The multilocus sequence typing network: mlst.net

The unambiguous characterization of strains of a pathogen is crucial for addressing questions relating to its epidemiology, population and evolutionary biology. Multilocus sequence typing (MLST), which defines strains from the sequences at seven house-keeping loci, has become the method of choice for molecular typing of many bacterial and fungal pathogens (and non-pathogens), and MLST schemes and strain databases are available for a growing number of prokaryotic and eukaryotic organisms. Sequence data are ideal for strain characterization as they are unambiguous, meaning strains can readily be compared between laboratories via the Internet. Laboratories undertaking MLST can quickly progress from sequencing the seven gene fragments to characterizing their strains and relating them to those submitted by others and to the population as a whole. We provide the gateway to a number of MLST schemes, each of which contain a set of tools for the initial characterization of strains, and methods for relating query strains to other strains of the species, including clustering based on differences in allelic profiles, phylogenetic trees based on concatenated sequences, and a recently developed method (eBURST) for identifying clonal complexes within a species and displaying the overall structure of the population. This network of MLST websites is available a

Assessing the reliability of eBURST using simulated populations with known ancestry

BACKGROUND: The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known. RESULTS: For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant relationships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a useful guide to when eBURST is likely to be unreliable. CONCLUSION: Examination of eBURST groups within populations of a range of bacterial species showed that most were within the range in which eBURST is reliable, and only a small number (e.g. Burkholderia pseudomallei and Enterococcus faecium) appeared to have such high rates of recombination that eBURST is likely to be unreliable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise populations in which there appears to be a high rate of recombination relative to mutation

Modelling bacterial speciation

A central problem in understanding bacterial speciation is how clusters of closely related strains emerge and persist in the face of recombination. We use a neutral Fisher–Wright model in which genotypes, defined by the alleles at 140 house-keeping loci, change in each generation by mutation or recombination, and examine conditions in which an initially uniform population gives rise to resolved clusters. Where recombination occurs at equal frequency between all members of the population, we observe a transition between clonal structure and sexual structure as the rate of recombination increases. In the clonal situation, clearly resolved clusters are regularly formed, break up or go extinct. In the sexual situation, the formation of distinct clusters is prevented by the cohesive force of recombination. Where the rate of recombination is a declining log-linear function of the genetic distance between the donor and recipient strain, distinct clusters emerge even with high rates of recombination. These clusters arise in the absence of selection, and have many of the properties of species, with high recombination rates and thus sexual cohesion within clusters and low rates between clusters. Distance-scaled recombination can thus lead to a population splitting into distinct genotypic clusters, a process that mimics sympatric speciation. However, empirical estimates of the relationship between sequence divergence and recombination rate indicate that the decline in recombination is an insufficiently steep function of genetic distance to generate species in nature under neutral drift, and thus that other mechanisms should be invoked to explain speciation in the presence of recombination

Sequences, sequence clusters and bacterial species

Whatever else they should share, strains of bacteria assigned to the same species should have house-keeping genes that are similar in sequence. Single gene sequences (or rRNA gene sequences) have very few informative sites to resolve the strains of closely related species, and relationships among similar species may be confounded by interspecies recombination. A more promising approach (multilocus sequence analysis, MLSA) is to concatenate the sequences of multiple house-keeping loci and to observe the patterns of clustering among large populations of strains of closely related named bacterial species. Recent studies have shown that large populations can be resolved into non-overlapping sequence clusters that agree well with species assigned by the standard microbiological methods. The use of clustering patterns to inform the division of closely related populations into species has many advantages for poorly studied bacteria (or to re-evaluate well-studied species), as it provides a way of recognizing natural discontinuities in the distribution of similar genotypes. Clustering patterns can be used by expert groups as the basis of a pragmatic approach to assigning species, taking into account whatever additional data are available (e.g. similarities in ecology, phenotype and gene content). The development of large MLSA Internet databases provides the ability to assign new strains to previously defined species clusters and an electronic taxonomy. The advantages and problems in using sequence clusters as the basis of species assignments are discussed

