One set of cDNA will be labelled with a green fluorescent dye (Cy3) and the other a
red fluorescent dye (Cy5). Therefore, cDNA from the two growth conditions can be distinguished by fluorescence. The two sets of cDNA are then incubated with the DNA array, during
which time complementary regions with the array will bind together. The array is then scanned
twice. Once to detect the spots containing cDNAs labelled with green dye, and then to detect
the spots contain red‐labelled cDNAs. By merging the scan images, yellow spots correspond
with DNA regions that bound both the red‐ and green‐labelled cDNAs. Therefore, genes
(transcripts) that are expressed under both sets of growth conditions are identified. Similarly,
based on the merged spot colours, genes which are up‐ or down‐regulated are also identified.
6.5.3 Loop‐mediated isothermal amplification (LAMP) technique
An alternative to PCR is the LAMP technique, which was invented in Japan in 2000. Being
isothermal, the reactions are at one fixed temperature, which simplifies instrumentation. The
key step is the production of stem‐loop DNA structures during initiation steps, which can then
serve as the starting material for second‐stage LAMP cycling. LAMP uses a strand‐displacing
Bst DNA polymerase large fragment, which allows autocycling amplification under a constant
temperature (60–65°C). This means that thermal cycling, as used in PCR, is not necessary to
denature DNA double strains in order to generate new initiation sites.
LAMP uses four to six specially designed LAMP primers that target several (six to eight)
regions of the template DNA. Amplification can generate 109 copies within an hour. The reaction
appears to be less susceptible to interference from compounds in food that would normally
inhibit the PCR reaction. The end‐product can be detected by various methods including colorimetry, fluorescence and bioluminescence. LAMP methods have been successfully used to detect
a number of foodborne bacterial pathogens including Salmonella serovars (Yang et al. 2018).
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6.5.4 Pulsed‐field gel electrophoresis (PFGE)
PFGE has been applied to a number of bacteria species, and has been one of the most widely
used methods for microbial source tracking in epidemiology. It used to be the genotyping
method of choice, or the ‘gold standard’ by which other genotyping methods were compared.
However the method is dated, has many limitations and is being superseded. The CDC, like
other health authorities, used standardised PFGE methods for specific pathogens. It was the
key method used for establishing PulseNet for the active surveillance of foodborne infections
due to Salmonella, E. coli O157, Shigella species, L. monocytogenes, C. jejuni and norovirus (see
Section 1.12.3; Graves and Swaminathan 2001; Ribot et al. 2001). However, it should be noted
that the PFGE network PulseNet is changing to using whole‐genome sequencing in place of
PFGE due to its limitations and improvements in DNA sequencing techniques (Section 13.1.3).
Genomic DNA is digested with a rare cutting restriction enzyme, such as XbaI for
Enterobacteriaceae. The resulting DNA fragments will be too big to be separated by conventional gel electrophoresis. Instead the polarity of the electric field is briefly reversed periodically throughout the run. The field reversal causes the DNA molecules to be re‐orientated in
order to move through the pores of the gel in the opposite direction. The longer the molecule
is, the slower this process will be. Consequently, the net migration of the DNA fragments will
be size‐dependent. It is important that the starting DNA is intact or at least very large fragments. To achieve this the bacterial cells are embedded in agarose before lysis and restriction
digestion. Then the agarose plug is inserted into the gel for electrophoresis. The resultant
banding patterns can be digitised and compared using appropriate cluster analysis software.
Genomic variation occurs even between related bacterial strains resulting in changes in the
length of DNA fragments between restriction enzyme digestion sites. Therefore there will be
differences in the banding pattern of related strains. However there is no definitive threshold
of difference between ‘indistinguishable’ and ‘unrelated’. A common guidance has been to initially assume the strains are indistinguishable if less than three bands different (Tenover et al.
1995). In practice the user will come to their own conclusion based on experience.
Although PFGE has been of considerable value in outbreak investigate and control, it has a
number of limitations (www.cdc.gov/pulsenet/whatis.htm#limitations). These include:
• Time‐consuming procedure, requiring a high level of skill and is prone to operator variation.
• Cannot optimise separation in every part of the gel at the same time.
• More than one section of DNA could give the same band size, i.e. a band may be the result
of two or more separate pieces of DNA.
• Do not really know if bands of same size are the same regions of DNA.
• Bands are not independent as the change in one restriction site can mean more than one
band change.
• ‘Relatedness’ of strains is not a true phylogenetic measure. Also, the word ‘related’ is ambiguous and can be misleading as it can refer to ‘relevant’ strains in the epidemiological investigation, or in the phylogenetic context of relatedness.
• Frequently strains are untypable by PFGE due to the intrinsic presence of DNases and therefore no banding pattern is obtained. These can then be overlooked and not included in
subsequent analysis using other methods.
PFGE has limited usefulness with clonal organisms as by definition they are genetically homogeneous with little sequence variation. Examples are Salmonella Enteritidis, which has only
five PFGE patterns, one of which (XbaI restriction pattern JEGX01.0004) is given by ~45% of
all clinical isolates in the CDC database, and Cronobacter species (Allard et al. 2013; den
Bakker et al. 2014; Ogrodzki and Forsythe 2016).
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6.5.5 Restriction fragment length polymorphism (RFLP)
The basis of the RFLP method is that if a DNA probe is added to a restricted genomic DNA
preparation and it hybridises to a DNA sequence that is present only as a single copy in the
genome, then only a single band will be detected. The size of the fragment will depend on the
position of the restriction sites flanking the detected sequence. The band will be the same size
between two strains if the structure and location of that gene is the same; whereas, if there is
variation in the distance between the restriction sites, then there will be a difference in the size
of the detected band. The variation can be caused by loss of a restriction site due to a point
mutation (less frequent), and the insertion or deletion of a DNA region. This is called restriction fragment length polymorphism or RFLP. The most useful polymorphisms are due to
duplication or transposition of repetitive sequences. These are short sequences that occur twice
or more in succession in the genome. The technique is applicable to both bacteria and eucaryotes: Campylobacter (Messens et al. 2009) and Toxoplasma gondii (Velmurugan et al. 2009).
6.5.6 Amplified fragment length polymorphism (AFLP)
In the AFLP method, genomic DNA is cut with two restriction enzymes, and double‐stranded
adaptors are specifically ligated to one of the sticky ends of the restriction fragments. The subsequent PCR step using primers complementary to the adaptor sequence will amplify the
restriction fragments ending with the adaptor, the restriction site sequence and a number of
additional nucleotides (usually one to three nucleotides) from the end of the unknown DNA
template. At the start of the amplification, highly stringent conditions are used to ensure efficient binding of primers to fully complementary nucleotide sequences of the template. AFLP
allows the specific co‐amplification of high numbers (typically between 50 and 100) of restriction fragments and is often carried out with fluorescent dye‐labelled PCR primers. The PCR
amplicons can then be detected, after size separation, on an automated DNA sequencer. The
genetic relatedness of bacterial isolates can then be determined by comparison of the banding
patterns. AFLP can be as discriminatory as PFGE.
6.5.7 Random amplification of polymorphic DNA (RAPD)
Unlike the previous methods that used targeted DNA probes/primers, RAPD is based on the
parallel amplification of a set of fragments by using short arbitrary sequences as primers (usually 10 bases) that target several unspecified genomic sequences. Subsequently, the PCR amplification step uses a low, non‐stringent annealing temperature, which allows the hybridisation
of multiple mismatched sequences. When the distance between two arbitrary primer binding
sites on both DNA strands is within the range of 0.1–3 kb, a PCR amplicon will be generated
for the length between the two binding sites. RAPD amplicons can be analysed by agarose gel
electrophoresis or DNA sequencing depending on the labelling of primers. The number and
length of PCR amplicons will be unique to a particular bacterial strain and therefore can discriminate between non‐related, non‐clonal strains. The advantage of the technique is that it is
simple and relatively inexpensive to perform for microbial source tracking. However, it may
not be as discriminatory as PFGE and is not as reproducible.
6.5.8 Repetitive‐element polymerase chain reaction (Rep‐PCR)
Rep‐PCR uses primers that hybridise to non‐coding intergenic repetitive sequences that occur
in bacterial genomes. PCR is then used to amplify the DNA sequence between adjacent repetitive elements. As this occurs across multiple sites so multiple amplicons will be produced according to the distribution of the repeat elements across the genome and they will differ between
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unrelated, non‐clonal strains. The PCR amplicons can be separated according to size and the
subsequent banding patterns used to assess the relatedness amongst the multiple isolates.
Different groupings of repeat sequences have been used in the variants of rep‐PCR, such as
ERIC‐PCR using enterobacterial repetitive intergenic consensus and BOX‐PCR sequences.
Since rep‐PCR uses conventional PCR and gel electrophoresis results can be obtained relatively quickly with low cost and expertise.
6.5.9 Nucleic acid sequence‐based amplification (NASBA)
NASBA is a versatile technique that amplifies nucleic acids under isothermal conditions,
unlike PCR, which is based on thermocycling. Essentially NASBA is used to amplify RNA to
generate a single‐stranded RNA template. This can then be converted into cDNA using reverse
transcriptase. The sequence of reactions is carried out at ~41°C, and requires two specific
primers and three enzymes: avian myeloblastosis virus (AMV) reverse transcriptase, T7 RNA
polymerase and RNaseH. The NASBA amplicons can be detected by conventional agarose gel
electrophoresis, or in real time by using fluorescently labelled probes to detect the single‐
stranded RNA amplicons.
Real‐time NASBA has been used for the detection of Salmonella serovars, V. cholerae, St.
aureus and Campylobacter species. In addition, real‐time NASBA is able to directly detect
viable target organisms in food samples (i.e. without a time‐consuming cultivation step)
through mRNA amplification. The positive detection of RNA targets would indicate the presence of viable target organisms. NASBA offers high‐throughput analysis and it has been commercialised as kits.
6.5.10 Multiple‐locus variable number tandem (VNTR) repeat analysis
The MLVA method is based on the amplification of variable number of tandem repeat (VNTR)
areas. In MLVA, primers are used to hybridise either side of the tandem repeat. Each strain can
be given a number corresponding to the number of tandem repeats. The number of copies of
each VNTR generates a profile that is then used for genotyping. MLVA schemes have been
developed for Enterobacteriaceae: E. coli O157, S. Typhi and S. Typhimurium. It has been
reported to be better than PFGE for both surveillance and outbreak investigations of the latter,
probably as it is able to discriminate within clonal groups (Torpdahl et al. 2007).
A limitation of MLVA is that the banding patterns generated by low‐resolution gel electrophoresis data cannot be compared directly between different laboratories. Subsequently the
exact numbers of repeats cannot be determined and neither can the target site be identified.
However, for a centralised typing system, akin to PulseNet, the exact number of repeat units in
each MLVA locus must be determined. A better separation of the amplified DNA fragments by
size is achievable using capillary electrophoresis. By labelling the primers with different fluorescently coloured dyes and combining capillary electrophoresis with DNA sequencing the
mixture of MLVA amplicons can be analysed in one run and the strain described according to
the number of repeat units at each MLVA locus. This allelic profile (e.g. 2‐9‐7‐3‐2) can be
stored in a centralised reference database. Since specific primers have to be designed and tested
for each target organism, this means that MLVA is not generally suitable to replace PFGE for
epidemiological investigations in general. However, PFGE has limited application for highly
clonal organisms such as S. Enteritidis (which only has approximately five PFGE profiles) as it
cannot discriminate between unrelated strains. Similarly (in Belgium) one single MLVA profile of S. Enteritidis represented more than a quarter of 1498 S. Enteritidis strains isolated during 2007–2012. Nevertheless, the most common MLVA types can be further divided into
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subgroups using phage typing and PFGE. Consequently, MLVA cannot be relied upon as a
single typing method but can be used with parallel methods for prevalent MLVA types. In the
EU and US the method has been standardised for S. Typhimurium, but is still regarded as
problematic for S. Enteritidis due to its high level of clonality (Allard et al. 2013; CDC 2013;
den Bakker et al. 2014; ECDC 2016; Peters et al. 2017).
6.5.11 PCR‐probe based serotyping
The O antigen, also known as lipopolysaccharide (LPS), is anchored in the outer membrane of
Gram‐negative bacteria. Unlike the K antigen it elicits an immunological response.
Consequently, LPS has been used for a typing scheme referred to as O‐serotyping – the
Kauffmann–White Salmonella and E. coli serotyping schemes being well‐known examples
(Section 4.3.2). Originally, bacterial extracts would have been injected into laboratory animals
(rabbits or mice) and corresponding antigens produced for use in serotyping assays. The
advent of molecular methods and a reduction in the use of animals have largely replaced this
now historic approach. Alternative laboratory‐based serotyping approaches have used PCR
probes designed for the galF and gnd genes as these flank the O antigen region, also known as
the rfb locus. The method may use long‐range PCR to generate a large single PCR amplicon
(size range 9.8–14.8 kb). This is then restricted using the restriction enzyme MboII, and the
DNA fragments separated by standard gel electrophoresis. The RFLP banding patterns can
then be further analysed. However, it is commonly overlooked that standard gel electrophoresis does not distinguish DNA fragments that are ±10% in size. Therefore, a single band may be
composed of multiple bands (with differing DNA sequences) that happen to be similar in size.
Also the O antigen does not necessarily follow phylogeny, resulting in the same antigen occurring in different species, even different genera; E. coli O29 and E. coli O103 and Cronobacter.
There are also open access automated serotype prediction pipelines that can predict the
serotype within minutes from the whole genome sequences (i.e. Center for Genomics
Epidemiology; Section 14.3.4).
6.5.12 Ribotyping
Ribotyping is a molecular technique for bacterial identification and characterisation that is
based on the DNA sequence encoding for the ribosomal rRNA (rDNA genes). Extracted
DNA is cut with specific restriction enzymes, and the resulting fragments are separated by gel
electrophoresis. These are then probed with labelled 16S or 23S rRNA sequences. The resulting hybridisation pattern can be digitised and compared with reference organisms in a database. The technique was popularised in the 1990s but is now largely redundant due to more
discriminatory and cheaper genome sequence‐based methods.
6.5.13 Matrix‐associated laser desorption ionisation – time
of flight (MALDI‐TOF)
Identification of bacteria by mass spectrometry (MS) has been an active research area for decades. Most MS‐based bacterial identification methods rely on the reproducible patterns generated from the measurement of masses of proteins and/or lipids from intact bacterial cells or cell
extracts. Consequently, MS‐based methods can directly detect expressed bacterial proteins.
Tens to hundreds of proteins are measured in a single experiment. The result is a reproducible
mass fingerprint that will be unique to a given genus or species. The significant advantage of MS
methods over phenotypic and molecular methods for bacterial identification is that no advanced
knowledge of the microorganism is necessary in order to choose the method of analysis.
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MALDI‐TOF MS is the most common technique used for bacterial analysis by MS. The
method has been refined over the years such that it is easy to operate, the cost per sample of
analysis is low and analysis is as fast as 10 minutes from colony selection to identification.
As multiple laboratories began developing libraries of reference spectra representing species
of interest, it became clear that lab‐to‐lab reproducibility was going to require standardisation
of spectral libraries. Subsequently, in 2008, multiple commercial MALDI‐TOF MS instruments were released that included reference spectra libraries. The research use versions of
these systems also include methods for creating user libraries. A thorough review of bacterial
identification by MALDI‐TOF MS for clinical use can be found in Clark et al. (2013).
Most commercially available MALDI‐TOF MS bacterial identification instruments contain
reference databases that are primarily based on clinically relevant isolates. Consequently,
MALDI‐TOF MS is an effective and rapid tool for genus‐ and some species‐level identifications. However, it is not able to identify bacteria directly within food samples, and cannot differentiate strains within mixed cultures. Therefore, a single colony or pure culture is generally
required. However, the speed at which even a genus‐level identification can be made makes
MALDI‐TOF MS a potentially important screening tool.
6.6 Identification and typing methods based on high‐throughput
DNA sequencing
The epidemiological investigation of a foodborne outbreak and microbial sourcing such as in
the food processing environment in order to curtail further infections depend on typing methods to differentiate relevant strains from non‐relevant ones. Historically methods such as serotyping and PFGE have been used. However, techniques based on high‐throughput sequencing
of genomes offer greater resolution and discrimination than previously achievable. The microbial genomes will contain sequence variation between strains due to mutations and recombination events.
DNA sequence‐based methods are more repeatable and reproducible than DNA gel electrophoresis‐based methods. There are a very large number of typing methods, such as core‐
genome MLST, single nucleotide polymorphism (SNP) and CRISPR‐cas array profiling, which
are based on high‐throughput sequencing of whole genomes. These offer considerably better
discrimination than methods based on PCR and PFGE (Carriço et al. 2013; Ronholm et al.
2016; Sekse et al. 2017). Additionally, high‐throughput sequencing enables the analysis of specific target sites, such as CRISPR‐cas array profiling, which is not easily achievable using conventional methods. Where large‐scale genome sequencing is not available due to limited
equipment and expertise, the whole‐genome sequencing of a few representative strains can
enable the design of primers etc. for a larger diversity analysis of laboratory strain collections
using conventional methods.
6.6.1 Conventional seven‐loci MLST
MLST of bacteria is usually based on DNA sequence variation within alleles (short regions
within a gene, also known as loci). Conventional, laboratory‐based MLST is based on the analysis of seven housekeeping genes, though sometimes this can be as low as five. The maximum
length of the allele is usually between 450 and 500 bp, due to the original limitation of DNA
sequencers. This limitation is no longer necessary as the allele sequences can be predicted in
silico from whole genome sequences and includes ribosomal MLST (rMLST, 53 loci)
(Figure 4.13), and core‐genome MLST (cg‐MLST, >1000 loci) (Section 6.6.2). Although overall
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more expensive and limiting, due to accessibility and expertise, the laboratory‐based seven‐loci
MLST continues in use.
For each housekeeping gene analysed, each sequence variation is assigned a distinct allele
number. If using conventional seven‐loci MLST, then the seven alleles will generate a seven‐
digit number. In turn, each unique seven‐digit number is assigned a number known as the
sequence type (ST). For example, Cronobacter sakazakii allele profile atpD5, fusA1, glnS3, gltB3,
gyrB5, infB5 and ppsA4 is simplified to ST 4 as it was the fourth seven‐digit profile in the database (Forsythe 2018a, b). Since by definition a single nucleotide difference generates a different
allele number, this means two strains with one nucleotide difference would have different STs
and not be easily recognised as related. Therefore, by convention STs that have five or more loci
in common are referred to as a clonal complex, and are numbered after the central ST.
A considerable advantage of MLST is that the sequence data are unambiguous and the allelic
profiles can be compared with those in large online central databases that are curated and that
have the standardised protocols. There are three such international open access MLST databases supporting an increasing range of organisms: http://pubMLST.org, http://bigsdb.pasteur.
fr and www.mlst.net. For example, the Pasteur Institute E. coli MLST protocol uses PCR primers to specifically amplify seven genes: dinB (DNA polymerase), cdA (isocitrate dehydrogenase), pabB (p‐aminobenzoate synthase), polB (polymerase PolII), putP (proline permease),
trpA (tryptophan synthase subunit A), trpB (tryptophan synthase subunit B) and uidA
(β‐glucuronidase). Sequence data for each allele generate a seven‐digit profile that is designated a ST, and can be compared with other E. coli strains in the database (the URL is given in
the ‘Food Safety Resources’ section).
The MLST databases are curated, open access, public domain sites to which any laboratory
can submit sequence data (alleleic or whole genome). In contrast, PulseNet is only accessible
by member laboratories for reasons of privacy and confidentiality.
