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High-throughput genome sequencing of two Listeria monocytogenes clinical isolates during a large foodborne outbreak

Authors
Journal
BMC Genomics
1471-2164
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Volume
11
Issue
1
Identifiers
DOI: 10.1186/1471-2164-11-120
Keywords
  • Research Article
Disciplines
  • Biology
  • Ecology
  • Geography
  • Medicine

Abstract

Background A large, multi-province outbreak of listeriosis associated with ready-to-eat meat products contaminated with Listeria monocytogenes serotype 1/2a occurred in Canada in 2008. Subtyping of outbreak-associated isolates using pulsed-field gel electrophoresis (PFGE) revealed two similar but distinct AscI PFGE patterns. High-throughput pyrosequencing of two L. monocytogenes isolates was used to rapidly provide the genome sequence of the primary outbreak strain and to investigate the extent of genetic diversity associated with a change of a single restriction enzyme fragment during PFGE. Results The chromosomes were collinear, but differences included 28 single nucleotide polymorphisms (SNPs) and three indels, including a 33 kbp prophage that accounted for the observed difference in AscI PFGE patterns. The distribution of these traits was assessed within further clinical, environmental and food isolates associated with the outbreak, and this comparison indicated that three distinct, but highly related strains may have been involved in this nationwide outbreak. Notably, these two isolates were found to harbor a 50 kbp putative mobile genomic island encoding translocation and efflux functions that has not been observed in other Listeria genomes. Conclusions High-throughput genome sequencing provided a more detailed real-time assessment of genetic traits characteristic of the outbreak strains than could be achieved with routine subtyping methods. This study confirms that the latest generation of DNA sequencing technologies can be applied during high priority public health events, and laboratories need to prepare for this inevitability and assess how to properly analyze and interpret whole genome sequences in the context of molecular epidemiology.

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