Proteomics in Analysis of Bacterial Pathogens
Tina Guina
University of Washington, Seattle
Outline
Postgenomic studies of Pseudomonas in context of
lung infection in patients with cystic fibrosis
Study of bacterial posttranslational regulation by
monitoring changes in protein subcellular localization
Pseudomonas aeruginosa and Cystic Fibrosis
Gram-negative environmental bacterium (soil, water)
Invades plants, animals; causes disease in immunocompromised
humans and chronic lung disease in cystic fibrosis patients
Cystic fibrosis (CF): most common genetic disease in Caucasians
caused by a mutation in chloride channel CFTR
Chronic Pseudomonas lung infection is a major cause of morbidity in
CF patients
Bacteria persist and multiply in lung (up to 109 cfu/g of sputum)
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Environmental P. aeruginosa
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Environmental P. aeruginosa
CFTR-
Unknown
Innate
immune
defect
PA colonization - ASYMPTOMATIC
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Environmental P. aeruginosa
CFTR-
Unknown
Innate
immune
defect
Bacterial
Adaptation
Innate Immune Selective Pressure
PA colonization - ASYMPTOMATIC
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Environmental Pseudomonas
CFTR-
Unknown
Innate
immune
defect
Bacterial
Adaptation
Increased
airway
inflammation
Unique surface
modifications
Resistance to
antimicrobials
Chronic
Lung
Disease
Innate Immune Selective Pressure
PA colonization - ASYMPTOMATIC
Increased bacterial burden - SYMPTOMATIC
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Bacterial
Adaptation
Chronic
Lung
Disease
?
PA colonization - ASYMPTOMATIC
Increased bacterial burden - SYMPTOMATIC
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Intervention
Bacterial
Adaptation
Chronic
Lung
Disease
?
PA colonization - ASYMPTOMATIC
Increased bacterial burden - SYMPTOMATIC
Questions:
Can we characterize stages of bacterial adaptation to the lung ?
Can we use characteristics of these stages to develop assays
to predict CF patients’ clinical outcome ?
Can drugs be developed that would arrest adaptation ?
Can Pseudomonas “staging” be used for therapy ?
Approaches for Studying Pseudomonas Adaptation
in CF Lung
•
Analysis of laboratory-adapted Pseudomonas strains grown under
conditions that promote phenotypes typical to the clinical isolates
•
Analysis of Pseudomonas clinical isolates from CF airway
- serial isolates from young children with CF
- isolates from patients with mild vs. severe disease symptoms
•
Analysis of bacterial phenotypes: morphology, surface properties,
production of secreted factors
•
Postgenomic analysis: whole genome sequencing, genome typing,
transcriptional profiling, protein expression profiling
Analysis of Pseudomonas Clinical Isolates From
Young Children With CF
Natural history study to determine infection and inflammation in
young children, three centers in US
– Early isolates from 29 children, 4 to 36 months of age,
2 to 30 isolates for each patient
– Later isolates from 11/29 children enrolled into the original study,
currently up to 9 years of age
– Isolates from upper airway (OP) and lower airway (BAL)
(Rosenfeld et al. 2001)
Postgenomic Analysis of Pseudomonas in CF
Environmental isolates
Clinical CF Isolates
Phenotypic
Analysis
Genomic Microarray
Analysis Analysis
Proteomic
Analysis
Bioinformatics
Identification of CF-unique Characteristics
Pseudomonas Adapt to the Cystic Fibrosis
Lung Environment
CF Isolate-Specific Characteristics:
Outer Membrane LPS Modifications
aminoarabinose
NH
2
O
OH
O
HO
OH
O
O
P O
OH
O
O
NH
O
O
O
NH
HO
O
O
HO
O
O
O
NH
O
P
O
O
-
OH
O
O
OH
O
HO
3-OH C10
2
O
O
1) Increased Antimicrobial
Peptide Resistance
3-OH
2) Increased Proinflammatory
Signaling Through Tlr4
C12
C12
C16
3-OH C12
3-OH C12
LPS modifications are induced in:
- all early isolates from infants with CF (as early as 4 months of age)
- laboratory-adapted strain PAO1 during magnesium limitation and
anaerobic growth
(Ernst et al. 1999, Hajjar et al. 2002)
I. Adaptation to the CF Lung: Is Genomic
Organization of Pseudomonas CF Infant and
Environmental Isolates Similar?
