Whole-genome sequencing (WGS) via next-generation sequencing (NGS) technologies is a powerful tool for determining the relatedness of bacterial isolates in foodborne illness detection and outbreak investigations. WGS has been applied to national outbreaks (for example, Listeria monocytogenes); however, WGS has rarely been used in smaller local outbreaks. The current study demonstrates the superior resolution of genetic and evolutionary relatedness generated by WGS data analysis, compared to pulsed-field gel electrophoresis (PFGE). The current study retrospectively applies WGS and a reference-free bioinformatic analysis to a Utah-specific outbreak of Campylobacter jejuni associated with raw milk and to a national multistate outbreak of Salmonella enterica subsp. enterica serovar Typhimurium associated with rotisserie chicken, both of which were characterized previously by PFGE. Together, these analyses demonstrate how a reference-free WGS workflow is not reliant on determination of a reference sequence, like WGS workflows that are based on single-nucleotide polymorphisms, or the need for curated allele databases, like multilocus sequence typing workflows.
Keywords: bioinformatics; food-borne pathogens; next-generation sequencing.
Copyright © 2018 Oakeson et al.