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

• Yi Chen ^[1] ; Yan Luo ^[1] ; Heather Carleton ^[2] ; Ruth Timme ^[1] ; David Melka ^[1] ; Tim Muruvanda ^[1] ; Charles Wang ^[1] ; George Kastanis ^[1] ; Lee S. Katz ^[2] ; Lauren Turner ^[3] ; Angela Fritzinger ^[3] ; Terence Moore ^[4] ; Robert Stones ^[5] ; Joseph Blankenship ^[1] ; Monique Salter ^[1] ; Mickey Parish ^[1] ; Thomas S. Hammack ^[1] ; Peter S. Evans ^[1] ; Cheryl L. Tarr ^[2] ; Marc W. Allard ^[1] ; Errol A. Strain ^[1] ; Eric W. Brown ^[1]
  1. [1] University of Maryland, College Park

     University of Maryland, College Park

     Estados Unidos

     
  2. [2] bCenters for Disease Control and Prevention, Atlanta, Georgia, USA
  3. [3] cVirginia Division of Consolidated Laboratory Services, Richmond, Virginia, USA
  4. [4] dMaryland Department of Health and Mental Hygiene, Baltimore, Maryland, USA
  5. [5] eNewcastle University, Newcastle upon Tyne, United Kingdom

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• Localización: Applied and Environmental Microbiology, ISSN 0099-2240, Vol. 83, Nº 15, 2017
• Idioma: inglés
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  • 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.