Researchers have identified genetic causes of drug resistance to tuberculosis (TB) treatments.
The team generated a dataset which it used to measure how changes in the genetic code on M. tuberculosis reduce how well different drugs kill these bacteria that cause TB.
It used two new advances – a new test for drug resistance and a new approach which identifies all the genetic changes in a sample of drug-resistant TB bacteria.
Researchers say these innovations, combined with ongoing work in the field, will improve how patients with TB are treated in the future.
The Comprehensive Resistance Prediction for Tuberculosis International Consortium (CRyPTIC) research project collected the largest ever global dataset of clinical M. tuberculosis samples, consisting of 15,211 samples from 27 countries on five continents.
Researchers suggest the infection kills more people each year than any other bacteria, virus, or parasite, except for Covid-19.
Although it is treatable, over the past 30 years drug resistance has emerged as a major problem.
Testing for mutations in the M. tuberculosis genome to determine which drugs will give a patient the best chance of cure is the most realistic way of getting drug resistance testing to every patient who needs it, the scientists say.
The genome is the complete set of genetic information in an organism.
Dr Derrick Crook, professor of microbiology at the University of Oxford, said: “This innovative, large-scale, international collaboration has enabled us to create possibly the most comprehensive map yet of the genetic changes responsible for drug resistance in tuberculosis.”
Through nine new pre-prints, which have not yet been peer-reviewed, the researchers revealed a number of findings.
They included how the new drug resistance tests should be interpreted, and how a massive citizen science project helped solve this problem.
The research also revealed how a new approach to detecting and describing genetic changes in the whole TB genome sequence improved the way genetic changes driving drug resistance can be detected.
It further indicates how individual mutations, and combinations of mutations, can be related to even minor changes in the way a drug kills the infection, thereby reducing the effectiveness of treatment, with special attention being paid to two novel compounds being used to treat tuberculosis.
The research also revealed how artificial intelligence can predict drug resistance, and how the data contributed to the first list of drug resistance mutations in the TB genome to be endorsed for global use by the World Health Organisation (WHO).
It is hoped the findings will help improve control of TB and facilitate the WHO’s end TB strategy through better, faster and more targeted treatment of drug-resistant tuberculosis, and pave the way towards universal drug susceptibility testing (DST).
Prof Crook said: “Our ultimate goal is to achieve a sufficiently accurate genetic prediction of resistance to most anti-tuberculosis drugs, so that whole genome sequencing can replace culture-based DST for TB.
“This will enable rapid-turnaround near-to-patient assays to revolutionise MDR-TB identification and management.”
This project is funded by the MRC Newton Fund, Wellcome Trust, and Bill & Melinda Gates Foundation, and the work of Prof Crook’s team is supported through the NIHR Oxford Biomedical Research Centre’s Antimicrobial Resistance and Microbiology Theme.