ArticlePLoS biology2022
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics.
Article in PLoS biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis that pooled it.
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Who cites it
79 citing papers in PubMed, 1 synthesis or guideline pooled it, 110 citations in OpenAlex.
- Opportunities and limitations of genomics for diagnosing bedaquiline-resistant tuberculosis: a systematic review and individual isolate meta-analysis.The Lancet. Microbe · 2024Pooled it
- Algorithmic Determinants of Performance Heterogeneity in Whole-Genome Sequencing-Based Prediction of Drug Resistance inMicroorganisms · 2026Review
- ComparativeMicrobiology spectrum · 2026Article
- Encoded metabolic remodeling amplifies drug resistance in Mycobacterium tuberculosis.PLoS pathogens · 2026Article
- Bedaquiline resistance: a predictable consequence of a game-changing drug?ASM case reports · 2026Article
- Genome scale CRISPRi reveals both shared and strain-specific vulnerabilities in genetically diverse drug-resistant strains of Mycobacterium tuberculosis.Nature communications · 2026Article
- Transmission of rifampicin-resistant tuberculosis in Ho Chi Minh City, Viet Nam: a prospective genomic epidemiology study.The Lancet regional health. Western Pacific · 2026Article
- Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.Nature communications · 2026Article
- Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network.BMC microbiology · 2026Article
- From mutation detection to treatment decisions: CRISPR-enabled diagnostics for drug-resistant tuberculosis.Frontiers in bioengineering and biotechnology · 2026Review
- Cross- Wellcome Africa Asian Programmes (AAPs) Acceleration of Genomics for Escalating infectious Diseases, (CAGED) Consortium.Wellcome open research · 2026Article
- A Frameshift Mutation in the MethyltransferaseComputational and structural biotechnology journal · 2026Article
- Machine learning-based analysis of drug resistance mutations in Mycobacterium tuberculosis.PloS one · 2026Article
- Genomic Surveillance of 3R Genes Associated with Antibiotic Resistance inAntibiotics (Basel, Switzerland) · 2025Article
- Characterizing the performance of an antibiotic resistance prediction tool, gnomonicus, using a diverse test set of 2,663Microbial genomics · 2025Article
- An explainable artificial intelligence framework reveals mutations associated with drug resistance inBiosafety and health · 2025Article
- A Pandemic-Scale Ancestral Recombination Graph for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025Article
- Rapid, accurate, and reproduciblemSphere · 2025Article
- Subpopulations in clinical samples ofJAC-antimicrobial resistance · 2025Article
- Pyrazinamide killsbioRxiv : the preprint server for biology · 2025Article
19 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
The Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) presents here a data compendium of 12,289 Mycobacterium tuberculosis global clinical isolates, all of which have undergone whole-genome sequencing and have had their minimum inhibitory concentrations to 13 antitubercular drugs measured in a single assay. It is the largest matched phenotypic and genotypic dataset for M. tuberculosis to date. Here, we provide a summary detailing the breadth of data collected, along with a description of how the isolates were selected, collected, and uniformly processed in CRyPTIC partner laboratories across 23 countries. The compendium contains 6,814 isolates resistant to at least 1 drug, including 2,129 samples that fully satisfy the clinical definitions of rifampicin resistant (RR), multidrug resistant (MDR), pre-extensively drug resistant (pre-XDR), or extensively drug resistant (XDR). The data are enriched for rare resistance-associated variants, and the current limits of genotypic prediction of resistance status (sensitive/resistant) are presented by using a genetic mutation catalogue, along with the presence of suspected resistance-conferring mutations for isolates resistant to the newly introduced drugs bedaquiline, clofazimine, delamanid, and linezolid. Finally, a case study of rifampicin monoresistance demonstrates how this compendium could be used to advance our genetic understanding of rare resistance phenotypes. The data compendium is fully open source and it is hoped that it will facilitate and inspire future research for years to come.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.