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Guidance Document
Identification of probiotics at strain level
Knut J. Heller1, W. Bockelmann1, E. Brockmann2
Max Rubner-Institut (Federeal Research Institute for Nutrition and Food), Department of
Microbiology and Biotechnology, Hermann-Weigmann-Str. 1, D-24103 Kiel, Germany;
2
Chr. Hansen, Bøge Allé 10-12, DK-2970 Hørsholm, Denmark
*Corresponding author: Email <knut.heller@mri.bund.de>
1
Probiotic properties are those of strains, not of species or even higher taxa (Heller, 2003).
This has been stressed by WHO/FAO in 2002 (N.N., 2006) by the following statement:
“Strain typing has to be performed with a reproducible genetic method or using a unique
phenotypic trait. Pulsed Field Gel Electrophoresis (PFGE) is the gold standard. Randomly
Amplified Polymorphic DNA (RAPD) can also be used, but is less reproducible.
Determination of the presence of extrachromosomal genetic elements, such as plasmids can
contribute to strain typing and characterization.” That probiotic properties are those of strains
and not of higher taxa is reflected by the fact that species names of micro-organisms with
established probiotic properties are extended by additional identifiers: e.g. a combination of
letters and numbers or the name of the person who isolated it. Examples are: Lactobacillus
rhamnosus GG, Bifidobacterium animalis subsp. lactis BB-12, Lactobacillus casei Shirota,
etc.
In addition to strain-specific methods needed for identification of probiotic strains, correct
assignment to species or sub-species remains indispensable. The latter is important for
evaluating the genetic background probiotic micro-organisms are imbedded in: whether they
belong to groups with established positive impacts on human health or whether they belong to
groups which include spoilage or even pathogenic micro-organisms (Pot et al., 1997). In this
communication we focus on strain identification. However, it has to be clear that this
identification is just based on a typing method, which only allows to demonstrate identity or
non-identity of a strain in question with that of a given probiotic strain in the context/frame of
the typing scheme of the applied method.
Typing methods have been compared in several reviews (Vandamme et al., 1996; Salvelkoul
et al., 1999; Domigk et al., 2003) and they have been discussed with respect to their
taxonomic resolution powers. A consensus of the latter is represented in Fig. 1. In a rather
recent review, Li et al. (2009) have focussed on genomic typing methods and have extended
the overview by including methods based solely on DNA extracted from the environment.
The methods with the broadest range of application are “DNA hybridization probes” and
“DNA sequencing”. They basically allow taxonomic discrimination from the highest down to
the lowest level, the strain level. However, while many “DNA hybridization probes” have
been developed and published for higher taxonomic levels (targeting rDNA), only few are
available for strain levels (targeting genes specific for the strains). The reasons for this are
rather simple: DNA probes for strain level identification have very limited applications but
require intensive and laborious testing for their development. DNA sequencing, on the other
hand, has the potential to become the standard method for all problems of taxonomic
resolution, even when considering resolution below species level. At present, sequencing of
ribosomal RNA genes (16S rDNA) represents the standard for species identification, since
standard amplification primers binding to conserved regions and standard sequencing primers
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can be applied. For strain identification, however, 16S rDNA sequencing cannot be
successfully applied, due to limited variability of this gene. One has to acknowledge that very
powerful sequencing techniques have been developed during recent years, which allow
sequencing of large numbers of nucleotides at rather low cost. This has led to the
development of the “Multi Locus Sequencing Typing / Multi Locus Sequence Analysis
(MLST / MLSA)” technique (Maiden et al., 1998), in which several gene loci are sequenced
and the sequence information generated is catenated and used for differentiation and typing
purposes. During recent years this technique has gained momentum and several MLST
databases have been developed and are accessible online. The most recently developed “next
generation” sequencing techniques, the “454 sequencing” (Margulies et al., 2005) and the
“Solexa/Illumina” and “SOLiD” sequencing, bear the potential of sequencing and analysing
entire genomes of microorganisms within one or a few days. Thus, whole genome sequencing
may eventually develop into the standard method of strain typing at least for industrially
important strains. However, before whole genome sequencing can become a standard typing
method, a clear concept has to be developed for defining the extent of allowable sequence
deviation within one and the same strain.