MLST has been highly informative in the diversity of bacterial species and genera, and in
identifying particular pathovars. Sopwith et al. (2006) used MLST for the first continuous
population‐based survey of campylobacteriosis. They demonstrated that MLST could identify
variations in the epidemiology of campylobacteriosis between distinct populations over a 3‐
year period and described the distribution of major subtypes of interest. It was based on 493
cases, from which 93 distinct MLST STs of C. jejuni were obtained. The most common type
was ST‐21 (102 cases), which was isolated three times more frequently than the next complex,
ST‐45. The clonal complex ST‐21 has previously been reported from humans, cattle, chicken,
milk, sand and water. Hence ST‐21 is associated with environmental and foodborne transmission of C. jejuni, whereas ST‐45 is principally from humans and chickens. Cronobacter sakazakii ST4 and ST12 are strongly associated with neonatal meningitis and necrotising
enterocolitis, respectively (Forsythe 2018a, b; Joseph and Forsythe 2011)
6.6.2 Genome sequence‐based MLST
Whole‐genome sequencing of target organisms enables the further expansion of DNA
sequence‐based typing methods, by substantially increasing the number of loci examined
simultaneously. By combining MLST with whole‐genome sequencing the number of loci profiled can be considerably increased from the traditional seven. cg‐MLST schemes typically use
a comprehensive set of loci (>1000) that are present in most members of the target bacterial
group and therefore offer higher resolution than the conventional seven loci. For example,
cg‐MLST for L. monocytogenes uses ~1700 loci, and that for Cronobacter species uses 1865
(Forsythe et al. 2014; Ruppitsch et al. 2015).
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Genomic methods such as rMLST (Figure 4.13) and cg‐MLST are expansive methods and
can be directly compared with the previous laboratory‐derived seven‐loci typing schemes.
Given that rMLST and cg‐MLST use 53 and >1000 loci, respectively, it is self‐evident that these
newer genomic methods provide considerable greater discrimination between strains.
Similar to generating a genotype from a whole genome sequence as described above for
rMLST, it is also possible to generate a genotype profile using a core‐genome approach.
Forsythe et al. (2014) demonstrated its application across the Cronobacter genus for 1865
loci to profile all Cronobacter genomes in the database, and also generate a phylogenetic
analysis across the genome. Additionally, as an example for studying the organism’s biology,
they expanded on the cell wall division genes. This was achieved using the comparative
genomics analysis facility within the Cronobacter PubMLST database. The cg‐MLST analysis
used C. sakazakii ES15 as the reference genome since it is well annotated, but the user can
choose their own genome for comparative analysis if they wish. The user can either profile
all annotated genes, or choose their own interest area, for example, biochemical pathways,
adhesins and virulence traits. The output is a self‐explanatory Excel spreadsheet, and no
bioinformatic knowledge or specialist software is required; thus the approach is highly
accessible with no usage costs.
Loci that recurrently show variations between same‐patient isolates and epidemiologically
linked isolates are commonly homopolymeric tracts in contingency genes. The cg‐MLST
approach enables the clustering of isolates (which vary in only a few loci) that have been
obtained from cases spread over a large geographical area, despite lacking an apparent epidemiological link between them. Investigators commonly define clusters of genetically indistinguishable isolates based on a five‐single nucleotide variant (SNV) cutoff value for allele
differences, while excluding indels in homopolymeric tracts.
A cg‐MLST scheme of 1748 loci for L. monocytogenes is more discriminatory than PFGE,
and can separate unrelated isolates that share identical PFGE profiles and phylogenetically
closely related isolates with distinct PFGE profiles. This helps to refine epidemiologic investigations by focusing on phylogenetically closely related isolates to improve source identification, and enables the recognition outbreaks at earlier stages.
For C. jejuni and C. coli a set of 1343 loci has been collated as a human campylobacteriosis
cg‐MLST scheme. The 1343 loci are present in ~95% of draft genomes of 2472 representative
UK campylobacteriosis isolates, 89.3% C. jejuni isolates and 10.7% C. coli. In addition to the
rapid high‐resolution analysis of large numbers of Campylobacter isolates, the cg‐MLST
scheme enabled the efficient identification of very closely related isolates from a well‐defined
single‐source campylobacteriosis outbreak (Cody et al. 2017). The scheme, as per other MLST
schemes, is open access via the www.pubmlst.org site.
6.6.3 CRISPR‐cas array typing
Clustered regularly interspaced short palindromic repeats (CRISPRs) are chromosomal loci
that are very useful for high‐resolution genotyping, even with highly clonal organisms. They
were first identified in ~1990 as ambiguous repeats in the genome of E. coli, and are now
known as CRISPR spacer arrays or CRISPR‐cas arrays.
In brief, CRISPR‐cas systems may be composed of up to three sections: (i) a group of
CRISPR‐associated (cas) genes; (ii) an AT‐rich leader sequence upstream of the array; and (iii)
a CRISPR array, composed of short (~24–48‐nucleotide) direct repeat (DR) sequences separated by similarly sized, unique spacers (Plate 18). These spacers are usually derived from
mobile genetic elements such as bacteriophages and plasmids. The CRISPR spacer array is
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constitutively transcribed into a precursor CRISPR RNA that is cleaved by specific Cas proteins and then processed to generate small interfering crRNAs. These then lead to the degradation of invading bacteriophages or plasmids. New spacers are always added to the leader end
of the array. The subject area is too large to consider in detail here, instead the reader should
consult core texts for background information such as Koonin et al. (2017).
Analysing CRISPR‐cas arrays has helped our understanding of bacterial lineages in E. coli,
Yersinia, Salmonella enterica serovars Enteritidis and Heidelberg, as well as Cronobacter.
CRISPR arrays may differ between closely related strains due to their different exposure histories to phages and plasmids, leading to differences in their spacer acquisitions. CRISPR loci
between strains can also differ due to the loss of internal spacers and SNPs. Therefore, the
CRISPR‐cas array loci can be used for molecular subtyping, offering greater discrimination
between strains than MLST and PFGE.
Since CRISPR‐cas arrays reflect the exposure of strains to phages and plasmids there should
be differences between strains despite being related (Ogrodzki and Forsythe 2015; Zeng et al.
2017) (Plate 18). Therefore identifying epidemiologically associated isolates from unrelated
strains which were very difficult to separate if not impossible with previous genotyping methods
such as PFGE.
CRISPR‐cas arrays have been analysed in Salmonella serovars. Salmonella have two CRISPR
loci (CRISPR1 and CRISPR2) that are separated by ~16 kb. These share the same consensus
DR sequence (29 nt), and the spacers are 32 nt in length. Analysis of >1000 Salmonella CRISPRs
has shown that this organism is not rapidly acquiring new spacers. Consequently these two
CRISPR loci appear no longer to be active. Instead CRISPR‐cas array variation is due to the
multiplication and/or loss of internal spacers, as well as SNP variants of spacer or DR loci.
Retrospective analysis of 783 Salmonella strains from 10 outbreaks that belonged to 130 serotypes has shown correlation between CRISPR‐cas arrays with serotyping and MLST.
Furthermore, the spacer variants meant it was possible to discriminate between subtypes
within the prevalent serotypes (Fabre et al. 2012).
6.6.4 Single nucleotide polymorphism (SNP)‐based analysis
SNPs occur in genes, non‐coding regions and mobile elements (i.e. plasmids). SNPs that occur
within a gene are termed synonymous if they do not result in a change in the resultant amino
acid sequence after transcription and translation, or non‐synonymous if there is a change in
the resultant amino acid sequence. This is related to the wobble base and redundancy of
codons. The term ‘diversifying population’ is used if there are more non‐synonymous than
synonymous SNPs in a bacterial population. If the same SNP occurs in two or more isolates
then it is termed ‘parsimonious’.
To detect SNPs, genomes sequences need to be aligned. This can be computationally
demanding, and often a reference genome is used to which the DNA sequencing reads are
mapped. A ‘SNP caller’ program is then used to identify the SNPs that are different between
the genomes. This method is very useful for determining the phylogenetic relationship between
two or more genomes. However, it introduces an issue of reference bias and difficulties in
standardising SNP analysis for outbreak investigations as the choice of reference strain is crucial. SNP analysis in the accessory genes is only possible if those regions have been sequenced
in all genomes, and a plasmid, etc. has not been lost during subculturing. Alternatively SNP
analysis can be achieved using de novo‐assembled genomes by annotating the contigs and then
comparing the open‐reading frames.
Examples of SNP analysis in outbreak investigations are given in Section 14.4.
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6.7 Specific detection procedures and accreditation
Standardised protocols for the isolation of most foodborne pathogens have been defined by
various regulatory and accreditation bodies such as the ISO, and the FDA. The methods also
need to be validated by a national or international body. The AOAC International (Anon.
1999b) and ISO are the most widely accepted; others include UKAS (UK), EMMAS (European),
AFNOR (French), DIN (Germany) and the European MICROVAL. Appropriate control
organisms should always be run to ensure the media is conforming to its specification.
There is however not always a single ideal method for each pathogen and countries may
vary in their preferred technique. Therefore, only an overview of techniques will be given here,
and specific instructions must be obtained from the relevant authoritative source before using
the methods. The procedures for a number of regulatory authorities, such as the FDA and
Health Canada, are available online and are listed in the ‘Food Safety Resources’ section at the
end of the book. A consequence of the variation in methodology is the uncertainty about how
confidently one can compare food poisoning statistics between countries.
Because batches of media can vary in their composition, as a means of monitoring personnel proficiency, good laboratory management requires that standardised positive and negative
control organisms are used to confirm the selectivity of the media. The control organisms
originate from national and international culture collections such as the National Collection of
Type Cultures (NCTC) and American Type Culture Collection (ATCC). This is indicated by
the culture collection index numbering, i.e. St. aureus ATCC® 25923. These are well‐characterised strains available to all quality control laboratories and act as an international standard for
referencing.
6.7.1 Aerobic plate count (APC)
The APC is commonly used to determine the general microbial load of the food and not specific
organisms. It is a complex growth medium containing vitamins and hydrolysed proteins that
enables the growth of non‐fastidious organisms. The agar plates may be inoculated by a variety
of techniques (Miles‐Misra, spread plate, pour plate) that vary in the volume of sample (20 μl to
1 ml) applied. The plates are generally incubated at 30°C for 48 hours before enumerating the
number of colonies. The accuracy of colony numbers is given in Table 6.1. The advantage of
pour plates is that up to 1 ml of sample can be applied giving a lower limit of detection (10 cfu/g)
than spread plate and Miles‐Misra (100 and 500 cfu/g, respectively). However, it is difficult to
remove colonies from within the agar of a pour plate for confirmation of their identity and further characterisation. Consequently, most methods use the spread plate approach (0.1 ml/plate),
which combines a lower detection limit with the generation of well‐separated colonies for further analysis, though requiring large volumes of agar preparation and disposal.
6.7.2 Salmonella serovars
Internationally standardised procedures are necessary for the isolation of Salmonella serovars
from food in order to collate results together for microbial source tracing and epidemiological
analysis. These methods commonly involve a mixture of conventional cultivation procedures
followed by molecular analysis (Table 6.5). Nevertheless, the ISO approved method (ISO
6579‐1:2017) is considered primarily as it is an internationally approved method that accredited laboratories analysing food have to follow.
Typically Salmonella cells are only present at very low levels in food, and are likely to be in
a stressed condition following processing. Therefore, large volumes need to be sampled. Due
to its severity, presence/absence testing is used instead of enumeration. Consequently, the
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Table 6.5 Salmonella detection media.
Differential indicator
Medium
Common
abbreviation
Brilliant green agar
Bismuth sulphite agar
Brilliance™ Salmonella agar
Chromogenic Salmonella Esterase
Desoxycholate citrate lactose agar
Desoxycholate citrate agar
Hektoen enteric agar
Salmonella Shigella agar
Xylose lysine deoxycholate agar
BGA
BS
BSA
CSE
DCLS
DCA
HE
SS
XLD
H2S
positive
Lysine decarboxylase
positive
Lactose
negative
Sucrose
negative
x
x
Xylose
positive
Salicin
negative
β‐glucosidase
negative
Esterase
positive
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
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Pre-enrichment
Test portion, 25 g + buffered peptone water, 225 ml
16–20 hours, 37°C
Selective enrichment
Culture, 0.1 ml +
Culture, 10 ml +
Rappaport (RVS) broth, 10 ml
Selenite cystine broth, 100 ml
18–24 hours, 41–43°C
18–24 hours, 37°C
Selective diagnostic isolation
Plate on xylose lysine deoxycholate agar and any other solid selective medium
24 hours, 35°C or 37°C
(48 hours, if necessary)
Pick five presumptive Salmonella colonies from each agar plate
and inoculate on nutrient agar
18–24 hours, 35°C to 37°C
Biochemical confirmation
4 hours, 37°C
Serological confirmation
Slide agglutinations – O, Vi, H antisera
Figure 6.11 BSI/ISO Salmonella isolation procedure.
microbiological specification for ready‐to‐eat foods is the isolation of one Salmonella cell
from 25 g of food. The isolation protocols have a number of steps to recover Salmonella cells,
which are present in low initial numbers, and start with resuscitation of cells that may have
been injured during processing (see Section 6.3.2 on IMS technique). It is possible to obtain
an estimate of the number of Salmonella cells in the food by using the MPN approach whereby
10‐fold sample volumes are analysed.
The flow chart for ISO 6579‐1:2017 is given in Figure 6.11, and FDA‐BAM in Figure 6.12.
The general isolation procedure is:
1 Pre‐enrichment, to enable injured cells to resuscitate. Normally 25 g of food is homogenised
and added to 225 ml BPW broth and incubated overnight (34–38°C). This step requires a
nutritious non‐selective medium and therefore should result in the resuscitation of all bacteria present. The BPW broth may be modified if large numbers of Gram‐positive bacteria
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Pre-enrichment
Test portion, 25 g + pre-enrichment medium, 225 ml
16–20 hours, 37°C
Selective enrichment
Culture, 1 ml +
Culture, 1 ml + Selenite cystine
Tetrathionate broth, 10 ml
broth, 100 ml or Rappaport (RV) broth, 10 ml
24 h +/– 2h, 35°C
Selective diagnostic isolation
Plate on Bismuth sulphite agar, Xylose lysine desoxycholate agar,
Hektoen enteric agar
24 h +/– 2h, 35°C
(48 h, if necessary)
Pick two or more suspect Salmonella colonies from each agar plate for biochemical tests
Biochemical confirmation
24–48h, 35°C
Serological confirmation
Slide and tube agglutination – O, H antisera
Figure 6.12 FDA‐AOAC BAM Salmonella isolation procedure.
are suspected to be present indicated by the addition of 0.002% brilliant green or 0.01% of
malachite green. Since milk products are already highly nutritious, BPW broth can be distilled water plus 0.002% brilliant green instead. If the food is highly bacteriostatic (in the
case of onion) this can be overcome by the addition of sodium thiosulphate or an increased
dilution factor, for example 25 g in 2.25 l.
2 Selective enrichment, to suppress the growth of non‐Salmonella cells and enable Salmonella
cells to multiply. This is achieved by the addition of inhibitors such as bile, tetrathionate,
sodium biselenite (this compound is very toxic) and either brilliant green or malachite
green dyes. Selectivity is enhanced by incubation at 41–43°C. Two selective broths are used.
These are commonly Rappaport–Vassiliadis (RVS) broth and Mu(e)ller Kauffmann tetrathionate novobiocin (MKTTn) broth. More than one selective broth is used because the broths
have different selectivities towards the 2500+ Salmonella serovars. Ideally this step will
result in a 1000‐fold greater number of Salmonella compared with non‐Salmonella, and
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therefore it will be easier to spot Salmonella colonies on the isolation agar plates used in the
next step.
3 Selective differential isolation, to isolate Salmonella cells on an agar medium enabling single
colonies to be isolated and identified. The media contain selective agents similar to the
selective broths such as bile salts and brilliant green. They also contain substrates to enable
Salmonella colonies to be differentiated from non‐Salmonella. Typically, Salmonella serovars do not ferment lactose, but do produce H2S. It should be noted however that atypical
strains occur and are still virulent (Section 14.4.5). Commonly used selective agars are
xylose lysine desoxycholate (XLD) agar, brilliant green agar (BGA), as well as Rambach™
agar and CHROMagar™ (Plate 13). As for the previous selective enrichment stage, more
than one agar medium is used since the media differ in their selectivities. It should be noted
that ISO approved selective agars are not used for the clinical isolation of Salmonella.
The most commonly approved selective agar for the isolation of Salmonella from food is
XLD. On this agar Salmonella colonies typically appear red with a black centre, or entirely
black. This medium is designed for the isolation and differentiation of Salmonella (and Shigella)
from other Enterobacteriaceae in the enrichment broth from the previous step. Almost all
Enterobacteriaceae ferment xylose, except Shigella. The metabolism of xylose and lysine results
in the pH of the medium becoming alkaline and blackening due to the H2S production. In
contrast, acidification due to lactose and sucrose fermentation prevents non‐Salmonella lysine
metabolising Enterobacteriaceae generating an alkaline pH value, and non‐pathogenic hydrogen sulphide producers do not decarboxylate lysine. The acid level also prevents blackening by
these latter organisms until after the prescribed 18–24‐hour incubation period. XLD also contains sodium desoxycholate as an inhibitor of non‐enteric bacteria.
Since Salmonella is so diverse, a second isolation agar must be used. This is commonly BGA
in order to pick up the H2S‐negative Salmonella. On BGA, Salmonella colonies typically appear
as red to pink‐white colonies surrounded by a red zone in the medium. Note this medium is
not recommended for the isolation of Salmonella Typhi or Shigella species.
According to the ISO 6579‐1:2017 procedure only one suspect colony needs to be confirmed. If negative, four more suspect colonies from different media combinations have to be
tested.
1 Biochemical confirmation, to confirm the identity of presumptive Salmonella colonies.
2 Serological confirmation, to confirm the identity of presumptive Salmonella colonies and to
identify the serotype of the Salmonella isolate, which is useful in epidemiology.
Aside from the international standard ISO and FDA‐BAM methods for Salmonella detection,
more rapid detection procedures have been developed based on molecular biology. These are
based on PCR and real‐time, quantitative PCR (qPCR). One of the most frequently used target
genes is invA.
Genotyping Salmonella isolates is very important for epidemiological investigations. PFGE
has been the common method used for most Salmonella serovars, but is not applicable for the
highly clonal serovars S. Enteritidis and S. Heidelberg (den Bakker et al. 2014; Peters et al.
2017). More discriminatory methods have included genome‐based methods such as MLVA,
SNP and CRISPR‐cas array profiling (Section 6.6). Examples of genotyping methods with S.
Typhimurium and S. Enteritidis in outbreak investigations are given in Section 4.3.7 as well as
in Section 14.4.
As an example of the limitations of PFGE with clonal organisms, an investigation into S.
Heidelberg is discussed. Whole‐genome sequence‐based typing methods were used to differentiate 145 S. Heidelberg strains, which were associated with four distinct outbreaks and sporadic
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cases of salmonellosis in Québec (Canada) between 2007 and 2016. All isolates were indistinguishable by PFGE. The core‐genome SNV, and genome‐based MLST (i.e. cg‐MLST) were
highly discriminatory. These methods separated the outbreak strains into four distinct phylogenetic clusters, which was in agreement with the epidemiological data. However, the CRISPR
typing method was less discriminatory.
6.7.3 Campylobacter species
There are many methods, based on both cultivation and DNA amplification, for Campylobacter
detection. It is likely, however, as is probably true for many other organisms, that no single
method is ideal. Some of the major methods and protocols have been reviewed by Corry et al.
(2002) and are summarised in Table 6.2 and Figure 6.13. Readers should consult the original
articles for precise details.
Campylobacter cells can be stressed during processing and hence a pre‐enrichment stage to
enable injured cells to be resuscitated is commonly used prior to selection for the organism.
Frequently selective agents are added as supplements and lower incubation temperatures are
used. In order to aid the growth of the organism ferrous sulphate, sodium metabisulphite and
sodium pyruvate are added to growth media to quench toxic radicals and increase the organisms’ aerotolerance. The organism is microaerophilic and is unable to grow in normal air levels
of oxygen. The preferred atmosphere is 6% oxygen and 10% carbon dioxide. This is easily
achieved in gas jars by using gas sachets that generate the required gases.
PCR‐based detection methods include the detection of the genus Campylobacter using the
highly conserved 16S rRNA gene sequence as a target for PCR, and the more specific C. jejuni
probe targeting the hippurate gene.
