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J Clin Microbiol. Jul 2006; 44(7): 2553–2557.
PMCID: PMC1489466

Nonrandom Distribution of Burkholderia pseudomallei Clones in Relation to Geographical Location and Virulence

Abstract

Burkholderia pseudomallei is a soil-dwelling saprophyte and the causative agent of melioidosis, a life-threatening human infection. Most cases are reported from northeast Thailand and northern Australia. Using multilocus sequence typing (MLST), we have compared (i) soil and invasive isolates from northeast Thailand and (ii) invasive isolates from Thailand and Australia. A total of 266 Thai B. pseudomallei isolates were characterized (83 soil and 183 invasive). These corresponded to 123 sequence types (STs), the most abundant being ST70 (n = 21), ST167 (n = 15), ST54 (n = 12), and ST58 (n = 11). Two clusters of related STs (clonal complexes) were identified; the larger clonal complex (CC48) did not conform to a simple pattern of radial expansion from an assumed ancestor, while a second (CC70) corresponded to a simple radial expansion from ST70. Despite the large number of STs, overall nucleotide diversity was low. Of the Thai isolates, those isolated from patients with melioidosis were overrepresented in the 10 largest clones (P < 0.0001). There was a significant difference in the classification index between environmental and disease isolates (P < 0.001), confirming that genotypes were not distributed randomly between the two samples. MLST profiles for 158 isolates from Australia (mainly disease associated) contained a number of STs (96) similar to that seen with the Thai invasive isolates, but no ST was found in both populations. There were also differences in diversity and allele frequency distribution between the two populations. This analysis reveals strong genetic differentiation on the basis of geographical isolation and a significant differentiation on the basis of virulence potential.

Burkholderia pseudomallei is the causative agent of melioidosis and a recognized biothreat agent (15, 18). This gram-negative bacillus is found in soil and water over a wide area of the Far East, together with northern Australia (2, 18). Infection results from inoculation or inhalation of organisms from the environment. Melioidosis most commonly presents as a septicemic illness, often associated with bacterial dissemination to distant sites (18), and leads to death in approximately 50% and 20% of patients in Thailand and Australia, respectively (2, 18). Infection usually occurs in individuals with one or more predisposing factors associated with impaired immunity such as diabetes mellitus and renal failure (3, 18), suggesting that host factors are central to pathogenesis. The extent to which variation in bacterial genetic factors also determines the likelihood of disease acquisition and subsequent severity is not known, but the fact that B. pseudomallei is associated with a higher disease burden than other members of the genus points to the presence of numerous virulence factors in the genome of this species. The observation that virulence of B. pseudomallei in animal models is variable between strains (17) indicates that there may be considerable intraspecies genetic variability. The completed 7.25-Mb B. pseudomallei (K96243) genome is divided into two chromosomes, the smaller of which (chromosome 2) may have evolved from a megaplasmid (11). Proportionately more genes of unknown function or encoding an “accessory” role are present on chromosome 2 than on chromosome 1. Considering both chromosomes, 16 genomic islands have been identified, and variable distribution of these islands among strains may account for differences in virulence (11).

Multilocus sequence typing (MLST) has been used to characterize the population structure and diversity of a number of important human pathogens, most of which are associated with colonization and human-to-human transmission. The free movement of colonized individuals between countries and continents leads to worldwide dispersal of bacterial genotypes with little geographic structure apparent in many species. In contrast, B. pseudomallei is an environmental saprophyte which does not colonize humans or other mammals and is not transmitted between them. Intercontinental migration of soil microorganisms may potentially arise by long-range wind dispersal (8), but the survival of non-spore-forming bacteria may be limited to shorter distances. If so, allopatric populations should arise corresponding to distinct endemic genotypes (“geotypes”). B. pseudomallei provides an ideal species to address the issue of migration and its effect on population structure. Furthermore, the ability to assign a country or geographic region as the likely source of a deliberately released strain may be of value.

