Retrospective whole-genome sequencing analysis distinguished PFGE and drug-resistance-matched retail meat and clinical Salmonella isolates

Andrea B. Keefer, Lingzi Xiaoli, Nkuchia M. M’ikanatha, Kuan Yao, Maria Hoffmann, Edward G. Dudley

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Non-typhoidal Salmonella is a leading cause of outbreak and sporadic-associated foodborne illnesses in the United States. These infections have been associated with a range of foods, including retail meats. Traditionally, pulsed-field gel electrophoresis (PFGE) and antibiotic susceptibility testing (AST) have been used to facilitate public health investigations of Salmonella infections. However, whole-genome sequencing (WGS) has emerged as an alternative tool that can be routinely implemented. To assess its potential in enhancing integrated surveillance in Pennsylvania, USA, WGS was used to directly compare the genetic characteristics of 7 retail meat and 43 clinical historic Salmonella isolates, subdivided into 3 subsets based on PFGE and AST results, to retrospectively resolve their genetic relatedness and identify antimicrobial resistance (AMR) determinants. Single nucleotide polymorphism (SNP) analyses revealed that the retail meat isolates within S. Heidelberg, S. Typhimurium var. O5- subset 1 and S. Typhimurium var. O5- subset 2 were separated from each primary PFGE pattern-matched clinical isolate by 6-12, 41-96 and 21-81 SNPs, respectively. Fifteen resistance genes were identified across all isolates, including fosA7, a gene only recently found in a limited number of Salmonella and a ≥95%phenotype to genotype correlation was observed for all tested antimicrobials. Moreover, AMR was primarily plasmid-mediated in S. Heidelberg and S. Typhimurium var. O5- subset 2, whereas AMR was chromosomally carried in S. Typhimurium var. O5- subset 1. Similar plasmids were identified in both the retail meat and clinical isolates. Collectively, these data highlight the utility of WGS in retrospective analyses and enhancing integrated surveillance for Salmonella from multiple sources.

Original languageEnglish (US)
Article number000768
Pages (from-to)270-286
Number of pages17
JournalMicrobiology (United Kingdom)
Volume165
Issue number3
DOIs
StatePublished - Mar 2019

All Science Journal Classification (ASJC) codes

  • Microbiology

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