For very obvious reasons, “phenotype determination by classical methods” is not an
appropriate method for taxonomic resolution at strain level: it simply requires too much time
and experimental efforts.
Many other methods listed in Fig. 1, e.g. rRNA sequencing, cell wall structure, % G+C, are
not suitable for discriminating at strain level, since discrimination is limited to higher taxa.
These methods will not be discussed any further.
Of the methods suitable for strain identification, those based on serology target the surfaces of
micro-organisms. Serology has been very successfully applied for differentiation of
pathogenic bacteria. However, so far it has not been shown whether serology is capable of
identifying a probiotic strain among its non-probiotic relatives within the same species.
SDS-PAGE (sodium dodecylsulphate polyacrylamide gel electrophoresis) of total cellular
protein separated basically according to size (molecular mass) has been successfully shown to
be applicable in lactic acid bacteria for differentiation at strain level (Pot et al., 1997).
However, due to the necessity of growing and harvesting the cells under strictly defined
conditions for generation of absolutely reproducible protein patterns, this method is powerful
when used as “in-house” method. However, for identification of strains in different
laboratories the method may not be robust enough. Similar considerations regard DNAamplification techniques, where amplification conditions are applied, which are based on
primers and primer binding conditions allowing to target sequences not exactly matching the
primer sequences. This is especially true for RAPD (random amplification of polymorphic
DNA), where primers with arbitrary sequences are applied, and to a somewhat lesser extent
for rep-PCR (Repetitive Element PCR) and other similar methods like ERIC-PCR
(Enterobacterial Repetitive Intergenic Consensus PCR) (de Bruijn, 1992), Box-PCR (BOXA1R-based repetitive extragenic palindromic PCR) (Louws et al., 1994) etc. In these cases
small changes in the amplification procedures result in significant changes in the
electrophoretic patterns generated. As a consequence, inter-laboratory identification at strain
level becomes very difficult if not impossible. Somewhat reduced robustness is also the major
argument against AFLP (amplified fragment length polymorphism) (Vos et al., 1995), which
otherwise is a method of very high discriminating power and which allows high throughput of
samples to be tested. In this method, genomic DNA is hydrolysed by two restriction enzymes
of which at least one is a frequent cutter enzyme. To the ends generated, two different
adapters are ligated, which differentially recognize the two different ends produced by the two
enzymes. For subsequent PCR, primers basically corresponding to the adapter sequences but
with extended selectivity are applied.
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In contrast to AFLP, ribotyping (Snipes et al., 1989) and PFGE (Snell and Wilkins, 1986) do
not involve any step of amplification by PCR. For ribotyping, chromosomal DNA is
hydrolysed by restriction enzymes and separated by agarose gel electrophoresis. In the
following Southern blot, a labelled (radioactive, fluorescence, digoxigenin etc.) probe specific
for rRNA genes identifies those DNA fragments, which carry regions of those rRNA genes.
Due to the larges heterogeneity of DNA regions flanking the rRNA genes, the banding
patterns of hybridizing fragments show very high intra-species variation. In PFGE,
chromosomal DNA is hydrolyzed by means of a rare cutting restriction enzyme. The very
large DNA fragments obtained are separated by an electrophoresis technique, in which the
electric field frequently changes between two different directions, which leads to clear
separation of DNA fragments several hundred thousand basepairs in length. This leads to
typical banding patterns , which are used for fingerprinting. Thus, both ribotyping and PFGE
are very robust techniques, since exactly defined, reproducible electrophoresis patterns are
generated by complete hydrolysis of DNA with restriction endonucleases: ambiguities
resulting from varying amplification conditions are thus excluded. However, ambiguities with
this technique may arise from poor hydrolysis of bacterial cell walls for liberation of DNA
within the plug moulds, incomplete restriction hydrolysis, and variations in the
electrophoresis conditions. The latter, however, can be compensated for by always using
defined marker-DNA as control in the electrophoretic separation. Actually, for epidemiologic
studies, PFGE has been demonstrated to be applicable as a standardized effective method for
identification of strains in foodborne disease outbreaks by concerted actions of laboratories
joined in the so-called Pulse-Net (Boxrud et al., 2010).