There are a number of typing methods for campylobacters. Traditional typing methods
based on differences of key surface antigens such as LPS and flagella have been applied to
campylobacters, but are problematic as their surface structures are variable even within an
(a)
Pre-enrichment
Dilute sample 1/10 in Bolton broth
Selective enrichment
Incubate in a microaerobic atmosphere at 37°C for 4–6 hours,
followed by 41.5°C for 44 ± 4 hours
Selective diagnostic isolation
Isolate on mCCDA agar and a second medium as preferred
Incubate in a microaerobic atmosphere at 41.5°C for 44 ± 4 hours
Confirmation
Confirm presumptive Campylobacter colonies
Figure 6.13 (a) Horizontal method for detection and enumeration of Campylobacter species (ISO, 2006).
(b) FDA‐BAM method for detecting Campylobacter species in foods.
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(b)
Pre-enrichment
25g sample prepared in Hunt & Radle Campylobacter enrichment broth
1/10 dilution of sample
preparation (optional)
Selective enrichment
Pre-enrich for 4 or 5 h, 30°C and/or 37°C
Enrich at 42°C (or 37°C if C. fetusis being analysed)
Selective diagnostic isolation
Plate out :
(a) Undiluted enrichment culture
(b) 1/100 dilution of enrichment culture
Karmali blood-free agar
Incubate at 37°C (C. fetus) or 42°C
Campy-cefoperazone blood
agar. Incubate at 42°C
Sub-culture to blood agar or
heart infusion blood agar
Subculture to lysed horse blood agar for confirmation
Figure 6.13 (Continued )
individual strain. The biotyping (biochemical activity profiling) scheme of Preston is more
extensive than that of Lior. Two serotyping procedures are used: the Penner and Hennessy
scheme for the heat‐stable antigens (lipopolysaccharide) and the Lior scheme for the heat‐
labile antigens (flagella). Phage typing can differentiate strains within a serotype and is a simple enough technique to apply to a large number of strains simultaneously.
MLST (Section 6.6.1) of Campylobacter isolates has an advantage that it is unambiguous and
more reliable than phenotyping. However, this is also a disadvantage as common clones will
require further differentiation. Two genes involved in the synthesis of flagella proteins may
also be included as they are more variable (Dingle et al. 2002). Different clonal groupings of C.
jejuni have been identified in specific animals. However, some are also widespread, and can be
found in humans. Real‐time PCR Taqman assays to detect SNPs specific for the six major
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MLST clonal complexes have been developed (Best et al. 2005). This can be applied to the
rapid detection of C. jejuni and clonal allocation. Campylobacter typing methods have been
reviewed by Wassenaar and Newell (2000) and the UK Advisory Committee for the
Microbiological Safety of Food (ACMSF 2005). CRISPR‐cas array profiling (Section 6.6) has
not been investigated as much in Campylobacter compared with Salmonella, probably because
most Campylobacter infections are single cases, and not cluster outbreaks.
The two most common molecular typing methods for Campylobacter isolates are laboratory‐based PFGE and seven‐loci MLST (Carrillo et al. 2012). However, these methods have
been difficult to implement in the context of routine surveillance. The methods have limitations that lessen their robustness and reliability as the sole subtyping methods for assessing
epidemiological links amongst C. jejuni isolates. Instead whole‐genome sequencing methods
for typing are more promising especially with the declining costs of sequencing and increasing
access to sequencing facilities.
6.7.4 Enterobacteriaceae and E. coli
Escherichia coli and other Enterobacteriaceae are often initially detected together in liquid
media and then differentiated by secondary tests of indole production, lactose metabolism,
gas production and growth at 44°C. Escherichia coli produces acid and gas at 44°C within
48 hours. MacConkey broth is a commonly used medium for the presumptive detection of
lactose‐fermenting Enterobacteriaceae from water and milk. It selects for lactose‐fermenting,
bile‐tolerant organisms, which in the past have been given the general term ‘coliforms’. Acid
formation from lactose metabolism is shown by a yellow coloration of the broth (due to a pH
indicator dye, neutral red or bromocresol purple) and gas formation is indicated by gas being
trapped in an upturned Durham tube. Lauryl tryptose broth (also known as lauryl sulphate
broth) can be used for the detection of lactose‐fermenting Enterobacteriaceae from food.
Initially the inoculated medium is incubated at 35°C and afterwards presumptive positive
tubes are used to inoculate duplicate tubes: one for incubation at 35°C and the other at 44°C.
Both broths can be supplemented with 4‐methylumbelliferyl‐β‐D‐glucuronide (Section 5.2.1)
to enhance E. coli detection. Enterobacteriaceae enrichment (EE) broth, also known as buffered glucose‐brilliant green bile broth, is an enrichment medium for Enterobacteriaceae from
food. The broth is inoculated with samples that have been incubated at 25°C in aerated tryptone soya broth (1:10 dilution) for resuscitation of any injured cells. There are numerous solid
media employed for the detection of E. coli‐coliforms and Enterobacteriaceae. For example,
there are two types of violet red bile agars. First, VRBL for lactose‐fermenting Enterobacteriaceae
in food and dairy products. Second, violet red glucose (VRBG) agar for the general detection
of Enterobacteriaceae. These select for bile‐tolerant organisms, a predicted trait for intestinal
bacteria. Other media include MacConkey agar, china blue lactose agar, desoxycholate agar
and eosin methylene blue agar. These have different differentiation efficiencies and regulatory
approval. A recent trend has been the inclusion of chromogenic and fluorogenic substrates in
particular to detect β‐glucuronidase, which is produced by ~97% of E. coli strains (Section 6.2.1).
The ISO 21528:2004 standardised methods for the detection and enumeration of
Enterobacteriaceae include the MPN technique and colony counts. These involve several steps.
• Pre‐enrichment. A portion of the food is added to BPW in the ratio 1:9, and incubated at
37°C for 18 hours to resuscitate cells. For the MPN procedure triplicate tubes are incubated
of three different sample volumes equivalent to neat, 10−1 and 10−2 dilutions.
• Enrichment. A total of 1 ml of incubated BPW and sample is pipetted into 10 ml of
EE broth, which is incubated at 37°C for 24 hours. This supresses the growth of
non‐Enterobacteriaceae.
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• Selective plating, by streaking the EE broth on VRBG agar, incubated at 37°C, for 24 hours.
Presumptive Enterobacteriaceae colonies (pink to red or purple, with or without precipitation halo) are streaked on nutrient agar, incubated at 37°C, for 24 hours.
• Confirmation of Enterobacteriaceae. Five presumptive colonies are selected and streaked for
purity on nutrient agar plates before confirmation as Enterobacteriaceae according to negative oxidase reaction and glucose fermentation.
For direct enumeration the pour plate method (ISO 21528‐2:2004) is used with 1 ml sample
volume (in duplicate) in VRBGA, with an overlay of VRBGA to prevent spreading colonies
and encourage anaerobic conditions during colony growth. Presumptive Enterobacteriaceae
colonies, streaked on nutrient agar for purity checking and standardisation, are confirmed
using the oxidase and glucose fermentation tests.
E. coli can be detected using chromogenic agar (TBX) for the β‐glucuronidase reaction (i.e.
ISO 16649‐2:2001). The medium contains the chromophore 5‐bromo‐4‐chloro‐3‐indolyl
β‐D‐glucuronic acid (BCIG). A pour plate method is used, in which 1 ml test sample is pipetted into a sterile Petri dish (in duplicate) and molten TBX agar (at 44–47°C) is added. The
plates are incubated at 44°C for 18–24 hours. Typical E. coli colonies are blue. In order to resuscitate cells, the sample is initially spread onto a cellulose membrane (pore size 0.45–1.2 μm,
85 mm diameter) on two minerals‐modified glutamate agar (MMGA) plates, which are then
incubated for 4 hours at 37°C. Afterwards, the membranes are transferred to TBX agar plates
for incubation at 44°C, for 18–24 hours. This method will not detect E. coli strains that do not
grow at 44°C, and those that are β‐glucuronidase negative. Hence E. coli O157 will not be
detected.
6.7.5 Pathogenic E. coli, including E. coli O157:H7
Since E. coli is a commensal organism in the human large intestine there is an inherent problem isolating and differentiating pathogenic strains such as serotype O157:H7 from the more
numerous non‐pathogenic varieties. The key differentiation traits have been based on the
observation that, unlike most non‐pathogenic E. coli strains, E. coli O157:H7 does not ferment
sorbitol, does not possess β‐glucuronidase and does not grow above 42°C. Consequently,
MacConkey agar was modified to include sorbitol in place of lactose as the fermentable carbohydrate (SMAC). This medium has been further modified by the inclusion of various other
selective agents such as tellurite and cefixime. Pre‐enrichment in a modified BPW broth or
modified tryptone soya broth is used to resuscitate injured cells before plating onto solid
media. Because the cell surface antigenic determinant (O157:H7) is indicative of pathogenicity
(though not 100%) the IMS technique (Section 6.3.2) greatly increases the recovery of E. coli
O157:H7 (Chapman and Siddons 1996). The IMS technique is used worldwide and is one of
the most sensitive methods for E. coli O157:H7. It has been approved for use in a number of
countries.
The toxins of E. coli O157:H7 can be detected using cultured Vero cells and RPLA, which are
sensitive to 1–2 mg/ml culture filtrate (Figure 6.6). Polymyxin B is added to the culture to
facilitate the release of the verocytotoxins/Shiga toxins. ELISA methods specific for pathogenic
strains of E. coli have been developed.
The ISO horizontal method for the detection of E. coli O157 (ISO 16654:2001) is applicable
for a large variety of foods. It has four steps:
1 Enrichment in modified tryptone soya broth containing novobiocin. There is usually a 1:9
ratio of sample to broth. The mixture is incubated at 41.5°C for 6 hours before IMS, followed
by a further 12–18 hours after which time the IMS can be repeated.
Methods of detection and characterisation
301
2 Separation and concentration of the target organism is achieved using IMS as previously
described (Section 6.3.2).
3 Isolation by plating the IMS mixture onto cefixime tellurite sorbitol MacConkey agar
(CT‐SMAC) and a second agar of the user’s choice. Escherichia coli O157 colonies are
about 1 mm in diameter, transparent with a pale yellowish‐brown appearance. As stated
in the ISO standard method, the enrichment broth may give heavy bacterial growth
after overnight incubation, and this can give rise to problems recognising E. coli O157
colonies even on selective agars. Therefore, modified techniques such as plating out
dilutions of the IMS mixture, or plating smaller volumes may be used, while also
accepting this will decrease the sensitivity of the procedure. Five typical colonies are
selected from each plate and streaked on nutrient agar, followed by incubation for
18–24 hours at 37°C.
4 Confirmation is by detection of indole formation and agglutination with E. coli O157
antiserum.
6.7.6 Shigella species
The differentiation between E. coli and Shigella is troublesome since the two organisms are
genetically closely related. In particular, Shigella and enteroinvasive strains of E. coli are phenotypically very similar and they have a close antigenic relationship. Serologically Sh. dysenteriae
Peptone water dilutent 90 ml + sample 10 g
Method A
Prepare serial ten-fold dilutions
in peptone water diluent (10–1–10–6)
Spread-inoculate two plates of each
dilution to sorbitol MacConkey agar
Incubate 35 °C, 18 h
Method B
Tryptone soya broth +
novobiocin 90ml
Incubate 35 °C, 20 h
HC agar
Incubation 35 °C, 20 h
Test non-sorbitol fermenting colonies
serologically using 0157 and H7 antisera
Test sorbitol negative colonies
serologically using O157 and
H7 antisera
Figure 6.14 FDA‐BAM methods for isolation of enterohaemorrhagic Escherichia coli (EHEC).
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Table 6.6 Major differentiation characteristics between
Escherichia coli and Shigella species.
Property
Escherichia coli
Shigella species
Motility
Lactose fermentation
Indole fermentation
Gas from glucose
+
+
+
+
−
−
−
−
3 and E. coli 0124, Sh. boydii 8 and E. coli 0143, and Sh. dysenteriae 12 and E. coli 0152 appear
identical. Distinguishing traits are given in Table 6.6. Other useful differential traits are:
• Cultures that ferment mucate, utilise citrate or produce alkali on acetate agar are likely to be
E. coli.
• Cultures that decarboxylate ornithine are most likely to be Sh. sonnei.
• Cultures that ferment sucrose are likely to be E. coli.
Direct plating onto selective media is unlikely to be successful due to the close relationship
of Shigella and E. coli. Hence the detection of Shigella is generally through use of the distinguishing biochemical differences of presumptive isolates (Table 6.6). For example, on
MacConkey agar Shigella colonies initially appear as non‐lactose fermentors.
The ISO method for Shigella species (ISO 21567:2004) has several stages:
1 Enrichment of sample in 9× volume of Shigella broth containing novobiocin, followed by
anaerobic incubation at 41.5°C for 16–20 hours.
2 Selective plating on MacConkey agar, XLD agar and HE agar. These are incubated at 37°C for
20–24 hours. If no suspect colonies are visible then the plates are incubated for a further
18–24 hours. Five suspect colonies are picked and streaked on nutrient agar plates followed
by incubation for 20–24 hours at 37°C.
3 Identification is by biochemical tests followed by serological analysis of positive isolates.
Biochemical tests include growth on Triple Sugar Iron agar (TSI) for H2S and gas production,
motility and a number of other phenotyping tests that can be achieved using commercial
biochemical test kits (i.e. API 20E and Microbact). Polyvalent antisera are used with biochemically identified Shigella isolates to identify the species: Sh. flexneri, Sh. dysenteriae, Sh.
boydii and Sh. sonnei.
An abbreviated version of the FDA‐BAM method is given in Figure 6.15 for illustrative purposes. The FAD‐BAM method also uses anaerobic incubation as under these conditions
Shigella cells can compete against other Enterobacteriaceae, and novobiocin is added to the
media as a selective agent.
Shiga toxins are virtually identical to the verocytotoxin produced by EHEC and therefore
detection methods are applicable to both groups of foodborne pathogens.
6.7.7 Cronobacter genus
As previously described in Section 4.6, this organism is primarily associated with severe,
albeit rare, neonatal infections. It does also cause infections in all other age groups. The link
of some neonatal cases to contaminated reconstituted powdered infant formula has led to a
revision in hygienic practices and microbiological criteria for this product. Similar to
Salmonella isolation, the recovery of Cronobacter by conventional microbiology involves the
three steps of pre‐enrichment, enrichment and plating on selective media. Just like Salmonella
Methods of detection and characterisation
303
225 ml Shigella broth + 25 g sample
For Sh. sonnei add
For other Shigella spp., add
novobiocin (0.5 µg/ml)
novobiocin (3 µg/ml)
Adjust pH to 7.0 ± 0.2
Incubate anaerobically
Incubate anaerobically
44 °C, 20 hours
42 °C, 20 hours
MacConkey agar 35 °C in air, 20 hours
Test for indole discard culture if positive
Subculture presumptive colonies:
Glucose broth, triple sugar iron agar,
lysine decarboxylate broth, motility agar, tryptone water
Incubate at 35°C, examine at 20 hours. Continue incubation to 48 hours
Discard cultures showing positive tests for the following:
Motility, H2S, gas production, sucrose fermentation, lactose fermentation, indole
Confirm presumptive Shigella cultures as Gram-negative bacilli
Full biochemical screen
Serology
Figure 6.15 FDA‐BAM method for enrichment culture of Shigella species in foods.
testing, this method is primarily a presence/absence screening and not enumeration.
However, by using multiple different sample volumes, an MPN estimate of Cronobacter numbers can be made.
Pre‐enrichment
Just like Salmonella detection, this uses BPW, but a 10 g sample volume is added to 90 ml BPW
as the microbiological criteria are the absence of Cronobacter in 10 g quantities from a batch of
infant formula.
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The microbiology of safe food
Enrichment
The overnight BPW mixture pre‐enrichment is then enriched for any Cronobacter by adding
to EE broth or a more specific Cronobacter selective broth.
Selective plating
The enrichment broth is streaked for single colony isolation on Druggan–Forsythe–Iversen
(DFI) agar or a similar chromogenic agar (Iversen et al. 2004; Iversen and Forsythe 2007;
Plate 5). Using chromogenic agars that differentiate Cronobacter from most other
Enterobacteriaceae is necessary as the enrichment broths enrich for Enterobacteriaceae and not
just Cronobacter. The DFI agar contains the chromogen 5‐bromo‐4‐chloro‐3‐indolyl‐α‐D‐
glucopryranoside (X‐αGlc) as Cronobacter have α‐glucosidase activity, which results in blue‐
green colony formation after 18 hours at 37°C. A number of other Enterobacteriaceae, including
Salmonella and Proteus, have α‐glucosidase activity and are H2S producers. So the medium
also contains sodium thiosulphate and ferric ammonium citrate, which together act as a H2S
indicator distinguishing these organisms from Cronobacter by their black colonies. An added
benefit is that Salmonella is also detected on this agar along with Cronobacter. Sodium desoxycholate is also an ingredient to suppress the growth of Gram‐positive organisms.
6.7.8 Aeromonas species
The detection of Aeromonas is not routinely undertaken by food microbiology laboratories;
however, it is included here due to its association with contaminated water and food. A number
of selective and differential isolation media can be used for the recovery of Aeromonas species
from the environment, foods and clinical specimens. However, since no individual medium is
optimal for the recovery of Aeromonas species, a number of combinations of approaches can
be undertaken: direct plating, membrane filtration and most probable number. Approaches
include: (i) starch ampicillin agar (SAA), bile salts inositol brilliant green agar (BIBG) with
initial enrichment in alkaline peptone water (APW), or (ii) tryptose broth containing ampicillin (TSB‐30, ampicillin 30 mg/l) with commercially available media such as Aeromonas
Medium (Ryan’s Medium). Starch glutamate ampicillin penicillin (SGAP‐10) medium has
been used to detect aeromonads from foods.
To facilitate recovery of aeromonads from highly contaminated samples such as faeces, an
initial stage is incubation overnight in an enrichment broth such as APW and subculturing
onto cefsulodin irgasan novobiocin (CIN) agar and blood ampicillin agar (10 mg/l ampicillin).
The plates are then incubated aerobically at 35°C for 24–48 hours. Aeromonas species produce
distinctive colonies, with or without haemolysis on blood agar. Colonies are screened by
carrying out oxidase tests and identified phenotypically.
6.7.9 Arcobacter species
Arcobacter are not routinely tested for by food microbiology laboratories, nevertheless due to
their association with contaminated food and water they have been included in this chapter.
Methods of isolation are similar to those for Campylobacter species due to their physiological
and genetic relatedness. In general Arcobacter species are more aerotolerant and have lower
growth temperature limits than Campylobacter species. Their isolation requires selective
media such as mCCDA and CAT. On blood‐based agars Arcobacter species produce round
white, off‐white or greyish colonies, 2–4 mm in diameter after 3 days of incubation. The colonies are generally small, non‐pigmented and convex with entire edges. Swarming has been
reported on fresh agar. Brain heart infusion agar supplemented with 0.6% (w/v) yeast extract
and 10% (w/v) blood agar has been used recently for routine culturing.
Methods of detection and characterisation
305
Arcobacter isolates can be presumptively identified by their shape (small comma‐shaped or
spiral rods) and motility (darting or corkscrew motility). They can be easily distinguished
from Campylobacter and related genera by their ability to grow in air at 25°C. The main phenotypic traits used for Arcobacter species differentiation are catalase activity, nitrate reduction,
cadmium chloride susceptibility, microaerophilic growth at 20°C, and growth on MacConkey
agar and in the presence of 3.5% NaCl and 1% glycine. Organic acids and amino acids are used
as carbon sources. Hydrogen is not required for growth. All Arcobacter isolates hydrolyse
indoxyl acetate. A simple diagnostic characteristic useful for the presumptive identification of
C. jejuni, C. coli and Arcobacter species is the cadmium chloride test. Isolates can be identified
using 16S rRNA gene probes and genotyped.