The MLST data currently available for B. pseudomallei have revealed a low level of sequence diversity but a relatively large number of multilocus genotypes (sequence types [STs]) and limited clustering (1, 9). Analyses of these data, which are restricted mostly to isolates from northern Australia, suggest a high rate of recombination (10). However, there is currently little evidence concerning variation in virulence potential between isolates, nor have comparisons been drawn between isolates from different geographical origins to examine the extent of large-scale migration. Here, we use MLST to compare B. pseudomallei isolates recovered from disease patients and from the environment within a single geographical region (northeast Thailand), and we compare these results to preexisting data to examine the extent of migration between northern Australia and Southeast Asia. We note a significant difference in the frequencies of the genotypes causing invasive disease compared to the local soil reservoir, suggesting that some strains may have an enhanced ability to cause disease. It is also clear that the Thai and Australian populations are strikingly distinct, indicating very limited migration and gene flow on an intercontinental scale.

MATERIALS AND METHODS

Bacterial strains.

A total of 266 B. pseudomallei isolates were characterized by MLST. Of these, 83 were isolated from the soil of rice paddies in the province of Ubon Ratchathani, northeast Thailand, between 1990 and 2003 and were not associated with clinical disease. One hundred eighty-three isolates were from patients presenting to Sappasithiprasong Hospital in Ubon Ratchathani between 1989 and 2002, of which 79 were associated with a single clinical syndrome (acute suppurative parotitis in children). The remaining 104 invasive isolates were from consecutive patients diagnosed with melioidosis admitted to Sappasithiprasong Hospital in 2001. These patients presented with a spectrum of clinical syndromes; 61 had positive blood cultures with or without involvement of one or more organs or tissues, and 43 had negative blood cultures but had recovery of B. pseudomallei from one or more infected organs or tissues. A single isolate was used from each patient. Isolates were maintained at −70°C in tryptic soy broth with 15% glycerol. The previously published MLST profiles for 158 strains isolated by B. J. Currie in northern Australia were downloaded from the MLST website for comparison (http://www.mlst.net).

DNA extraction and multilocus sequence typing.

Bacterial isolates were streaked from the freezer vial onto Ashdown's agar. A single colony was inoculated into tryptic soy broth and incubated overnight in air at 37°C, after which genomic DNA was extracted using the Wizard genomic DNA purification kit (Promega). The following primer pairs were used for the amplification of housekeeping gene fragments on chromosome 1: ace-up (5′-GCTCGGCGCTTCTCAAAA) and ace-dn (5′-ATGTCCGTGCCGATGTAGC), gltB-up (5′-GGCGGCAAGTCGAACACGG) and gltB-dn (5′-GCAGGCGGTTCAGCACGAG), lepA-up (5′-TTTCGCTTGATCGGCACTG) and lepA-dn (5′-CGAACCACGAATCGATGATGAGC), lipA-up (5′-CATACGGTGTGCGAGGAAGC) and lipA-dn (5′-GCAGGATCTCGTCGGTCGTCT), narK-up (5′-GCCTTGCTTCCTCGTCATCTT) and narK-dn (5′-GAACGGCACCCACACGAA), and ndh-up (5′-GCAGTTCGTCGCGGACTATCTC) and ndh-dn (5′-GGCGCGGCATGAAGCTC). Amplification of gmhD was performed using a nested approach using the following primers: gmdD-up outer primer (5′-TCGCGCAGGGCACGCAGTT) and gmdD-dn outer primer (GGCTGCCGACCGTGAGACC), and gmhD-up inner primer (5′-TCGCGCAGGGCACGCAGTT) and gmhD-dn inner primer (GTCAGGAACGGCGCGTCGTAGC).

Data analysis.

The alleles at each of the previously described loci were assigned using the B. pseudomallei MLST website (http://bpseudomallei.mlst.net/). Sequences that were not in the database were checked by resequencing, assigned as new alleles, and deposited in the MLST allele database. Following the standard MLST protocol, each allele was assigned a different allele number and the allelic profile (string of seven integers) was used to define the sequence type (ST).