Whole genome analysis using DNA microarrays
- 13 CF, 4 environmental, and 3 clinical non-CF isolates
- 38 common chromosomal islands divergent or absent (N >1)
when compared to PAO-1
Results:
Suggest no selection of a Pseudomonas subpopulation from the
environment in colonization of the CF airways.
(Ernst et al. 2003)
II. Adaptation to the CF Lung : Is Genomic Organization
of Longitudinal Pseudomonas CF Isolates Similar?
Sequencing of parentally-related Pseudomonas isolates from a CF patient
< 6 mo
60 mo
Isolates from 6 months to 8 years of age
CF416 (6 months): 4.0 X coverage
CF5296 (8 years): 4.0 X coverage
Results:
40 point mutations/deletions between
early and late isolate
96 mo
(Smith, Olson et al.)
Analysis of 40 Chromosomal Regions:
Comparison of Longitudinal CF Isolates
Key
1
No changes
No changes
C
C
T
C
T
C
T
G
T
G
A
G
A
T
C
C
T
CGG --C
T
T
C
C
C
A
G
G
C
T
C
A
G
-CC
G
C
T
C
G
T
G
A
C
T
G
A
A
G
A
C
C
T
C
T
C
C
T
A
C
A
T
7 Cs 6 Cs
A
G
A
G
C
T
Age (months)<6
<9
24
27
30
30
33
36
36
60
96
2 Case \ Strain 416 547 1328 1438 1543 1546 1590 1638 1642 190383 5295
17
1
1
1
1
1
1
1
1
1
1
14
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
1
1
1
1
1
1
1
1
1
2
5
1
1
1
1
1
1
1
1
1
1
2
6
1
1
1
1
1
1
1
1
2
7
1
1
1
1
1
1
1
1
1
1
2
12
1
1
1
1
1
1
1
1
1
1
2
18
1
1
1
1
1
1
1
1
2
19
1
1
1
1
1
1
1
1
1
1
2
21
1
1
1
1
1
1
1
1
1
1
2
22
1
1
1
1
1
1
1
1
2
23
1
1
1
1
1
1
1
1
1
1
2
25
1
1
1
1
1
1
1
1
1
1
2
27
1
1
1
1
1
1
1
1
1
1
2
29
1
1
1
1
1
1
1
1
1
1
2
31
1
1
1
1
1
1
1
1
1
2
39
1
1
1
1
1
1
1
1
1
1
32
1
1
1
1
1
1
1
1
1
1
11
1
1
1
1
1
1
1
1
1
1
4
1
1
1
1
1
1
1
1
1
1
35
1
1
1
1
1
1
1
1
1
1
36
1
1
1
1
1
1
1
1
1
1
37
1
1
1
1
1
1
1
1
1
1
38
1
1
1
1
1
1
1
1
34
1
1
1
1
1
1
1
2
40
1
1
1
1
1
1
1
1
1
1
2
33
1
1
1
1
1
1
1
1
1
2
16
1
1
1
1
1
1
1
1
1
2
2
10
1
1
1
1
1
1
2
2
9
1
1
1
1
1
1
1
1
1
2
28
1
1
1
1
1
1
1
1
1
2
2
26
1
1
1
1
1
1
1
1
2
2
3
1
1
1
1
1
1
2
1
1
2
24
1
1
1
1
1
2
2
1
1
2
2
8
1
1
1
1
1
2
2
1
1
2
2
13
1
1
1
1
1
2
2
1
1
2
2
15
1
1
1
1
1
2
2
1
1
2
20
1
1
1
1
1
2
2
1
2
2
2
30
1
1
1
1
1
2
2
2
2
2
96
5296
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
III. Adaptation to the CF Lung : Is There a Gene Expression
Pattern Unique to the Infant CF Isolates?
Transcriptional (mRNA) profiling using DNA microarrays
CF-activated genes
PA1290: probable transcriptional regulator
PA5095: ABC transporter permease
CF-repressed genes
PA1008: bacterioferritin comigratory protein
PA1244: hypothetical gene
PA1708: popB - translocator protein
PA1752: hypothetical gene
PA2461: hypothetical gene
# of patients (N=5)
5
5
5
5
5
5
5
Results: Mode of regulation for 7 genes is unique to a subset
of clinical isolates
(Ernst et al.)
