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. 2016 Aug 22;60(9):5515-20.
doi: 10.1128/AAC.01030-16. Print 2016 Sep.

Whole-Genome Sequencing for Detecting Antimicrobial Resistance in Nontyphoidal Salmonella

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Whole-Genome Sequencing for Detecting Antimicrobial Resistance in Nontyphoidal Salmonella

Patrick F McDermott et al. Antimicrob Agents Chemother. .

Abstract

Laboratory-based in vitro antimicrobial susceptibility testing is the foundation for guiding anti-infective therapy and monitoring antimicrobial resistance trends. We used whole-genome sequencing (WGS) technology to identify known antimicrobial resistance determinants among strains of nontyphoidal Salmonella and correlated these with susceptibility phenotypes to evaluate the utility of WGS for antimicrobial resistance surveillance. Six hundred forty Salmonella of 43 different serotypes were selected from among retail meat and human clinical isolates that were tested for susceptibility to 14 antimicrobials using broth microdilution. The MIC for each drug was used to categorize isolates as susceptible or resistant based on Clinical and Laboratory Standards Institute clinical breakpoints or National Antimicrobial Resistance Monitoring System (NARMS) consensus interpretive criteria. Each isolate was subjected to whole-genome shotgun sequencing, and resistance genes were identified from assembled sequences. A total of 65 unique resistance genes, plus mutations in two structural resistance loci, were identified. There were more unique resistance genes (n = 59) in the 104 human isolates than in the 536 retail meat isolates (n = 36). Overall, resistance genotypes and phenotypes correlated in 99.0% of cases. Correlations approached 100% for most classes of antibiotics but were lower for aminoglycosides and beta-lactams. We report the first finding of extended-spectrum β-lactamases (ESBLs) (blaCTX-M1 and blaSHV2a) in retail meat isolates of Salmonella in the United States. Whole-genome sequencing is an effective tool for predicting antibiotic resistance in nontyphoidal Salmonella, although the use of more appropriate surveillance breakpoints and increased knowledge of new resistance alleles will further improve correlations.

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This work was supported by the U.S. Food and Drug Administration with internal funds as part of routine work.

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