is supported by EMBL’s EIPOD3 programme funded by the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska Curie Actions. is supported by the National Science and Technology Major Project, China Grant No. is supported by the Wellcome Trust (203919/Z/16/Z). Oxford CRyPTIC consortium members are funded/supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), the views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health, and the National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, a partnership between Public Health England and the University of Oxford, the views expressed are those of the authors and not necessarily those of the NIHR, Public Health England or the Department of Health and Social Care. See /kerrimalone/Brankin_Malone_2022 for codebase.įunding: This work was supported by Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z) and Bill & Melinda Gates Foundation Trust (OPP1133541). All data for this study were analysed and visualised using either R or python3 libraries and packages. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data are available from .uk/pub/databases/cryptic/release_june2022/ The FTP site contains two top level directories: “reuse” and “reproducibility”. Received: ApAccepted: JPublished: August 9, 2022Ĭopyright: © 2022 The CRyPTIC Consortium. PLoS Biol 20(8):Īcademic Editor: Jason Ladner, Northern Arizona University, UNITED STATES The data compendium is fully open source and it is hoped that it will facilitate and inspire future research for years to come.Ĭitation: The CRyPTIC Consortium (2022) A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics. 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 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. 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). 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. It is the largest matched phenotypic and genotypic dataset for M. 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.
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