6.7.10 Listeria monocytogenes
Unlike the isolation procedures for salmonellae, E. coli and Cronobacter, pre‐enrichment is not
commonly used for the isolation of Listeria species. This is because other organisms present
will outgrow Listeria cells. Instead various enrichment media have been developed and have
regulatory approval. A common enrichment broth is Fraser broth (modified from UVM
broth), which employs aesculin hydrolysis coupled with ferrous iron as an indicator of presumptive Listeria species. Enrichments are streaked onto agars such as ALOA, Oxford and
PALCAM. Oxford agar is often incubated at 30°C, whereas PALCAM agar is incubated at 37°C
under microaerophilic conditions; Plate 14. A large number of selective agents are used in
Listeria media, such as acriflavine, cycloheximide, colistin and polymyxin B as L. monocytogenes can be quickly outgrown by competing flora. Typical L. monocytogenes colonies are
surrounded by a black zone due to black iron phenolic compounds. On PALCAM agar the
centre of the colony may have a sunken centre after 48 hours of incubation.
Presumptive L. monocytogenes colonies are confirmed using biochemical and serological
testing. Most non‐Listeria isolates can be eliminated using the motility test, catalase test and
Gram staining. Listeria species are short Gram‐positive rods, catalase‐positive and are non‐
motile if incubated above 30°C. Motility of cultures grown at room temperature is characterised
by a tumbling action. Listeria monocytogenes is β‐haemolytic on horse blood agar. The CAMP
test (named after Christie, Atkins, Munch and Peterson) is used for species differentiation
(Plate 15). The Listeria isolates are streaked on sheep blood agar and St. aureus NCTC 1803 and
Rhodococcus equi NCTC 1621 are streaked in parallel close to the Listeria streaks (Figure 6.16).
The phenomenon of enhanced zones of haemolysis is observed (Table 6.7).
The ISO 11290 method for L. monocytogenes is in two parts: detection and enumeration
methods (Figure 6.17). The detection method has four stages:
1 Primary enrichment is in a selective enrichment broth that has a reduced concentration of
the selective agents acriflavine and nalidixic acid (i.e. half‐Fraser broth). Caution: this
medium uses lithium chloride, which gives a strong exothermic reaction with water, and
irritates the mucous membranes of the throat. Normally the ratio of test sample to broth is
1:9. This is incubated at 30°C for 24 hours before inoculating with the secondary enrichment broth and also plating onto selective agar.
2 Secondary enrichment in selective enrichment broth with full strength selective agents
(i.e. Fraser broth), for 48 hours at 35 or 37°C. Typically 0.1 ml of the incubated primary
enrichment mixture is added to 10 ml Fraser broth. After incubation the mixture is
streaked onto selective agars.
3 Plating out and presumptive identification on two selective agars: ALOA (or equivalent formulation) and a second agar according to the user’s choice, such as Oxford agar or PALCAM.
ALOA plates are incubated at 37°C for 24 hours, and up to 48 hours if necessary. As given
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The microbiology of safe food
Enrichment
Test sample 1:
Test sample 2:
25 g + FDA enrichment broth 225 ml
25 g + FDA enrichment broth
After 24 + 48 hours, 30°C
225 ml, without selective agents + 0.1%
sodium pyruvate
Incubate 6 hours, 30°C
Add selective agents.
After 24 + 48 hours, 30°C
Selective diagnostic isolation
Oxford agar
LPM agar
Incubate 24–48 hours, 35°C
Incubate 24–48 hours, 30°C
After 24 and 48 hours
After 24 and 48 hours
Examine for brownish-black
Examine by Henry
colonies with brown halos
illumination
Subculture to tryptone soya agar + 0.6% yeast extract
CAMP test motility test and biochemical tests
Subculture to tryptone soya broth + 0.6% yeast extract
Subculture to tryptose broth
Serological tests
Figure 6.16 FDA/BAM Listeria isolation procedure.
Table 6.7 CAMP reactions for Listeria species.
Listeria species
Staphylococcus aureus
Rhodococcus equi
Listeria monocytogenes
Listeria seeligeri
Listeria ivanovii
+
+
−
−
−
+
Methods of detection and characterisation
Zone of
enhanced
haemolysis
307
L.monocytogenes
St. aureus
L. ivanovii
L. seeligeri
Rhodococcus equi
Figure 6.17 The CAMP test for haemolysis testing of L. monocytogenes.
above the selective agars are inoculated with primary and secondary enriched cultures. On
ALOA typical Listeria colonies are green‐blue surrounded by an opaque halo.
4 Confirmation using morphological, physiological and biochemical tests. Five presumptive
Listeria colonies are picked from each plate, and streaked on tryptone soya yeast extract
agar (TSYEA), and incubated at 35 or 37°C for 18–24 hours. Confirmation tests include
Gram stain, catalase production and motility of culture grown at 25°C. Listeria are small
Gram‐positive rods, which are catalase‐positive and are motile with a tumbling motion.
Listeria monocytogenes isolates are confirmed by positive β‐haemolytic reaction on sheep
blood agar plates, utilisation of rhamnose but not xylose sugars and enhanced β‐haemolysis by St. aureus and not Rh. equi in the CAMP test (Plate 15). When observed by the
Henry illumination tests, Listeria species colonies have a bluish colour and a granular surface. This test involves observing the colonies that are illuminated underneath by reflected
white light.
The ISO enumeration method has several stages:
1 Sample preparation in the ratio 1:9 in BPW or half‐Fraser broth (without selective agents).
2 Resuscitation for 1 hour at 20°C before inoculation of selective agar given below. After which
the selective agents (lithium chloride, acriflavine and nalidixic acid) can be added and the
sample incubated as given above for the detection method.
3 Inoculation of PALCAM agar; usually 0.1 ml or 1 ml if low numbers of L. monocytogenes are
expected. Incubate plates at 35 or 37°C for 24 hours, or incubate for a further 24 hours if only
slight growth or no growth is obtained.
4 Identification and enumeration by counting colonies with typical Listeria morphology.
5 Confirmation of Listeria species, and L. monocytogenes by selecting five presumptive colonies from each plate. Same tests are applied as previously described in the detection method.
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The microbiology of safe food
6.7.11 Staphylococcus aureus
Large numbers of St. aureus cells are required to produce sufficient amounts of heat‐stable
toxin. Therefore small numbers of St. aureus in food are of little significance, and so an enrichment step is not used for the organism’s isolation. Consequently tests for viable cells are applicable for samples before heat treatment, and tests for the enterotoxin and heat‐stable
thermonuclease are for heat‐treated samples. The Baird–Parker agar is the most widely
accepted selective agar for St. aureus (Plate 16). This medium includes sodium pyruvate to aid
the resuscitation of injured cells. The selectivity is due to the presence of tellurite, lithium
chloride and glycine. Staphylococcus aureus forms black colonies due to tellurite reduction
and clearance of egg yolk due to lipase activity. Glycine acts as a growth stimulant and is an
essential component of the staphylococcal cell wall. An alternative medium, mannitol salt
agar, has better recovery efficiency of St. aureus from cheese. The selective agent is salt (7.5%)
and mannitol fermentation is indicated by the pH indicator phenol red (reddish‐purple zones
surrounding St. aureus colonies).
The coagulase test (clotting of diluted mammalian blood plasma) is a reliable test for
pathogenic St. aureus. DNase production correlates with the coagulase test and is therefore
also indicative of pathogenicity. Testing for DNase activity used to involve growing the
organism on agar containing DNA and then flooding with HCl to visualise zones of DNA
degradation: a clear zone being due to the lack of precipitated DNA. However, the acid kills
the organism resulting in a non‐viable culture. Therefore, current alternatives use indicator
dyes toluidine blue and methyl green, which are included in the agar medium. The dyes
form coloured complexes with the DNA and so presumptive pathogenic St. aureus colonies
will show colour changes on DNA hydrolysis: toluidine blue produces pink zones, whereas
methyl green goes almost colourless. Staphylococcal enterotoxins can be detected using
RPLA (Section 6.4). The limit of sensitivity is about 0.5 ng of enterotoxin per g food. A number of enzyme immunoassays are available for staphylococcal enterotoxin detection. ELISA
kits are also available that have a detection limit of >0.5 μg toxin per 100 g food and require
7 hours to obtain the result.
Staphylococcus aureus causes a variety of diseases including boils and carbuncles, but in
food‐related illness it is principally the production of heat‐stable toxins, termed enterotoxins,
that causes vomiting (Section 4.13.3). Initially the enterotoxins were divided serologically into
five major types – SEA to SEE – of which SEC is further divided into three variants. More
recently a number of other SEs have been identified: SEG to SEQ. In addition, SEs are members of the pyrogenic toxin (PT) superantigens.
6.7.12 Clostridium perfringens
Clostridium perfringens is a strict anaerobe which produces spores that can survive heating
processes. Therefore enrichment is required to detect low numbers of Clostridium cells, which
may be outnumbered by other organisms (Figure 6.18). Numerous media include sulphite and
iron, which result in a characteristic blackening of Cl. perfringens colonies (Table 6.2). However,
this blackening reaction is not limited to Cl. perfringens and hence the term ‘sulphite reducers’
is often used instead of specifying the species Cl. perfringens. The lecithinase (phospholipase
c) activity of Cl. perfringens is also a common test in diagnostic media resulting in opaque
zones surrounding the colonies. Selectivity is by the inclusion of cycloserine or neomycin. All
media are incubated under anaerobic conditions, which are either generated using an anaerobe jar or an anaerobic cabinet.
Tests to distinguish Cl. perfringens from other anaerobic sulphite reducers are the Gram
stain reaction, metronidazole sensitivity, the Nagler reaction and the reversed CAMP test. The
Methods of detection and characterisation
Anaerobic plate count
Optional enrichment if cell numbers are very low
Blend sample 1/10 in 0.1%
Suspend sample (0.2 g) in 2 ml of liver
peptone water
broth or peptone–glucose–yeast extract broth
Decimal dilute to 10–7 in 0.1%
Incubate 18–24 hours, 35–37°C
309
peptone water
Plate out (0.1 ml in duplicate)
Plate out tubes showing gas on TSC agar with
on TCS with egg yolk or 1 ml on
gas production on TSC agar with egg yolk
TSC without egg yolk
Overlay 5–10 ml of egg yolk
Incubate anaerobically 18–24 hours, 35–37°C
free TSC agar
Incubate 18–24 hours, 35–37°C
Confirmatory tests on egg yolk positive black
colonies
Confirmatory tests on egg yolk positive black colonies on TSC with egg yolk and black
colonies on TSC without egg yolk
Figure 6.18 Procedure for the isolation and quantification of Clostridium perfringens.
Nagler test uses Cl. perfringens type A antitoxin to neutralise lecithinase activity. The reversed
CAMP test involves streaking sheep blood agar with Streptococcus agalactiae and the test isolate at right angles, without touching. After anaerobic incubation at 37°C for 24 hours, a positive result is indicated by arrow‐shaped areas of synergistic enhanced haemolysis at the
junction of the two streaks (Figure 6.19). Production of ‘stormy clot’ in litmus milk and the
detection of acid phosphatase are useful confirmatory tests. A number of biological methods
are available including the rabbit ligated ileal loop tests, which though very effective and widely
used, do require live animal testing. To date, few commercially produced kits are available for
the detection of the extracellular toxins produced by Cl. perfringens. RPLA (Section 6.4.2) is
available for Cl. perfringens enterotoxin.
6.7.13 B. cereus, B. subtilis and B. licheniformis
Enrichment is not normally used for the detection of B. cereus since low numbers of the organism are not regarded as being of significance (Figure 6.20). Direct plating onto selective media
containing the antibiotic polymyxin B is often used. The two key distinguishing features incorporated into media design are the demonstration of phospholipase c activity and the inability
to produce acid from the sugar mannitol as shown in Plate 17. If it is necessary to only count
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The microbiology of safe food
Area of enhanced
haemolysis at
junction of α-toxin
and CAMP factor
Area of
Cl. perfringens α-toxin
Horizontal streak of
Cl. perfringens
Vertical streak of
St. agalactiae
Area of CAMP factor β -haemolysis
Figure 6.19 Reversed CAMP test for Clostridium perfringens haemolysis.
spores, then the vegetative cells must be killed by heat treatment (1:10 dilution, 15 minutes,
70°C) or alcohol treatment (1:1 dilution in 95% ethyl alcohol, 30 minutes at room
temperature).
Bacillus subtilis and B. licheniformis can be isolated easily using routine non‐selective media.
They have a similar appearance on PEMBA medium, but are distinguishable from B. cereus.
ELISA and RPLA tests are commercially available for Bacillus diarrhoeal enterotoxin. They
have a sensitivity limit of 1 ng toxin/ml of material and take approximately 4 hours to obtain a
result. However, no test has been developed for the emetic toxin due to problems of
purification.
6.7.14 Mycotoxins
The toxins are visualised under UV light since the four naturally produced aflatoxins, B1, B2,
G1 and G2, are named after the blue and green fluorescence they produce. Trichothecenes,
fumonisins and moniliformin (from Fusarium species) can be detected using high‐performance liquid chromatography. ELISA and latex agglutination assays are commercially available for the detection of aflatoxins. ELISA assays can be used for the quantitative detection of
moulds in foods. Compared with ELISA tests, which require 5–10 hours to complete, the latex
agglutination method is much faster taking only 10–20 minutes. Test kits for mycotoxins have
been developed that are rapid and simple to use. They are designed to be used in the field,
country elevators, feed mills and processing plants.
6.7.15 Viruses
In most studies of food and waterborne viruses, samples have been screened for viruses by
electron microscopy, DNA probe, ELISA or tissue culture. But not all these techniques are
feasible with all viruses, i.e. norovirus viruses cannot be grown in tissue culture. Electron
Methods of detection and characterisation
311
Vegetative cells
Make an initial dilution (1/10) of the sample in an appropriate diluent
(e.g. phosphate buffer saline, maximum recovery diluent, peptone water)
Decimal dilute to 10–6
Incubate duplicate plates of B. cereus selective medium (PEMBA) with 0.1 ml of
10–3 –10–6 dilutions
Spread the inoculum over the entire surface
Incubate aerobically for 24–48 hours, 35–37°C
Examine for peacock-blue colonies with blue egg yolk precipitate zone
Confirm with rapid screening procedure
If necessary, verify with biochemical tests
Spores
If necessary to count spores, then first treat with heat or alcohol to destroy the vegetative
cells
Heat treatment: Heat the initial 1/10 suspension for 15 minutes 70°C. Proceed as for detection
of vegetative cells
Alcohol treatment: Dilute the initial suspension 1:1 in 95% ethyl alcohol. Leave for 30 minutes,
room temperature. Proceed as for detection of vegetative cells, adjusting the dilutions to
account for the 1:1 dilution of the sample suspension in alcohol
Figure 6.20 Typical procedure for detection of Bacillus cereus.
microscopy has a limit of sensitivity of 105–106 particles per ml of faecal suspension. ELISA‐
based assays have been developed for group A rotavirus and adenovirus in clinical samples
only. Although the presence of bacterial indicators (Enterobacteriaceae, E. coli) does not correlate with the presence of viral pathogens, there are no established virus detection methods
for foods other than shellfish. Consequently foodborne viral gastroenteritis is not usually diagnosed and detection methods for viruses and viral genomic material have not been adopted by
routine food analysis laboratories.
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For epidemiological studies, large volumes (25–100 g) of food need to be analysed for enteric
viruses since the level of food contamination is assumed to be low. If tissue culture is to be used
to detect enteric viruses, then the viruses need to be separated from the bulk of the food. The
viruses may be enumerated using plaque assays with dilution endpoint assays. Cell culture
technique, however, is not applicable for noroviruses (formerly Norwalk‐like virus and small
round structured viruses) due to the lack of host cell line, and is only moderately successful
with hepatitis A virus (HAV). The sequencing of norovirus and HAV genomes has enabled the
reverse transcriptase polymerase chain reaction (RT‐PCR) to be developed for detection and
characterisation of the viruses in faecal, vomit and shellfish samples. The norovirus can be
characterised by sequencing the amplified products of the test (amplicons), and this has enabled outbreaks in different locations to be linked to a single source. Electron microscopic analysis for norovirus is only of use with samples during the first 2 days of symptoms, whereas
RT‐PCR is usable within 4 days of symptoms appearing (Atmar and Estes 2001). HAV genome
is detectable by RT‐PCR in artificial sterile seawater for 232 days, compared with only 35 days
for cell culture. Therefore, RT‐PCR is not a reliable indicator of infectious HAV.
7 Microbiological criteria
7.1 Background to microbiological criteria and end‐product testing
Testing food at the end of production for micro‐organisms (‘end‐product testing’) has been
standard practice in the food industry for decades. However, a statistical appreciation of its
usefulness has been largely overlooked. In 1974 the International Commission on
Microbiological Specifications for Foods (ICMSF) wrote an excellent text regarding the setting
of microbiological criteria. The book was written at a time of increasing global food transportation and was primarily aimed at being applied to food entering a country (port of entry) with
no known history. Nevertheless these criteria have been applied within industry for their own
products despite in‐house knowledge of the product.
It is very important nowadays to recognise that microbiological testing of foods should be
carried out under the umbrella of Hazard Analysis Critical Control Point (HACCP) as part of
the verification principle (Section 9.7). In other words, end‐product testing in itself does not
guarantee a safe food product, but could support the HACCP plan implementation. Nevertheless
microbiological criteria (levels of microbes acceptable in a particular food) are required by
regulatory authorities and between companies in a supply chain. The specifics of these criteria
are often historical, not necessarily the most appropriate. Also, as in the case of criteria between
companies, they are often confidential. These criteria may eventually be replaced by ‘Food
Safety Objectives’ (Section 10.7).
7.2 International commission on microbiological
specifications for foods (ICMSF)
In the 1960s the role of micro‐organisms in foodborne disease had become well recognised,
and in addition, international trade had significantly increased. However, microbiological testing of food was hampered due to the lack of standardised methods and the use of sampling
plans that lacked statistical validity. Consequently in 1962 the ICMSF was formed by the
International Committee on Food Microbiology and Hygiene. The ICMSF’s aims were to:
1 Assess data on the microbiological safety and quality (including spoilage) of foods.
2 Determine if the use of microbiological criteria would both improve and assure the
microbiological safety of certain foods.
3 Recommend methods of sampling and examination.
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
313
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These objectives have evolved as knowledge of foodborne micro‐organisms and their control has increased and is reflected in the series of ICMSF books and papers. The first ICMSF
book (initially published in 1968 and revised in 1978, 1982 and 1988) was centred upon
encouraging a comparison of worldwide testing methods in order to obtain agreed methods
for use in international trade. In 1974 the ICMSF published Microorganisms in Foods 2.
Sampling for Microbiological Analysis: Principles and Specific Applications. This recognised
the need for scientifically based sampling plans for foods in international trade. It described
two‐ and three‐class sampling plans and ‘choice of case’. The sampling plans were originally
designed for application at port of entry; that is, when there is no prior knowledge on the
history of the food. This pioneering work set forth the principles of sampling plans for the
microbiological evaluation of foods and is also known as attributes and variables sampling
depending on the extent of microbiological knowledge of the food. The second edition of
the book in 1986 took note of the successful application of the acceptance sampling plans on
a worldwide basis, not only at an international level but at national and local levels by both
industry and regulatory agencies. The ICMSF book has subsequently been updated in 2002.
The third (two‐volume) ICMSF book was on the Microbiological Ecology of Foods (Volume
1, ICMSF 1980a) and Factors Affecting Growth and Death of Microorganisms (Volume 2,
ICMSF 1980b). In addition, this detailed the microbial load, spoilage patterns and microbial
hazards of 14 food commodity groups. The use of HACCP as the most assured means of
safety food production was the subject of the Commission’s fourth book (ICMSF 1988). In
order to support HACCP and good hygienic practices (GHP), in 1996 the Commission produced their fifth book as a reference source on the growth and death response of foodborne
pathogens (ICMSF 1996a). Due to increased knowledge of foodborne pathogens in 1998,
the Commission updated its earlier 1980b publication on 16 commodity foods (ICMSF
1998c). This was again with regard to typical microbial loads, spoilage patterns and control
measures. More recently (2002) the ICMSF has produced book seven (Microbiological
Testing in Food Safety Management), which is a revision of the 1986 publication. It has a
threefold purpose:
1 Supporting the use of statistically valid sampling plans at port of entry (i.e. where there is no
prior knowledge concerning the processing conditions).
