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Population structure of pathogenic bacteria revisited
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International Journal of Medical Microbiology 294 (2004) 67–73 www.elsevier.de/ijmm
REVIEW
Population structure of pathogenic bacteria revisited Mark Achtman Department of Molecular Biology, Max-Planck Institut fu¨r Infektionsbiologie, Schumannstrasse 21/22, D-10117 Berlin, Germany
Abstract This minireview summarizes the historical development of bacterial population genetic concepts since the early 1980s. Initially multilocus enzyme electrophoresis was used to determine population structures but this technique is poorly portable between laboratories and was replaced in 1998 by multilocus sequence typing. Diverse population structures exist in different bacterial species. Two distinctive structures are described in greater detail. ‘‘Young’’ organisms, such as Yersinia pestis, have evolved or undergone a severe bottleneck in recent millennia and have not yet accumulated much sequence diversity. ‘‘genoclouds’’ in subgroup III Neisseria meningitidis arise because of the accumulation of diversity due to herd immunity, which is then purified during subsequent epidemic spread. r 2004 Elsevier GmbH. All rights reserved. Keywords: Bacterial population genetics; Yersinia pestis; Neisseria meningitides
Content Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Y. pestis, a ‘‘Young’’ species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 N. meningitidis subgroup III: clonal expansion and genoclouds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Introduction Population genetics as a discipline has developed over many decades, but only for eukaryotic organisms. Corresponding author. Tel.: +49-30-2846-0751; fax: +49-30-28460-750 E-mail address: [email protected] (M. Achtman).
1438-4221/$ - see front matter r 2004 Elsevier GmbH. All rights reserved. doi:10.1016/j.ijmm.2004.06.028
Bacterial population genetics first began when Bob Selander used the standard eukaryotic technique of multilocus enzyme electrophoresis (MLEE) on Escherichia coli (Selander and Levin, 1980) to show that particular combinations of alleles (electrophoretic types, ETs) were found significantly more often than would be expected for recombining organisms. From a eukaryotic viewpoint, the apparent lack of recombination (resulting
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in clones) was novel because mating eukaryotes shuffle chromosomes and recombine every generation. But bacteriologists had already previously recognized that certain uniform groups of pathogens in diverse species arose by clonal descent from a common ancestor (Old and Duguid, 1979; Ørskov et al., 1976) and the clonal concept for bacteria soon received strong support from a variety of sources of data (Achtman and Pluschke, 1986; Achtman et al., 1983; Ørskov and Ørskov, 1983). Selander and his disciples (Jim Musser, Tom Whittam, Howard Ochman and Dominique Caugant) proceeded to use MLEE to map the diversity of one pathogenic species after another (Selander et al., 1986). For each species, they identified ETs and clusters of related ETs, called clonal complexes. Unfortunately, these schemes have been only of limited use to the scientific community because extending them depends on being able to compare a potentially new variant to all previously defined variants and it is difficult to reproduce all electrophoretic differences in multiple laboratories. As a result, each publication used novel designations, and due to their lack of a uniform system of nomenclature, sequential analyses are difficult to relate to each other. Much of the diversity discovered in those numerous publications is not available for modern research. For example, thousands of E. coli isolates were examined by MLEE, but the only currently available reference E. coli collection is the EcoR collection of 72 isolates that was chosen in 1984 to represent the diversity known at that time (Ochman and Selander, 1984). The validity of these interpretations of universal clonality was questioned in 1993 by a seminal publication (Maynard Smith et al., 1993). John Maynard Smith and his colleagues pointed out that the evidence for clonality was not overwhelming and that recombination is so frequent in some species that apparent clonal complexes might exist only temporarily and were doomed to dissipate once sufficient recombination had occurred. They also introduced the concept that epidemic spread might result in apparent clonality, because it temporarily results in numerous isolates that are very similar, particularly when the focus is on bacteria that are isolated from invasive disease rather than from healthy carriers. Numerous examples of recombination have been described, even among bacteria that are thought to be highly clonal, such as Salmonella enterica (Brown et al., 2003). Recombination is so frequent that it is impossible or difficult to reconstruct the phylogenetic framework of evolution of many pathogenic species (Feil et al., 2001) and the genomic content of many organisms consists of a mosaic of genes that have been imported over millions of years (Lawrence and Ochman, 1997). The seminal publication by Maynard Smith and colleagues was so influential that many scientists began to doubt whether clonal group-
