Comparison of phenotypic and WGS-derived antimicrobial resistance profiles of Campylobacter jejuni and Campylobacter coli isolated from cases of diarrhoeal disease in England and Wales, 2015–16. (16th January 2020)

• Record Type: Journal Article
• Authors: Painset, Anaïs; Day, Martin; Doumith, Michel; Rigby, Jonathan; Jenkins, Claire; Grant, Kathie; Dallman, Timothy J; Godbole, Gauri; Swift, Craig
• Is Part Of: Journal of antimicrobial chemotherapy. Volume 75:Number 4(2020)
• Page Start: 883
• Page End: 889
• Publication Date: 2020-01-16
• Subjects: Anti-infective agents -- Periodicals; Chemotherapy -- Periodicals; 615.58
• DOI: 10.1093/jac/dkz539
• Languages: English
• ISSNs: 0305-7453

Abstract

Abstract: Objectives: To compare and evaluate phenotypic and genotypic methods for the detection of antimicrobial resistance (AMR) in Campylobacter jejuni and Campylobacter coli in England and Wales. Methods: WGS data from 528 isolates of Campylobacter spp. (452 C. jejuni and 76 C. coli ) from human (494), food (21) and environmental (2) sources, collected between January 2015 and December 2016, and from the PHE culture collection (11) were mapped to genes known to be associated with phenotypic resistance to antimicrobials in the genus. Phenotypic antibiotic susceptibility (erythromycin, ciprofloxacin, tetracycline, gentamicin and streptomycin) testing using an in-agar dilution method was performed on all isolates. Results: Concordance between phenotypic resistance and the presence of corresponding AMR determinants was 97.5% (515/528 isolates). Only 13 out of 528 isolates (10 C. jejuni and 3 C. coli ) had discordant interpretations for at least one of the five antibiotics tested, equating to a total of 15 (0.6%) discrepancies out of 2640 isolate/antimicrobial combinations. Seven discrepant results were genotypically resistant but phenotypically susceptible (major errors) and eight discrepant results were genotypically susceptible but phenotypically resistant (very major errors). Conclusions: The use of this bioinformatics approach for predicting AMR from WGS data for routine public health surveillance is a reliable method for real-time monitoring of changing AMR patterns in isolates of C. jejuni and C. coli.