2 Demonstrating the application of HACCP and GHP for structured food safety management, along with end‐product testing (cf. Chapter 9).
3 Recommending the incorporation of ‘food safety objectives’ (Section 10.7) as a means of
translating ‘risk’ into the principles of HACCP and GHP.
7.3 Codex Alimentarius principles for the establishment and application
of microbiological criteria
The Codex Alimentarius Commission has become the reference for international food safety
requirements (cf. Section 12.4 for more detail). The Codex Alimentarius Commission (1997b,
p.1) definition of a microbiological criterion is:
A microbiological criterion for food defines the acceptability of a product or a food lot,
based on the absence or presence, or number of microorganisms including parasites,
and/or quantity of their toxins/metabolites, per unit(s) of mass, volume, area or lot.
Microbiological criteria
315
Codex Alimentarius Commission (1997b, c) requires that a microbiological criterion
consists of:
• A statement of the micro‐organisms of concern and/or their toxins/metabolites and the
reason for that concern.
• The analytical methods for their detection and/or quantification.
• A plan defining the number of field samples to be taken and the size of the analytical unit.
• Microbiological limits considered appropriate to the food at the specified point(s) of the
food chain.
• The number of analytical units that should conform to these limits.
A microbiological criterion should also state:
• The food to which the criterion applies.
• The point(s) in the food chain where the criterion applies.
• Any actions to be taken when the criterion is not met.
The value of microbiological testing as a control measure varies along the food chain. Therefore,
a microbiological criterion should be established and applied only where there is a definite need
and where its application is practical. Such need is demonstrated, for example, by epidemiological evidence that the food under consideration may represent a public health risk and that a
criterion is meaningful for consumer protection, or as the result of a risk assessment. The criterion should be technically attainable by applying good manufacturing practices (GMPs) (Codes
of Practice). Criteria should be reviewed periodically for relevance with respect to emerging
pathogens (Section 4.18), changing technologies and new understandings of science.
A sampling plan includes the sampling procedure and the decision criteria to be applied to
a lot, based on examination of a prescribed number of sample units and subsequent analytical
units of a stated size by defined methods. A well‐designed sampling plan defines the probability of detecting micro‐organisms in a lot, but it should be borne in mind that no sampling plan
can ensure the absence of a particular organism. Sampling plans should be administratively
and economically feasible (Codex Alimentarius Commission 1997b, c).
In particular, the choice of sampling plans should take into account:
1 Risks to public health associated with the hazard.
2 The susceptibility of the target group of consumers.
3 The heterogeneity of distribution of micro‐organisms where variable sampling plans are
employed.
4 The acceptable quality level (AQL) and the desired statistical probability of accepting a non‐
conforming lot.
The AQL is the percentage of non‐conforming sample units in the entire lot for which the
sampling plan will indicate lot acceptance for a prescribed probability (usually 95%). For many
applications, two‐ or three‐class attribute plans may prove useful.
Microbiological criteria should be based on scientific analysis and advice and, where sufficient data are available, on a risk analysis appropriate to the foodstuff and its use (CAC 1997b).
These criteria may be relevant to the examination of foods, including raw materials and ingredients of unknown or uncertain origin, or when no other means of verifying the efficacy of
HACCP‐based systems and GHP are available. Microbiological criteria may also be used to
determine that processes are consistent with the general principles of food hygiene.
Microbiological criteria are not normally suitable for monitoring Critical Limits as defined in
the HACCP system.
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The microbiology of safe food
The purpose of establishing microbiological criteria is to protect the public’s health by providing food that is safe, sound and wholesome, and to meet the requirements of fair trade
practices. The presence of criteria, however, does not protect the consumer’s health since it is
possible for a food lot to be accepted that contains defective units. Microbiological criteria may
be applied at any point along the food chain and can be used to examine food at the port of
entry and at the retail level.
The statistical performance characteristics or operating characteristics curve should be provided in the sampling plan (Section 7.4). Performance characteristics provide specific information to estimate the probability of accepting a non‐conforming lot. The time between taking
the field samples and analysis should be as short as reasonably possible, and during transport
to the laboratory the conditions (e.g. temperature) should not allow increase or decrease of the
numbers of the target organism, so that the results reflect – within the limitations given by the
sampling plan – the microbiological conditions of the lot.
7.4 Sampling plans
In addition to the ICMSF 1986 and 2002 publications on sampling plans, Harrigan and Park
(1991) wrote an excellent book on their practical mathematics. Just as it is impractical to test a
sample for every possible food pathogen, so it is also impractical to destructively test 100% of
an ingredient or end‐product. Whilst it is accepted that no sampling plan can guarantee the
absence of a pathogen in a batch of food (food lot), there is a need to use sampling plans to
appropriately test a batch of material and give a statistical basis for acceptance or rejection of a
food lot.
Microbiological sampling plans are frequently used in food production, import control and
in contractual agreements with suppliers and customers. Sampling plans are used to check the
microbiological status of a commodity, its compliance to safety requirements and adherence to
GHP (Section 9.11) during or after manufacture. The results from single sample examinations
may give valuable baseline data which can be used for trend analysis, particularly where samples form part of a specific survey. However, statistical principles should be observed when
sampling particular food commodities many of which (usually end‐products) are heterogeneous, even when they have a similar formulation. In situations where a food inspector might be
concerned about a particular food, a sample taken for microbiological analysis may provide
evidence that food hygiene regulations have been contravened or may provide the basis for
additional inspection and/or examination. The single sample concept is likely to retain a role
in assessing food safety in small‐scale food production businesses, which will have fewer
resources for implementation of HACCP, but will nevertheless have to take proper account of
the risk to public health posed by each individual operation.
There are two types of sampling plans:
1 Variables plans, when the microbial counts conform to a ‘log‐normal’ distribution
(Section 7.5). These data would be known by a producer and are not applicable to an
importer at the port of entry situation. These are less frequently used as primarily food is
produced and widely distributed, rather than regionally.
2 Attribute plans, when no prior knowledge of the distribution of micro‐organisms in the
food is known, i.e. at port of entry or the distribution of target organism is not log‐normal
(Section 7.6).
Attributes sampling plans can be either according to a two‐class plan or a three‐class plan. The
two‐class plan is used almost exclusively for pathogens, whereas a three‐class plan is frequently
Microbiological criteria
317
used to examine for hygiene indicators. The main advantage of using sampling plans is that
they are statistically based and provide a uniform basis for acceptance against defined
criteria.
The type of sampling plan required can be decided using Figure 7.1.
Attributes plans also involve the concept of ‘choice of case’, based on microbiological risk.
‘Case’ is a classification of sampling plans ranging from 1 (least stringent) to 15 (most stringent). The choice of case, and therefore the sampling plan, depends on:
• The relative severity of the hazard to food quality or consumer health on the basis of the
micro‐organisms involved. See Chapters 4 and 5.
• The expectation of their destruction, survival or multiplication during normal handling of
the food. See Chapters 2 and 3.
Table 7.1 and the decisions trees of Figures 7.1 and 7.2 should be referred to aid deciding on
the appropriate sampling plan. For example, cases 1–3 refer to utility applications, such as shelf
life, whereas cases 13, 14 and 15 refer to severely hazardous foodborne pathogens. The severity
of the microbiological hazard has been covered in Chapters 4 and 5 and the foodborne pathogens grouped to assist in referring to Table 4.2.
Organism in question is to be measured by:
Presence or absence test
Enumeration
Use a two-class plan
Use a three-class plan*
Is it permissible to accept
Choose the n and c values
presence of the target
(Table 7.6) for desired
organism in food?
probability
No
Yes
c=0
c>0
Choose value of n
Choose value of n and c
to give desired probability
to give desired probability
(Table 7.4)
(Table 7.5)
Figure 7.1 Decision tree for choosing a sampling plan Source: Adapted from ICMSF (1986). * A variable plan
may be applicable if the organism is distributed in a log‐normal fashion.
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The microbiology of safe food
Table 7.1 Sampling plans in relation to degree of health hazard and conditions of use.
Conditions in which food is expected to be handled
and consumed after sampling
Type of hazard
No direct health hazard
Utility, for example reduced
shelf life and spoilage
Health hazard
Low, indirect (indicator)
Moderate, direct, limited
spread
Moderate, direct, potentially
extensive spread
Severe, direct
Reduce degree
of hazard
Cause no change
in hazard
May increase
hazard
Case l
Three‐class,
n = 5, c = 3
Case 4
Three‐class,
n = 5, c = 3
Case 7
Three‐class,
n = 5, c = 2
Case 10
Two‐class,
n = 5, c = 0
Case 13
Two‐class,
n = 15, c = 0
Case 2
Three‐class,
n = 5, c = 2
Case 5
Three‐class,
n = 5, c = 2
Case 8
Three‐class,
n = 5, c = 1
Case 11
Two‐class,
n = 10, c = 0
Case 14
Two‐class,
n = 30, c = 0
Case 3
Three‐class,
n = 5, c = 1
Case 6
Three‐class,
n = 5, c = 1
Case 9
Three‐class,
n = 10, c = 1
Case 12
Two‐class,
n = 20, c = 0
Case 15
Two‐class,
n = 60, c = 0
Source: ICMSF (1986). Reprinted with permission of the University of Toronto Press.
Sampling plans and recommended microbiological limits were published by ICMSF (1986)
for the following foods:
1 raw meats, processed meats, poultry and poultry products;
2 pet foods;
3 dried milk and cheese;
4 pasteurised liquid, frozen and dried egg products;
5 seafoods;
6 vegetables, fruit, nuts and yeast;
7 cereals and cereal products;
8 peanut butter and other nut butters;
9 cocoa, chocolate and confectionery;
10 infant and certain categories of dietetic foods;
11 bottled water.
7.5 Variables plans
Variables plans can be applied when the micro‐organisms in the food are distributed ‘log‐normally’; that is the logarithms of the viable counts conform to a normal distribution (Figure 7.3;
Kilsby et al. 1979). This applies to certain foods that have been analysed over a period of time
by the producer and therefore does not apply at port of entry.
If the micro‐organisms’ distribution within a lot is log‐normal then sampling plans can be
used to develop acceptance sampling plans. The sample mean (x) and standard deviation (s)
are determined from previous studies. The sample mean and standard deviation are used to
decide whether a ‘lot’ of food should be accepted or rejected.
Microbiological criteria
Is the criterion to be applied at the food production site?
Yes
Yes
No
Origin of food known?
Are GHP and HACCP expected to be applied and verified?
Is criterion to be used for official control?
No
319
No
No
Producer to consider
need for own criterion
Is there evidence of a risk to health for this food?
No criterion should
be established
No
Yes
Will the application of a criterion benefit public health?
No
Yes
Indicator
Case 5
Pathogen
Potential for unacceptable multiplication during
storage, distribution, preparation or use?
Case 8, 11 or 14
Yes
Case 6
Potential for acceptable reduction during storage,
distribution, preparation or use?
Case 9, 12 or 15
Yes
Case 4
Killing before consumption assured?
Case 7, 10 or 13
Yes
No criterion should be established
Figure 7.2 Decision tree for choice of criteria for microbiological pathogens and indicator organisms.
In addition:
The proportion (pd) of units in a lot that can have a concentration above the limit value, V must
be decided.
The desired probability P can be chosen where P is the probability of rejecting a lot that
contains at least a proportion pd above V.
The lot of food is rejected if x + k1 s > V
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The microbiology of safe food
Frequency of occurrence (%)
35
30
25
20
15
10
5
0
0
1
2
3
4
5
6
Log10 conc (cfu/g)
Figure 7.3 Normal log distribution of a micro‐organism.
Table 7.2 Safety and quality specification (reject if x + k1 s > V).
Number of sample units
Probability (P)
of rejection
Proportion (pd)
exceeding V
3
5
7
10
0.95
0.05
0.1
0.3
0.1
0.25
7.7
6.2
3.3
4.3
2.6
4.2
3.4
1.9
2.7
1.7
3.4
2.8
1.5
2.3
1.4
2.9
2.4
1.3
2.1
1.3
0.90
Source: adapted from ICMSF (1986) and reprinted with permission of the University of Toronto Press.
Where:
k1 is obtained from reference tables (Table 7.2) according to the pd and P values. It is therefore
dependent upon the stringency of the sampling plan and number of sample units, n, analysed.
V is the microbial count as a log‐concentration that has been set as a safety limit.
Deciding that a lot would be rejected if 10% (pd = 0.1) of samples exceeded the value V, with a
probability of 0.95 and taking five sample units (n) gives k1s as 3.4. The more samples (n) are
taken, the lower the chance of rejecting an acceptable lot of food.
The value of V is set by the microbiologist from previous experience. It can be similar to M
in the three‐class plan (Section 7.6.2).
For example:
The aerobic plate count for ice cream from the old milk products Directive 92 / 46 / EEC gives
M 500000 cfu / g.
500000 log 5.
ThereforeV
5.
Microbiological criteria
321
Table 7.3 Determining the good manufacturing practice limit (accept if x + k2 < v).
Probability (P)
of rejection
Proportion (pd)
exceeding v
0.90
0.05
0.1
0.3
0.01
0.1
0.25
0.5
0.75
Number of sample units
3
5
7
10
0.84
0.53
−0.26
1.87
0.91
0.31
−0.47
0.98
0.68
−0.05
1.92
0.97
0.38
−0.33
1.07
0.75
0.04
1.96
1.01
0.42
−0.27
1.15
0.83
0.12
2.01
1.04
0.46
−0.22
Source: Adapted from ICMSF (1986) and reprinted with permission of the University of Toronto Press.
Previous analysis gave a mean log value of 5.111 and s = 0.201. Therefore, deciding:
1 pd = 0.1, probability that a lot would be rejected if 10% samples exceeded V
2 probability of rejection = 0.95
3 number of sample units = 3
Gives k1 = 6.2
Hence:
x k1 s 5.111
6.2 0.201
6.3572
Since V = 5, the lot would be rejected.
Variables plans can be applied to GMP standards using the k2 values in Table 7.3 (Kilsby
1982; ICMSF 1986).
A similar formula is applied where the lot is accepted if x + k2 s < v.
The value of P and pd are decided as before, v is similar to ‘m’ in the three‐class plan
(Section 7.6.2) and the GMP values of IFST (1999) can be used.
For example:
GMP value for the aerobic plate count for raw poultry IFST1999
Previous analysis had given x 4.3 witha standard deviation s
105 5.0
0.475
Therefore deciding:
1 Proportion of acceptance, P = 0.9
2 Proportion exceeding v, pd = 0.1
3 Number of sample units = 7
Gives k2 = 0.75
Hence x + k2 s = 4.3 + (0.75 × 0.475) = 4.65625.
Therefore, the lot of raw chicken is below the GMP value.
7.6 Attributes sampling plan
The attributes sampling plan(s) is applied when there is no previous microbiological knowledge
of the distribution of micro‐organisms in the food or the micro‐organisms are not distributed
‘log‐normally’. There are two types of attributes sampling plans as defined by ICMSF (1986):
the two‐class plan and the three‐class plan.
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The microbiology of safe food
The two‐class plan is used almost exclusively for pathogens, whereas a three‐class plan is
often applied for indicator organisms. The main advantage of using sampling plans is that they
are statistically based and provide a uniform basis for acceptance against defined criteria.
7.6.1 Two‐class plan
A two‐class plan consists of the specifications n, c and m.
Where:
n = the number of sample units from a lot that must be examined.
c = the maximum acceptable number of sample units that may exceed the value of m. The lot
is rejected if the ‘m’ number is exceeded.
m = the maximum number of relevant bacteria/g.
For example:
n = 5, c = 0.
This means that five sample units are analysed for a specific pathogen (e.g. Salmonella). If one
unit contains Salmonella then the complete batch is unacceptable. Each sample unit analysed
is normally 25 g for Salmonella testing (Section 6.7.2).
7.6.2 Three‐class plan
The additional parameter in a three‐class plan is:
M = a quantity that is used to separate marginally acceptable from unacceptable. A value at or
above M in any sample is unacceptable.
Hence the three‐class plan is where the food can be divided into three classes according to the
concentration of micro‐organisms detected:
• ‘acceptable’ if counts are below m;
• ‘marginally acceptable’ if counts are above m but less than M;
• ‘unacceptable’ (reject) if counts are greater than M.
For example, a sampling plan for Enterobacteriaceae could be:
n 5, c 2, m 10, M 100
This means that 2 units from a sample number of 5 can contain between 10 and 100
Enterobacteriaceae and be acceptable. However if 3 units contain Enterobacteriaceae between
10 and 100 or just 1 sample has >100 Enterobacteriaceae, then the batch is unacceptable and
the lot is rejected. Hence the three‐class sampling plan includes a tolerance value for the
random distribution of microbes in foods.
The stringency of the sampling plan can be decided using the ICMSF (1986) concept based
on the hazard potential of the food and the conditions which a food is expected to be subject
to before consumption (Table 7.1).
7.7 Principles
7.7.1 Defining a ‘lot’ of food
A lot is ‘a quantity of food or food units produced and handled under uniform conditions’. This
implies homogeneity within a lot. However, in most instances the distribution of micro‐organisms
within a ‘lot’ of food is heterogeneous. If a lot is in fact composed of different production
batches then the producer’s risk (i.e. the risk that an acceptable lot will be rejected) can be high
since the sample units analysed may by chance be those from a poor‐quality batch. In contrast,
Microbiological criteria
323
by defining individual production batches as lots a more precise identification of poor‐quality
(reject) food can be made.
7.7.2 Sample unit number
The number of sample units ‘n’ refers to the number of units that are chosen randomly. The
samples should represent the composition of the lot from which they are taken. A sample unit
can be an individual package or portions. The sample units must be taken in an unbiased fashion and must represent the food lot as well as possible. Micro‐organisms in food are often
heterogeneously distributed and this makes the interpretation of sample unit results difficult.
Random choice of samples is required to try and avoid biased sampling; however, difficulties
arise when the food is non‐homogeneous, i.e. a quiche.
The choice of n is usually a compromise between what is an ideal probability of assurance of
consumer safety and the work load the laboratory can handle. It is important first to determine
the nature of the hazard and then determine the appropriate probabilities of acceptance
(Tables 7.4–7.6). It is uneconomical to test a large portion of a food lot. However, the stringency of a sampling plan for a hazardous micro‐organism can be set using the relationship
between the number of sample units analysed and the acceptance/rejection criteria (n and c
values; Section 7.4).
7.7.3 Operating characteristic curve
It is possible when using a sample plan that a relatively poor lot of food will be accepted and a
good lot is rejected. This is represented by the ‘operating characteristic’ curve. This is a plot of:
1 The probability of acceptance (Pa) on the ‘y’ axis. Where Pa is the expected proportion of
times a lot of this given quality is sampled for a decision.
2 The percentage of defective sample units comprising a lot (p) on the ‘x’ axis. This is also
known as a measure of lot quality.
Figure 7.4 gives the operating characteristic curve for the sampling plan n = 5, c = 3.
The operating characteristic curve changes according to the values of n and c. Figure 7.5b is
a selected area of Figure 7.5a to emphasise the high chance of accepting lots with up to 30%
defectives. If a producer sets a limit of 10% defectives (i.e. p = 10%) using a two‐class plan of
n = 5, c = 2, then the probability of acceptance (Pa) is 99%. This means that on 99 of every 100
occasions when a 10% defective lot is sampled, one may expect to have 2 or fewer of the 5 tests
showing the presence of the organism and thus calling for ‘acceptance’, whilst on 1 of every 100
times there will be 3 or more positives, calling for non‐acceptance. Therefore a sampling plan
Table 7.4 Probability of accepting (Pa%) a food lot: two‐class plan, c = 0.
Probability of acceptance (Pa%)
Actual percentage of defective samples
Number of
samples (n)
2
5
10
20
30
40
50
3
5
10
20
94
90
82
67
86
77
60
36
73
59
35
12
51
33
11
1
34
17
3
(<0.5)
22
8
1
(<0.5)
13
3
(<0.5)
(<0.5)
Source: Adapted from ICMSF (1986) and reprinted with permission from the University of Toronto Press.
