Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli

The increasing prevalence of antimicrobial resistance (AMR) in Campylobacter spp. is a global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict AMR in Campylobacter jejuni and C. coli. A panel of 271 isolates recovered from Canadian poultry was used to compare AMR gen...

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Autores principales:	Lisa M. Hodges, Eduardo N. Taboada, Adam Koziol, Steven Mutschall, Burton W. Blais, G. Douglas Inglis, Daniel Leclair, Catherine D. Carrillo
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	Campylobacter antimicrobial resistance whole-genome sequence (WGS) bioinformatic tools AMR surveillance Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/02e31b638c124180b853c7b13adb14a0
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spelling	oai:doaj.org-article:02e31b638c124180b853c7b13adb14a02021-11-16T06:00:29ZSystematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli1664-302X10.3389/fmicb.2021.776967https://doaj.org/article/02e31b638c124180b853c7b13adb14a02021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmicb.2021.776967/fullhttps://doaj.org/toc/1664-302XThe increasing prevalence of antimicrobial resistance (AMR) in Campylobacter spp. is a global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict AMR in Campylobacter jejuni and C. coli. A panel of 271 isolates recovered from Canadian poultry was used to compare AMR genotype to antimicrobial susceptibility testing (AST) results (azithromycin, ciprofloxacin, erythromycin, gentamicin, tetracycline, florfenicol, nalidixic acid, telithromycin, and clindamycin). The presence of antibiotic resistance genes (ARGs) was determined for each isolate using five computational approaches to evaluate the effect of: ARG screening software, input data (i.e., raw reads, draft genome assemblies), genome coverage and genome assembly software. Overall, concordance between the genotype and phenotype was influenced by the computational pipelines, level of genome coverage and the type of ARG but not by input data. For example, three of the pipelines showed a 99% agreement between detection of a tet(O) gene and tetracycline resistance, whereas agreement between the detection of tet(O) and TET resistance was 98 and 93% for two pipelines. Overall, higher levels of genome coverage were needed to reliably detect some ARGs; for example, at 15X coverage a tet(O) gene was detected in >70% of the genomes, compared to <60% of the genomes for bla(OXA). No genes associated with florfenicol or gentamicin resistance were found in the set of strains included in this study, consistent with AST results. Macrolide and fluoroquinolone resistance was associated 100% with mutations in the 23S rRNA (A2075G) and gyrA (T86I) genes, respectively. A lower association between a A2075G 23S rRNA gene mutation and resistance to clindamycin and telithromycin (92.8 and 78.6%, respectively) was found. While WGS is an effective approach to predicting AMR in Campylobacter, this study demonstrated the impact that computational pipelines, genome coverage and the genes can have on the reliable identification of an AMR genotype.Lisa M. HodgesEduardo N. TaboadaAdam KoziolSteven MutschallBurton W. BlaisG. Douglas InglisDaniel LeclairCatherine D. CarrilloFrontiers Media S.A.articleCampylobacterantimicrobial resistancewhole-genome sequence (WGS)bioinformatic toolsAMR surveillanceMicrobiologyQR1-502ENFrontiers in Microbiology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Campylobacter antimicrobial resistance whole-genome sequence (WGS) bioinformatic tools AMR surveillance Microbiology QR1-502
spellingShingle	Campylobacter antimicrobial resistance whole-genome sequence (WGS) bioinformatic tools AMR surveillance Microbiology QR1-502 Lisa M. Hodges Eduardo N. Taboada Adam Koziol Steven Mutschall Burton W. Blais G. Douglas Inglis Daniel Leclair Catherine D. Carrillo Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli
description	The increasing prevalence of antimicrobial resistance (AMR) in Campylobacter spp. is a global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict AMR in Campylobacter jejuni and C. coli. A panel of 271 isolates recovered from Canadian poultry was used to compare AMR genotype to antimicrobial susceptibility testing (AST) results (azithromycin, ciprofloxacin, erythromycin, gentamicin, tetracycline, florfenicol, nalidixic acid, telithromycin, and clindamycin). The presence of antibiotic resistance genes (ARGs) was determined for each isolate using five computational approaches to evaluate the effect of: ARG screening software, input data (i.e., raw reads, draft genome assemblies), genome coverage and genome assembly software. Overall, concordance between the genotype and phenotype was influenced by the computational pipelines, level of genome coverage and the type of ARG but not by input data. For example, three of the pipelines showed a 99% agreement between detection of a tet(O) gene and tetracycline resistance, whereas agreement between the detection of tet(O) and TET resistance was 98 and 93% for two pipelines. Overall, higher levels of genome coverage were needed to reliably detect some ARGs; for example, at 15X coverage a tet(O) gene was detected in >70% of the genomes, compared to <60% of the genomes for bla(OXA). No genes associated with florfenicol or gentamicin resistance were found in the set of strains included in this study, consistent with AST results. Macrolide and fluoroquinolone resistance was associated 100% with mutations in the 23S rRNA (A2075G) and gyrA (T86I) genes, respectively. A lower association between a A2075G 23S rRNA gene mutation and resistance to clindamycin and telithromycin (92.8 and 78.6%, respectively) was found. While WGS is an effective approach to predicting AMR in Campylobacter, this study demonstrated the impact that computational pipelines, genome coverage and the genes can have on the reliable identification of an AMR genotype.
format	article
author	Lisa M. Hodges Eduardo N. Taboada Adam Koziol Steven Mutschall Burton W. Blais G. Douglas Inglis Daniel Leclair Catherine D. Carrillo
author_facet	Lisa M. Hodges Eduardo N. Taboada Adam Koziol Steven Mutschall Burton W. Blais G. Douglas Inglis Daniel Leclair Catherine D. Carrillo
author_sort	Lisa M. Hodges
title	Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli
title_short	Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli
title_full	Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli
title_fullStr	Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli
title_full_unstemmed	Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli
title_sort	systematic evaluation of whole-genome sequencing based prediction of antimicrobial resistance in campylobacter jejuni and c. coli
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/02e31b638c124180b853c7b13adb14a0
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Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli

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