Literature DB >> 27381390

Whole-Genome Sequencing for Detecting Antimicrobial Resistance in Nontyphoidal Salmonella.

Patrick F McDermott1, Gregory H Tyson2, Claudine Kabera2, Yuansha Chen2, Cong Li2, Jason P Folster3, Sherry L Ayers2, Claudia Lam2, Heather P Tate2, Shaohua Zhao2.   

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.
Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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Year:  2016        PMID: 27381390      PMCID: PMC4997858          DOI: 10.1128/AAC.01030-16

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  31 in total

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Journal:  J Clin Microbiol       Date:  2020-09-22       Impact factor: 5.948

2.  Circulation of Plasmids Harboring Resistance Genes to Quinolones and/or Extended-Spectrum Cephalosporins in Multiple Salmonella enterica Serotypes from Swine in the United States.

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3.  Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates.

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Journal:  Antimicrob Agents Chemother       Date:  2019-10-22       Impact factor: 5.191

4.  Establishing Genotypic Cutoff Values To Measure Antimicrobial Resistance in Salmonella.

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Journal:  Antimicrob Agents Chemother       Date:  2017-02-23       Impact factor: 5.191

5.  Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella.

Authors:  Marcus Nguyen; S Wesley Long; Patrick F McDermott; Randall J Olsen; Robert Olson; Rick L Stevens; Gregory H Tyson; Shaohua Zhao; James J Davis
Journal:  J Clin Microbiol       Date:  2019-01-30       Impact factor: 5.948

6.  Temporal encoding of bacterial identity and traits in growth dynamics.

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7.  Horizontal Gene Transfer and Acquired Antibiotic Resistance in Salmonella enterica Serovar Heidelberg following In Vitro Incubation in Broiler Ceca.

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8.  Occurrence, quantification, pulse types, and antimicrobial susceptibility of Salmonella sp. isolated from chicken meat in the state of Paraná, Brazil.

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9.  Genomic Investigation of the Emergence of Invasive Multidrug-Resistant Salmonella enterica Serovar Dublin in Humans and Animals in Canada.

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Journal:  Antimicrob Agents Chemother       Date:  2019-05-24       Impact factor: 5.191

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Authors:  Scott Quainoo; Jordy P M Coolen; Sacha A F T van Hijum; Martijn A Huynen; Willem J G Melchers; Willem van Schaik; Heiman F L Wertheim
Journal:  Clin Microbiol Rev       Date:  2017-10       Impact factor: 26.132

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