Some of the typing techniques have been compared with each other with respect to their
discriminating powers. In a survey involving 35 isolates of Campylobacter jejuni, Männinen
et al. (2001) discriminated 8 different strains by ribotyping, 10 by PFGE and 10 by AFLP.
Tynkkynen et al. (1999) analysed 19 Lactobacillus rhamnosus isolates and were able to
discriminate 7 different strains by RAPD, 10 by ribotyping, and 12 by PFGE. Finally, Mättö
et al. (2004) analysed 18 Bifidobacterium longum and 10 Bifidobacterium adolescentis
isolates. They were able to discriminate for B. longum 7 different strains by RAPD, 13 by
ribotyping, and 14 by PFGE (only 14 of the 18 isolates were analysed by PFGE). For B.
adolescentis, RAPD yielded 6, and ribotyping as well as PFGE 9 different strains each. Thus,
PFGE is a robust method with the best discriminative power at strain level of all methods –
except AFLP (Vogel et al., 2004) - described. It is more labour-intensive than e.g. AFLP, but
less labour-intensive than ribotyping (a rapid PFGE method for analysis of bifidobacteria has
been described some years ago) (Briczinski and Roberts, 2006)). For these reasons, PFGE is
called the “gold-standard” of strain identification. This has been acknowledged by
FAO/WHO as already indicated in the first paragraph of this document (N.N., 2006).
In the Annex I to this Document, the most suitable methods for strain identification are listed
together with short descriptions of the methods. The literature cited in Annex I is included in
the list of references at the end of the body of this text.
The availability of techniques for fingerprinting below species level allows for strain
differentiation. However, when applying such techniques, one always has to bear in mind that
fingerprinting methods are just typing methods: they analyse one characteristic trait, which
then is used for attributing the organisms to groups of identical or very similar organisms
(strains) or non-identical ones. Except for methods based on DNA sequencing, typing
methods are not suited for phylogenetic considerations. The results of the typing methods for
different strains within one species have to be interpreted with care.
It has to be clear from the beginning of an experiment, whether any observed deviation from a
given pattern is supposed to result in the denomination of a new strain or not. Since strains do
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not form a taxonomic unit but form a group of members, which have been assigned to the
same strain on the basis of an arbitrary definition, the definition may be such that it either
does not allow for any deviations in a banding pattern or that it allows for small deviations of
up to 10% in a banding pattern of one and the same strain. The latter definition is often
applied, when tracing back microorganisms in outbreaks to the original source of infection
(Chiou et al., 2001).
When just one method is applied for assigning microorganisms to one group, one has to be
aware, that the group identified by this method may in fact be somewhat heterogeneous.
Recently, it has been described that Lactobacillus fermentum strains with identical PFGE
patterns differed in up to four characteristic traits (ARDRA pattern generated with a particular
restriction enzyme, growth at a particular temperature, ability to metabolize two different
sugars) (Njeru et al., 2010). This certainly raises the fundamental question of whether typing
methods are really useful in attributing microorganisms to groups of microorganisms sharing
one or few important functional traits, which are not tested by the typing method. The Joint
FAO/WHO Working Group Report on Drafting Guidelines for the Evaluation of Probiotics in
Food (N.N., 2006) states that “Strain identity is important to link a strain to a specific health
effect as well as to enable accurate surveillance and epidemiological studies”, thereby
indicating that strain identification serves different purposes. High resolving typing methods
like PFGE will be adequate for the assessment of recovery in studies investigating probiotic
functionality as well as safety, where the strain identity of the probiotic applied is typically
not only secured by typing methods but also through a documented origin traceable to a
reference material. Due to the described possible heterogeneity of strains belonging to one
typing group, typing methods can however not be fully sufficient to generally make the link to
probiotic functionality. The same argument will also limit their applicability for accurate
surveillance as well as epidemiological studies where there is no documented link to the
probiotic reference material. The conclusion for probiotic strains can only be that typing
methods like PFGE are important as long as specific tests for those genes – or even for the
activity of those genes - involved in making a strain probiotic are not available, due to lack of
information of the genes involved. As soon as such information is available, typing methods
together with methods testing the activities of relevant genes will show that certain functional
traits are present within the correct strain, i.e. in a microorganism with the correct genetic
background.
