The AMR-ARRAY: A modular bead array detecting β-lactam, (fluoro) quinolone, colistin, aminoglycoside and macrolide resistance determinants in Gram-negative bacteria.


Journal

Journal of microbiological methods
ISSN: 1872-8359
Titre abrégé: J Microbiol Methods
Pays: Netherlands
ID NLM: 8306883

Informations de publication

Date de publication:
05 2022
Historique:
received: 24 12 2021
revised: 15 04 2022
accepted: 18 04 2022
pubmed: 25 4 2022
medline: 18 5 2022
entrez: 24 4 2022
Statut: ppublish

Résumé

The aim of this study was to develop a highly multiplexed bead array to detect genes and/or mutations frequently associated with resistance to antimicrobials of the β-lactam, (fluoro)quinolone, colistin, macrolide and aminoglycoside families in Enterobacteriaceae such as Escherichia coli, Shigella spp. and Salmonella spp. Ligase Chain Reaction and the Luminex® technology were combined in a 53-plex assay designed to target selected genetic markers with 3 internal controls. The AMR-ARRAY consistently detected resistance determinants as compared to phenotypically expressed resistance for 94.7% (856/904) of the assessed resistances. When compared to resistance profiles inferred from whole genome sequencing results, the AMR-ARRAY showed a selectivity and specificity of 99.3% and 100%, respectively. The strong features of the AMR-ARRAY are (i) its competitive cost, currently 18€/sample (ii) its wide analytical scope, currently 50 markers covering 5 antimicrobial families, (iii) its robust and user-friendly design consisting in a single-tube assay conducted in 4 successive steps (iv) its relatively short turnaround time, less than 8 h (v) its ability to detect allelic variability at critical SNPs (vi) its open access and easily upgradable design, with probes sequences, procedure and software source code freely available. The use of the AMR-ARRAY as a screening method in official antimicrobial resistance monitoring could improve the granularity of the collected data and pinpoint remarkable isolates harbouring unusual resistance determinants thereby enabling fit-for-purpose selection of isolates for Whole Genome analysis.

Identifiants

pubmed: 35461920
pii: S0167-7012(22)00067-7
doi: 10.1016/j.mimet.2022.106472
pii:
doi:

Substances chimiques

Aminoglycosides 0
Anti-Bacterial Agents 0
Macrolides 0
Quinolones 0
beta-Lactams 0
Colistin Z67X93HJG1

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

106472

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Auteurs

Michaël Timmermans (M)

Veterinary Bacteriology, Sciensano, Ixelles, Belgium; Faculté de médecine, Université Libre de Bruxelles, Brussels, Belgium.

Samuel Latour (S)

Veterinary Bacteriology, Sciensano, Ixelles, Belgium.

Pieter-Jan Ceyssens (PJ)

Bacterial diseases, Sciensano, Ixelles, Belgium.

Cristina Garcia-Graells (C)

Foodborne Pathogens, Sciensano, Ixelles, Belgium.

Carole Kowalewicz (C)

Veterinary Bacteriology, Sciensano, Ixelles, Belgium.

David Fretin (D)

Veterinary Bacteriology, Sciensano, Ixelles, Belgium.

Olivier Denis (O)

Ecole de Santé Publique, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Clinical Microbiology, National Reference Center for Monitoring Antimicrobial Resistance in Gram-Negative Bacteria, CHU UCL Namur, Yvoir, Belgium.

Pierre Wattiau (P)

Veterinary Bacteriology, Sciensano, Ixelles, Belgium.

Cécile Boland (C)

Veterinary Bacteriology, Sciensano, Ixelles, Belgium. Electronic address: cecile.boland@sciensano.be.

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Classifications MeSH