Cellular Protein Levels Do Not Always Correlate With
Levels of the Corresponding Gene Transcripts
Anaerobic regulation in PAO1: Postgenomic Analysis
Genes/Proteins
Total Quantified
Regulated
Induced
Represed
Regulated
Genes
209
42
Microarray Analysis
5600
209
108
101
13
Regulated
Proteins
122
Proteomic Analysis
553
122
54
68
Quantified
Proteins
553
IV. Adaptation to the CF Lung : Is There a Protein
Expression Pattern Unique to the Infant CF Isolates?
Quantitative protein profiling of differentially labeled whole cell protein
Strain/Condition A
Whole cell
protein
+ ICAT
mLC-MS/MS
Combine and
proteolyze
ICAT-peptide
mixture
in silico analysis
[Protein X in A]
Strain/Condition B
[Protein X in B]
Pseudomonas aeruginosa Proteome Analysis:
Regulation by Low Magnesium Stress Induces CF isolateSpecific Surface Modifications
Laboratory-adapted
Pseudomonas strain PAO-1
8 mM Mg2+
CF-like phenotype
1 mM Mg2+
Differential protein labeling
MS/in silico protein identification and quantitative analysis
Postgenomic Analysis of Pseudomonas
During Mg Limitation
Transcriptional Profiling: ~2250 (40%) genes expressed
650 genes regulated
Qualitative proteomic analysis: 1331 proteins identified
Quantitative analysis (ICAT):
546 proteins quantified
76 proteins induced
69 proteins repressed
~ 50% correlation with transcriptional profiling data
Selected Proteins Induced During Growth of
Pseudomonas in Low Mg
Fold increase
Conserved low Mg stress-response proteins
two-component response regulator PhoP
magnesium transport ATPase MgtA
MgtC homologue
10.3
5.8
4.0
CF-specific surface modifications, resistance to antimicrobial peptides
PmrH homologue
2.8
PmrF homologue
2.3
PmrI homologue
6.1
Enzymes for synthesis of quorum sensing signal PQS
PA0996, PA0997, PA0998, PA0999
1.5 - 2.0
Quorum Sensing: Bacterial Intercellular Communication Via
Small Signaling Molecules
C4-HSL
C12-HSL
PQS
Quorum Sensing: Secretion of Toxins, Virulence Factors
Quorum Sensing: Biofilm, Antibiotic Resistance
AB
AB
AB
AB
b-keto-decanoic acid
Butyryl-ACP
S-adenosylmethionine
(SAM)
PQS
RhlI
Acyl-homoserine lactones
LasI
Dodecanoyl-ACP
C4-HSL
C12-HSL
PQS Production by Laboratory Strain of
Pseudomonas Is Increased During Growth in Low Mg
Mg2+
Conc.
WT
PQS -
High Levels of PQS Are Produced by CF Pseudomonas
Isolates Grown in High Mg
PQS Production by Pseudomonas Isolates From
Infants with Cystic Fibrosis
Patient
1
2
3
4
6
7
8
9
10
102
103
104
105
107
108
109
111
201
202
203
204
205
206
209
211
212
# of isolates
Age (mo)
3
4
5
20
5
15
4
27
10
8
2
10
2
1
6
5
3
2
6
6
2
17
8
2
11
6
4 to 36
12 to 21
3 to 36
9 to 36
21 to 36
6 to 33
18 to 27
6 to 36
12 to 36
27 to 36
27 to 33
18 to 36
27 to 33
33
12 to 21
30 to 36
12 to 24
15 to 18
24 to 36
18 to 36
33
15 to 36
12 to 33
21 to 30
12 to 36
12 to 36
190 isolates from 25 children
up to 3 years of age analyzed for
PQS production
Bacteria were grown in medium
with high [Mg2+]
PQS Production by Isolates from Infants with CF
Patients (N=25)
Isolates producing
high PQS levels
12
> 75%
7
50-74%
2
25-49%
4
< 25%
Similar to CF-specific surface modifications, most
Pseudomonas clinical isolates from young children with CF
produce high PQS levels
Model of Chronic Pseudomonas aeruginosa
Infection in Cystic Fibrosis
Environmental Pseudomonas
Bacterial Adaptation
Lung
Disease
• surface modifications • Alginate/mucoidy
• Increased PQS
• Auxotrophy
(biofilm, virulence,
antibiotic resistance)
Innate Immune Selective Pressure
PA colonization-ASYMPTOMATIC
Increased bacteria - SYMPTOMATIC
Natural History Study:
