Title
Genomic signatures of pre-resistance in Mycobacterium tuberculosis
Date Issued
01 December 2021
Access level
open access
Resource Type
journal article
Author(s)
Torres Ortiz A.
Vidal J.R.
Balloux F.
Kon O.M.
Didelot X.
Grandjean L.
London School of Hygiene and Tropical Medicine
Johns Hopkins Bloomberg School of Public Health
Publisher(s)
Nature Research
Abstract
Recent advances in bacterial whole-genome sequencing have resulted in a comprehensive catalog of antibiotic resistance genomic signatures in Mycobacterium tuberculosis. With a view to pre-empt the emergence of resistance, we hypothesized that pre-existing polymorphisms in susceptible genotypes (pre-resistance mutations) could increase the risk of becoming resistant in the future. We sequenced whole genomes from 3135 isolates sampled over a 17-year period. After reconstructing ancestral genomes on time-calibrated phylogenetic trees, we developed and applied a genome-wide survival analysis to determine the hazard of resistance acquisition. We demonstrate that M. tuberculosis lineage 2 has a higher risk of acquiring resistance than lineage 4, and estimate a higher hazard of rifampicin resistance evolution following isoniazid mono-resistance. Furthermore, we describe loci and genomic polymorphisms associated with a higher risk of resistance acquisition. Identifying markers of future antibiotic resistance could enable targeted therapy to prevent resistance emergence in M. tuberculosis and other pathogens.
Volume
12
Issue
1
Language
English
OCDE Knowledge area
Enfermedades infecciosas
Tecnología para la identificación y funcionamiento del ADN, proteínas y enzimas y como influencian la enfermedad)
Scopus EID
2-s2.0-85121336482
PubMed ID
Source
Nature Communications
ISSN of the container
20411723
Sponsor(s)
We would like to thank the participants of the study. LG was supported by the Wellcome Trust (201470/Z/16/Z), the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award number 1R01AI146338 and by the GOSH/ ICH Biomedical Research Centre. OMK was supported by the Imperial Biomedical Research Centre (NIHR Imperial BRC, grant P45058). XD was supported by the NIHR Health Protection Research Unit in Genomics and Enabling Data. We thank the CRyPTIC project and the Tandem project for making whole-genome data available in the public domain. All authors acknowledge UCL Computer Science Technical Support Group (TSG) and the UCL Department of Computer Science High Performance Computing Cluster.
Sources of information:
Directorio de Producción Científica
Scopus