ings could even exist within bacterial species where recombination was known to occur. It was not readily possible to test models of population genetic structure in the early 1990s due to lack of sequence data. This situation has changed drastically since 1998, when multilocus sequence typing (MLST) was introduced (Maiden et al., 1998). MLST operates on the same principles as MLEE, i.e. fragments of multiple housekeeping genes (typically seven) scattered around the genome are sequenced from each isolate and combinations of alleles are referred to as a sequence type (ST) (Enright and Spratt, 1999). Unlike MLEE, MLST data are readily comparable between laboratories, because they are sequence-based, and a single, publicly available database is established for all isolates within a species (http://www.mlst.net/). Some of these databases now include data for previously inconceivably large numbers of isolates. For example, at the beginning of February, 2004, the database for Neisseria meningitidis contained information on almost 5000 isolates that were assigned to almost 3500 STs and the Campylobacter database contained 2215 isolates in 870 STs. Databases for sixteen microbial species are currently accessible via http://www.mlst.net/, including unpublished data from my laboratory for E. coli, S. enterica and Moraxella catarrhalis (http://web.mpiibberlin.mpg.de/mlst). We no longer lack data. Instead, the major shortage is tools to classify the diversity and concepts to understand it (Feil et al., 2004). Furthermore, it has also become clear that the distinction between clonality and frequent recombination is too simplistic to reflect the multitude of population structures that are found in diverse bacterial species. In this review, I will concentrate on two particular population structures, exemplified by Yersinia pestis and subgroup III of serogroup A N. meningitidis. Other species that I have investigated possess still different structures but are not described here because those data have not yet been accepted for publication.
Y. pestis, a ‘‘Young’’ species Y. pestis is indistinguishable from Y. pseudotuberculosis by the gold standard of taxonomy, DNA–DNA hybridization (Bercovier et al., 1980), and should hence be included within that species by taxonomic criteria. Sequence comparisons of rRNA genes confirmed this conclusion: 16S rRNA is identical between the two species and 23S rRNA is almost identical (Trebesius et al., 1998). However, it was first after an attempt was made to apply MLST to Y. pestis (Achtman et al., 1999), that it became apparent that Y. pestis is simply a clone of Y. pseudotuberculosis that has evolved in the last few
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millennia. Fragments of five housekeeping genes plus a sixth gene involved in lipopolysaccharide (LPS) biosynthesis were sequenced from 36 isolates that had been isolated from humans, rodents and fleas from diverse global sources. The same gene fragments were sequenced from 12 isolates of Y. pseudotuberculosis. Only one allele was found for each of the gene fragments in Y. pestis, i.e. all strains possessed identical sequences. In contrast, 2–5 alleles were found for each gene fragment in Y. pseudotuberculosis. Furthermore, each of the Y. pestis alleles was either identical, or almost identical, to an allele within Y. pseudotuberculosis. Age calculations showed that Y. pestis has evolved from Y. pseudotuberculosis in the last 1000–20,000 years (Achtman et al., 1999), which has since been revised to about 10,000–40,000 years (Achtman, 2004). A number of species have now been recognized that possess little sequence diversity and are of recent descent. The time since a last common ancestor for Mycobacterium tuberculosis is about the same as for Y. pestis (Sreevatsan et al., 1997; Gutacker et al., 2002). Bacillus anthracis also shows very little sequence diversity (Hill et al., 2004; Keim et al., 1999) and is probably of recent origin. Some other pathogens that do not have species status are also highly uniform because of severe bottlenecks in the last 50,000 