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Clin Microbiol Infect. 2017 Jan;23(1):2-22. doi: 10.1016/j.cmi.2016.11.012. Epub 2016 Nov 23.

The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee.

Author information

1
Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK.
2
Department of Clinical Microbiology and the EUCAST Development Laboratory, Kronoberg Region, Central Hospital, Växjö, Sweden.
3
National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
4
Servicio de Microbiología, Hospital Ramón y Cajal and Instituto Ramón y Cajal de Investigación Sanitaria, Madrid, Spain.
5
Department of Laboratory Medicine, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden.
6
University Medical Centre Freiburg, Infection Prevention and Hospital Hygiene, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
7
Statens Serum Institute, Department of Microbiology and Infection Control, Copenhagen, Denmark.
8
School of Medicine, Medical & Biological Sciences, North Haugh, University of St Andrews, UK.
9
Westmead Institute for Medical Research, University of Sydney and Marie Bashir Institute, Sydney, NSW, Australia.
10
Department of Medicine, University of Cambridge, Cambridge, UK.
11
Department of Medical Microbiology, North Bristol NHS Trust, Southmead Hospital, Bristol, UK.
12
Central Veterinary Institute (CVI) part of Wageningen University and Research Centre (WUR), Lelystad, The Netherlands; Department of Infectious Diseases and Immunology, Utrecht University, Utrecht, The Netherlands.
13
National Microbiology Laboratory, Winnipeg, Manitoba, Canada.
14
French National Reference Centre for Antibiotic Resistance, Bacteriology-Hygiene unit, Hôpital Bicêtre, APHP, LabEx LERMIT, University Paris Sud, Le Kremlin-Bicêtre, France.
15
Nuffield Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK.
16
PU-PH des Disciplines Pharmaceutiques, 1-URMITE CNRS IRD UMR 6236, IHU Méditerranée Infection, Valorization and Transfer, Aix Marseille Université, Faculté de Médecine et de Pharmacie, Marseille, France.
17
Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, University Hospital of North Norway, Department of Microbiology and Infection Control, Tromsø, Norway.
18
Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK. Electronic address: neil.woodford@phe.gov.uk.

Abstract

Whole genome sequencing (WGS) offers the potential to predict antimicrobial susceptibility from a single assay. The European Committee on Antimicrobial Susceptibility Testing established a subcommittee to review the current development status of WGS for bacterial antimicrobial susceptibility testing (AST). The published evidence for using WGS as a tool to infer antimicrobial susceptibility accurately is currently either poor or non-existent and the evidence / knowledge base requires significant expansion. The primary comparators for assessing genotypic-phenotypic concordance from WGS data should be changed to epidemiological cut-off values in order to improve differentiation of wild-type from non-wild-type isolates (harbouring an acquired resistance). Clinical breakpoints should be a secondary comparator. This assessment will reveal whether genetic predictions could also be used to guide clinical decision making. Internationally agreed principles and quality control (QC) metrics will facilitate early harmonization of analytical approaches and interpretive criteria for WGS-based predictive AST. Only data sets that pass agreed QC metrics should be used in AST predictions. Minimum performance standards should exist and comparative accuracies across different WGS laboratories and processes should be measured. To facilitate comparisons, a single public database of all known resistance loci should be established, regularly updated and strictly curated using minimum standards for the inclusion of resistance loci. For most bacterial species the major limitations to widespread adoption for WGS-based AST in clinical laboratories remain the current high-cost and limited speed of inferring antimicrobial susceptibility from WGS data as well as the dependency on previous culture because analysis directly on specimens remains challenging. For most bacterial species there is currently insufficient evidence to support the use of WGS-inferred AST to guide clinical decision making. WGS-AST should be a funding priority if it is to become a rival to phenotypic AST. This report will be updated as the available evidence increases.

KEYWORDS:

Antimicrobial resistance; ECOFF; Epidemiological cut-off values; Next generation sequencing

PMID:
27890457
DOI:
10.1016/j.cmi.2016.11.012
[Indexed for MEDLINE]
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