Neighbor-joining trees were constructed using the Kimura two-parameter method of distance estimation as implemented in MEGA version 2.1. Dendrograms with the unweighted pair group method with averages were constructed using the START package available from http://www.pubmlst.org (12). Maximum likelihood congruence analysis of gene trees was carried out using PAUP* version 4b following the method of Feil et al. (6), except that all trees were reconstructed and scored on the basis of the HKY85+G+Γ model of DNA substitution. eBURST v3 (http://eburst.mlst.net) was used to demonstrate relationships between closely related STs (those differing at only a single locus) (7). Estimates of synonymous and nonsynonymous changes (dS/dN) were calculated using the method of Nei and Gojobori as implemented in MEGA version 2.1. Mean heterozygosity per locus (H) was calculated using LIAN version 3.1 (http://adenine.biz.fh-weihenstephan.de/lian/). Comparisons of allelic and nucleotide divergence were calculated using the program BLAND, available on request. Comparisons between isolates from Thailand and Australia and between Thai isolates recovered from soil and those recovered from cases of invasive disease were carried out using the classification index (CI) proposed by Jolley et al. (13). This parameter is similar to FST but more sensitive in cases where more than two alleles are present, as it directly considers the frequencies of each allele. Significant differences in the frequency of STs, and the frequency of alleles at specific loci, were identified by comparing the observed classification index with those obtained from 10,000 randomized trials.

RESULTS AND DISCUSSION

Diversity within the B. pseudomallei population from northeast Thailand.

The 266 clinical and environmental isolates of B. pseudomallei from Thailand characterized by MLST in this study corresponded to 123 STs. The four most commonly recovered STs were ST70 (n = 21), ST167 (n = 15), ST54 (n = 12), and ST58 (n = 11). Of the remainder, 37 (13.9%) STs were represented by two to eight isolates, and 82 (66.7%) of the STs were represented by a single isolate. A greater degree of allelic diversity was noted in gmhD and narK than in the other five gene loci; 10 and 13 alleles were found in these two loci, respectively, whereas only three to six alleles were noted at the other five loci (Table (Table1).1). Despite the large number of STs detected, overall nucleotide sequence diversity was very low; when all unique alleles identified in the current study were considered, pairwise comparisons revealed an average of only 0.26 to 0.50% nucleotide divergence over all seven loci (Table (Table1).1). Estimates of synonymous and nonsynonymous changes are shown in Table Table11.

TABLE 1.
Allele frequency and diversity for 266 Thai isolates of B. pseudomallei

eBURST was used to identify groups of closely related STs (clonal complexes) and to examine the extent to which the data corresponded to a simple model of clonal expansion (Fig. (Fig.1).1). The majority of Thai isolates corresponded to a single large clonal complex (CC48) which did not conform to a simple pattern of radial expansion; the bootstrap support for the founder of this group was 75%, and therefore it could not be assigned with a high degree of confidence. Because of the relatively high level of diversity at narK and gmhD, many of the single-locus variant (SLV) links shown in Fig. Fig.11 correspond to allelic differences at these two loci. A second clonal complex (CC70) was also identified which much more closely corresponded to a simple radial expansion from a founding genotype, ST70 (bootstrap support, 99%). In contrast, a much higher degree of variation (a greater proportion of singleton or unlinked isolates) was observed for the Australian population (Fig. (Fig.11).

FIG. 1.
eBURST of 266 Thai B. pseudomallei isolates obtained from the environment (n = 83) or associated with human melioidosis (n = 183), together with 158 isolates from northern Australia which were mainly disease associated. Isolates from Thailand ...

Comparisons within the Thai population.

It is unclear whether strains of B. pseudomallei differ substantially in their ability to cause human infection or whether strains are equally likely to cause disease in susceptible hosts. We addressed this question by comparing the genotypes of isolates from invasive disease and those cultured from soil or water in northeast Thailand. Fifty-nine STs were identified among the 83 environmental isolates (0.71 STs per isolate) and 88 STs among the 183 invasive disease isolates (0.48 STs per isolate). The origins (environmental or invasive) of isolates corresponding to the 10 most commonly observed STs are shown in Table Table2.2. Invasive isolates predominated within these common STs: 43.7% of all invasive isolates belonged to these 10 STs compared to only 25.3% of soil isolates (P < 0.0001). There was a significant difference in the CI between environmental and invasive isolates (P < 0.001), confirming that genotypes were not distributed randomly between the two samples.

TABLE 2.
Sources of B. pseudomallei isolates in the 10 largest MLST clones for Thai data

ST70 was the strain most frequently recovered from invasive disease in northeast Thailand and was noted 17 times among the 183 disease isolates (9.3%) but only four times in the 83 environmental isolates (4.8%). ST70 and an SLV of ST70 (ST32) have been identified as the cause of melioidosis in captive birds, marine mammals, and humans in Hong Kong (9). Other STs also appeared to be associated with invasive disease in northeast Thailand (e.g., ST34, ST58, ST167, and ST221), while others were underrepresented among the disease isolates (e.g., ST54 and ST60).

