Use of whole genome sequencing of commensal Escherichia coli in pigs for antimicrobial resistance surveillance, United Kingdom, 2018

Author:

Stubberfield Emma1,AbuOun Manal1,Sayers Ellie21,O’Connor Heather M3,Card Roderick M1,Anjum Muna F1

Affiliation:

1. Department of Bacteriology, Animal and Plant Health Agency, Weybridge, Surrey, United Kingdom

2. University of East Anglia/Quadram Institute Bioscience, Norwich Research Park, Norwich, United Kingdom

3. Department of Epidemiological Sciences, Animal and Plant Health Agency, Weybridge, Surrey, United Kingdom

Abstract

Background Surveillance of commensal Escherichia coli, a possible reservoir of antimicrobial resistance (AMR) genes, is important as they pose a risk to human and animal health. Most surveillance activities rely on phenotypic characterisation, but whole genome sequencing (WGS) presents an alternative. Aim In this retrospective study, we tested 515 E. coli isolated from pigs to evaluate the use of WGS to predict resistance phenotype. Methods Minimum inhibitory concentration (MIC) was determined for nine antimicrobials of clinical and veterinary importance. Deviation from wild-type, fully-susceptible MIC was assessed using European Committee on Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off (ECOFF) values. Presence of AMR genes and mutations were determined using APHA SeqFinder. Statistical two-by-two table analysis and Cohen’s kappa (k) test were applied to assess genotype and phenotype concordance. Results Overall, correlation of WGS with susceptibility to the nine antimicrobials was 98.9% for test specificity, and 97.5% for the positive predictive value of a test. The overall kappa score (k = 0.914) indicated AMR gene presence was highly predictive of reduced susceptibility and showed excellent correlation with MIC. However, there was variation for each antimicrobial; five showed excellent correlation; four very good and one moderate. Suggested ECOFF adjustments increased concordance between genotypic data and kappa values for four antimicrobials. Conclusion WGS is a powerful tool for accurately predicting AMR that can be used for national surveillance purposes. Additionally, it can detect resistance genes from a wider panel of antimicrobials whose phenotypes are currently not monitored but may be of importance in the future.

Publisher

European Centre for Disease Control and Prevention (ECDC)

Subject

Virology,Public Health, Environmental and Occupational Health,Epidemiology

Reference37 articles.

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4. The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2015.;EFSA J,2017

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