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The microbiology of safe food
Table 7.5 Probability of accepting (Pa%) a food lot; two‐class plan, c = 1 to 3.
Probability of acceptance (Pa%)
Actual percentage of defective samples
Number of samples
Value of c (n)
2
5
10
20
30
40
50
5
1
2
3
100
100
100
98
100
100
92
99
100
74
94
99
53
84
97
34
68
91
19
50
81
10
1
2
3
98
100
100
91
99
100
74
93
99
38
68
88
15
38
65
5
17
38
1
5
17
15
1
2
4
96
100
100
83
96
100
55
82
99
17
40
84
4
13
52
1
3
22
<0.5
<0.5
6
20
1
4
9
94
100
100
74
100
100
39
96
100
7
63
100
1
24
95
<0.5
5
76
<0.5
1
41
Source: Adapted from ICMSF (1986) and reprinted with permission from the University of Toronto Press.
of n = 5, c = 2 will mean that 10% defective lots will be accepted on most (99%) sampling occasions!
Even increasing the number of samples to 10 (n = 10, c = 2) means that 10% defective batches
will be accepted on 93% of occasions. Hence the need for the proactive approach of HACCP
for assured food safety (Chapter 9).
It is therefore apparent that no practical sampling plan can ensure the absence of the target
micro‐organism and the concentration of the target organism may be greater than the set limit
in parts of the food lot not sampled. The absence of a target organism in 5 randomly chosen
samples only gives 95% confidence that the food lot is <50% contaminated. If 30 samples had
been analysed, then the food lot is (with 95% confidence) contaminated at <10%. It requires
300 randomly taken samples giving the absence of the target micro‐organism at 95% confidence to indicate that the food lot is <1% contaminated. Therefore, no sampling plan can
guarantee the absence of a pathogen, unless every gram of the food was analysed leaving nothing for consumption.
7.7.4 Producer risk and consumer risk
It follows from the operating characteristic curve that it is possible that a ‘bad’ lot of food will
on occasions be accepted, and conversely a ‘good’ lot will be rejected. This is known as the
‘consumer’s risk’ and ‘producer’s risk’, respectively. The consumer’s risk is considered to be the
probability of accepting a lot whose actual microbial content is substandard as specified in the
plan, even though the microbiological analysis of the sample units conform to acceptance (Pa).
The producer’s risk is the converse; i.e. the producer rejects a batch of food due to unrepresentative poor microbiological results. It is expressed by ‘1 – Pa’ in Figure 7.6.
7.7.5 Stringency of two‐ and three‐class plans, setting n and c
The stringency of the two‐class sampling plan depends upon the values chosen for n and c.
Where n is the number of samples units analysed and c is the maximum acceptable number of
sample units that may exceed the value of m. Where m is the maximum number of relevant
Microbiological criteria
325
Table 7.6 Probability of accepting (Pa%) a food lot; three‐class plan.
Percentage marginal (Pm%)
Percentage defective (Pd%)
Number of samples (n) = 5
50
40
30
20
10
5
0
Number of samples (n) = 10
40
30
20
10
5
0
Value of c
10
20
30
50
3
2
1
3
2
1
3
2
1
3
2
1
3
2
1
3
2
1
3
2
1
3
3
2
8
8
6
17
16
14
33
32
29
59
58
53
77
77
70
100
99
92
3
2
1
7
6
4
16
14
9
32
29
21
58
55
41
77
72
55
99
94
74
2
1
<0.5
6
4
1
15
11
5
31
24
13
56
47
27
75
63
38
97
84
53
<0.5
<0.5
3
2
1
3
2
1
3
2
1
3
2
1
3
2
1
3
2
1
1
<0.5
<0.5
<0.5
2
1
<0.5
8
6
3
29
21
11
51
39
21
88
68
38
1
<0.5
<0.5
5
2
1
20
10
4
36
20
8
65
38
15
<0.5
<0.5
<0.5
3
1
1
20
8
2
17
5
5
3
2
2
10
9
7
34
32
24
59
55
43
99
93
74
2
<0.5
<0.5
7
2
2
20
9
2
43
23
7
60
35
12
81
50
19
70
90
<0.5
<0.5
<0.5
<0.5
4
1
<0.5
18
5
1
31
9
1
47
16
3
<0.5
<0.5
<0.5
8
2
<0.5
1
<0.5
1
<0.5
<0.5
<0.5
<0.5
<0.5
2
<0.5
<0.5
8
1
<0.5
2
<0.5
<0.5
<0.5
Source: Adapted from ICMSF (1986) and reprinted with permission of the University of Toronto Press.
bacteria/g. The lot is rejected if c is exceeded. If the number of sample units (n) is increased for
a given value for c, then the better in microbiological terms the food lot must be to have the
same chance of being passed. Conversely, for a given sample size n, if c is increased the sampling plan becomes more lenient as there is a higher probability of acceptance (Pa). This can be
seen in Figure 7.7a, where increasing c = 0 to 3 means the plan becomes more stringent, with
Probability of acceptance (Pa%)
100
80
60
40
20
0
0
20
40
60
80
100
Defective (%)
Figure 7.4 Operating characteristic curve for sample plan n = 5, c = 3.
Probability of acceptance (Pa%)
100
80
60
c=1
c=3
c=2
40
20
0
0
20
40
60
80
100
Defective (%)
(a)
100
Probability of acceptance (Pa%)
n = 5, c = 3
90
n = 5, c = 2
80
n = 5, c = 1
70
60
50
0
5
10
15
Defective (%)
20
25
30
(b)
Figure 7.5 (a) Operating characteristic curve for n = 5, c = 1 to 3. (b) Enlarged area of Figure 7.5a.
Probability of acceptance (Pa%)
Microbiological criteria
100
100
80
80
327
Producer risk
60
60
40
40
20
20
Consumer risk
0
0
10
20
30
60
40
50
Defective (%)
70
80
90
0
100
Figure 7.6 Producer risk/consumer risk curve.
less chance of accepting a defective lot. Whereas in Figure 7.7b, where the number of samples
is increased (n = 5–20) and c is fixed (c = 1) the plan becomes more stringent.
In a three‐class plan it is the values of n and c that determine the probability of acceptance,
Pa, for a food lot of given microbiological quality.
The microbiological quality is given by determining the percentage of ‘defective’
proportions:
Pd = % defective; above M;
Pm = % ‘marginally acceptable’; m to M;
Pa = % ‘acceptable’; equal to or less than m.
Since the three terms must equal 100%, then only the first two terms need to be determined.
Probability values for three‐class plans are given in Table 7.5.
Taking a lot of food in which 20% of the sample counts are marginally acceptable (Pm = 20%)
and 10% ‘defective’ (Pd = 10%), the effect of n and c can be compared in Table 7.6. For n = 5,
c = 3 the probability of acceptance (Pa) is 58% of occasions; if c is lowered to 1 then Pa decreases
to 41%. Whereas if n is increased to 10 (c = 3), then Pa is 29% of occasions. The most stringent
is n = 10, c = 3, where the Pa = 11% of occasions.
This level of acceptance (11 in 100) for lots in which 10% are defective and 20% are marginally acceptable reinforces the fact that microbiological hazards must be controlled in food
using the proactive HACCP approach rather than a retrospective end‐product testing
approach.
Therefore, the setting of n and c varies with the desired stringency (probability of rejection).
For stringent cases n is high and c is low; for lenient cases n is low and c is high. As n decreases
the chance of acceptance of bad lots increases.
7.7.6 Setting the values for m and M
The level of the target organism that is acceptable and attainable in the food is ‘m’. It can be set
from levels attained in GMP or, if the target organism is a pathogen, then m may be set at zero
for a given volume of sample (i.e. 25 g).
328
The microbiology of safe food
Probability of acceptance (Pa%)
100
80
c=3
60
c=2
c=1
40
c=0
20
0
0
10
20
30
Defective (%)
40
50
(a)
Probability of acceptance (Pa%)
100
80
n=5
60
c = 10
40
c = 20
20
0
0
5
10
15
Defective (%)
20
25
30
(b)
Figure 7.7 (a) Stringency of sampling plans, illustrated by n = 10, c = 0 to 3. (b) Stringency of sampling plans,
illustrated by n = 5 to 20, c = 1.
‘M’ is only used in three‐class plans as the hazardous or unacceptable level of contamination
caused by poor hygienic practice. There are three methods of setting the value of M:
1 As a utility (spoilage or shelf life) index where it relates to levels of bacteria causing detectable spoilage (odour, flavour) or to a decrease in shelf life to an unacceptable short period
(Section 3.2).
2 As a general hygiene indicator, relating to levels of an indicator organism reflecting an unacceptable condition of hygiene.
3 As a health hazard where it relates to infectious dose. This value can be set using epidemiological and laboratory data, and similar sources of information; see Table 4.1.
Therefore, the values of m and M are independent of each other and have no set relationship.
Microbiological criteria
329
7.8 Microbiological limits
7.8.1 Definitions
There are various terms used in reference to microbiological limits and these are defined as
follows:
• ‘Microbiological standards’ refers to compulsory microbiological levels laid down in
statute.
• ‘Microbiological guidelines’ refers to levels set out in guidance that does not have legal force.
• ‘Microbiological criteria’ may refer to either of the above or to levels in use by the food
industry.
• ‘Microbiological specifications’ are agreed within or between companies and generally have
no direct legal implications.
Thus specifications can be prepared for raw materials supplied to a food processor, of foods at
various stages of preparation and for final products. In the last case, the microbiological specifications may be those agreed as reasonable and attainable by the company or they may be standards imposed by or jointly agreed with an external agency. Specifications may include standards
for total numbers of micro‐organisms, food pathogens, indicator or spoilage organisms.
When compiling microbiological specifications for raw materials and final products it is
desirable to start with as wide a range of relevant test methods as is practicable so that comprehensive data on the background microbiology can be built up. These methods should give the
highest recovery of organisms and reproducible results. Ideally test samples should be
exchanged between laboratories and analysed by the agreed methods to ensure that similar
results are being obtained. Greater attention should be paid to raw materials and foods where
erratic or unexpected results are obtained. Specifications should reflect what is attainable
under GMP but should include tolerances to allow for sampling inaccuracies.
7.8.2 Limitations of microbiological testing
When intending to use microbiological criteria for testing food, a large number of problems
need to be considered:
1 Cost of analysis with regard to trained personnel, equipment and consumables.
2 Sampling problems, obtaining ‘representative’ samples is very difficult.
3 Accepting a food lot that contains unacceptable levels of micro‐organisms/toxins, simply
because of presence at low levels and heterogeneous distribution.
4 Variation in results, such as plate counts that have 95% confidence limits of ±0.5 log cycles
(see Table 6.1).
5 Destructive testing means that samples cannot be retested.
6 Time‐consuming due to need for prolonged incubation periods.
7 Sensitivity and robustness of detection methods.
7.8.3 Examples of sampling plans
Egg products
Eggs are perishable since they are highly nutritious and hence subject to microbiological
growth and spoilage. They are associated with certain foodborne pathogens most notably
Salmonella serovars. Despite pasteurisation processes (liquid egg: 64.4°C, 2.5 minutes or 60°C,
3.5 minutes), eggs and egg products may be contaminated due to insufficient heat treatment or
from post‐pasteurisation contamination. Salmonella cells can subsequently multiply to an
330
The microbiology of safe food
Table 7.7 Sampling plan for egg products.
Limit (g−1)
Target organism
Case
Plan class
n
c
m
M
Aerobic plate count
Coliforms
Salmonella serovars
(General population)
2
5
10
11
12
10
11
12
3
3
2
2
2
2
2
2
5
5
5
10
20
15
30
60
2
2
0
0
0
0
0
0
5 × 104
10
0
0
0
0
0
0
106
103
–
–
–
–
–
–
Salmonella serovars
(High‐risk population)
Source: Adapted from ICMSF (1986).
infectious dose due to temperature abuse after thawing or rehydration. Staphylococcus aureus
has been identified as a foodborne pathogen associated with pasta, where it can grow and
produce toxic levels of enterotoxins. Sampling plans for eggs and egg products are given in
Table 7.7.
Sampling plans for milk and milk products
Dairy products are highly nutritious, have a neutral pH and water activity conducive to the
growth of foodborne pathogens. Dairy products are divided into two groups:
1 The more perishable (‘fresh’) products such as milk, cream, flavoured milk and skimmed
milk drinks, fresh cheese (cottage cheese) and fermented milks.
2 The relatively stable products with extended shelf life under appropriate conditions of
storage, such as hard cheese, butter, dried milk products, ice cream mixes, evaporated
(canned) milk and sterilised or ultra‐high temperature (UHT) milk (for fluid consumption).
Microbiological criteria cannot be effectively applied to group 1, since the products will probably
have been consumed before the microbiological analysis has been completed. Milk products of
group 2 that are associated with microbiological hazards (i.e. dried milk and ripened cheese)
are usually microbiologically tested before distribution. Sampling plans proposed by ICMSF
(1986) are given in Table 7.8.
Table 7.8 Sampling plan for dairy products.
Limit (g−1)
Product
Target organism
Case
Plan
n
c
m
Dried milk
Aerobic plate count
Coliforms
Salmonella serovars
(Normal population)
2
5
10
11
12
10
11
12
8
3
3
2
2
2
2
2
2
2
5
5
5
10
20
15
30
60
5
2
1
0
0
0
0
0
0
0
3 × 104
10
0
0
0
0
0
0
104
Salmonella serovars
(High‐risk population)
Cheese ‘hard’ and semi‐soft types
Staphylococcus aureus
Source: Adapted from ICMSF (1986) and reprinted with permission of the University of Toronto Press.
M
3 × 105
102
–
–
–
–
–
–
–
Microbiological criteria
331
Processed meats
Processed meats include a range of meat products that have been processed by heat treatment,
curing, drying and fermenting. There are a number of microbiological hazards associated with
meat products. The ICMSF (1986) sampling plans are given in Table 7.9. The main target
organisms are St. aureus, Clostridium perfringens and Salmonella.
Cereals and cereal products
A range of bakery products are covered by this sampling plan; Table 7.10. Since the products are
often dry (low water activity), moulds and the persistence of bacterial spore‐formers is important.
Cook–chill and cook–freeze products
Guidelines from the Department of Health (UK) are given in Table 7.11. The guidelines target
five foodborne pathogens and the aerobic plate count as an indicator of microbial load.
Seafoods
The Food and Drug Administration and Environmental Protection Agency have given guidance levels for seafood microbiological hazards (Table 7.12).
Table 7.9 Sampling plan for processed meats.
Limit (g−1)
Product
Target organism
Case
Plan class
n
c
m
M
Dried blood, plasma
and gelatin
Staphylococcus aureus
Clostridium perfringens
Salmonella serovars
Salmonella serovars
8
8
11
12
3
3
2
2
5
5
10
20
1
1
0
0
102
102
0
0
104
104
–
–
Roast beef and pâté
Source: Adapted from ICMSF (1986) and reprinted with permission of the University of Toronto Press.
Table 7.10 Sampling plan for cereals and bakery products.
Limit (g−1)
Product
Target organism
Case Plan class n
c m
M
Cereals
Moulds
5
3
5
105
Soya flour, concentrates and isolates
Moulds
5
3
5
Salmonella serovars
10
Staphylococcus aureus 9
2
3
5
5
2 102–
104a
2 102–
104
0 0
1 102
12
8
2
3
20 0 0
5 1 102
–
104
10
8
2
3
5
5
0 0
1 103
–
104
8
10
3
2
5
5
1 102
0 0
104
–
Frozen bakery products (ready‐to‐eat) with low acid
or high aw fillings or toppings
Salmonella serovars
Frozen bakery products (to be cooked) with low acid St. aureus
or high aw fillings or toppings (e.g. meat pies, pizzas)
Salmonella serovars
Frozen entrées containing rice or cornflour as a main Bacillus cereus
ingredient
Frozen and dried products
St. aureus
Salmonella serovars
Source: Adapted from ICMSF (1986) and reprinted with permission of the University of Toronto Press.
a
The exact value will vary with the type of grain.
105
–
104
332
The microbiology of safe food
Table 7.11 Sampling plan for cook–chill and cook–freeze
foods at point of consumption.
Target organism
Limit
Aerobic plate count
Escherichia coli
Staphylococcus aureus
Clostridium perfringens
Salmonella serovars
Listeria monocytogenes
<105/g
<10/g
<100/g
<100/g
Absent in 25 g
Absent in 25 g
Source: Adapted from Department of Health (UK)
guidelines.
Table 7.12 Food and Drug Administration and Environmental Protection Agency guidelines for seafood
microbial hazards.
Product
Guideline/tolerance
Ready‐to‐eat fishery
products (minimal
cooking by consumer)
Ready‐to‐eat fishery
products (minimal
cooking by consumer)
All fish
All fish
Enterotoxigenic Escherichia coli (ETEC) – 1 × 103 ETEC/g, heat‐labile or
heat‐stable positive
Ready‐to‐eat fishery
products (minimal
cooking by consumer)
Ready‐to‐eat fishery
products (minimal
cooking by consumer)
Ready‐to‐eat fishery
products (minimal
cooking by consumer)
All fish
Clams and oysters,
and mussels fresh or
frozen – imports
Clams, oysters, and
mussels, fresh or
frozen ‐ domestic
Salt‐cured, air‐dried
uneviscerated fish
Tuna, mahi mahi and
related fish
Listeria monocytogenes – presence of organism
Salmonella species – presence of organism
Staphylococcus aureus – (1) positive for staphylococcal enterotoxin, or (2)
St. aureus level is ≥104/g(MPN)
Vibrio cholerae – presence of toxigenic 01 or non‐01
Vibrio parahaemolyticus – levels ≥1 × 104/g (Kanagawa positive or negative)
Vibrio vulnificus – presence of pathogenic organism
Clostridium botulinum – (1) Presence of viable spores or vegetative cells in
products that will support their growth, or (2) presence of toxin
Microbiological – (1) E. coli – MPN of 230/100 g (average of subs or three or
more of five subs); or (2) APC – 500 000/g (average of subs or three or more
of five subs)
Microbiological – (1) E. coli or faecal coliform – one or more of five subs
exceeding MPN of 330/100 g or two or more exceeding 230/100 g; or
(2) APC – one or more of five subs exceeding 1 500 000/g or two or more
exceeding 500 000/g
Not permitted in commerce (Note: small fish exemption)
Histamine – 500 ppm set based on toxicity, 50 ppm set as defect action
level, because histamine is generally not uniformly distributed in a
decomposed fish. Therefore, if 50 ppm is found in one section, there is the
possibility that other units may exceed 500 ppm
Microbiological criteria
333
7.9 Implemented microbiological criteria
7.9.1 Microbiological criteria in the European Union
Most countries in the European Union (EU) have implemented the Food Hygiene Directive
(93/43/EEC; Section 12.6) into national law, although most have restricted the implementation
to the first five principles of HACCP. There are differences in implementation within Europe;
for example, the Netherlands have a high emphasis on sampling programmes within inspections. Many businesses use microbiological criteria in contractual agreements with suppliers
and customers and as a means of monitoring the hygiene of the production environment.
These criteria are laid out in guidelines developed by individual companies of the relevant
industry sector, and are generally based on GMP. Under the EC Food Hygiene Directive, it is
possible to include microbiological guidelines in industry guides to GHP. The EU microbiological criteria have recently been revised.
The Food Hygiene Directive (93/34/EEC, p.4) provides:
Without prejudice to more specific Community rules, microbiological criteria and
temperature control criteria for certain classes of foodstuffs may be adopted in
accordance with the procedure laid down in Article 14 and after consulting the Scientific
Committee for Food set up by Decision 74/234/EEC.
7.9.2 EU Directives specifying microbiological standards for foods
Some microbiological criteria are standards that are specified in EC product‐specific food
hygiene Directives. Some of these ‘Vertical’ Directives make provision for them to be
introduced in the future, or, where standards have been set, there is scope for them to be
revised or added to. The EU may also lay down suitable laboratory methods. Such
Directives relate to food primarily during manufacturing, transport and wholesale storage, but not usually at retail or catering level (except where small producers sell direct to
the consumer).
