Comparison of advanced whole genome sequence-based methods to distinguish strains of Salmonella enterica serovar Heidelberg involved in foodborne outbreaks in Québec. (August 2018) - Vincent, Caroline; Usongo, Valentine; Berry, Chrystal; Tremblay, Denise M.; Moineau, Sylvain; Yousfi, Khadidja; Doualla-Bell, Florence; Fournier, Eric; Nadon, Céline; Goodridge, Lawrence; Bekal, Sadjia
Abstract: Salmonella enterica serovar Heidelberg ( S. Heidelberg) is one of the top serovars causing human salmonellosis. This serovar ranks second and third among serovars that cause human infections in Québec and Canada, respectively, and has been associated with severe infections. Traditional typing methods such as PFGE do not display adequate discrimination required to resolve outbreak investigations due to the low level of genetic diversity of isolates belonging to this serovar. This study evaluates the ability of four whole genome sequence (WGS)-based typing methods to differentiate among 145 S. Heidelberg strains involved in four distinct outbreak events and sporadic cases of salmonellosis that occurred in Québec between 2007 and 2016. Isolates from all outbreaks were indistinguishable by PFGE. The core genome single nucleotide variant (SNV), core genome multilocus sequence typing (MLST) and whole genome MLST approaches were highly discriminatory and separated outbreak strains into four distinct phylogenetic clusters that were concordant with the epidemiological data. The clustered regularly interspaced short palindromic repeats (CRISPR) typing method was less discriminatory. However, CRISPR typing may be used as a secondary method to differentiate isolates of S. Heidelberg that are genetically similar but epidemiologically unrelated to outbreak events. WGS-based typing methods provide a highly discriminatory alternative to PFGE for the laboratory investigation of foodborne outbreaks. Highlights: PFGE lacks the discriminatory power to accurately inform the relatedness of S. Heidelberg isolates. Combining multiple WGS-based approaches together with epidemiologic evidence increases the accuracy of foodborne outbreaks. CRISPR typing can be useful as a complimentary method to add another layer of discriminatory power to cgSNV and cg/wgMLST. This study provides strong validation data to support the capacity of using recently developed WGS-based subtyping methods.