References
Bennasar, A., Mulet, M., Lalucat, J., García-Valdés, E. 2010. PseudoMLSA: a database for
multigenic sequence analysis of Pseudomonas species. BMC Microbiol. 10:118.
Briczinski, E.P., Roberts, R.F. 2006. Technical Note: A rapid pulsed-field gel electrophoresis
method for analysis of bifidobacteria. J. Dairy Sci. 89:2424-2427
Boxrud, D., Monson, T., Stiles, T., et al. 2010. The role, challenges, and support of Pulse-Net
laboratories in detecting foodborne disease outbreaks. Publ. Health Rep. 125:57-62
Busconi, M., Reggi, S., Fogher, C. 2008. Evaluation of biodiversity of lactic acid bacteria
microbiota in the calf intestinal tracts. Antonie Van Leeuwenhoek 94(2):145-155.
de Bruijn, F.J. 1998. Use of repetitive (Repetitive Extragenic Palindromic and Enterobacterial
Repetitive Intergeneric Consensus) sequences and the polymerase chain reaction to
fingerprint the genomes of Rhizobium meliloti isolates and other soil bacteria. Appl.
Environ. Microbiol. 58:2180-2187
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Chiou, C.S., Hsu, W.B., Wei, H.L., Chen, J.H. 2001. Molecular epidemiology of a Shigella
flexneri outbreak in a mountainous township in Taiwan, Republic of China. J. Clin.
Microbiol. 39:1048-1056
De Vuyst, L., Vancanneyt, M. 2007. Biodiversity and identification of sourdough lactic acid
bacteria. Food Microbiol. 24(2):120-127.
Domigk, K.J., Mayer, H.K., Kneifel, W. 2003. Methods used for the isolation, enumeration,
characterisation and identification of Enterococcus spp. Int. J. Food Microbiol. 88:165188
Engel, G., Roesch, N., Heller, K.J. 2003. Typing by pulsed-field gel electrophoresis (PFGE)
of bifidobacteria from fermented dairy products. Kieler Milchw. Forsch. 55:225–232 (in
German)
Hanage, W.P., Fraser, C., Spratt, B.G. 2006. Sequences, sequence clusters and bacterial
species. Philos. Trans. R. Soc. Lond. B Biol. Sci. 361(1475):1917-1927.
Hänninen, M.-L., Perko-Mäkelä, P., Rautelin, H., Duim, B., Wagenaar, J. A. (2001). Genomic
Relatedness within Five Common Finnish Campylobacter jejuni Pulsed-Field Gel
Electrophoresis Genotypes Studied by Amplified Fragment Length Polymorphism
Analysis, Ribotyping, and Serotyping. Appl. Environ. Microbiol. 67:1581-1586.
Heller, K.J. 2003. Inclusion of Probiotics in Beverages: Can it Lead to Improved Health? pp.
247-257. In T. Wilson and N. J. Temple (Eds.), Beverages in Nutrition and Health.
Humana Press Inc., Totowa, New Jersey.
Hudson, M.E. 2008. Sequencing breakthroughs for genomic ecology and evolutionary
biology. Mol. Ecol. Resour. 8(1):3-17.
Klein, G., Pack, A., Bonaparte, C., et al. 1998. Taxonomy and physiology of probiotic lactic
acid bacteria. Int. J. Food Microbiol. 41:103-125
Li, W., Raoult, D. Fournier, P.-E. 2009. Bacterial strain typing in the genomic era. FEMS
Microbiol. Rev. 33:892–916
Lortal, S., Rouault, A., Guezenec, S., Gautier, M. 1997. Lactobacillus helveticus: strain typing
and genome size estimation by pulsed field gel electrophoresis. Curr. Microbiol.
