Bastolla, Ugo, Rotkevich, Mikhail, Arenas, Miguel, Arrayás, Manuel, Dogonadze, Marine, Lavrova, Anastasia, Molina-Sejas, Jorge, Tadesse, Michael, Xulvi-Brunet, Ramon, Cox, Jonathan A. G., Nerukh, Dmitry, Gonzalez-Benitez, Natalia and Stich, Michael (2025). Fitness effect of the isoniazid resistance mutation S315T of the catalase-peroxidase enzyme KatG of Mycobacterium tuberculosis. Genome Biology and Evolution ,
Abstract
The mutation S315T of the catalase-peroxidase protein KatG of Mycobacterium tuberculosis is the most common mutation that confers resistance to the prodrug isoniazid. Here we reconstruct its evolutionary history in 145 whole genome sequences of M. tuberculosis from Russian hospitals, inferring 11 independent appearances of this mutation and 5 reversion events, with an estimated reversion rate 1500 times higher than the rate of preserved non-synonymous or intragenic mutations. This suggests that, contrary to the commonly held view, the mutation KatG(S315T) results in a fitness cost, possibly because of reduced tolerance to oxidative stress. Consistent with this interpretation, the mutant enzyme presents reduced catalase and peroxidase activities (Wengenack et al. 1997). Applying the torsional network model, we found that the mutant protein shows more restricted thermal dynamics, although its functional site moves quite similarly to the wild type. Of the four internal clones where KatG(S315T) arose, two present high reproductive rates and secondary mutations at the 5’-UTR region of the gene encoding superoxide dismutase A (sodA), while the other two present significantly lower reproductive rate and lack mutations at genes related with tolerance to oxidative stress. Our results suggest that the resistance mutation KatG(S315T) incurs a fitness cost, which may be alleviated through compensatory mutations at the gene sodA or other genes that respond to oxidative stress such as the previously known gene ahpC. This suggests that isoniazid treatment could be complemented with drugs that produce oxidative stress in order to hinder the propagation of resistant strains devoid of compensatory mutations.
Publication DOI: | https://doi.org/10.1093/gbe/evaf120 |
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Divisions: | College of Health & Life Sciences > School of Biosciences College of Health & Life Sciences College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied Mathematics & Data Science College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies College of Engineering & Physical Sciences |
Funding Information: | The authors thank the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Research and Innovation Staff Exchange, MSCA-RISE-2018, number: 823922, AMR-TB for financial support. |
Additional Information: | Copyright © The Author(s) 2025. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Uncontrolled Keywords: | Mycobacterium tuberculosis,antimicrobial resistance,isoniazid,S315T,oxidative stress,Regularized Maximum Likelihood and Minimum Evolution (REGMLAME) |
Publication ISSN: | 1759-6653 |
Data Access Statement: | The data generated in this study is available as Supplementary Information. The program Torsional Network Model (TNM) is available at https://github.com/ugobas/tnm |
Last Modified: | 09 Jul 2025 07:29 |
Date Deposited: | 08 Jul 2025 14:46 |
Full Text Link: | |
Related URLs: |
https://academi ... evaf120/8171503
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2025-06-23 |
Published Online Date: | 2025-06-23 |
Accepted Date: | 2025-04-30 |
Authors: |
Bastolla, Ugo
Rotkevich, Mikhail Arenas, Miguel Arrayás, Manuel Dogonadze, Marine Lavrova, Anastasia Molina-Sejas, Jorge Tadesse, Michael Xulvi-Brunet, Ramon Cox, Jonathan A. G. ( ![]() Nerukh, Dmitry ( ![]() Gonzalez-Benitez, Natalia Stich, Michael |