Prediction of antimicrobial resistance in clinical Campylobacter jejuni isolates from whole-genome sequencing data
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ORIGINAL ARTICLE
Prediction of antimicrobial resistance in clinical Campylobacter jejuni isolates from whole-genome sequencing data Louise Gade Dahl 1 & Katrine Grimstrup Joensen 1 & Mark Thomas Østerlund 1 & Kristoffer Kiil 1 & Eva Møller Nielsen 1 Received: 14 July 2020 / Accepted: 17 September 2020 # The Author(s) 2020
Abstract Campylobacter jejuni is recognised as the leading cause of bacterial gastroenteritis in industrialised countries. Although the majority of Campylobacter infections are self-limiting, antimicrobial treatment is necessary in severe cases. Therefore, the development of antimicrobial resistance (AMR) in Campylobacter is a growing public health challenge and surveillance of AMR is important for bacterial disease control. The aim of this study was to predict antimicrobial resistance in C. jejuni from whole-genome sequencing data. A total of 516 clinical C. jejuni isolates collected between 2014 and 2017 were subjected to WGS. Resistance phenotypes were determined by standard broth dilution, categorising isolates as either susceptible or resistant based on epidemiological cutoffs for six antimicrobials: ciprofloxacin, nalidixic acid, erythromycin, gentamicin, streptomycin, and tetracycline. Resistance genotypes were identified using an in-house database containing reference genes with known point mutations and the presence of resistance genes was determined using the ResFinder database and four bioinformatical methods (modified KMA, ABRicate, ARIBA, and ResFinder Batch Upload). We identified seven resistance genes including tet(O), tet(O/32/O), ant(6)-Ia, aph(2″)-If, blaOXA, aph(3′)-III, and cat as well as mutations in three genes: gyrA, 23S rRNA, and rpsL. There was a high correlation between phenotypic resistance and the presence of known resistance genes and/or point mutations. A correlation above 98% was seen for all antimicrobials except streptomycin with a correlation of 92%. In conclusion, we found that WGS can predict antimicrobial resistance with a high degree of accuracy and have the potential to be a powerful tool for AMR surveillance. Keywords Campylobacter jejuni . Antimicrobial resistance . Whole-genome sequencing . Public health . AMR surveillance
Introduction Campylobacter is a foodborne bacterial pathogen, which is able to cause gastroenteritis in humans and is found in the environment where it is widely distributed in the gastrointestinal tract of most warm-blooded animals [1]. Foodborne transmission is believed to be the main route of human infection [2, 3]. In 2018, Campylobacter continued to be the most common foodborne pathogen causing infections in Denmark with more than 4500 registered cases; most of these were Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10096-020-04043-y) contains supplementary material, which is available to authorized users. * Eva Møller Nielsen [email protected] 1
Department of Bacteria, Parasites & Fungi, Statens Serum Institut, Copenhagen, Denmark
caused by C. jejuni (85–95%) [4]. Clinical symptoms du
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