The CI can also be used to detect population differences in allele frequency at each of the MLST loci (13). This approach is likely to be less sensitive in detecting differences between populations than when STs are examined, particularly in highly recombinogenic species. When the environmental and invasive isolates were compared on a locus-by-locus basis, only gmhD (P = 0.01) and narK (P = 0.05) showed a nonrandom distribution of alleles. For example, gmhD allele 5 was noted 13 times in the 183 invasive isolates but was absent from the 83 environmental strains (P = 0.01). Similarly, narK allele 29 was noted seven times in the invasive isolates but was absent from the environmental strains, while narK allele 2 was noted 20 times in both cases. A relatively high allelic diversity (and hence discriminatory power [Table [Table1])1]) may account for why differences were detected in only two genes. We do not suggest that these alleles have any direct bearing on virulence potential, but it is possible that they are linked to nearby alleles or genomic islands that influence pathogenicity. Such close linkage may also help to explain the high level of diversity at these loci.

To explore further the putative role of bacterial factors in disease, we examined Thai isolates associated with acute suppurative parotitis, a single defined clinical manifestation with a relatively good prognosis that is rare in northern Australia but is the presenting feature in one-third of Thai childhood cases (4). There were 45 STs among the 79 isolates associated with parotitis (0.56 STs per strain) and 63 STs among the other 104 invasive disease isolates (0.6 STs per strain), indicating that isolates causing parotid infection were as diverse as those associated with a range of other clinical presentations. There were no significant differences between the CI for STs associated with parotid disease and the CI for other invasive isolates, but a significant difference was found in the distribution of ace alleles (P = 0.03). Only three alleles were observed at this locus for all Thai isolates, one of which (allele 3) was rare and occurred five times. ace allele 1 was represented in 46 (58.2%) of the 79 isolates associated with parotitis and 41 (39.8%) of the other 103 invasive isolates. These figures are inverted for allele 2, being noted in 31 (39.2%) of the 79 parotid isolates and 60 (58.2%) of the other 103 invasive isolates.

Comparison of the Thai and Australian bacterial populations.

To detect geographical structuring on an intercontinental scale, we compared the 88 STs from invasive isolates in Thailand from this study with 96 STs identified previously among 158 isolates (mainly associated with disease) from northern Australia. No STs were common to both Thailand and Australia (P < 0.0001). This complete differentiation was also found when the environmental isolates from Thailand were included in the analysis. Comparisons of CIs also revealed that allele frequencies at each gene were nonrandomly distributed between the Thai and Australian populations (P = 0.0001). There was also a nonrandom distribution of single polymorphic sites; of the 67 polymorphisms present in the Australian data, only 19 (28.3%) were also present in the Thai data. Individual 2 × 2 chi-squared tests revealed highly significant differences in the frequencies of 12 of these 19 polymorphisms (P < 0.0001). Together, these analyses strongly suggest very limited gene flow and that the populations of B. pseudomallei have been diverging independently in Australia and Thailand.

To explore further the separation of Australian and Thai isolates, a neighbor-joining tree using the concatenated sequences of all seven loci was constructed (Fig. (Fig.2).2). This dendrogram confirmed that the Australian and Thai isolates were distinct, with some exceptions. The tree suggested four separate clades; one consisted of Thai isolates alone, another consisted of the majority of Australian isolates, and the remaining two clades were mixed, with some evidence for separation of the two populations within the clades. The tree was poorly supported by bootstrap scores (not shown); hence, the topological details are not likely to be indicative of the true phylogeny. Despite the poor phylogenetic signal, however, the tree supports a broad distinction between the Thai and Australian populations.

FIG. 2.
Neighbor-joining tree using the concatenated sequences of all seven loci for Thai and Australian isolates (n = 266 and n = 158, respectively). Isolates from Thailand are labeled in red; those from Australia are labeled in blue. The majority ...

