Dataset Information

Genomic Analysis Reveals Antibiotic-Susceptible Clones and Emerging Resistance in Neisseria gonorrhoeae in Saskatchewan, Canada.

ABSTRACT: Whole-genome sequencing was used to identify mutations in antibiotic resistance-conferring genes to compare susceptibility predictions with MICs and to ascertain strain types in 99 isolates of Neisseria gonorrhoeae Genotypes associated with susceptibility, as well as MIC creep or emerging resistance, were noted. Phylogenomic analysis revealed three distinctive clades and putative gonococcal transmission linkages involving a tetracycline-resistant N. gonorrhoeae outbreak and the clonal spread of susceptible isolates in men.

SUBMITTER: Parmar NR

PROVIDER: S-EPMC7449210 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Genomic Analysis Reveals Antibiotic-Susceptible Clones and Emerging Resistance in Neisseria gonorrhoeae in Saskatchewan, Canada.

Parmar Nidhi R NR Singh Reema R Martin Irene I Perera Sumudu R SR Demczuk Walter W Kusalik Anthony A Minion Jessica J Dillon Jo-Anne R JR

Antimicrobial agents and chemotherapy 20200820 9

Whole-genome sequencing was used to identify mutations in antibiotic resistance-conferring genes to compare susceptibility predictions with MICs and to ascertain strain types in 99 isolates of <i>Neisseria gonorrhoeae</i> Genotypes associated with susceptibility, as well as MIC creep or emerging resistance, were noted. Phylogenomic analysis revealed three distinctive clades and putative gonococcal transmission linkages involving a tetracycline-resistant <i>N. gonorrhoeae</i> outbreak and the clo ...[more]

PMID: 32571818

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Project description:BackgroundTraditional methods for molecular epidemiology of Neisseria gonorrhoeae are suboptimal. Whole-genome sequencing (WGS) offers ideal resolution to describe population dynamics and to predict and infer transmission of antimicrobial resistance, and can enhance infection control through linkage with epidemiological data. We used WGS, in conjunction with linked epidemiological and phenotypic data, to describe the gonococcal population in 20 European countries. We aimed to detail changes in phenotypic antimicrobial resistance levels (and the reasons for these changes) and strain distribution (with a focus on antimicrobial resistance strains in risk groups), and to predict antimicrobial resistance from WGS data.MethodsWe carried out an observational study, in which we sequenced isolates taken from patients with gonorrhoea from the European Gonococcal Antimicrobial Surveillance Programme in 20 countries from September to November, 2013. We also developed a web platform that we used for automated antimicrobial resistance prediction, molecular typing (N gonorrhoeae multi-antigen sequence typing [NG-MAST] and multilocus sequence typing), and phylogenetic clustering in conjunction with epidemiological and phenotypic data.FindingsThe multidrug-resistant NG-MAST genogroup G1407 was predominant and accounted for the most cephalosporin resistance, but the prevalence of this genogroup decreased from 248 (23%) of 1066 isolates in a previous study from 2009-10 to 174 (17%) of 1054 isolates in this survey in 2013. This genogroup previously showed an association with men who have sex with men, but changed to an association with heterosexual people (odds ratio=4·29). WGS provided substantially improved resolution and accuracy over NG-MAST and multilocus sequence typing, predicted antimicrobial resistance relatively well, and identified discrepant isolates, mixed infections or contaminants, and multidrug-resistant clades linked to risk groups.InterpretationTo our knowledge, we provide the first use of joint analysis of WGS and epidemiological data in an international programme for regional surveillance of sexually transmitted infections. WGS provided enhanced understanding of the distribution of antimicrobial resistance clones, including replacement with clones that were more susceptible to antimicrobials, in several risk groups nationally and regionally. We provide a framework for genomic surveillance of gonococci through standardised sampling, use of WGS, and a shared information architecture for interpretation and dissemination by use of open access software.FundingThe European Centre for Disease Prevention and Control, The Centre for Genomic Pathogen Surveillance, Örebro University Hospital, and Wellcome.

Project description:Neisseria meningitidis and Neisseria gonorrhoeae are pathogenic bacteria that can cause human infections. While N. meningitidis infections are associated with bacterial meningitis and bacteremia, a strain of N. meningitidis, isolated from the urogenital system, has recently been associated with urethritis. As this strain is becoming prominent as an emerging pathogen, it is essential to assess identification tools for N. meningitidis and N. gonorrhoeae urogenital isolates. Consecutive N. meningitidis isolates recovered from urogenital cultures of symptomatic patients with presumptive diagnoses of gonorrhea and a random selection of N. gonorrhoeae isolates recovered from the same population within the same time frame were characterized with routine identification systems, antimicrobial susceptibility testing, and whole-genome sequencing. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), multilocus sequence typing, 16S rRNA gene sequence, and average nucleotide identity methods accurately identified 95% (18/19) of N. meningitidis and N. gonorrhoeae isolates. With the Aptima Combo 2 CT/NG test, 30% (3/10) of N. meningitidis isolates were misidentified as N. gonorrhoeae, but no misidentifications were found with the Xpert CT/NG nucleic acid amplification test (NAAT). Phylogenetic core genome and single nucleotide polymorphism (SNP)-based grouping analyses showed that urogenital N. meningitidis isolates were highly related and phylogenetically distinct from N. gonorrhoeae and respiratory N. meningitidis isolates but similar to urogenital N. meningitidis isolates from patients with urethritis in the United States. Urogenital N. meningitidis isolates were predominantly azithromycin resistant, while N. gonorrhoeae isolates were azithromycin susceptible. These data indicate that urogenital isolates of N. meningitidis can cause false-positive detections with N. gonorrhoeae diagnostic assays. Misidentification of urogenital N. meningitidis isolates may confound public health-related activities for gonorrhea, and future studies are needed to understand the impact on clinical outcome of N. meningitidis urogenital infection.

Dataset Information

Genomic Analysis Reveals Antibiotic-Susceptible Clones and Emerging Resistance in Neisseria gonorrhoeae in Saskatchewan, Canada.

Publications

Genomic Analysis Reveals Antibiotic-Susceptible Clones and Emerging Resistance in Neisseria gonorrhoeae in Saskatchewan, Canada.

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