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BMC Medicine
Published in: BMC Medicine 1/2016

Open Access 01-12-2016 | Research article

Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

Authors: Jody Phelan, Francesc Coll, Ruth McNerney, David B. Ascher, Douglas E. V. Pires, Nick Furnham, Nele Coeck, Grant A. Hill-Cawthorne, Mridul B. Nair, Kim Mallard, Andrew Ramsay, Susana Campino, Martin L. Hibberd, Arnab Pain, Leen Rigouts, Taane G. Clark

Published in: BMC Medicine | Issue 1/2016

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Abstract

Background

Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance.

Methods

To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods.

Results

The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites.

Conclusions

Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.
Appendix
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Metadata
Title
Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance
Authors
Jody Phelan
Francesc Coll
Ruth McNerney
David B. Ascher
Douglas E. V. Pires
Nick Furnham
Nele Coeck
Grant A. Hill-Cawthorne
Mridul B. Nair
Kim Mallard
Andrew Ramsay
Susana Campino
Martin L. Hibberd
Arnab Pain
Leen Rigouts
Taane G. Clark
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2016
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-016-0575-9

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