ArticleNature communications2024
Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Drug-resistance profiles, population structure, genomic clustering, and temporal trends in drug resistance amongThe Lancet regional health. Europe · 2026Article
- Future-proofing tuberculosis therapy: framework for concurrent drug and resistance testing development.The Lancet. Infectious diseases · 2026Review
- A Case of Transmission of Bedaquiline- and Linezolid-Resistant Tuberculosis.International journal of molecular sciences · 2026Article
- Uncovering resistance pathways to first- and last-line antibiotics inMicrobial genomics · 2026Article
- Molecular Mechanisms of Resistance and Treatment Efficacy of Delamanid AgainstHealth science reports · 2026Review
- Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.Nature communications · 2026Article
- Clinical Characteristics and Drug Resistance Profile ofInfection and drug resistance · 2026Article
- Genome graphs reveal the importance of structural variation in Mycobacterium tuberculosis evolution and drug resistance.Nature communications · 2025Article
- Clinical and bacterial determinants of unfavorable tuberculosis treatment outcomes: an observational study in Georgia.Genome medicine · 2025Observational
- Reply to Schön et al., "Quality control and considering systematic MIC shifts are key when evaluating the role ofAntimicrobial agents and chemotherapy · 2025Article
- Evolution and evolvability of rifampicin resistance across the bacterial tree of life.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- NProceedings of the National Academy of Sciences of the United States of America · 2025Article
- An improved catalogue for whole-genome sequencing prediction of bedaquiline resistance inMicrobial genomics · 2025Article
- Engineered Mycobacteriophage TM4::GeNL Rapidly Determines Bedaquiline, Pretomanid, Linezolid, Rifampicin, and Clofazimine Sensitivity in Mycobacterium tuberculosis Clinical Isolates.The Journal of infectious diseases · 2025Article
- 15-year trends in efficacy and effectiveness of treatment outcomes in drug-resistant pulmonary TB.IJTLD open · 2025Article
- Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosis.Nature communications · 2025Article
- Integrating sequencing methods with machine learning for antimicrobial susceptibility testing in pediatric infections: current advances and future insights.Frontiers in microbiology · 2025Review
- Rifampicin and isoniazid resistance not promote fluoroquinolone resistance in Mycobacterium smegmatis.PloS one · 2025Article
- Whole genomic analysis uncovers high genetic diversity of rifampicin-resistantFrontiers in microbiology · 2025Article
- Response to treatment and low serum vitamin D levels in North Indian patients with treatment-naive category I and multi-drug resistant pulmonary tuberculosis.Annals of medicine · 2024Article
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Abstract
The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis. However, molecular diagnostics to date have focused largely on first-line drugs and predicting susceptibilities in a binary manner (classifying strains as either susceptible or resistant). Here, we used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration (MIC) in 15,211 Mycobacterium tuberculosis clinical isolates from 23 countries across five continents. We identified 492 unique MIC-elevating variants across 13 drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.
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