Improving the ability of antimicrobial susceptibility tests to predict clinical outcome accurately: Adding metabolic evasion to the equation.
Antimicrobial resistance
Antimicrobial susceptibility test
Bacterial physiology
Biofilm
Dormancy
Intracellular growth
Minimal inhibitory concentration (MIC) breakpoints
Persisters
Slow growing bacteria
Tolerance
Journal
Drug discovery today
ISSN: 1878-5832
Titre abrégé: Drug Discov Today
Pays: England
ID NLM: 9604391
Informations de publication
Date de publication:
09 2021
09 2021
Historique:
received:
30
11
2020
revised:
09
03
2021
accepted:
25
05
2021
pubmed:
14
6
2021
medline:
27
1
2022
entrez:
13
6
2021
Statut:
ppublish
Résumé
Antimicrobial susceptibility tests (AST) are based on the minimal inhibitory concentration (MIC), the method used worldwide to guide antimicrobial therapy. Despite its relevance in correctly predicting clinical outcome for most acute infections, this approach is misleading for multiple clinical cases in which pathogens do not grow rapidly, uniformly or with physical protection. This behaviour, named 'metabolic evasion' (ME), enables bacteria to survive antimicrobials. ME can result from different, and sometimes combined, bacterial mechanisms such as biofilms, intracellular growth, persisters or dormancy. We discuss how ME can influence the MIC-based probability of target attainment. We identify clinical cases in which this approach is undermined by ME and propose a new approach that takes ME into account in order to improve patient management and the evaluation of innovative drugs.
Identifiants
pubmed: 34119667
pii: S1359-6446(21)00251-8
doi: 10.1016/j.drudis.2021.05.018
pii:
doi:
Substances chimiques
Anti-Bacterial Agents
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
2182-2189Informations de copyright
Copyright © 2021 Elsevier Ltd. All rights reserved.