TY - JOUR
T1 - Latent class analysis to assess whole-genome sequencing versus broth microdilution for monitoring antimicrobial resistance in livestock
AU - Hesp, Ayla
AU - Veldman, Kees
AU - Brouwer, Michael S M
AU - Wagenaar, Jaap A
AU - Mevius, Dik
AU - van Schaik, Gerdien
N1 - Funding Information:
We thank the Ministry of Agriculture, Nature and Food Quality for funding the WOT-O project (WOT-01-002-003) for the sequencing of the bacterial isolates, and the EFFORT consortium for funding the susceptibility testing of the bacterial strains. Roosmarijn Luiken and Liese van Gompel we would like to thank for organizing the sampling of the EFFORT strains. We thankfully acknowledge Yvon Geurts, Alieda van Essen, Joop Testerink, Marga Japing and Albert de Boer for their technical assistance. We also acknowledge the contribution of Jeanet van der Goot to this work and Daniela Ceccarelli for analysing the MIC dataset within EFFORT, and Haitske Graveland for the project management within EFFORT. Finally, we would like to thank Bas Engel for his aid in optimizing the OpenBUGS coding.
Funding Information:
This research was supported by the Ministry of Agriculture, Nature and Food Quality ( WOT-01-002-003 ) and Wageningen Bioveterinary Research . The susceptibility testing of the bacterial strains was part of the Ecology from Farm to Fork Of microbial drug Resistance and Transmission (EFFORT) project, funded by the European Commission, 7th Framework Program for Research and Innovation ( FP7-KBBE-2013–7 , grant agreement: 613754).
Publisher Copyright:
© 2021 The Authors
PY - 2021/8
Y1 - 2021/8
N2 - Antimicrobial resistance (AMR) monitoring in animals is performed in commensal Escherichia coli, and other microorganisms relevant for human or veterinary health. Due to advances in the field and major reductions in cost, it is expected that whole-genome sequencing (WGS)-based antimicrobial susceptibility testing (AST) will (partly) replace culture-based AST. So far, no studies have been performed without using culture-based AST as the gold standard. Our aim was to use Bayesian latent class analysis to evaluate the accuracy of susceptibility testing of commensal E. coli by WGS-based AST versus culture-based AST as this test does not assume a gold standard. OpenBUGS was used to model two independent tests in three animal populations (N = 150, 50 bacterial isolates per population): veal calves, pigs, and broilers. This resulted in the first estimation of sensitivity and specificity of WGS-based AST versus culture-based AST to detect AMR without a gold standard. Both methods had high sensitivity (>0.92, lowest limit probability interval: 0.76) and specificity was generally high for both methods for all antimicrobial classes except for aminoglycosides and macrolides. We compared WGS results for different length and identity settings (%) of gene alignment and found few differences between the 60/90, 90/90 and 95/95 settings. We recommend to further investigate sensitivity and specificity of WGS-based AST by means of latent class analysis, especially for low-prevalent resistance.
AB - Antimicrobial resistance (AMR) monitoring in animals is performed in commensal Escherichia coli, and other microorganisms relevant for human or veterinary health. Due to advances in the field and major reductions in cost, it is expected that whole-genome sequencing (WGS)-based antimicrobial susceptibility testing (AST) will (partly) replace culture-based AST. So far, no studies have been performed without using culture-based AST as the gold standard. Our aim was to use Bayesian latent class analysis to evaluate the accuracy of susceptibility testing of commensal E. coli by WGS-based AST versus culture-based AST as this test does not assume a gold standard. OpenBUGS was used to model two independent tests in three animal populations (N = 150, 50 bacterial isolates per population): veal calves, pigs, and broilers. This resulted in the first estimation of sensitivity and specificity of WGS-based AST versus culture-based AST to detect AMR without a gold standard. Both methods had high sensitivity (>0.92, lowest limit probability interval: 0.76) and specificity was generally high for both methods for all antimicrobial classes except for aminoglycosides and macrolides. We compared WGS results for different length and identity settings (%) of gene alignment and found few differences between the 60/90, 90/90 and 95/95 settings. We recommend to further investigate sensitivity and specificity of WGS-based AST by means of latent class analysis, especially for low-prevalent resistance.
KW - Antimicrobial resistance
KW - Bayesian
KW - Broth microdilution
KW - Escherichia coli
KW - Livestock
KW - Monitoring
KW - Surveillance
KW - Whole-genome sequencing
UR - http://www.scopus.com/inward/record.url?scp=85108233494&partnerID=8YFLogxK
U2 - 10.1016/j.prevetmed.2021.105406
DO - 10.1016/j.prevetmed.2021.105406
M3 - Article
C2 - 34147959
SN - 0167-5877
VL - 193
SP - 1
EP - 6
JO - Preventive Veterinary Medicine
JF - Preventive Veterinary Medicine
M1 - 105406
ER -