In addition to being distinct on the basis of ST, allele, and polymorphic site frequency, there were other notable differences between the Thai and Australian samples. A total of 46 different alleles were noted in the 183 invasive Thai isolates, whereas 98 distinct alleles were noted in the 158 Australian isolates, confirming the suggestion from Fig. Fig.11 that the Australian population is more diverse. The mean heterozygosity per locus (H) was higher for the Australian (0.67 ± 0.07) than for the Thai (0.57 ± 0.07) invasive isolates, although this difference was not significant. There was a striking difference in the distribution of allele frequencies between the two populations. Of the 98 alleles in the Australian data, 38 (38.7%) were found in only one isolate, corresponding to an average of 0.24 unique alleles per isolate. In contrast, the number of alleles occurring once in Thai isolates was 9/46 (19.6%), corresponding to an average of 0.05 unique alleles per isolate (P = 0.02). Australian strains containing one or more unique alleles were no more divergent from each other (average pairwise allelic mismatch = 4.7, mean H = 0.694 ± 0.0976) than Australian isolates overall (average pairwise allelic mismatch = 4.6; mean H = 0.67 ± 0.07), confirming that this difference is not due to the inclusion of a few very distinct genotypes in the Australian sample. Alternative possibilities include sampling artifacts (the Australian isolates were recovered over a wider geographic area), differences in mutation or recombination rates, or an Australian origin of B. pseudomallei in Australia and subsequent spread to Southeast Asia.

Impact of homologous recombination on the diversification of the natural B. pseudomallei population.

The Thai data revealed a small number of alleles at each locus but a relatively large number of STs, suggesting that alleles in the population may frequently recombine. This is consistent with a previous analysis for the entire MLST data set (10). The most direct method to evaluate the contribution of recombination is to observe the nature of the changes that occur as an ancestral ST diversifies to form SLVs. Applying this approach to the ST70 clonal complex showed that the altered alleles in 9 of the 10 SLVs differed from the allele in ST70 at more than one nucleotide site. The low level of sequence diversity would be expected to lead to an underestimate of the extent of recombination, as alleles introduced by recombination may frequently differ at a single site and could be scored as a point mutation. The fact that only 1/10 allelic changes among the SLVs involved a single nucleotide change suggests that the rate of recombination is very high, relative to mutation. This is supported by an examination of the SLVs of the subgroup founders (5, 16) in the major clonal complex, where again the great majority of allelic changes can be assigned as the result of recombination.

An examination of phylogenetic congruence based on the method of Feil et al. (6) was also performed. A tree for the unweighted pair group method with averages was constructed from the allelic profiles of all the Thai isolates using the START package. Thirty diverse STs were picked from this tree, and maximum likelihood trees were constructed for each gene. For all 42 pairwise comparisons, the maximum likelihood trees constructed for each gene from the Thai data set were no more similar to the other gene trees than to trees of random topology (data not shown). This total lack of congruence is consistent with high rates of recombination, but the paucity of informative sites might limit the ability to detect significant congruence between the loci. The lack of phylogenetic consistency within the Thai data contrasts with the broad differentiation between the Thai and Australian data evident from Fig. Fig.22.

In conclusion, we have demonstrated the utility of MLST in defining intercontinental geographical segregation of an important soil-dwelling pathogen. It is likely that the differences between the Australian and Thai populations of B. pseudomallei reflect a historical pattern of migration and concomitant genetic drift, possibly in association with niche adaptation (14). The clear distinction between the endemic populations of Thailand and Australia shown here has important implications for tracking the source of outbreaks or deliberate release. From the study of isolates from Thailand, it was apparent that the most common STs are overrepresented in the isolate population associated with disease. Putative differences in virulence potential in a given ST may reflect rapid acquisition and loss of mobile genetic elements, and strain differentiation may underlie differences in disease presentation between Thailand and Australia. Many cases of melioidosis occur in individuals with risk factors such as diabetes mellitus and renal impairment. Further study is required to define whether at-risk individuals become infected by the same bacterial population as those without definable risk factors, or whether only a subset of strains are able to cause disease in the latter group.

Acknowledgments

We dedicate this paper to the memory of Nick G. C. Smith.

We are grateful to staff at the Sappasithiprasong Hospital, in particular to Wipada Chaowagul.

S.J.P. is supported by a Wellcome Trust Career Development Award in Clinical Tropical Medicine. E.J.F. is funded by an MRC Career Development Award. This study was part of the Wellcome Trust-Oxford University-Mahidol University Tropical Medicine Research Program.

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