No 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.

The Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) presents here a global collection of 15,211 Mycobacterium tuberculosis clinical isolates, all of which have undergone whole genome sequencing and have had their minimum inhibitory concentrations to 13 antitubercular drugs measured. The isolates represent five major M. tuberculosis lineages originating from 23 countries across four continents. 6,814 isolates were found resistant to at least one drug, including 2,129 samples fully satisfy the clinical definitions of RR/MDR, pre-XDR or XDR. Resistance status to eight antitubercular drugs can be accurately predicted using a genetic mutation catalogue for over 90% of the isolates. Furthermore, we show 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 mono-resistance is presented to showcase how this compendium could be used to advance our genetic understanding of rare resistance phenotypes and evaluate the likely performance of a widely used molecular diagnostic tool. It is hoped that this compendium, the largest M. tuberculosis matched phenotypic and genotypic dataset to date, will facilitate and inspire new research projects for years to come.

Tackling drug resistance needs predictive methods rooted in chemistry that can contribute to both diagnostics and drug development.