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EBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

ABSTRACT: The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.

SUBMITTER: Feil EJ

PROVIDER: S-EPMC344416 | biostudies-other | 2004 Mar

REPOSITORIES: biostudies-other

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Project description:Leishmaniasis is a debilitating infectious disease that has a variety of clinical forms. In China, visceral leishmaniasis (VL) is the most common symptom, and L. donovani and/or L. infantum are the likely pathogens. In this study, multilocus sequence typing (MLST) of five enzyme-coding genes (fh, g6pdh, icd, mpi, pgd) and two conserved genes (hsp70, lack) was used to investigate the phylogenetic relationships of Chinese Leishmania strains. Concatenated alignment of the nucleotide sequences of the seven genes was analyzed and phylogenetic trees were constructed using neighbor-joining and maximum parsimony models. A set of additional sequences from 25 strains (24 strains belong to the L. donovani complex and one strain belongs to L. gerbilli) were retrieved from GenBank to infer the molecular evolutionary history of Leishmania from China and other endemic areas worldwide. Phylogenetic analyses consolidated Chinese Leishmania into four groups: (i) one clade A population comprised 13 isolates from different foci in China, which were pathogenic to humans and canines. This population was subdivided into two subclades, clade A1 and clade A2, which comprised sister organisms to the remaining members of the worldwide L. donovani complex; (ii) a population in clade B consisted of one reference strain of L. turanica and five Chinese strains from Xinjiang; (iii) clade C (SELF-7 and EJNI-154) formed a population that was closely related to clade B, and both isolates were identified as L. gerbilli; and (iv) the final group, clade D, included Sauroleishmania (LIZRD and KXG-E) and was distinct from the other strains. We hypothesize that the phylogeny of Chinese Leishmania is associated with the geographical origins rather than with the clinical forms (VL or CL) of leishmaniasis. To conclude, this study provides further molecular information on Chinese Leishmania isolates and the Chinese isolates appear to have a more complex evolutionary history than previously thought.

Project description:BackgroundVarious typing methods have been developed for Neisseria gonorrhoeae, but none provide the combination of discrimination, reproducibility, portability, and genetic inference that allows the analysis of all aspects of the epidemiology of this pathogen from a single data set. Multilocus sequence typing (MLST) has been used successfully to characterize the related organisms Neisseria meningitidis and Neisseria lactamica. Here, the same seven locus Neisseria scheme was used to characterize a diverse collection of N. gonorrhoeae isolates to investigate whether this method would allow differentiation among isolates, and to distinguish these three species.ResultsA total of 149 gonococcal isolates were typed and submitted to the Neisseria MLST database. Although relatively few (27) polymorphisms were detected among the seven MLST loci, a total of 66 unique allele combinations (sequence types, STs), were observed, a number comparable to that seen among isolate collections of the more diverse meningococcus. Patterns of genetic variation were consistent with high levels of recombination generating this diversity. There was no evidence for geographical structuring among the isolates examined, with isolates collected in Liverpool, UK, showing levels of diversity similar to a global collection of isolates. There was, however, evidence that populations of N. meningitidis, N. gonorrhoeae and N. lactamica were distinct, with little support for frequent genetic recombination among these species, with the sequences from the gdh locus alone grouping the species into distinct clusters.ConclusionThe seven loci Neisseria MLST scheme was readily adapted to N. gonorrhoeae isolates, providing a highly discriminatory typing method. In addition, these data permitted phylogenetic and population genetic inferences to be made, including direct comparisons with N. meningitidis and N. lactamica. Examination of these data demonstrated that alleles were rarely shared among the three species. Analysis of variation at a single locus, gdh, provided a rapid means of identifying misclassified isolates and determining whether mixed cultures were present.

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EBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

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