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

Abstract

BackgroundSurveillance 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.AimIn this retrospective study, we tested 515 E. coli isolated from pigs to evaluate the use of WGS to predict resistance phenotype.MethodsMinimum 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.ResultsOverall, 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.ConclusionWGS 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.

The importance of using whole genome sequencing and extended spectrum beta-lactamase selective media when monitoring antimicrobial resistance

“…The monitoring of isolates by WGS provides a wealth of data, as we have shown previously 16 , and in this paper there was very good correlation between resistance genotypes and resistance phenotypes determined by MICs and applying ECOFFs, which improved further on addition of a gene variant to our APHA SeqFinder AMR database. We believe this criterion applies widely, and demonstrates the need for continual assessment, and iterative improvement of WGS pipelines.…”

“…A secondary aim of the study was to compare isolates from the EU monitoring agar, MacConkey + 1 mg/L cefotaxime with an additional ESBL agar, to determine any benefits from using an additional agar. AMR genotypes of isolates were characterised in detail through the APHA SeqFinder WGS pipeline that we have validated for use in AMR surveillance 16 . Selected plasmids carrying AMR genes, including MDR plasmids, were characterised by long read sequencing, and compared to those from NCBI and other studies to look at transmission and persistence.…”

Comparative Evaluation of CHROMagar COL-APSE, MicroScan Walkaway, ComASP Colistin, and Colistin MAC Test in Detecting Colistin-resistant Gram-Negative Bacteria

“…It's efficacy in detecting mcr genes among K. pneumoniae also needs further investigation. Further studies must look at WGS and its performance in rapidly detecting mcr-harbouring strains of Gram-negative bacteria that are colistin-resistant 25 ethical consent. This study is part of an umbrella study with the ethics no 483/2016.…”

ResFinder 4.0 for predictions of phenotypes from genotypes

“…It has been shown that the number of isolates showing genotype–phenotype concordance notably increased when adjusting the ECOFF of certain antimicrobial agents. 26 Low read depth was also a likely source of some of the genotype–phenotype discordances observed (Figure 1 ). There is no unequivocally accepted threshold for acceptable read depth for detection of AMR genes and mutations, and our definition of ‘low read depth’ derived from a case-by-case examination.…”

“…We are aware that the use of WGS to guide antimicrobial therapy is often encountered with scepticism, and indeed genotype–phenotype concordance when using phenotypic results interpreted according to clinical breakpoints diminished for a few antimicrobial–species combinations (Tables S6 and S7 ), as also previously observed. 26 However, several discordances concerned isolates that harboured AMR determinants despite being classified as phenotypically susceptible, which may lead to therapeutic failures. Thus, the current practice of using MICs to guide dosing regimens may not be as appropriate as commonly believed, as also indicated recently by others.…”