Genomic analysis of Salmonella Typhimurium from humans and food sources accurately predicts phenotypic multi-drug resistance

Xin Yin, Yezhi Fu, Heather Tate, Casey Pinto, Edward G. Dudley, Nkuchia M. M'ikanatha

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Salmonella Typhimurium is the leading cause of foodborne illnesses in the U.S., causing over a million cases each year. In recent years, whole-genome sequencing (WGS) has become a standard tool for routine epidemiological subtyping. Objectives: The objectives of this study are 1) to compare the phenotypic and genotypic antimicrobial resistance (AMR) profiles of multidrug resistant (MDR) S. Typhimurium isolates, 2) to examine the genetic relatedness of a historic collection of MDR and pan-susceptible isolates from retail chickens. Methods: We used data on Salmonella Typhimurium isolates in the publicly available NARMS national clinical and retail meat datasets from 2016 to 2018. Staramr (0.5.1) was used to identify AMR determinants and predictive resistance from genomes submitted to NCBI. Sensitivity and specificity of the WGS method were calculated with phenotypic resistance results as the reference. SNP-based cluster analysis was used to examine the genetic relatedness of MDR resistant and pan-susceptible isolates from retail chickens. Results: The overall sensitivity of WGS as a predictor of clinical resistance was 96.47% and the overall specificity was 100.00%. The disagreement between phenotypic and genotypic results were mostly related to streptomycin. The MDR isolates differed by an average of 73.1 SNPs, while the pan-susceptible isolates differed by an average of 473.1 SNPs (p < 0.0001). The nearest distance between a pan-susceptible and an MDR isolate was 547 SNPs. Conclusion: WGS can reliably predict AMR in S. Typhimurium isolates and it can reveal genetic determinants to elucidate the evolution of antimicrobial resistance.

Original languageEnglish (US)
Article number103957
JournalFood Microbiology
Volume103
DOIs
StatePublished - May 2022

All Science Journal Classification (ASJC) codes

  • Food Science
  • Microbiology

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