Whole Genome and Core Genome Multilocus Sequence Typing and Single Nucleotide Polymorphism Analyses of Listeria monocytogenes Isolates Associated with an Outbreak Linked to Cheese, United States, 2013

Abstract

Epidemiological findings of a listeriosis outbreak in 2013 implicated Hispanic-style cheese produced by company A, and pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) were performed on clinical isolates and representative isolates collected from company A cheese and environmental samples during the investigation. The results strengthened the evidence for cheese as the vehicle. Surveillance sampling and WGS 3 months later revealed that the equipment purchased by company B from company A yielded an environmental isolate highly similar to all outbreak isolates. The whole genome and core genome multilocus sequence typing and single nucleotide polymorphism (SNP) analyses results were compared to demonstrate the maximum discriminatory power obtained by using multiple analyses, which were needed to differentiate outbreak-associated isolates from a PFGE-indistinguishable isolate collected in a nonimplicated food source in 2012. This unrelated isolate differed from the outbreak isolates by only 7 to 14 SNPs, and as a result, the minimum spanning tree from the whole genome analyses and certain variant calling approach and phylogenetic algorithm for core genome-based analyses could not provide differentiation between unrelated isolates. Our data also suggest that SNP/allele counts should always be combined with WGS clustering analysis generated by phylogenetically meaningful algorithms on a sufficient number of isolates, and the SNP/allele threshold alone does not provide sufficient evidence to delineate an outbreak. The putative prophages were conserved across all the outbreak isolates. All outbreak isolates belonged to clonal complex 5 and serotype 1/2b and had an identical inlA sequence which did not have premature stop codons.IMPORTANCE In this outbreak, multiple analytical approaches were used for maximum discriminatory power. A PFGE-matched, epidemiologically unrelated isolate had high genetic similarity to the outbreak-associated isolates, with as few as 7 SNP differences. Therefore, the SNP/allele threshold should not be used as the only evidence to define the scope of an outbreak. It is critical that the SNP/allele counts be complemented by WGS clustering analysis generated by phylogenetically meaningful algorithms to distinguish outbreak-associated isolates from epidemiologically unrelated isolates. Careful selection of a variant calling approach and phylogenetic algorithm is critical for core-genome-based analyses. The whole-genome-based analyses were able to construct the highly resolved phylogeny needed to support the findings of the outbreak investigation. Ultimately, epidemiologic evidence and multiple WGS analyses should be combined to increase confidence levels during outbreak investigations.

An outbreak of multiple genotypes of Listeria monocytogenes in New Zealand linked to contaminated ready-to-eat meats—a retrospective analysis using whole-genome sequencing

“…These levels of allele and SNP differences between clinical isolates B1 and A1 and the absence of any epidemiological connection suggest that the clinical isolate from hospital B was outside the epidemiologically relevant timeframe and therefore not associated with the outbreak in hospital A. Multiple WGS analyses, such as cgMLST and SNP analysis, were also observed to increase the confidence during the current outbreak investigation as previously reported (Chen et al 2017). Figure 2 Dendrogram of whole-genome single nucleotide polymorphism (SNP) analysis of Listeria monocytogenes isolates associated with the outbreak and relevant isolates from the microbiological survey.…”

“…Internationally recognized thresholds for cgMLST allele or SNP analysis differences between genetically related isolates are still being established. Publications describing the use of WGS within listeriosis outbreaks globally have reported ≤12 alleles by whole‐genome MLST or ranges of 0–50 SNPs as criteria to distinguish outbreak‐related isolates from unrelated isolates (Ruppitsch et al ; Jackson et al ; Moura et al ; Chen et al ; Moura et al ; Smith et al ). However, there is some variation between studies regarding the classification of strains as closely linked (Jackson et al ; Besser et al ).…”

ConFindr: Rapid detection of intraspecies and cross-species contamination in bacterial whole-genome sequence data

“…WGS pipelines for public-health microbiology often include analyses of SNVs among a group of isolates to assess evolutionary relatedness and/or detection of genetic targets (e.g. serotype markers, virulence determinants) (Lambert et al, 2015;Ronholm et al, 2016;Allard et al, 2016;Chen et al, 2017).…”

Applications of Genomics in Regulatory Food Safety Testing in Canada

“…The highest-resolution WGS-based analyses such as wgMLST and singlenucleotide variant (SNV) analyses provide unrivaled DNA fingerprinting capability and offer tremendous potential for food safety applications [41,42,47]. Still, the use of these analyses in a food safety context is in its infancy, and the interpretation of genomic data from foodborne pathogens in support of regulatory interventions remains challenging [48].…”