34:180-185
Louws, F.J., Fulbright, D.W., Taylor-Stephens, C., de Bruijn, F.J. 1994. Specific Genomic
Fingerprints of Phytopathogenic Xanthomonas and Pseudomonas Pathovars and Strains
Generated with Repetitive Sequences and PCR. Appl. Environ. Microbiol. 60:22862295
Maiden, M.C.J., Bygraves, J.A., Feil, E. et al. 1998. Multilocus sequence typing: A portable
approach to the identification of clones within populations of pathogenic
microorganisms Proc. Natl. Acad. Sci. U.S.A. 95: 3140–3145
Margulies, M. Egholm, M. Altman, W.E. et al., 2005. Genome sequencing in microfabricated
high-density picolitre reactors. Nature 437:376-380
Mättö, J., Malinen, E., Suihko, M.-L., Alander, M., Palva, A., Saarela, M. 2004. Genetic
heterogeneity and functional properties of intestinal bifidobacteria. J. Appl. Microbiol.
97:459-462
Möller, C. 2002. Application of new selection strategies for yoghurt starter cultures suitable
for yielding yoghurt with mild taste. Ph.D. thesis, University at Kiel, Germany (in
German)
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N.N. 2006. Joint FAO/WHO Working Group Report on Drafting Guidelines for the
Evaluation of Probiotics in Food. FAO Food and Nutrition Paper 85
Njeru, P.N., Roesch, N., Ghadimi, D., et al., 2010. Identification and characterization of
lactobacilli isolated from 1 Kimere, a spontaneously 2 fermented pearl millet dough
from Mbeere, Kenya (East Africa). Beneficial Microbes (in press)
Pennacchia, C., Vaughan, E.E., Villani, F. 2006. Potential probiotic Lactobacillus strains from
fermented sausages: Further investigations on their probiotic properties. Meat Sci. 73:
90-101
Picozzi, C, Bonacina G, Vigentini I, et al. 2010. Genetic diversity in Italian Lactobacillus
sanfranciscensis strains assessed by multilocus sequence typing and pulsed-field gel
electrophoresis analyses. Microbiology-SGM 156: 2035-2045
Pot, B., Coenye, T, Kersters, K. 1997. The taxonomy of microorganisms used as probiotics
with special focus on enterococci, lactococci, and lactobacilli. Microecology and
Therapy, 26: 11-25
Rong, X., Liu, N., Ruan, J., Huang, Y. 2010. Multilocus sequence analysis of Streptomyces
griseus isolates delineating intraspecific diversity in terms of both taxonomy and
biosynthetic potential. Antonie van Leeuwenhoek 98:237–248
Roy, D., Ward, P., Champagne, G. 1996. Differentiation of bifidobacteria by use of pulsedfield gel electrophoresis and polymerase chain reaction. INTERNATIONAL
JOURNAL OF FOOD MICROBIOLOGY 29: 1:11-29
Savelkoul, P.H., Aarts, H.J., de Haas, J., Dijkshoorn, L., Duim, B., Otsen, M., Rademake,r
J.L., Schouls, L., Lenstra, J.A. 1999. Amplified-fragment length polymorphism
analysis: the state of an art. J. Clin. Microbiol. 37:3083-91
Scheirlinck, I., Van der Meulen, R., De Vuyst, L., Vandamme, P., Huys, G. 2009. Molecular
source tracking of predominant lactic acid bacteria in traditional Belgian sourdoughs
and their production environments. J. Appl. Microbiol. 106(4):1081-92.
Snell RG, Wilkins RJ. 1986. Separation of chromosomal DNA molecules from C.albicans by
pulsed field gel electrophoresis. Nucleic Acids Res. 14:4401-4406
Snipes, K.P., Hirsh, D.C., Kasten, R.W. et al.1989. Use of an rRNA probe and restriction
endonuclease analysis to fingerprint Pasteurella multocida isolated from turkeys and
wildlife. J. Clin. Microbiol.27:1847-1853
Tynkkynen, S., Satokari, R., Saarela, M., Mattila-Sandholm, T., Saxelin, M. 1999.
