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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.

Original publication

DOI

10.1098/rstb.2006.1917

Type

Journal article

Journal

Philosophical transactions of the Royal Society of London. Series B, Biological sciences

Publication Date

11/2006

Volume

361

Pages

1917 - 1927

Addresses

Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Hospital Campus, Norfolk Place, London W2 1PG, UK.

Keywords

Bacteria, Cluster Analysis, Sequence Analysis, DNA, Phylogeny, Genes, Bacterial, Classification, Databases, Genetic, Genetic Speciation