Phylogenetic diversity of the enteric pathogen Salmonella enterica subsp. enterica inferred from genome-wide reference-free SNP characters

Ruth E. Timme, James B. Pettengill, Marc W. Allard, Errol Strain, Rodolphe Barrangou, Chris Wehnes, Joann S. Van Kessel, Jeffrey S. Karns, Steven M. Musser, Eric W. Brown

Research output: Contribution to journalArticlepeer-review

87 Scopus citations

Abstract

The enteric pathogen Salmonella enterica is one of the leading causes of foodborne illness in the world. The species is extremely diverse, containing more than 2,500 named serovars that are designated for their unique antigen characters and pathogenicity profiles-some are known to be virulent pathogens, while others are not. Questions regarding the evolution of pathogenicity, significance of antigen characters, diversity of clustered regularly interspaced short palindromic repeat (CRISPR) loci, among others, will remain elusive until a strong evolutionary framework is established. We present the first large-scale S. enterica subsp. enterica phylogeny inferred from a new reference-free k-mer approach of gathering single nucleotide polymorphisms (SNPs) from whole genomes. The phylogeny of 156 isolates representing 78 serovars (102 were newly sequenced) reveals two major lineages, each with many strongly supported sublineages. One of these lineages is the S. Typhi group; well nested within the phylogeny. Lineage-throughtime analyses suggest there have been two instances of accelerated rates of diversification within the subspecies. We also found that antigen characters and CRISPR loci reveal different evolutionary patterns than that of the phylogeny, suggesting that a horizontal gene transfer or possibly a shared environmental acquisition might have influenced the present character distribution. Our study also shows the ability to extract reference-free SNPs from a large set of genomes and then to use these SNPs for phylogenetic reconstruction. This automated, annotation-free approach is an important step forward for bacterial disease tracking and in efficiently elucidating the evolutionary history of highly clonal organisms.

Original languageEnglish (US)
Pages (from-to)2109-2123
Number of pages15
JournalGenome biology and evolution
Volume5
Issue number11
DOIs
StatePublished - Nov 2013

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Genetics

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