Comparison of ribotyping, randomly amplified polymorphic DNA analysis, and pulsedfield gel electrophoresis in typing of Lactobacillus rhamnosus and L. casei strains. Appl.
Environ. Microbiol. 65:3908-14
Vancanneyt, M., Huys, G., Lefebvre, K., Vankerckhoven, V., Goossens, H., Swings, J. 2006.
Intraspecific genotypic characterization of Lactobacillus rhamnosus strains intended for
probiotic use and isolates of human origin. Appl. Environ. Microbiol. 72:5376-83
Vandamme, P., Pot, B., Gillis, M., De Vos, P., Kersters, K., Swings, J. 1996. Polyphasic
taxonomy, a consensus approach to bacterial systematics. Microbiol Rev. 60:407–438
Ventura, M., Zink, R. 2002. Rapid identification, differentiation, and proposed new
taxonomic classification of Bifidobacterium lactis. Appl. Environ. Microbiol. 68: 64296434
Vogel, B., Fussing, V., Ojeniyi, B., Gram, L., Ahrens, P. 2004. High-resolution genotyping of
Listeria monocytogenes by fluorescent amplified fragment length polymorphism
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analysis compared to pulsed-field gel electrophoresis, random amplified polymorphic
DNA analysis, ribotyping, and PCR-restriction fragment length polymorphism analysis.
J. Food Prot. 67:1656-1665
Vos, P., Hogers, R., Bleeker, M., et al. 1995 AFLP – a new technique for DNA-fingerprintig.
Nucl. Acids Res. 23:4407-4414
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FAMILY GENUS SPECIES STRAIN
DNA probes, DNA sequencing
rDNA sequencing
phenotype (classical, API, Biolog etc.)
Cell wall structure
Cellular fatty acid fingerprinting (FAME)
% G+C
DNA-DNA hybridization
Phage and bacteriocin typing
DNA amplification (ARDRA)
SDS-PAGE patterns
Serological methods
DNA amplification (AFLP, RAPD, rep-PCR etc.)
Ribotyping
Restriction fragment length polymorphism (RFLP, PFGE)
Fig. 1: Taxonomic resolution of different typing techniques. The figure was created based
on information presented in Vandamme et al. (1996), Salvelkoul et al. (1999),
Domigk et al. (2003).
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Annex I
Most suitable methods for strain identification

DNA sequencing-based methods
Due to extreme advances in development of DNA sequencing methodology, DNA
sequencing-based methods offer great advantages for typing at all phylogenetic levels,
including strain level. An update on typing methods in the genomic era has been
published by Li et al. (2009). DNA sequencing, in contrast to other typing methods, bears
the advantage of simultaneously comprising typing and phylogenetic classification.
-
MLSA/MLST (Multi Locus Sequence Analysis/Multi Locus Sequence Typing)
MLSA/MLST is a technique, which has been developed during recent years (Maiden et
al., 1998). In this technique, several gene loci are sequenced and the sequence
information generated is catenated and used for differentiation and typing purposes. The
gene loci chosen usually are house-keeping genes (Hanage et al., 2006), like atpD, gyrB,
recA, rpoB, rpoD, etc., which may be combined with the 16S and 23S rRNA genes
(Bennasar et al., 2010), which are rather conserved. Inclusion of the rRNA genes allows
for inclusion of all phylogenetic data produced so far for species identification.
Application of MLSA has been described for lactic acid bacteria populations in
sourdough (De Vuyst and Vancanneyt, 2007).
While the concept for applying MLSA/MLST for species identification is rather
straightforward and clear, this does not hold true for strain identification. It is by no
means clear, how much sequence divergence would be allowed to still cluster isolates
within the same strain.