years, e.g. S. enterica Typhi (Kidgell et al., 2002) and Plasmodium falciparum (Rich et al., 1998; Conway et al., 2000; Volkman et al., 2001; Joy et al., 2003). What is somewhat unusual about Y. pestis is that it has not simply undergone a recent bottleneck, but rather has actually evolved from Y. pseudotuberculosis within this time frame. Taken together, these various young groups of pathogens define a novel population structure, possibly best designated as ‘‘Young’’, which does not fall into the clonal versus recombination debate. What has happened to Y. pestis since it evolved? Initial steps in its evolution may have resulted due to the acquisition of two virulence plasmids (Achtman et al., 1999). Subsequently, the genome of Y. pestis has been disrupted by multiple insertions of IS100 (Achtman et al., 1999; Motin et al., 2002) and other insertion elements (Deng et al., 2002; Parkhill et al., 2001), resulting in deletions (Radnedge et al., 2002) and genomic rearrangements (Deng et al., 2002). Numerous genes have been inactivated by these mechanisms as well as by frameshift mutations (Deng et al., 2002). However, a comparison of 3237 homologous coding sequences between two Y. pestis genomes revealed only 38 synonymous polymorphisms in non-repetitive DNA (Achtman, 2004), confirming that there has been extremely little accumulation of neutral sequence diversity during its limited time of existence. Microbiologists have identified considerable diversity within Y. pestis by a variety of methods. Y. pestis can be subdivided into biovars that differ in their nutritional
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properties (Anisimov et al., 2004), into ribotypes (Guiyoule et al., 1994), and by the locations of IS100 (Motin et al., 2002), the presence of DNA islands (Radnedge et al., 2002) or the number of repeats within repetitive DNA stretches (Adair et al., 2000). Splitting Y. pestis into subtypes may be useful for epidemiological purposes, although even this remains to be proven, but does not negate my primary conclusion that this species is young and amazingly uniform.
N. meningitidis subgroup III: clonal expansion and genoclouds As mentioned above, the MLST database for N. meningitidis (meningococci) contains almost 3500 STs for 5000 bacteria isolated from diseased patients and healthy carriers since 1917 (Fig. 1). Of these, 231 meningococci expressing the serogroup A capsular polysaccharide have been tested by MLST but only 49 STs were detected. The isolates tested by MLST represent the most diverse genotypes found among approximately 1000 isolates from diverse epidemics and global sources by more sensitive typing methods (MLEE, RAPD and PCR-RFLP) (Olyhoek et al., 1987; Wang et al., 1992; Bart et al., 1998; Achtman et al., 2001; Zhu et al., 2001) and reflect the continued surveillance of outbreaks and carrier isolates in diverse countries. 33 of the 49 STs cluster together tightly, with five STs containing the majority of isolates, and represent the known global diversity of serogroup A meningococci from all epidemics and hyperendemic disease since the 1950s. This extraordinary uniformity can be partially explained by the hypothesis that serogroup A meningococci represent the clonal expansion since 1805, when the first meningitis epidemic was reported (Vieusseux, 1806), of an organism that acquired genes encoding the A capsular polysaccharide (Achtman et al., 2001). The epidemic model proposed by Maynard Smith et al. (1993) can be excluded, because two major clonal groupings with strong linkage disequilibrium were indicated by MLEE, RAPD and MLST of epidemic serogroup A meningococci (Bart et al., 2001). This then raises the question how clonal expansion can prevail when recombination is frequent. Why are there so few STs among epidemic serogroup A and why are these bacteria so uniform? One of the characteristics of epidemic meningococcal disease is that epidemics in any one country only last for 2–3 years, even before the introduction of antibiotics and vaccines against A capsular polysaccharide. Furthermore, it is not only disease that disappears but also carriage of serogroup A meningococci returns to endemic levels very quickly (Hassan-King et al., 1988;
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Subgroup III
Fig. 1. Minimal spanning tree of the relationships among 3322 STs within N. meningitidis. Data from http://www.pubmlst.org/ as of early February, 2004. The tree shows one minimal spanning tree of relationships between sequence types and was generated with Bionumerics V 3.5 (Applied Maths, Belgium). Colored nodes represent clonal complex notations at the PubMLST web site. The arrow points to STs that belong to subgroup III of serogroup A.