Bayesian semi-supervised classification of bacterial samples using MLST databases

Peer reviewe

Burkholderia pseudomallei in Unchlorinated Domestic Bore Water, Tropical Northern Australia

To determine whether unchlorinated bore water in northern Australia contained Burkholderia pseudomallei organisms, we sampled 55 bores; 18 (33%) were culture positive. Multilocus sequence typing identified 15 sequence types. The B. pseudomallei sequence type from 1 water sample matched a clinical isolate from a resident with melioidosis on the same property

Role of interspecies transfer of chromosomal genes in the evolution of penicillin resistance in pathogenic and commensal Neisseria species

The two pathogenic species of Neisseria, N. meningitidis and N. gonorrhoeae , have evolved resistance to penicillin by alterations in chromosomal genes encoding the high molecular weight penicillin-binding proteins, or PBPs. The PBP 2 gene ( penA ) has been sequenced from over 20 Neisseria isolates, including susceptible and resistant strains of the two pathogenic species, and five human commensal species. The genes from penicillin-susceptible strains of N. meningitidis and N. gonorrhoeae are very uniform, whereas those from penicillin-resistant strains consist of a mosaic of regions resembling those in susceptible strains of the same species, interspersed with regions resembling those in one, or in some cases, two of the commensal species. The mosaic structure is interpreted as having arisen from the horizontal transfer, by genetic transformation, of blocks of DNA, usually of a few hundred base pairs. The commensal species identified as donors in these interspecies recombinational events ( N. flavescens and N. cinerea ) are intrinsically more resistant to penicillin than typical isolates of the pathogenic species. Transformation has apparently provided N. meningitidis and N. gonorrhoeae with a mechanism by which they can obtain increased resistance to penicillin by replacing their penA genes (or the relevant parts of them) with the penA genes of related species that fortuitously produce forms of PBP 2 that are less susceptible to inhibition by the antibiotic. The ends of the diverged blocks of DNA in the penA genes of different penicillin-resistant strains are located at the same position more often than would be the case if they represent independent crossovers at random points along the gene. Some of these common crossover points may represent common ancestry, but reasons are given for thinking that some may represent independent events occurring at recombinational hotspots.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48045/1/239_2004_Article_BF00182388.pd

EpiCollect: Linking Smartphones to Web Applications for Epidemiology, Ecology and Community Data Collection

Epidemiologists and ecologists often collect data in the field and, on returning to their laboratory, enter their data into a database for further analysis. The recent introduction of mobile phones that utilise the open source Android operating system, and which include (among other features) both GPS and Google Maps, provide new opportunities for developing mobile phone applications, which in conjunction with web applications, allow two-way communication between field workers and their project databases.Here we describe a generic framework, consisting of mobile phone software, EpiCollect, and a web application located within www.spatialepidemiology.net. Data collected by multiple field workers can be submitted by phone, together with GPS data, to a common web database and can be displayed and analysed, along with previously collected data, using Google Maps (or Google Earth). Similarly, data from the web database can be requested and displayed on the mobile phone, again using Google Maps. Data filtering options allow the display of data submitted by the individual field workers or, for example, those data within certain values of a measured variable or a time period.Data collection frameworks utilising mobile phones with data submission to and from central databases are widely applicable and can give a field worker similar display and analysis tools on their mobile phone that they would have if viewing the data in their laboratory via the web. We demonstrate their utility for epidemiological data collection and display, and briefly discuss their application in ecological and community data collection. Furthermore, such frameworks offer great potential for recruiting 'citizen scientists' to contribute data easily to central databases through their mobile phone

Melioidosis in Tsunami Survivors

Eugene Athan, Anthony M. Allworth, Catherine Engler, Ivan Bastian, and Allen C. Chen