-
Whole genome sequencing
Especially the most recently developed “next generation” sequencing techniques, the
“454 sequencing” (Margulies et al., 2005) and the “Solexa/Illumina” and “SOLiD”
sequencing (Hudson, 2008), bear the potential of generating raw sequence data for entire
genomes of microorganisms within less than one day. The powers of these techniques
rely on their abilities to generate millions to billions of small sequence reads at one time
and thus to produce as much as several gigabases of DNA sequences per run. These
techniques have reduced the cost per sequenced base to less than 0.0001 € per base of
final sequence and thus offer the possibility to sequence quite a large number of isolates
of one species in short time with rather little financial effort. The microbial genome
sequences generated can be compared and – as already described for MLSA/MLST
sequencing – can be applied for typing and phylogenetic purposes. However, although it
should be rather easy to identify organisms belonging to one species (on the basis of the
16S and 23S rRNA gene sequences), a concept for assigning members of one species to a
certain strain is still lacking.

AFLP (Amplified Fragment Length Polymorphism)
Of the PCR-based methods, AFLP (Vos et al., 1995) is the most promising for strain
identification. In this method, three steps are involved: i) genomic DNA is hydrolysed by
two restriction enzymes of which at least one is a frequent cutting enzyme. To the
restriction fragment ends generated, two different adapters are ligated, which
differentially recognize the two different ends produced by the two enzymes. ii) For PCR,
two different primers are applied, the sequences of which correspond to the respective
adapter sequences. However, the primer sequences are extended by at least one additional
nucleotide at their 3’-ends. Thus, selectivity of the primers is increased and amplification
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is restricted to maximally 1/16 of all potential possibilities. ii) The amplification products
are finally separated on denaturing polyacrylamide gels, the same type used for DNA
sequencing.
Typically, 50-100 restriction fragments are amplified and detected. Due to the accuracy
of the sequencing gels, the pattern generated are very exact and reproducible. The
robustness of the method is usually very good, since primer binding takes place at exactly
matching complementary sequences. The application of AFLP in the analysis of complex
populations of lactic acid bacteria has been described (Busconi et al., 2008; Scheirlinck et
al., 2009).

Ribotyping
For ribotyping, chromosomal DNA, hydrolysed by restriction enzymes and separated by
agarose gel electrophoresis, is subjected to a Southern blot and probed with labelled
(radioactive, fluorescence, digoxigenin etc.) probes specific for rRNA genes (Snipes et
al., 1989). Thereby, all DNA restriction fragments are identified, which carry DNA
regions complementary to the probes applied. Due to the large heterogeneity of DNA
regions flanking the rRNA genes, the banding patterns of hybridizing fragments show
very high intra-species variation. The discriminatory power below species level almost
matches that of PFGE, when lactobacilli or bifidobacteria were analysed (Tynkkynen et
al., 1999; Mättö et al., 2004). However, ribotyping – although robust - is a very labour
and cost intensive technique.

PFGE (Pulsed-Field Gel Electrophoresis)
As with ribotyping, PFGE does not involve any DNA amplification step, thought to be
the critical step when robustness of a technique is considered. For PFGE, chromosomal
DNA is hydrolyzed by means of a rare cutting restriction enzyme. The very large DNA
fragments obtained are separated by an electrophoresis technique, in which the electric
field frequently changes between two different directions. This leads to clear separation
of DNA fragments up to several hundred thousand basepairs in length. The banding
patterns obtained are used for fingerprinting.
Restriction endonucleases recommended have been described in the literature and
successfully applied in our laboratory: XbaI and SpeI for bifidobacteria (Roy et al., 1996;
Ventura and Zink, 2002; Engel et al., 2003) and AscI (Möller 2002; Vancanneyt et al.,
2006; Njeru et al., 2010) and NotI (Pennacchia et al., 2006; Vancanneyt et al., 2006) for
lactobacilli. Other enzymes, like e.g. SmaI (Lortal et al., 1997; Klein et al., 1998) and
ApaI (Picozzi et al., 2010) have been shown to yield more satisfying results for
Lactobacillus species with a low GC-content.
In contrast to other techniques, there exists a clear concept for strain identification, since
PFGE is the technique widely applied for tracking back foodborne outbreaks due to
pathogenic strains (Boxrud et al., 2010).
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