Gagneux et al., 2002b), possibly due to herd immunity. Towards the end of an epidemic, the frequency of both mutators and serological variants increases dramatically (Crowe et al., 1989; Linz et al., 2000; Richardson et al., 2002), presumably due to immune pressure (Meyers et al., 2003). Although these variants may temporarily escape herd immunity, they normally seem to be less fit than their parents and are lost by bottlenecks during spread from country to country (Zhu et al., 2001). As a result, most of the isolates from a pandemic that spans multiple countries and continents are indistinguishable, even by very sensitive methods, but multiple, unique variants can be isolated in each country. The resulting population type was designated a ‘‘genocloud’’ (Zhu et al., 2001). With time, fit variants can arise, which are transmitted as efficiently as their parents and form new genoclouds. Most of these are also lost with time but
some are transmitted so efficiently that they can spread pandemically to diverse countries and continents. During the last 35 years, nine genoclouds have been detected during three pandemic waves caused by ST5 and ST7 and their minor variants (Zhu et al., 2001). The purification of variants during epidemic spread of serogroup A meningococci ensures that these bacteria remain clonal. At any one time, the diversity is highly limited and disappears continuously as these bacteria spread. Variants cannot accumulate in any one area because herd immunity ensures that no single genocloud survives in one location for more than a few years. This mechanism is probably not limited to serogroup A, because epidemic spread has also been observed for serogroup X (Gagneux et al., 2002a, b). However, epidemic spread is rarely observed unless it is accompanied by disease and it is the combination of both
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properties, efficient transmission and frequent disease, that is so unique to serogroup A meningococci.
Concluding remarks The combination of MLST with high-throughput sequencing has drastically increased the amount of information available on the diversity of pathogenic bacteria. Our knowledge of natural diversity will continue to increase rapidly in the near future, especially as other numerical techniques with lower cost and higher throughput (variable number tandem repeat and single nucleotide polymorphism analysis) are applied to large strain collections. The problem for the future will be obtaining samples from those developing countries where disease is most frequent and handling the large datasets that arise. Interdisciplinary population genetic insights are needed to guide the planning of such experiments and novel algorithms will be needed to evaluate the data. So far, the hints given by our current understanding of the population structure of pathogenic bacteria indicate that fascinating insights into biological problems of general interest will be possible.
Acknowledgements The recent work described here was supported by the Deutsche Forschungsgemeinschaft priority program 1047 ‘‘Ecology of bacterial pathogens: molecular and evolutionary aspects’’ (Grant Ac 36/9).
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International Journal of Medical Microbiology 294 (2004) 67–73 www.elsevier.de/ijmm
REVIEW
Population structure of pathogenic bacteria revisited Mark Achtman Department of Molecular Biology, Max-Planck Institut fu¨r Infektionsbiologie, Schumannstrasse 21/22, D-10117 Berlin, Germany
Abstract This minireview summarizes the historical development of bacterial population genetic concepts since the early 1980s. Initially multilocus enzyme electrophoresis was used to determine population structures but this technique is poorly portable between laboratories and was replaced in 1998 by multilocus sequence typing. Diverse population structures exist in different bacterial species. Two distinctive structures are described in greater detail. ‘‘Young’’ organisms, such as Yersinia pestis, have evolved or undergone a severe bottleneck in recent millennia and have not yet accumulated much sequence diversity. ‘‘genoclouds’’ in subgroup III Neisseria meningitidis arise because of the accumulation of diversity due to herd immunity, which is then purified during subsequent epidemic spread. r 2004 Elsevier GmbH. All rights reserved. Keywords: Bacterial population genetics; Yersinia pestis; Neisseria meningitides
Content Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Y. pestis, a ‘‘Young’’ species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 N. meningitidis subgroup III: clonal expansion and genoclouds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Introduction Population genetics as a discipline has developed over many decades, but only for eukaryotic organisms. Corresponding author. Tel.: +49-30-2846-0751; fax: +49-30-28460-750 E-mail address: [email protected] (M. Achtman).