Infant patients isolates,
8-yr vs. early isolates
Mild vs. Severe Study
Genome sequencing
DNA Microarray, Proteomic Analyses
To Identify Additional Markers
Natural History Study:
Infant patients isolates,
8-yr vs. early isolates
Mild vs. Severe Study
Genome sequencing
DNA Microarray, Proteomic Analyses
To Identify Additional Markers
Develop tests for broad screening of large CF populations
to validate markers specific for Pseudomonas adaptation
Natural History Study:
Infant patients isolates,
8-yr vs. early isolates
Mild vs. Severe Study
Genome sequencing
DNA Microarray, Proteomic Analyses
To Identify Additional Markers
Develop tests for broad screening of large CF populations
to validate markers specific for Pseudomonas adaptation
Correlate with the disease outcome
Disease outcome prediction
Vaccine/drug development
Bacterial Posttranslational Regulation Study:
Pseudomonas Envelope Remodeling During Growth
In Low Mg
Gram-negative Bacterial Membrane
Magnesium Stabilizes Gram-negative Outer Membrane
O
HO
O
P O
O
OH
O
O
O O
NH
O
HO
O
O
O
P OO
NH
O
O
O
O OH
OH
OH
-O
O
P O
O
OH
Mg
Growth in low magnesium
Growth in low magnesium
O
O
O
O O
NH
O HOO
P OH
O
NH
O
O
O
O OH
OH
OH
Membrane stress
Lipid A
Membrane
stress
Membrane remodeling
Membrane remodeling
Gram-Negative Envelope Remodeling
During Magnesium Limitation
Lipid A acylation
Alteration in outer
membrane proteins
Proteases
PagP
PagC
PagN
PgtE
OprH
OM
IM
PmrF
LPS modifications
PhoQ
PmrB
Environmental sensing
MgtA
MgtC
Small molecule transport
Nutrient acquisition
Modulation and resistance to the host innate immune defense:
ICAT Analysis of Pseudomonas Membrane and Whole Cell
Protein During Mg Limitation
Pseudomonas strain PAO-1
8 mM Mg2+
membrane
1 mM Mg2+
membrane
8 mM Mg2+
whole cell
1 mM Mg2+
whole cell
ICAT analysis
ICAT analysis
163 proteins
486 proteins
106 proteins were quantified in both experiments:
Compare relative protein levels in membrane vs. in whole cell
Pseudomonas Metabolic Enzymes and Protein Translation Machinery
Concentrate at the Membrane During Growth in Low Magnesium
FI* membrane/FI whole cell
Energy metabolism
succinate dehydrogenase (A, B subunits)
1.6 - 2.4
2-oxoglutarate dehydrogenase (E1 subunit) SucA
3.0
phosphoenolpyruvate synthase
3.1
ATP synthase subunits
1.5 – 1.8
cytochrome c5
1.6
GroEL chaperone
3.0
Translation machinery
30S ribosomal proteins (S2, S4, S13, S5)
1.5 – 1.8
elongation and ribosome recycling factor G
2.0
*FI = fold induction
Bacterial ribosomal fractions
Cytoplasmic
Membrane-associated
Soluble protein
synthesis
Membrane and secreted
protein synthesis
Bacterial ribosomal fractions
Low Mg2+ membrane stress
Cytoplasmic
Membrane-associated
Low Mg2+ membrane stress
Soluble protein
synthesis
Increased membrane and
secreted protein synthesis
Formation of stress-induced
multienzyme complexes
Membrane lipid and protein remodeling
Decreased membrane permeability
Resistance to various antimicrobials
Proteomic Analysis in Studying Bacterial Pathogens:
Summary
Advantages:
•
Useful tool for analysis of bacteria for which there are little
or no genetic tools available
•
Analysis of posttranscriptional regulation
•
Analysis of protein compartmentalization, posttranslational regulation
Disadvantages:
•
Still expensive, time/labor intensive
•
Need for “dishwasher-like technology”, for improved data analysis software
Acknowledgements
Manhong Wu
Robert Ernst
Hai Nguyen
Sam Miller
Jane Burns
Eric Smith
Maynard Olson
David Goodlett
Sam Purvine
Ruedi Aebersold
Jimmy Eng
CFF
NIH