Food safety in the EU is partially controlled through:
1 Vertical Directives, which deal with products of animal origin: fresh meat, poultry, milk,
fish, eggs. These apply at manufacture, storage and during transport.
2 Horizontal Directives, which apply safety measures to all foodstuffs not covered by the
Vertical Directives and when all foods enter the retail market.
See Section 12.6 for a fuller account of EU regulations.
7.10 UK guidelines for ready‐to‐eat foods
In the UK microbiological guidelines for ready‐to‐eat foods were first published by the former
Public Health Laboratory Service (PHLS), now Health Protection Agency (HPA) in 1992 and
revised in 1996, 2000 and 2009 (PHLS 1992, 1996, 2000; HPA 2009). They were collated to
assist in the implementation of the UK Food Safety Act 1990 (Section 30), which provides for
food examiners to examine samples of food submitted to them and issue certificates specifying
the results of their examination. The guidelines are for application during the shelf life of the
334
The microbiology of safe food
Table 7.13 Aerobic plate count categories for different types of ready‐to‐eat foods.
Food group
Product
Category
Meat
Beef burgers and pork pies
Poultry (unsliced)
Pâté, sliced meat (except ham and tongue)
Tripe and other offal
Salami and fermented meat products
Herring and other pickled fish
Crustaceans, seafood meals
Shellfish (cooked), smoked fish, taramasalata
Oysters (raw)
Mousse/dessert
Cakes, pastries, slices and desserts – without dairy cream
Trifle
Cakes, pastries, slices and desserts – with dairy cream
Cheesecake
Bhaji
Cheese‐based bakery products
Spring rolls, satay
Houmous, tzatziki and other dips
Fermented foods, bean curd
Vegetables and vegetable meals (cooked)
Fruits and vegetables (dried)
Prepared mixed salads
Fruits and vegetables (fresh)
Ice cream (dairy and non‐dairy)
Cheese, yogurt
1
2
3
4
5
1
3
4
5
1
2
3
4
5
1
2
3
4
5
2
3
4
5
2
5
2
3
4
Seafood
Dessert
Savoury
Vegetable
Dairy
Ready‐to‐eat meals
Sandwiches and filled rolls
Without salad
With salad
Source: Adapted from HPA (2009), with permission of the Health Protection Agency.
product and are not at point of production, nor are they mandatory UK Government standards. Foods are divided into five categories (Table 7.13) for the aerobic colony count analysis,
whereas the same criteria are used for all indicator organisms and foodborne pathogens.
Revisions to the guidelines after 2000 included new Enterobacteriaceae and Escherichia coli
criteria (Table 7.14).
Apart from setting proscriptive limits for certain pathogens, the guidelines recommend
ranges of bacterial counts for a number of different types of food that allow the division of
results into ‘satisfactory’, ‘borderline – limit of acceptability’, ‘unsatisfactory’ or ‘unacceptable/
potentially hazardous’. Although the guidelines have no formal status and refer only to ‘ready‐
to‐eat’ food, they do reflect the opinions of experienced workers with access to a wealth of
unpublished data collected over 60 years by the UK health agencies. They are applied to single
samples and therefore do not have the statistical validity of the ICMSF sampling plans. The
application of the guidelines for surveillance purposes has already been covered in
Section 13.1.8.
Microbiological criteria
335
Table 7.14 Guidelines for ready‐to‐eat foods.
Criterion
Food category (see Table 7.13)
Satisfactory
Acceptable
Unsatisfactory
Unacceptable/potentially
hazardous
<103
<104
<105
<106
—a
103–<104
104–<105
105–<106
106–<107
—a
≥104
≥105
≥106
≥107
—a
N/A
N/A
N/A
N/A
—
Aerobic plate count
(30°C; 48 ± 2 hours)
1
2
3
4
5
a
1–5
Indicator organisms
Escherichia coli (total)
Enterobacteriaceae
Listeria spp. (total)
Pathogens
Salmonella serovars
1–5
Campylobacter spp.
1–5
E. coli O157:H7 and
other VTEC
V. parahaemolyticus
– seafoods
Listeria monocytogenes
Staphylococcus aureus
Clostridium perfringens
Bacillus cereus and
Bacillus subtilis group
1–5
1–5
1–5
1–5
1–5
1–5
1–5
1–5
<20
<100
<20
20–<100
102–<104
20–<100a
100
>104
>100
N/A
N/A
N/A
Not detected
in 25 g
Not detected
in 25 g
Not detected
in 25 g
<20
Present in 25 g
20–<102
102–<103
≥103
<20
<20
<20
<103
20–<102
20–100
20–< 100
103–<104
N/A
100–<104
100–<104
104–<105
≥102
≥104
≥104
≥105
Present in 25 g
Present in 25 g
Source: Adapted from Anon (1996); adapted from HPA (2009), with permission of the Health Protection
Agency.
N/A denotes not applicable.
a
Guidelines for aerobic plate counts may not apply to certain fermented foods, for example salami, soft cheese
and unpasteurised yogurt. These foods fall into category 5. Acceptability is based on appearance, smell, texture
and the levels or absence of pathogens.
8 Hygienic production practices
8.1 Contribution of food handlers to foodborne illness
Food handlers are often associated with food poisoning outbreaks, with estimates of their
contribution ranging from 7% to 20% of outbreaks. Table 8.1 summarises the human carriage
of foodborne pathogens, which would include workers in the food industry. A large review of
816 foodborne disease outbreaks (from 1927 to the first quarter of 2006) implicating food
handlers included outbreaks caused by bacteria (Salmonella, Staphylococcus aureus, Shigella
and Streptococcus), viruses (norovirus, hepatitis A) and protozoal parasites (Cyclospora,
Giardia and Cryptosporidium) (Greig et al. 2007; Todd et al. 2007a, b). Multiple foods and
multi‐ingredient foods are identified most frequently with outbreaks involving food handlers,
probably due to the more frequent hand contact during preparation and serving. Within the
816 outbreaks, 11 involved >1000 people, and 4 >3000 people.
Amongst the most frequently reported factors associated with the involvement of the infected
workers in the large study above, were bare hand contact with the food, and inadequate hand
washing. Many workers were asymptomatic spreaders of intestinal pathogens and therefore not
aware of the risk they represented, or had infected family members. Guzewich and Ross (1999)
reported that hepatitis A virus (HAV) and noroviruses probably accounted for >60% of foodborne
outbreaks, and that infected food handlers were the most common source of contamination.
Infected food handlers may be:
• Symptomatic and shed viruses during periods of illness.
• Asymptomatic (including those recovered from illness) and continue to shed viruses. For
example, noroviruses may continue to be shed for at least 3 weeks after recovery.
• Spreading viruses through contact with sick people (such as sick child at home).
The stability of human enteric viruses means that they can persist in food longer than bacterial
contaminants, and they have low infectious doses (~1000 particles).
A HAV vaccine is available, however it has not been used for food handlers, instead personal
hygiene has been emphasised to prevent food contamination.
8.2 Personnel hygiene and training
All applicants seeking employment in the food industry, who are likely to come into direct or
indirect contact with foods, should be examined medically to ensure fitness for work. The examination should include answering a questionnaire recording the past medical history of the appliThe Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
337
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Table 8.1 Human carriage of foodborne pathogens.
Source
Pathogen
Data
Faeces
Salmonella serovars, Escherichia
coli, Shigella species
Norovirus, hepatitis A
Giardia lamblia
1 in 50 employees are highly infective
and shedding
109 pathogens/g faeces
Vomit
Norovirus
10 viral particles are infectious
Skin, nose, boils
and skin infections
Staphylococcus aureus
30–40% of the population are carriers,
there are 108 organisms per drop of pus
Throat and skin
Streptococcus Group A
105 Streptococcus pyogenes in a cough
cant, especially enteric infections, skin rashes, boils or discharges from the eyes, nose and ears
(indicative of St. aureus infection), and recent travel in regions where intestinal disorders are
prevalent or endemic. Stool sampling may be used to screen for carriers of enteric pathogens
such as Salmonella, although sometimes their excretion can be intermittent. Obviously medical
examination and questionnaires should be applied to other employees on a regular basis. No‐one
suffering from enteric infections should be allowed to work in the high‐risk areas of food processing. As a matter of routine, all cuts, sores and other skin abrasions must be covered with
approved waterproof dressings that are brightly coloured (often blue) and incorporate a metal
strip to aid detection if lost. It may not be practical to exclude carriers of St. aureus from food
production areas, given the high percentage of human carriage (~30–40%); therefore, minimising the spread of the organism by additional means is necessary including wearing gloves, and
adopting good personal hygiene – no picking or wiping of nose with (gloved) hand.
All employees should be trained in the basic principles of food and personal hygiene. This
should also include basic concepts of bacteriology, such as the ubiquitous nature of bacteria,
their methods of dissemination and their rapid growth under certain conditions – hence, their
role in food poisoning and food spoilage. Complementing this should be methods for cleaning
and disinfecting of equipment and contact surfaces, and personal hygiene.
In order for training to be effective it must be continuous, which can take the form of one‐
to‐one talks, discussion groups and refresher courses. Supporting material such as posters and
photos of good and bad practices in suitable locations, and changing them to avoid indifference, can provide a visual impact.
Staff should be trained as appropriate for their duties as given by the International
Commission on Microbiological Specifications for Foods (ICMSF 1988). Table 8.2 shows the
level of knowledge expected for line operators. To be effective, the management level in a food
business management should be familiar with Hazard Analysis and Critical Control Point
(HACCP) and its implementation. Management support of hygiene training programmes
could lead to increased productivity, and reduction in customer complaints, which can be
extremely costly (cf. Table 1.8).
There is a considerable amount of food safety training material available online. Some is
from independent sources, and others from governmental regulatory bodies (Table 8.3).
Food handlers, including seasonal workers, need to be educated specifically with regard to
microbial hazards and personal hygiene. Most problems with foodborne viruses are due to
contamination of food products that require manual handling and receive minimal processing
(i.e. shellfish and salads). It has been recommended that food processing managers exclude
Hygienic production practices
339
Table 8.2 Level of knowledge expected for line operators (ICMSF 1988).
The major sources of micro‐organisms in the product for which they are responsible
The role of micro‐organisms in disease and food spoilage
Why good personal hygiene is required
The importance of reporting illness, lesions and cuts to supervisory personnel
The nature of the control required at their point in the process
The proper procedures and frequency for cleaning equipment for which they are responsible
The procedures necessary to report deviations from control specification
The characteristics of normal and abnormal product at their given step in the process (e.g. colour, texture,
package integrity, odour)
The importance of maintaining proper records
How to monitor Critical Control Points for operations within their responsibility
Table 8.3 Online food safety sites.
Name
URL
Comment
Five keys to safer food
www.who.int./foodsafety/
consumer/5keys/en/index.html
WHO global food hygiene
message
Gateway to Government
food safety information
www.foodsafety.gov
Gives access to a wide range of
US and other governments food
safety information sources
Food Safety Information
Center (USDA)
www.foodsafety.nal.usda.gov
Provides food safety information
for the general public, as well as
industry, researchers and those
in education
Foodlink
www.foodlink.org.uk
Contains a wide range of topics,
and organises National Food
Safety week (UK)
Eat well, be well
www.eatwell.gov.uk/keepingfoodsafe
Run by UK Food Standards
Agency
Food safety web
www.foodsafetyweb.info/resources/
NonEnglish.php
Food safety resources for non‐
English speakers
symptomatic food handlers from high‐risk areas until 48 hours after recovery (Cowden et al.
1995). However, this is more applicable to bacterial than viral pathogens.
It is evident that the causes of gastroenteritis vary with age (Figure 1.2). Noroviruses and
rotaviruses probably cause the majority of gastroenteritis in children under 4 years, whereas
Campylobacter species and Salmonella serovars are the major cause of gastroenteritis in other
age groups. Figure 1.3 indicates that males suffer from gastroenteritis more than females,
except for the age group >74 year, probably because of the lower ratio of men to women in this
age group. A possible reason for part of this difference is that fewer men than women wash
their hands after using the lavatory: 33% compared with 60%, taking an average of 47 seconds,
compared with 79 seconds.
More than 1000 HAV particles (9.2% transfer rate) can easily be transferred from faecally
contaminated fingers to foods and surfaces (Bidawid et al. 2000). Since the virus is likely to
survive and remain infectious after any food processing steps, it is important to emphasise the
need to implement good hygienic practice (GHP), good manufacturing practice (GMP) and
HACCP to prevent initial contamination.
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The microbial flora of the hand is composed of the resident flora, and transients. In the case
of food equipment contact surfaces, it is possible to reduce the numbers of contaminating
micro‐organisms such that any remaining organisms will not undermine the quality of the
processed food. Unfortunately, it is not possible to disinfect the skin to the same degree and
therefore bare hands are a potential means of transferring micro‐organisms. Such distribution
may involve the transfer of organisms from hands to food or their transfer from food to food
via the hands. Special care must therefore be taken to ensure that these transmission routes are
minimised.
Washing one’s hands with soap and water principally removes the transient skin flora, which
are mainly bacteria, from the skin surface. Therefore, the numbers of enteric pathogens,
including Escherichia coli and Salmonella, which can pass through toilet paper on to the hands
should be greatly reduced by thorough hand washing.
However, it is virtually impossible to remove the indigenous resident flora on the hands
even when using bactericidal soaps and creams. This resident flora is a particular problem
with employees who are carriers of St. aureus in their nasal passages. Many of these employees
will also carry the organism on their hands as part of the established flora. Since it is impractical to prohibit ~30–40% (the likely St. aureus carrier rate) of employees from contact with
foods, other means of restricting the dissemination of St. aureus must be adopted.
Personnel must be encouraged to develop an attitude where hand washing becomes a virtually automatic response to certain situations. Thus, hands, fingernails and wrists should be
thoroughly washed: (i) before starting work, (ii) before and after lunch and tea breaks, (iii)
after using the toilet, (iv) when leaving or returning to the processing area for any other reason,
(v) when changing jobs within the process area and (vi) when the hands become unexpectedly
soiled or contaminated in any way, such as after handling equipment or food that may be of a
substandard quality. See Table 8.1 for details of pathogens carried by food handlers.
8.3 Cleaning
Having an effective cleaning and disinfection programme is a crucial step in hygienic food
production. The main purpose is to reduce the number of pathogens in the environment and
hence reduce potential food contamination. Subsequently the efficiency of cleaning and
disinfection regimes greatly affects final product quality and is essential in food production.
However, the most effective sanitation programme cannot make up for poorly designed
equipment and factory design. The terminology used in cleaning and disinfection technology
is given in Table 8.4.
Cleaning must be performed at regular and frequent intervals, even continuously, so that a
consistently good product quality is maintained. How this cleaning is done depends principally on:
1 the nature of the soil or contamination to be removed;
2 the type of surface to be cleaned;
3 the materials used for cleaning;
4 the degree of water hardness;
5 the standard of cleanliness required.
Cleaning must be the first step to remove organic material that would otherwise protect the
pathogens from disinfection. The basic steps are:
• Dry cleaning to remove gross soil or organic material.
• Wet cleaning with detergent to remove any residual material. This involves soaking, washing,
rinsing and drying.
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Table 8.4 Definitions used concerning detergents and disinfectants.
Term
Definition
Bactericide
A chemical agent that, under defined conditions, is capable of killing vegetative forms of
bacteria but not necessarily bacterial spores
Bacteriostat
A chemical agent that, under defined conditions, is capable of preventing the growth of bacteria
Clean surface
One that is free from soil of whatever form and is odourless. Thus, it is one from which food
debris, detergents and disinfectants have been removed. It will not contaminate foods in
contact with it and has residual numbers of micro‐organisms, if any, that could not undermine
product quality during subsequent production. A clean surface is not necessarily sterile
Cleaning
Covers those processes concerned with the removal of soil from surfaces but not those
concerned with sterilisation
Detergent
A substance that assists in cleaning when added to water
Disinfectant
Originally defined in medical terms as a chemical agent that destroys disease‐producing
organisms; now more correctly defined as an agent capable of destroying a very wide
range of micro‐organisms but not necessarily bacterial spores
Disinfection
Covers those processes concerned with the destruction of most micro‐organisms, but not
necessarily bacterial spores, on surfaces and in equipment. Any viable micro‐organisms
remaining are not capable of affecting the microbiological quality of foods coming into
contact with the disinfected parts
Fungicide
A chemical agent that, under defined conditions, is capable of killing fungi including their spores
Sanitation
An all‐embracing term covering those factors that assist in improving the general
cleanliness of the environment and the preservation of health
Sanitiser
A substance that reduces the numbers of micro‐organisms to an acceptable level
(NB this term is widely used in the USA and is virtually synonymous with the popular
use of the term ‘disinfectant’)
Sanitising
See ‘disinfection’
Soil
Any unwanted food residue, organic or inorganic matter remaining on equipment and
other surfaces
Sterilisation
The process of destroying all forms of life, including microbial life
Steriliser
A chemical agent capable of destroying all forms of life
The final step is the disinfection process, which requires disinfectants to reduce or kill the
remaining pathogens, the rinsing off of these agents followed by drying. Since pathogens vary
in their sensitivity to disinfectants, it is important to have prior knowledge of the pathogens
that may be present.
The type of soil to be removed varies according to the composition of the food and the
nature of the process to which the food has been subjected. However, the food constituents
themselves vary tremendously in terms of their cleanability (Tables 8.5 and 8.6), so a wide
choice of cleaning materials must be available for their removal. Food residues may be dry
particulate, dried‐on, cooked‐on, sticky, fatty or slimy. Such residues may be best removed by
physical means or by the use of hot or cold water almost invariably supplemented with detergents of one type or another. The length of time a food residue is left undisturbed also affects
the ease of cleaning. For example, fresh raw milk can be readily washed away but if it is allowed
to dry greater difficulty will be experienced. This is due to the denaturation of the milk protein
and the breakdown of the fat emulsion, which results in the fat spreading over other milk
particles making them more difficult to remove.
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Table 8.5 Factors that influence the effectiveness of disinfectants.
Factors affecting
disinfectants
Organic matter
Low temperature
pH needed for maximum
effectiveness
Residual effects
Interaction with soaps
Aldehyde
Chlorine‐releasing
agent
Iodophor
Quaternary ammonium
compound
Phenols and
bisphenols
Inhibits
effectiveness
Inhibits
effectiveness
Alkaline
Inhibits
effectiveness
Slightly inhibits
effectiveness
Acid
Some inhibition
of effectiveness
Slightly inhibits
effectiveness
Acid
Inhibits effectiveness
Inhibits effectiveness
Slightly inhibits
effectiveness
Inhibits effectiveness
Acid
Alkaline or acid
Slightly inhibits
effectiveness
Acid
Yes
Compatible
No
Not compatible
Yes
Compatible
No
Not compatible
Yes
Compatible
No
Compatible
Peroxygen
Inhibits effectiveness
Table 8.6 Effectiveness of various disinfectants on microbial pathogens.
Pathogen
Chlorhexidine
Chlorine‐releasing
agent
Iodophor
Phenol and
bisphenols
Single ammonium
compound
Quaternary ammonium
compound
Campylobacter jejuni
Salmonella serovars
Escherichia coli
Clostridium perfringens
Staphylococcus aureus
Aspergillus flavus
Adenovirus
+
+++
+++
−
−
+
−
+++
+++
+++
++
+++
+++
+++
+++
+++
+++
++
+++
+++
+++
+++
+++
+++
−
+++
++
−
+
+
+
−
+++
+/−
−
+++
+++
+++
−
+++
+++
+++
Hygienic production practices
343
The preliminary cleaning of smaller items of equipment may involve presoaking in warm
(~45°C) or cold water to remove loosely adhering debris, followed by non‐abrasive brushing.
Steel wool and wire brushes should not be used since not only do they damage many surfaces,
including stainless steel, but metal particles may pass into foods and be a cause of customer
complaints (cf. HACCP Section 9.5). Any cleaning aid causing damage to stainless steel and
other food contact surfaces should be avoided since crevices can retain bacteria, which will
persist despite regular cleaning regimes (Holah and Thorpe 1990; cf. Section 8.5).