1438-4221/$ - see front matter r 2004 Elsevier GmbH. All rights reserved. doi:10.1016/j.ijmm.2004.06.028
Bacterial population genetics first began when Bob Selander used the standard eukaryotic technique of multilocus enzyme electrophoresis (MLEE) on Escherichia coli (Selander and Levin, 1980) to show that particular combinations of alleles (electrophoretic types, ETs) were found significantly more often than would be expected for recombining organisms. From a eukaryotic viewpoint, the apparent lack of recombination (resulting
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in clones) was novel because mating eukaryotes shuffle chromosomes and recombine every generation. But bacteriologists had already previously recognized that certain uniform groups of pathogens in diverse species arose by clonal descent from a common ancestor (Old and Duguid, 1979; Ørskov et al., 1976) and the clonal concept for bacteria soon received strong support from a variety of sources of data (Achtman and Pluschke, 1986; Achtman et al., 1983; Ørskov and Ørskov, 1983). Selander and his disciples (Jim Musser, Tom Whittam, Howard Ochman and Dominique Caugant) proceeded to use MLEE to map the diversity of one pathogenic species after another (Selander et al., 1986). For each species, they identified ETs and clusters of related ETs, called clonal complexes. Unfortunately, these schemes have been only of limited use to the scientific community because extending them depends on being able to compare a potentially new variant to all previously defined variants and it is difficult to reproduce all electrophoretic differences in multiple laboratories. As a result, each publication used novel designations, and due to their lack of a uniform system of nomenclature, sequential analyses are difficult to relate to each other. Much of the diversity discovered in those numerous publications is not available for modern research. For example, thousands of E. coli isolates were examined by MLEE, but the only currently available reference E. coli collection is the EcoR collection of 72 isolates that was chosen in 1984 to represent the diversity known at that time (Ochman and Selander, 1984). The validity of these interpretations of universal clonality was questioned in 1993 by a seminal publication (Maynard Smith et al., 1993). John Maynard Smith and his colleagues pointed out that the evidence for clonality was not overwhelming and that recombination is so frequent in some species that apparent clonal complexes might exist only temporarily and were doomed to dissipate once sufficient recombination had occurred. They also introduced the concept that epidemic spread might result in apparent clonality, because it temporarily results in numerous isolates that are very similar, particularly when the focus is on bacteria that are isolated from invasive disease rather than from healthy carriers. Numerous examples of recombination have been described, even among bacteria that are thought to be highly clonal, such as Salmonella enterica (Brown et al., 2003). Recombination is so frequent that it is impossible or difficult to reconstruct the phylogenetic framework of evolution of many pathogenic species (Feil et al., 2001) and the genomic content of many organisms consists of a mosaic of genes that have been imported over millions of years (Lawrence and Ochman, 1997). The seminal publication by Maynard Smith and colleagues was so influential that many scientists began to doubt whether clonal group-
ings could even exist within bacterial species where recombination was known to occur. It was not readily possible to test models of population genetic structure in the early 1990s due to lack of sequence data. This situation has changed drastically since 1998, when multilocus sequence typing (MLST) was introduced (Maiden et al., 1998). MLST operates on the same principles as MLEE, i.e. fragments of multiple housekeeping genes (typically seven) scattered around the genome are sequenced from each isolate and combinations of alleles are referred to as a sequence type (ST) (Enright and Spratt, 1999). Unlike MLEE, MLST data are readily comparable between laboratories, because they are sequence-based, and a single, publicly available database is established for all isolates within a species (http://www.mlst.net/). Some of these databases now include data for previously inconceivably large numbers of isolates. For example, at the beginning of February, 2004, the database for Neisseria meningitidis contained information on almost 5000 isolates that were assigned to almost 3500 STs and the Campylobacter database contained 2215 isolates in 870 STs. Databases for sixteen microbial species are currently accessible via http://www.mlst.net/, including unpublished data from my laboratory for E. coli, S. enterica and Moraxella catarrhalis (http://web.mpiibberlin.mpg.de/mlst). We no longer lack data. Instead, the major shortage is tools to classify the diversity and concepts to understand it (Feil et al., 2004). Furthermore, it has also become clear that the distinction between clonality and frequent recombination is too simplistic to reflect the multitude of population structures that are found in diverse bacterial species. In this review, I will concentrate on two particular population structures, exemplified by Yersinia pestis and subgroup III of serogroup A N. meningitidis. Other species that I have investigated possess still different structures but are not described here because those data have not yet been accepted for publication.
