A massive analysis of more than 10 000 different Mycobacterium tuberculosis bacteria isolated from 23 countries has revealed new genes associated with resistance to 13 first- and second-line new and repurposed antibiotics.
The work, carried out by Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC), is described in two papers published in the open-access journal PLOS Biology.
Tuberculosis (TB) is a curable and preventable disease; 85% of those affected can be successfully treated with a six-month regimen of drugs. Despite this, TB has killed more people than other infectious diseases in many recent years, and drug-resistant TB is a continual threat. A better understanding of the M. tuberculosis variants that confer antibiotic resistance is important for both better monitoring of resistant strains as well as the development of new drugs.
In the first new paper, the researchers outlined how they assembled an open-access data compendium of 12 289 M. tuberculosis isolates, processed in CRyPTIC partner laboratories around the world. Each isolate was sequenced, and then tested on a high-throughput grid with varying concentrations of 13 antimicrobials. Of the samples included in the compendium, 6 814 were resistant to at least one drug, including 4 685 samples resistant to multiple drugs or to the first-line treatment of rifampicin.
In the second paper, the consortium presented their findings from a genome-wide association study (GWAS) using the data on 10 228 M. tuberculosis isolates. For all 13 drugs, the group discovered uncatalogued variants associated with significant increases in the minimum inhibitory concentration – the lowest concentration of an antibiotic that stops the growth of M. tuberculosis.
Analysing this concentration, rather than a binary resistant-or-not-resistant result, allowed the identification of variants that cause only subtle changes to antibiotic response that may be overcome by increasing drug dose. The researchers selected the 20 most significant genes that confer resistance to each drug and described the effect size and variations within these specific genes in more depth.
“Our study demonstrates the ability of global partnerships to substantially improve our knowledge of genetic variants associated with antimicrobial resistance in M. tuberculosis,” the authors note. Together, the papers not only uncover specific genes that can be followed up on to better understand the resistance landscape of M. tuberculosis, but also a framework for future studies on the pathogen.
“The compendium is not designed for measuring prevalence or estimating ‘real-world’ error rates of resistance prediction tools; rather it serves as a resource to accelerate antimicrobial resistance diagnostic development by enriching mutation catalogues for (whole genome sequencing) resistance prediction, improving our understanding of the genetic mechanisms of resistance, and identifying important diagnostic gaps and drug resistance patterns,” the authors say. “The data compendium is fully open-source and it is hoped that it will facilitate and inspire future research for years to come.”
Study 1 details
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics
Derrick Crook, Timothy Peto, Sarah Hoosdally, Ana Lúıza Gibertoni Cruz, Sarah Walker, Timothy Walker, Philip Fowler, Zamin Iqbal, Daniela Maria Cirillo, Alice Brankin, Kerri Malone, Martin Hunt, Jeff Knaggs et al.
Published in PLOS Biology on 9 August 2022
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.
Study 2 details
Genome-wide association studies of global Mycobacterium tuberculosis resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms
Derrick Crook, Camilla Rodrigues, Nazir Ahmed Ismail, Nerges Mistry, Zamin Iqbal, Matthias Merker, David Moore, Sarah Walker, Guy Thwaites, Stefan Niemann, Daniel Wilson, Daniela Maria Cirillo, Alexander Lachapelle et al
Published in PLOS Biology on 9 August 2022
Abstract
The emergence of drug-resistant tuberculosis is a major global public health concern that threatens the ability to control the disease. Whole-genome sequencing as a tool to rapidly diagnose resistant infections can transform patient treatment and clinical practice. While resistance mechanisms are well understood for some drugs, there are likely many mechanisms yet to be uncovered, particularly for new and repurposed drugs. We sequenced 10,228 Mycobacterium tuberculosis (MTB) isolates worldwide and determined the minimum inhibitory concentration (MIC) on a grid of 2-fold concentration dilutions for 13 antimicrobials using quantitative microtiter plate assays. We performed oligopeptide- and oligonucleotide-based genome-wide association studies using linear mixed models to discover resistance-conferring mechanisms not currently catalogued. Use of MIC over binary resistance phenotypes increased sample heritability for the new and repurposed drugs by 26% to 37%, increasing our ability to detect novel associations. For all drugs, we discovered uncatalogued variants associated with MIC, including in the Rv1218c promoter binding site of the transcriptional repressor Rv1219c (isoniazid), upstream of the vapBC20 operon that cleaves 23S rRNA (linezolid) and in the region encoding an α-helix lining the active site of Cyp142 (clofazimine, all p < 10−7.7). We observed that artefactual signals of cross-resistance could be unravelled based on the relative effect size on MIC. Our study demonstrates the ability of very large-scale studies to substantially improve our knowledge of genetic variants associated with antimicrobial resistance in M. tuberculosis.
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