Dataset Information

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

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 ?-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.

SUBMITTER: McDermott PF

PROVIDER: S-EPMC4997858 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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

McDermott Patrick F PF Tyson Gregory H GH Kabera Claudine C Chen Yuansha Y Li Cong C Folster Jason P JP Ayers Sherry L SL Lam Claudia C Tate Heather P HP Zhao Shaohua S

Antimicrobial agents and chemotherapy 20160822 9

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 sele ...[more]

PMID: 27381390

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Project description:Antimicrobial resistance was investigated in 2,341 nontyphoidal Salmonella (NTS) isolates recovered from humans in Taiwan from 2017 to 2018 using antimicrobial susceptibility testing. Azithromycin resistance determinants were detected in 175 selected isolates using PCR and confirmed in 81 selected isolates using whole-genome sequencing. Multidrug resistance was found in 47.3% of total isolates and 96.2% of Salmonella enterica serovar Anatum and 81.7% of S. enterica serovar Typhimurium isolates. Resistance to the conventional first-line drugs (ampicillin, chloramphenicol, and cotrimoxazole), cefotaxime and ceftazidime, and ciprofloxacin was found in 32.5 to 49.0%, 20.3 to 20.4%, and 3.2% of isolates, respectively. A total of 76 (3.1%) isolates were resistant to azithromycin, which was associated with mph(A), erm(42), erm(B), and possibly the enhanced expression of efflux pump(s) due to ramAp or defective ramR. mph(A) was found in 53% of the 76 azithromycin-resistant isolates from 11 serovars and located in an IS26-mph(A)-mrx(A)-mphR(A)-IS6100 unit in various incompatibility plasmids and the chromosomes. erm(42) in S. enterica serovar Albany was carried by an integrative and conjugative element, ICE_erm42, and in S. enterica serovar Enteritidis and S. Typhimurium was located in IS26 composite transposons in the chromosomes. erm(B) was carried by IncI1-I(α) plasmids in S. Enteritidis and S. Typhimurium. ramAp was a plasmid-borne ramA, a regulatory activator of efflux pump(s), found in only S. enterica serovar Goldcoast. Since the azithromycin resistance determinants are primarily carried on mobile genetic elements, they could easily be disseminated among human bacterial pathogens. The ramAp-carrying S. Goldcoast isolates displayed azithromycin MICs of 16 to 32 mg/L. Thus, the epidemiological cutoff value of ≤16 mg/L of azithromycin proposed for wild-type NTS should be reconsidered. IMPORTANCE Antimicrobial resistance in NTS isolates is a major public health concern in Taiwan, and the mechanisms of azithromycin resistance are rarely investigated. Azithromycin and carbapenems are the last resort for the treatment of invasive salmonellosis caused by multidrug-resistant (MDR) and extensively drug-resistant Salmonella strains. Our study reports the epidemiological trend of resistance in NTS in Taiwan and the genetic determinants involved in azithromycin resistance. We point out that nearly half of NTS isolates from 2017 to 2018 are MDR, and 20% are resistant to third-generation cephalosporins. The azithromycin resistance rate (3.1%) for the NTS isolates from Taiwan is much higher than those for the NTS isolates from the United States and Europe. Our study also indicates that azithromycin resistance is primarily mediated by mph(A), erm(42), erm(B), and ramAp, which are frequently carried on mobile genetic elements. Thus, the azithromycin resistance determinants could be expected to be disseminated among diverse bacterial pathogens.

Dataset Information

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

Publications

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

Similar Datasets

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