Y. pestis, a ‘‘Young’’ species Y. pestis is indistinguishable from Y. pseudotuberculosis by the gold standard of taxonomy, DNA–DNA hybridization (Bercovier et al., 1980), and should hence be included within that species by taxonomic criteria. Sequence comparisons of rRNA genes confirmed this conclusion: 16S rRNA is identical between the two species and 23S rRNA is almost identical (Trebesius et al., 1998). However, it was first after an attempt was made to apply MLST to Y. pestis (Achtman et al., 1999), that it became apparent that Y. pestis is simply a clone of Y. pseudotuberculosis that has evolved in the last few
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millennia. Fragments of five housekeeping genes plus a sixth gene involved in lipopolysaccharide (LPS) biosynthesis were sequenced from 36 isolates that had been isolated from humans, rodents and fleas from diverse global sources. The same gene fragments were sequenced from 12 isolates of Y. pseudotuberculosis. Only one allele was found for each of the gene fragments in Y. pestis, i.e. all strains possessed identical sequences. In contrast, 2–5 alleles were found for each gene fragment in Y. pseudotuberculosis. Furthermore, each of the Y. pestis alleles was either identical, or almost identical, to an allele within Y. pseudotuberculosis. Age calculations showed that Y. pestis has evolved from Y. pseudotuberculosis in the last 1000–20,000 years (Achtman et al., 1999), which has since been revised to about 10,000–40,000 years (Achtman, 2004). A number of species have now been recognized that possess little sequence diversity and are of recent descent. The time since a last common ancestor for Mycobacterium tuberculosis is about the same as for Y. pestis (Sreevatsan et al., 1997; Gutacker et al., 2002). Bacillus anthracis also shows very little sequence diversity (Hill et al., 2004; Keim et al., 1999) and is probably of recent origin. Some other pathogens that do not have species status are also highly uniform because of severe bottlenecks in the last 50,000 years, e.g. S. enterica Typhi (Kidgell et al., 2002) and Plasmodium falciparum (Rich et al., 1998; Conway et al., 2000; Volkman et al., 2001; Joy et al., 2003). What is somewhat unusual about Y. pestis is that it has not simply undergone a recent bottleneck, but rather has actually evolved from Y. pseudotuberculosis within this time frame. Taken together, these various young groups of pathogens define a novel population structure, possibly best designated as ‘‘Young’’, which does not fall into the clonal versus recombination debate. What has happened to Y. pestis since it evolved? Initial steps in its evolution may have resulted due to the acquisition of two virulence plasmids (Achtman et al., 1999). Subsequently, the genome of Y. pestis has been disrupted by multiple insertions of IS100 (Achtman et al., 1999; Motin et al., 2002) and other insertion elements (Deng et al., 2002; Parkhill et al., 2001), resulting in deletions (Radnedge et al., 2002) and genomic rearrangements (Deng et al., 2002). Numerous genes have been inactivated by these mechanisms as well as by frameshift mutations (Deng et al., 2002). However, a comparison of 3237 homologous coding sequences between two Y. pestis genomes revealed only 38 synonymous polymorphisms in non-repetitive DNA (Achtman, 2004), confirming that there has been extremely little accumulation of neutral sequence diversity during its limited time of existence. Microbiologists have identified considerable diversity within Y. pestis by a variety of methods. Y. pestis can be subdivided into biovars that differ in their nutritional
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properties (Anisimov et al., 2004), into ribotypes (Guiyoule et al., 1994), and by the locations of IS100 (Motin et al., 2002), the presence of DNA islands (Radnedge et al., 2002) or the number of repeats within repetitive DNA stretches (Adair et al., 2000). Splitting Y. pestis into subtypes may be useful for epidemiological purposes, although even this remains to be proven, but does not negate my primary conclusion that this species is young and amazingly uniform.
