ArticleBMC medicine2016
Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance.
Article in BMC medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
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Who cites it
71 citing papers in PubMed, 112 citations in OpenAlex.
- Trial
- The structural context of mutations in proteins predicts their effect on antibiotic resistance.eLife · 2026Article
- Molecular Characterization of theAntibiotics (Basel, Switzerland) · 2026Article
- Genetic Characterization of First-Line Drug-Resistance Mutations in Multidrug-ResistantPathogens (Basel, Switzerland) · 2026Article
- Structural modeling and docking analysis of canonical and novel resistance-associated missense mutations in Sudanese Escherichia coli.Scientific reports · 2026Article
- Comprehensive Approaches to Protein Detection and Analysis in Mycobacterium tuberculosis.Advances in experimental medicine and biology · 2026Review
- From mutation detection to treatment decisions: CRISPR-enabled diagnostics for drug-resistant tuberculosis.Frontiers in bioengineering and biotechnology · 2026Review
- Machine learning-based approach for identification of new resistance associated mutations from whole genome sequences ofBioinformatics advances · 2025Article
- Article
- Whole-genome sequencing-based genetic diversity, transmission dynamics, and drug-resistant mutations inFrontiers in public health · 2024Article
- Genome-Wide Association Studies (GWAS) Approaches for the Detection of Genetic Variants Associated with Antibiotic Resistance: A Systematic Review.Microorganisms · 2023Review
- THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model.Bioinformatics (Oxford, England) · 2023Article
- Feature weighted models to address lineage dependency in drug-resistance prediction from Mycobacterium tuberculosis genome sequences.Bioinformatics (Oxford, England) · 2023Article
- Analysis of Genome-Wide Mutational Dependence in Naturally Evolving Mycobacterium tuberculosis Populations.Molecular biology and evolution · 2023Article
- Large-scale genomic analysis of Mycobacterium tuberculosis reveals extent of target and compensatory mutations linked to multi-drug resistant tuberculosis.Scientific reports · 2023Article
- A high proportion of caseous necrosis, abscess, and granulation tissue formation in spinal tuberculosis.Frontiers in microbiology · 2023Article
- Prediction of protein stability changes upon single-point variant using 3D structure profile.Computational and structural biotechnology journal · 2023Article
- Using Graph-Based Signatures to Guide Rational Antibody Engineering.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Characterisation of drug-resistant Mycobacterium tuberculosis mutations and transmission in Pakistan.Scientific reports · 2022Article
- Deciphering Isoniazid Drug Resistance Mechanisms on DimericACS omega · 2022Article
11 more citing papers are in PubMed but not listed here.
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Authors and funding
16 authors at 8 institutions in 7 countries.
Funding
Abstract
backgroundCombating 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.
methodsTo 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.
resultsThe 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.
conclusionsUsing 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.
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