Genome sequencing of Mycobacterium tuberculosis clinical isolates revealed isoniazid resistance mechanisms undetected by conventional molecular methods.


Journal

International journal of antimicrobial agents
ISSN: 1872-7913
Titre abrégé: Int J Antimicrob Agents
Pays: Netherlands
ID NLM: 9111860

Informations de publication

Date de publication:
Aug 2020
Historique:
received: 06 03 2020
revised: 14 06 2020
accepted: 21 06 2020
pubmed: 1 7 2020
medline: 20 5 2021
entrez: 1 7 2020
Statut: ppublish

Résumé

A combination of targeted molecular methods and phenotypic drug-susceptibility testing is the most widely used approach to detect drug resistance in Mycobacterium tuberculosis isolates. We report the delay in the introduction of an efficient anti-tuberculous drug regimen because of a M. tuberculosis strain displaying a high level of resistance to isoniazid, in the absence of the common mutations associated with isoniazid-resistance, including katG mutations and inhA promoter mutations. Whole-genome sequencing (WGS) identified a large loss-of-function insertion (>1000 pb) at the end of katG in the isolate together with a -57C>T ahpC mutation, a resistance mechanism that would have remained undetected by a conventional molecular targeted approach. A retrospective search using publicly available WGS data of more than 1200 isoniazid-resistant isolates and a similar sized control dataset of isoniazid-susceptible isolates revealed that most (22/31) isoniazid-resistant, KatG loss-of-function mutants had an associated rare ahpC promoter mutation. In contrast, only 7 of 1411 isoniazid-susceptible strains carried a rare ahpC promoter mutation, including shared mutations with the 31 isoniazid-resistant KatG loss-of-function mutants. These results indicate that rare ahpC promoter mutations could be used as a proxy for investigating simultaneous KatG loss-of-function or missense mutations. In addition, WGS in routine diagnosis would improve drug susceptibility testing in M. tuberculosis clinical isolates and is an efficient tool for detecting resistance mechanisms undetected by conventional molecular methods.

Identifiants

pubmed: 32603684
pii: S0924-8579(20)30238-7
doi: 10.1016/j.ijantimicag.2020.106068
pii:
doi:

Substances chimiques

Antitubercular Agents 0
Bacterial Proteins 0
DNA, Bacterial 0
ahpC protein, Mycobacterium tuberculosis 0
Peroxiredoxins EC 1.11.1.15
Catalase EC 1.11.1.6
katG protein, Mycobacterium tuberculosis EC 1.11.1.6
Isoniazid V83O1VOZ8L

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

106068

Informations de copyright

Copyright © 2020. Published by Elsevier Ltd.

Auteurs

Sacha Laurent (S)

Institute of Microbiology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Fathiah Zakham (F)

Institute of Microbiology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Claire Bertelli (C)

Institute of Microbiology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Laurent Merz (L)

Établissements Hospitaliers du Nord Vaudois Site de St Loup, St Loup, Switzerland.

Laurent Nicod (L)

Department of Pneumology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Jesica Mazza-Stalder (J)

Department of Pneumology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Gilbert Greub (G)

Institute of Microbiology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Katia Jaton (K)

Institute of Microbiology, University of Lausanne and University Hospital of Lausanne, Switzerland.

Onya Opota (O)

Institute of Microbiology, University of Lausanne and University Hospital of Lausanne, Switzerland. Electronic address: onya.opota@chuv.ch.

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Classifications MeSH