8.4 Detergents and disinfectants
Detergents must be capable of removing many different types of soil under a variety of conditions.
They are not expected to possess bactericidal properties. However, during cleaning, detergents
do physically remove a large number of bacteria. To achieve the above characteristics, various
chemicals are blended to produce the correct traits for a particular application.
Detergents can be classified as:
1 Inorganic alkalis – caustic and non‐caustic.
2 Inorganic and organic acids.
3 Surface active agents – anionic, non‐ionic, cationic and amphoteric.
4 Sequestering agents – inorganic and organic.
Disinfectants for use on food contact surfaces should rapidly kill both Gram‐positive and
Gram‐negative bacteria. The majority of mould spores should be killed and it would be advantageous if bacterial spores were inactivated as well. Disinfectants should be stable in the presence
of organic residues and hard water salts. They should also be:
• Non‐corrosive and non‐staining to plant surfaces of whatever type.
• Odourless or have an inoffensive odour.
• Non‐toxic and non‐irritating to the skin and eyes.
• Readily soluble in water and readily rinseable.
• Stable during prolonged storage in concentrated form and stable during short‐term storage
in dilute form.
• Competitively priced and cost‐effective in use.
Disinfectants used in the food industry are generally restricted to four groups:
1 Chlorine‐releasing agents, i.e. sodium hypochlorite, chlorine dioxide, sodium dichloroisocyanurate and chloramines‐T.
2 Quaternary ammonium compounds.
3 Iodophors, i.e. povidone-iodine and poloxamer-iodine.
4 Amphoteric compounds.
Disinfectants are effective against bacteria, viruses and fungi, but were not designed to be
effective against parasites (Table 8.6). In general, the descending order of sensitivity is:
lipid‐enveloped viruses, Gram‐negative bacteria, non‐enveloped viruses, fungi, Gram‐positive
bacteria and finally bacterial spores.
8.5 Microbial biofilms
8.5.1 Microbial biofilm formation
In nature and food systems, micro‐organisms attach to surfaces, grow into micro‐colonies and
produce biofilms (Kumar and Anand 1998; Stickler 1999). A surface is conditioned first by the
adsorption of organic molecules before bacterial colonisation. Rough surfaces provide areas for
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The microbiology of safe food
colonisation as they protect the bacteria from shear forces. The resulting build‐up of micro‐organisms
is called a ‘biofilm’. As well as the aspect of bacterial contamination of food, biofilm formation is
also an engineering and maintenance issue as it can also impair heat transfer and contribute to
metal corrosion. When biofilms are a nuisance the term ‘biofouling’ or ‘fouling’ is used.
Foodborne pathogens use a range of strategies to survive and persist in the environment and
this includes food production factories, including biofilm formation. The formation of
biofilms and subsequent encasement of the bacterial cells in a complex matrix can enhance
their resistance to antimicrobials and sterilising agents, making them difficult to eradicate and
control. Bacterial biofilms in food‐producing facilities can act as a source of food product
contamination both with respect to food spoilage and foodborne infections.
Biofilm formation is dependent upon several factors including expression of extracellular
matrix (ECM) components such as curli fimbriae and/or cellulose, temperature, hydrophobicity,
surface charge, surface structures and material properties. Biofilms are composed of viable and
non‐viable micro‐organisms that become embedded together and to the surface by ECM. The
ECM is primarily composed of polysaccharides (i.e. cellulose) as well as other microbial‐
derived compounds: proteins (curli fimbriae), phospholipids, teichoic and nucleic acids. The
ECM protects the microbes within the biofilm from biocides and desiccation and will also contribute to the persistence of micro‐organisms within the biofilm.
Microbial cells embedded in ECM are phenotypically different from when they are growing
in suspension (‘planktonic’). One major difference is the increased resistance (orders of
10–100‐fold) to antimicrobial agents (Le Chevallier et al. 1988; Holmes and Evans 1989;
Krysinski et al. 1992). A biofilm can less attractively be called ‘slime’ due to the build‐up of
ECM. Food can become contaminated with undesirable spoilage and pathogenic bacteria
from sloughed portions of biofilms. Hence biofilm formation leads to serious hygiene
problems and economic losses due to food spoilage and the persistence of food pathogens. The
major role proposed for the glycocalyx is that it protects attached bacteria from antibacterial
agents. In the dairy industry, milk lines and gaskets can be colonised and are therefore a potential
source of product contamination. Moulds may grow on the walls and ceilings of high‐humidity
food preparation areas and subsequently may infect the product. Many potentially pathogenic
species have been isolated from biofilms associated with food preparation surfaces, including
St. aureus and Listeria monocytogenes. Attached cells may not only exhibit the increased resistance to biocides expected from biofilm‐associated organisms but also an increased resistance
to heat treatment (Oh and Marshall 1995).
Biofilms form on any submerged surface where bacteria are present. They form in a sequence
of events (Figure 8.1).
1 Nutrients from the food are adsorbed to the surface to form a conditioning film. This leads
to a higher concentration of nutrients compared with the fluid phase and favours biofilm
formation. The conditioning also affects the physico‐chemical properties of the surface, i.e.
surface free energy, changes in hydrophobicity and electrostatic charges that influence the
microbial colonisation.
2 Micro‐organisms attach to the conditioned surface. The adhesion of bacteria is initially
reversible (van der Waals attraction forces, electrostatic forces and hydrophobic interactions) and subsequently irreversible (dipole–dipole interactions, hydrogen, ionic and covalent bonding and hydrophobic interactions). The bacterial appendages flagella, fimbriae
and exopolysaccharide fibrils (also known as glycocalyx, slime or capsule) are involved in
contact with the conditioning film. The exopolysaccharide is important in cell–cell and
cell–surface adhesion and also protects the cells from dehydration.
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345
Conditioning film of food residues on work surface
Food residues (nutrient source)
Work surface
Micro-organisms attached to conditioned surface
Micro-organisms divide and form micro-colonies. Polysaccharide formation stabilises the biofilm.
Secreted polysaccharide layer
Fragments of biofilm shed periodically
Clump of micro-organisms sloughed from biofilm
into food product
Figure 8.1 Biofilm formation. (a) Conditioning film of food residues on work surface. (b) Micro‐organisms
attached to conditioned surface. (c) Micro‐organisms divide and form micro‐colonies. Polysaccharide formation
stabilises the biofilm. (d) Fragments of biofilm shed periodically.
3 The irreversibly attached bacteria grow and divide to form micro‐colonies that enlarge and
subsequently coalesce to form a layer of cells covering the surface. During this phase the
cells produce more additional polymer, which increases the cells’ anchorage and stabilises
the colony from fluctuations of the environment.
4 The continuous attachment and growth of bacterial cells, and exopolysaccharide formation,
lead to the biofilm formation. The biofilm layer may be several millimetres thick within a
few days.
5 As the biofilm ages, sloughing occurs whereby detachment of relatively large particles of
biomass from the biofilm occurs. The sloughed bacteria can either contaminate the food
(note the subsequent non‐homogeneous presence of bacteria in food) or initiate a new
biofilm further along the production line.
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The microbiology of safe food
8.5.2 Bacterial biofilm induction
When bacterial cells form biofilms there are major changes in gene expression. These are
under the control of a global gene regulation system known as quorum‐sensing that responds
to fluctuations in population density. Essentially specific signalling molecules are produced by
individual cells that govern community behaviour. As the population density increases the
concentration of the signal compound will also increase until it passes a threshold. When this
happens, the quorum‐sensing system is activated with the subsequent expression of quorum‐
sensing‐related genes. These include the expression of genes regulating essential cell processes,
virulence factors and biofilm formation.
There are three main types of quorum‐sensing that are classified according to the signalling
molecules. First, the acyl homoserine lactone (AHL) or autoinducer‐I (AI‐I) system, which is
found in Gram‐negative bacteria. Second, the peptide‐mediated quorum‐sensing system
found in Gram‐positive bacteria. Third, the autoinducer‐2 (AI‐2) system, which is found in
both Gram‐negative and Gram‐positive bacteria. Many organisms in competing conditions
produce quorum‐quenching compounds. These may degrade or otherwise inactivate quorum‐sensing compounds. For example, lactonases, acylases and deaminases degrade the
homoserine lactone ring of AHL.
Within biofilms there is the opportunity for genetic exchange (prophages, etc.), and the
selection of resistance traits against cleaning agents such as heavy metals and quaternary
ammonium compounds. This can also lead to co‐resistance to antibiotics (Section 1.12.2).
Food production facilities are often colonised by a resident flora, which is potentially more
resistant to the cleaning agents used in that factory. Therefore, frequently encountered organisms within the factory as well as quality control strains should be used to test the efficacy of
the cleaning agents.
8.5.3 Biofilm removal and control
Equipment design and plant layout are important aspects of prevention and control strategies.
Obviously good design of equipment such as tanks, pipelines and joints is best to assist in the
cleanability of the production line. The microtopography of a surface can complicate cleaning
procedures when crevices and other surface imperfections shield attached cells from the rigours of cleaning. Stainless steel resists impact damage but is vulnerable to corrosion, while
rubber surfaces are prone to deterioration and may develop surface cracks where bacteria can
accumulate (Le Clercq‐Perlat and Lalande 1994).
Generally, an effective cleaning and sanitation programme will inhibit biofilm formation. Mechanical treatment and chemical breakage of the polysaccharide matrix are very
necessary for removal of biofilms. As can be seen in Figure 8.2, the adhered bacteria are
covered with organic material (polysaccharide and food residues), which may inhibit the
penetration of the disinfectant due to its lack of wetting properties. Therefore, a detergent
activity is required to remove this outer layer prior to disinfection. The dead microbial
biomass must be removed otherwise it may act as a conditioning film and nutrient source
for further biofilm formation. New cleaning agents and enzyme treatments are being formulated for the effective removal of biofilms.
As previously stated, biofilms are problematic in the food industry. They are difficult to
remove due to the combined issues of ECM recalcitrance, and difficulties of cleaning complex
processing equipment and production facilities. Therefore, biofilm control requires both the
implementation of effective cleaning and sanitising procedures, along with well‐designed processing equipment and the food processing environment, which are amenable to routine and
Hygienic production practices
347
Mature biofilm
Detergent removal of surface (polysaccharide, food residues, etc.) material
Disinfectant killing of micro-organisms
Rinse to remove dead microbial cells which otherwise could act as a nutrient source for a fresh biofilm
Figure 8.2 Biofilm removal. (a) Mature biofilm. (b) Detergent removal of surface (polysaccharide, food
residues, etc.) material. (c) Disinfectant killing of micro‐organisms. (d) Rinse to remove dead microbial cells that
otherwise could act as a nutrient source for fresh biofilm.
thorough cleaning. For rapid evaluation, ATP bioluminescence (Section 6.4.3) can be used to
evaluate the effectiveness of cleaning regimes.
There are many problems associated with achieving efficient cleaning. These include: (i) the
faulty design and incorrect siting of food processing equipment; (ii) recontamination of
equipment that has been previously cleaned; (iii) inadequate time for cleaning or cleaning too
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The microbiology of safe food
infrequently; (iv) inadequate labour employed; (v) misuse of cleaning and disinfecting agents
by gross variation from the recommended concentrations; and (vi) lack of commitment by
management and operatives.
Additional problems may be encountered if the factory hygiene officer does not enforce the
recommended procedures, and also if cleaning supervisors or operatives are absent and
nobody is detailed to replace them. These problems are exacerbated in the food industry where
there is a high turnover of labour resulting in new employees being given insufficient
training.
With regard to the cleaning methods themselves, these are sometimes altered without full
recognition of the possible long‐term detrimental effects that the change may have on the
physical state of the equipment or on the efficacy of action on the residual soils or micro‐
organisms. Promotion material for cleaning agents may well represent results that were
obtained under ideal test conditions, but are very different from the environment in which the
product is to be used commercially. It is important, therefore, to always test the cleaning or
disinfecting agent under typical commercial conditions before introducing it on a large scale
in the factory. This should include frequently encountered organisms of the resident flora.
Furthermore, since there could be a build‐up of resistant organisms over time, it should never
be assumed that cleaning or disinfecting methods are effective because they always have been
in the past. Checks should be made occasionally to confirm their continued reliability.
Finally, mechanical cleaning aids may break down and have to await repairs. When this happens it puts additional pressure on the remaining working equipment, which is, in turn, more
liable to fail. Repairs may in consequence be hurried or inadequate and the whole cleaning
programme may be jeopardised. This situation is often associated with a reluctance of senior
management to spend sufficient money on cleaning aids.
Advances in biofilm control include investigating strategies involve the use of bacteriophages, bacteriocins and quorum‐sensing inhibitors (Coughlan et al. 2016). Bacteriophage are
able to penetrate the matrix of a mature biofilm and lyse the otherwise protected target bacterium, lytic phage being more appropriate than lysogenic phage. Such phage control is permitted in the States, but does not have qualified presumption of safety (QPS) (European
Union) approval. Bacteriocins, such as those produced by the lactic acid bacteria can also be
used to disrupt biofilms. For example, nisin is active against L. monocytogenes.
8.6 Assessment of cleaning and disinfection efficiency
The efficiency of process line sanitation can be checked by visual inspection or by using microbiological techniques. Visual inspection is a simple but crude method that cannot determine
the microbiological cleanliness achieved. Much depends on the care taken by the inspector.
With experience the inspector may know where to look for signs of inadequate cleaning but
residual soils do vary in their visual detectability (e.g. some soils are not visible if there is a film
of water on the cleaned surface) and high‐intensity lighting must be directed on surfaces during inspection. In spite of these shortcomings visual inspections are worthwhile provided they
are performed assiduously. They can be carried out during or immediately after cleaning or
even shortly before the start of the next production run. Inspections should be performed
randomly so that employees involved in cleaning are unaware when they are due. A checklist
of various items of equipment should be prepared and items, once cleaned and inspected, can
be given a cleanliness rating that can be compared with earlier data. All the findings should be
recorded in an inspection report. Additionally, records of the cleaning materials, dilutions and
Hygienic production practices
349
application times used should be kept where applicable. If equipment has not been adequately
cleaned there should be time available for corrective action before processing is restarted; particular care should be taken with the subsequent inspection of equipment given low cleanliness
ratings.
The most commonly used surface cleaning assessment tests are by ATP bioluminescence,
protein detection, as well as microbiological culturing, and these have been discussed in
Chapter 6. The ATP bioluminescence and protein tests determine the general hygienic status
since they are not specific for microbial material, but will detect residual food material as well
(see Sections 6.4.3 and 6.4.4). Microbiological culturing typically involves estimations from
surface areas of the total numbers of viable bacteria, indicator organisms (i.e. Enterobacteriaceae,
E. coli, etc.) and, where warranted, specific food spoilage, or food poisoning bacteria (i.e.
Listeria). In general, however, estimations are limited to ‘total numbers’ as this is the most
sensitive guide to microbial hygienic status. The bacteria are removed from surfaces by means
of sterile swabs, by rinsing with a known volume of sterile diluent or by the agar contact
method. Because micro‐organisms are often unevenly distributed on equipment surfaces, as
large an area as possible, but including less accessible points such as drains, should be sampled.
For this reason, swabbing methods have found particular favour. The inherent problem with
standard microbiological methods is that test results are normally unavailable until after a
48‐hour period due to the need for incubation of the test samples. Hence the ATP bioluminescence and protein techniques have become test methods in the food industry as the results are
obtained rapidly and the equipment has become more portable and simple to use. The ATP
bioluminescence results can be collated, and trend analysis applied to determine if the level of
hygiene fluctuates during the week according to operatives, etc.
The processed food may also be used to check cleaning efficiency. Foods first in contact
with cleaned surfaces are most liable to pick up residual bacteria so that higher than expected
counts on such foods may be indicative of inadequate cleaning. This principle is often used to
monitor cleaning where liquid foods are being produced. Here samples are taken at regular
intervals early in a production run and if there is a gradual reduction in the bacterial count
from the first sample onwards, rather than a fairly constant set of results, cleaning has been
inadequate as the liquid is flushing out the residual bacteria.
In conclusion it is pertinent to stress that when monitoring techniques show up areas where
cleaning proves to be troublesome, it is vitally important to concentrate efforts in those areas
and not to accept evidence of inefficient cleaning complacently.
9 Food safety management tools
9.1 The manufacture of hygienic food
Is there a way forward for the manufacture of food that is nutritious and appetising, yet meets
the expectations of the consumer with regard to risk? A difficulty that arises in manufacturing
‘safe’ food is that the consumer is a mixed population with varying degrees of susceptibility and
general lifestyle. Additionally food with ‘high’ levels of preservatives to reduce microbial
growth is undesirable to the consumer and is perceived as ‘overprocessed’ with ‘chemical additives’. The consumer pressure is for greater varieties of fresh and minimally processed foods,
natural preservatives with a guarantee of absolute safety.
The manufacture of safe food is the responsibility of everyone in the food chain, and food
factory, from the operative on the conveyor belt to the higher management. It is not the sole
responsibility of the food microbiologist. Nevertheless the food microbiologist in industry will
need to not only know which food pathogens are likely to occur in the ingredients, but also the
effect of the food matrix and processing steps on cell survival in order to best advise on the
most appropriate manufacturing regimes.
The production of safe food requires:
• Control at source.
• Product design and process control.
• Good hygienic practice (GHP) during production, processing, handling, and distribution,
storage, sale, preparation and use.
• A preventative approach because effectiveness of microbial end‐product testing is limited.
Taken from CAC ALINORM 97/13 (Codex Alimentarius Commission 1995).
An initial means of improving food safety is to prevent contamination of the raw materials
in the first place. This has already been referred to with regard to water contamination by
hepatitis A virus (HAV) and protozoal parasites (Sections 5.1 and 5.3). However, preventing
microbial contamination is not always possible as microbes are part of our ecosystem. Soil
contains bacteria, viruses and protozoa. Plants have microflora and microbes are part of the
normal skin and intestinal flora of animals and fish. Many pathogens survive in the environment for long periods of time (Table 9.1) and can be transmitted to humans by a variety of
routes (Figure 9.1). Inadequate temperature control during food production and preparation
can increase the level of microbial pathogens and spoilage organisms prior to consumption.
The Microbiology of Safe Food, Third Edition. Stephen J. Forsythe.
© 2020 John Wiley & Sons Ltd. Published 2020 by John Wiley & Sons Ltd.
351
352
The microbiology of safe food
Table 9.1 Survival of pathogenic micro‐organisms.
Organism
Conditions
Survival
Coliforms
Mycobacterium tuberculosis
Soil
Soil
Soil
30 days
Up to 2 years
5–15 months
Radish
3 months
Salmonella spp.
Soil
Potatoes at soil surface
Vegetables
Beet leaves
Carrots
Cabbage/gooseberries
Apple juice, pH 3.68
Apple juice pH <3.4
72 weeks
40 days
7–40 days
21 days
10 days
5 days
>30 days and multiplies
2 days
Salmonella Typhimurium
Soil
Vegetables/fruit
30 days
1–69 days
Water
7–30 days
Shigella spp.
Tomatoes
2–7 days
Vibrio cholerae
Spinach, lettuce, non‐acid vegetables
2 days
Enterovirus group (polio, echo, coxsackie)
Soil
Cucumber, tomato, lettuce, at
6–10°C
Radish
150–170 days
>15 days
>2 months
Water
Sewage
Crops
Soil
Animals
Silage, feed
Faeces
Meat
Humans
Figure 9.1 Routes of enteric pathogen transmission to humans.
Food safety management tools
353
Traditional ways to control microbial spoilage and safety hazards in foods include freezing,
blanching, pasteurisation, sterilisation, canning, curing, syruping and the inclusion of preservatives.
Food additives such as preservatives are required to ensure that processed food remains safe and
unspoiled during its shelf life. A range of preservatives are used in food manufacture including
traditional foods. Many preservatives are effective under low pH conditions: benzoic acid (<pH 4.0),
propionic acid (<pH 5.0), sorbic acid (<pH 6.5) and sulphites (<pH 4.5). The parabens (benzoic acid
esters) are more effective in neutral pH conditions. For concise reference values on pH limits of
microbial growth the reader is directed to International Commission on Microbiological
Specific