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J Clin Microbiol. 2016 Feb;54(2):289-95. doi: 10.1128/JCM.02200-15. Epub 2015 Nov 18.

Usefulness of High-Quality Core Genome Single-Nucleotide Variant Analysis for Subtyping the Highly Clonal and the Most Prevalent Salmonella enterica Serovar Heidelberg Clone in the Context of Outbreak Investigations.

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Laboratoire de santé publique du Québec, Québec, Canada University of Montreal, Department of Microbiology and Immunology, Québec, Canada
National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada.
Laboratoire de santé publique du Québec, Québec, Canada.
Laboratoire de santé publique du Québec, Québec, Canada Department of Medicine, Division of Experimental Medicine, McGill University, Montréal, Québec, Canada.
Agence de la santé et des services sociaux de la Montérégie, Québec, Canada.
Ministère de la Santé et des Services Sociaux, Québec, Canada.
Ministère de l'Agriculture, des Pêcheries, et de l'Alimentation du Québec, Québec, Canada.
Direction de santé publique de la Capitale-Nationale, Québec, Canada.
Laboratoire de santé publique du Québec, Québec, Canada University of Montreal, Department of Microbiology and Immunology, Québec, Canada.


Salmonella enterica serovar Heidelberg is the second most frequently occurring serovar in Quebec and the third-most prevalent in Canada. Given that conventional pulsed-field gel electrophoresis (PFGE) subtyping for common Salmonella serovars, such as S. Heidelberg, yields identical subtypes for the majority of isolates recovered, public health laboratories are desperate for new subtyping tools to resolve highly clonal S. Heidelberg strains involved in outbreak events. As PFGE was unable to discriminate isolates from three epidemiologically distinct outbreaks in Quebec, this study was conducted to evaluate whole-genome sequencing (WGS) and phylogenetic analysis as an alternative to conventional subtyping tools. Genomes of 46 isolates from 3 Quebec outbreaks (2012, 2013, and 2014) supported by strong epidemiological evidence were sequenced and analyzed using a high-quality core genome single-nucleotide variant (hqSNV) bioinformatics approach (SNV phylogenomics [SNVphyl] pipeline). Outbreaks were indistinguishable by conventional PFGE subtyping, exhibiting the same PFGE pattern (SHEXAI.0001/SHEBNI.0001). Phylogenetic analysis based on hqSNVs extracted from WGS separated the outbreak isolates into three distinct groups, 100% concordant with the epidemiological data. The minimum and maximum number of hqSNVs between isolates from the same outbreak was 0 and 4, respectively, while >59 hqSNVs were measured between 2 previously indistinguishable outbreaks having the same PFGE and phage type, thus corroborating their distinction as separate unrelated outbreaks. This study demonstrates that despite the previously reported high clonality of this serovar, the WGS-based hqSNV approach is a superior typing method, capable of resolving events that were previously indistinguishable using classic subtyping tools.

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