New antibiotic resistance genes identified in tuberculosis
An international consortium analysed the genetic sequences and antibiotic susceptibility of more than 10,000 global Mycobacterium tuberculosis isolates.
A massive analysis of more than 10,000 different Mycobacterium tuberculosis bacteria isolates 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 new papers publishing recently 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 recent years, and drug-resistant TB is a continual threat. A better understanding of the M. tuberculosis variants confers antibiotic resistance is important for better monitoring resistant strains and developing new drugs.
The first new paper outlined how they assembled an open-access data compendium of 12,289 M. tuberculosis isolates, processed in CRyPTIC partner laboratories worldwide. 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 the first-line treatment of rifampicin.
The consortium presented their findings from a genome-wide association study (GWAS) in the second paper 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 the antibiotic response that may be overcome by increasing the 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.
"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."
Source: PLOS Biology