N. meningitidis subgroup III: clonal expansion and genoclouds As mentioned above, the MLST database for N. meningitidis (meningococci) contains almost 3500 STs for 5000 bacteria isolated from diseased patients and healthy carriers since 1917 (Fig. 1). Of these, 231 meningococci expressing the serogroup A capsular polysaccharide have been tested by MLST but only 49 STs were detected. The isolates tested by MLST represent the most diverse genotypes found among approximately 1000 isolates from diverse epidemics and global sources by more sensitive typing methods (MLEE, RAPD and PCR-RFLP) (Olyhoek et al., 1987; Wang et al., 1992; Bart et al., 1998; Achtman et al., 2001; Zhu et al., 2001) and reflect the continued surveillance of outbreaks and carrier isolates in diverse countries. 33 of the 49 STs cluster together tightly, with five STs containing the majority of isolates, and represent the known global diversity of serogroup A meningococci from all epidemics and hyperendemic disease since the 1950s. This extraordinary uniformity can be partially explained by the hypothesis that serogroup A meningococci represent the clonal expansion since 1805, when the first meningitis epidemic was reported (Vieusseux, 1806), of an organism that acquired genes encoding the A capsular polysaccharide (Achtman et al., 2001). The epidemic model proposed by Maynard Smith et al. (1993) can be excluded, because two major clonal groupings with strong linkage disequilibrium were indicated by MLEE, RAPD and MLST of epidemic serogroup A meningococci (Bart et al., 2001). This then raises the question how clonal expansion can prevail when recombination is frequent. Why are there so few STs among epidemic serogroup A and why are these bacteria so uniform? One of the characteristics of epidemic meningococcal disease is that epidemics in any one country only last for 2–3 years, even before the introduction of antibiotics and vaccines against A capsular polysaccharide. Furthermore, it is not only disease that disappears but also carriage of serogroup A meningococci returns to endemic levels very quickly (Hassan-King et al., 1988;
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Subgroup III
Fig. 1. Minimal spanning tree of the relationships among 3322 STs within N. meningitidis. Data from http://www.pubmlst.org/ as of early February, 2004. The tree shows one minimal spanning tree of relationships between sequence types and was generated with Bionumerics V 3.5 (Applied Maths, Belgium). Colored nodes represent clonal complex notations at the PubMLST web site. The arrow points to STs that belong to subgroup III of serogroup A.
Gagneux et al., 2002b), possibly due to herd immunity. Towards the end of an epidemic, the frequency of both mutators and serological variants increases dramatically (Crowe et al., 1989; Linz et al., 2000; Richardson et al., 2002), presumably due to immune pressure (Meyers et al., 2003). Although these variants may temporarily escape herd immunity, they normally seem to be less fit than their parents and are lost by bottlenecks during spread from country to country (Zhu et al., 2001). As a result, most of the isolates from a pandemic that spans multiple countries and continents are indistinguishable, even by very sensitive methods, but multiple, unique variants can be isolated in each country. The resulting population type was designated a ‘‘genocloud’’ (Zhu et al., 2001). With time, fit variants can arise, which are transmitted as efficiently as their parents and form new genoclouds. Most of these are also lost with time but
some are transmitted so efficiently that they can spread pandemically to diverse countries and continents. During the last 35 years, nine genoclouds have been detected during three pandemic waves caused by ST5 and ST7 and their minor variants (Zhu et al., 2001). The purification of variants during epidemic spread of serogroup A meningococci ensures that these bacteria remain clonal. At any one time, the diversity is highly limited and disappears continuously as these bacteria spread. Variants cannot accumulate in any one area because herd immunity ensures that no single genocloud survives in one location for more than a few years. This mechanism is probably not limited to serogroup A, because epidemic spread has also been observed for serogroup X (Gagneux et al., 2002a, b). However, epidemic spread is rarely observed unless it is accompanied by disease and it is the combination of both
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properties, efficient transmission and frequent disease, that is so unique to serogroup A meningococci.
Concluding remarks The combination of MLST with high-throughput sequencing has drastically increased the amount of information available on the diversity of pathogenic bacteria. Our knowledge of natural diversity will continue to increase rapidly in the near future, especially as other numerical techniques with lower cost and higher throughput (variable number tandem repeat and single nucleotide polymorphism analysis) are applied to large strain collections. The problem for the future will be obtaining samples from those developing countries where disease is most frequent and handling the large datasets that arise. Interdisciplinary population genetic insights are needed to guide the planning of such experiments and novel algorithms will be needed to evaluate the data. So far, the hints given by our current understanding of the population structure of pathogenic bacteria indicate that fascinating insights into biological problems of general interest will be possible.
Acknowledgements The recent work described here was supported by the Deutsche Forschungsgemeinschaft priority program 1047 ‘‘Ecology of bacterial pathogens: molecular and evolutionary aspects’’ (Grant Ac 36/9).
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