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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. 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. 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. 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. WGS can reliably predict AMR in S. Typhimurium isolates and it can reveal genetic determinants to elucidate the evolution of antimicrobial resistance. • Whole genome sequencing (WGS) can reliably predict AMR in S. Typhimurium isolates. • WGS can reveal genetic determinants to elucidate the evolution of antimicrobial resistance. • The overall specificity of WGS in predicting antimicrobial resistance is 100%. • Multi-drug resistant S. Typhimurium isolates were genetically closer compared to pan-susceptible isolates. [ABSTRACT FROM AUTHOR]

Abstract: Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is a major cause of foodborne salmonellosis. Rapid, efficient and accurate methods for identification are required to track specific strains of S. Enteritidis during outbreaks of human salmonellosis. By exploiting the hypervariable nature of virulence genes and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs), we previously developed a powerful sequence-based subtyping approach, designated CRISPR-MVLST. To substantiate the applicability of CRISPR-MVLST, we analyzed a broad set of S. Enteritidis isolates collected over a six-year period. Among 141 isolates we defined 22 Enteritidis Sequence Types (ESTs), the majority of which were novel. Notably, strains exhibiting the common PFGE pattern, JEGX01.0004 (characteristic of ∼40% of S. Enteritidis isolates in the United States), were separated into twelve distinct sequence types. Conversely, isolates of EST4, the most predominant EST we observed, comprised eight different PFGE patterns. Importantly, we showed that some genotypes that were previously associated with the food supply chain at the farm level have now been identified in clinical samples. CRISPR sequence data shows subtle but distinct differences among different alleles of S. Enteritidis, suggesting that evolution of these loci occurs vertically, as opposed to previously reported evolution by spacer acquisition in other bacteria. [Copyright &y& Elsevier]