Literature DB >> 27890457

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

M J Ellington1, O Ekelund2, F M Aarestrup3, R Canton4, M Doumith1, C Giske5, H Grundman6, H Hasman7, M T G Holden8, K L Hopkins1, J Iredell9, G Kahlmeter2, C U Köser10, A MacGowan11, D Mevius12, M Mulvey13, T Naas14, T Peto15, J-M Rolain16, Ø Samuelsen17, N Woodford18.   

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. Crown
Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Entities:  

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

Mesh:

Substances:

Year:  2016        PMID: 27890457     DOI: 10.1016/j.cmi.2016.11.012

Source DB:  PubMed          Journal:  Clin Microbiol Infect        ISSN: 1198-743X            Impact factor:   8.067


  143 in total

1.  Lowering the Barriers to Routine Whole-Genome Sequencing of Bacteria in the Clinical Microbiology Laboratory.

Authors:  Daniel D Rhoads
Journal:  J Clin Microbiol       Date:  2018-08-27       Impact factor: 5.948

2.  Evaluation of the Amplidiag CarbaR+VRE Kit for Accurate Detection of Carbapenemase-Producing Bacteria.

Authors:  Saoussen Oueslati; Delphine Girlich; Laurent Dortet; Thierry Naas
Journal:  J Clin Microbiol       Date:  2018-02-22       Impact factor: 5.948

Review 3.  Overview of bioinformatic methods for analysis of antibiotic resistome from genome and metagenome data.

Authors:  Kihyun Lee; Dae-Wi Kim; Chang-Jun Cha
Journal:  J Microbiol       Date:  2021-02-23       Impact factor: 3.422

Review 4.  A Decade of Development of Chromogenic Culture Media for Clinical Microbiology in an Era of Molecular Diagnostics.

Authors:  John D Perry
Journal:  Clin Microbiol Rev       Date:  2017-04       Impact factor: 26.132

5.  Establishing Genotypic Cutoff Values To Measure Antimicrobial Resistance in Salmonella.

Authors:  Gregory H Tyson; Shaohua Zhao; Cong Li; Sherry Ayers; Jonathan L Sabo; Claudia Lam; Ron A Miller; Patrick F McDermott
Journal:  Antimicrob Agents Chemother       Date:  2017-02-23       Impact factor: 5.191

6.  Diagnostic Stewardship: Opportunity for a Laboratory-Infectious Diseases Partnership.

Authors:  Robin Patel; Ferric C Fang
Journal:  Clin Infect Dis       Date:  2018-08-16       Impact factor: 9.079

7.  Breaking the code of antibiotic resistance.

Authors:  Stephanie W Lo; Narender Kumar; Nicole E Wheeler
Journal:  Nat Rev Microbiol       Date:  2018-03-26       Impact factor: 60.633

8.  Antimicrobial Resistance Following Azithromycin Mass Drug Administration: Potential Surveillance Strategies to Assess Public Health Impact.

Authors:  Ines Mack; Mike Sharland; James A Berkley; Nigel Klein; Surbhi Malhotra-Kumar; Julia Bielicki
Journal:  Clin Infect Dis       Date:  2020-03-17       Impact factor: 9.079

Review 9.  Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection.

Authors:  Wei Gu; Steve Miller; Charles Y Chiu
Journal:  Annu Rev Pathol       Date:  2018-10-24       Impact factor: 23.472

Review 10.  Whole-Genome Sequencing of Bacterial Pathogens: the Future of Nosocomial Outbreak Analysis.

Authors:  Scott Quainoo; Jordy P M Coolen; Sacha A F T van Hijum; Martijn A Huynen; Willem J G Melchers; Willem van Schaik; Heiman F L Wertheim
Journal:  Clin Microbiol Rev       Date:  2017-10       Impact factor: 26.132

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