New Delhi, 24 March 2025 – In a groundbreaking achievement, the Indian Tuberculosis Genome Sequencing (InTGS) consortium has successfully sequenced 10,000 whole genomes of Mycobacterium tuberculosis (MTB) clinical strains, marking a major milestone in the fight against tuberculosis (TB). This initiative, conceived by the Department of Biotechnology, Government of India, leverages genomics and artificial intelligence to map drug resistance in TB and represents the most extensive collection of MTB genome sequences from India. InTGS is set to revolutionise TB research, diagnosis, and treatment strategies nationwide.
Tuberculosis remains one of the deadliest infectious diseases, with the rise of multi-drug-resistant (MDR) and extensively drug-resistant (XDR) strains posing a significant global challenge. Continuous genome surveillance is critical to detecting novel antimicrobial resistance (AMR) mutations and guiding effective treatment strategies. However, current research and drug development efforts rely predominantly on a limited number of well-characterized reference strains such as H37Rv, which fail to capture the diversity of MTB clinical isolates. This limitation hampers the development of targeted therapies and diagnostic tools.
To address this gap, the InTGS consortium was established, uniting leading research institutions across India to generate whole genome sequence data and create a repository for numerous clinical MTB isolates from various regions of the country. Additionally, the consortium is developing AI/ML-powered tools for the rapid genotypic prediction of drug resistance in tuberculosis (TB). The consortium includes JIPMER Puducherry, Hinduja Mumbai, BJGMC Pune, BMMRC Hyderabad, PGI Chandigarh, CCMB Hyderabad, NIBMG Kalyani, NITRD New Delhi, St. John's Medical College Bangalore, NEIGRIHMS Shillong, and ICGEB New Delhi, coordinated by BRIC-NII, New Delhi.
Within just 17 months of its inception, the InTGS project has made substantial progress, successfully sequencing 10,000 MTB genomes. The drug resistance and mutation data derived from these genomes are now available on the InTGS web portal(http://intgs.nii.ac.in/InTGS/index.php), providing a valuable resource for researchers, clinicians, and policymakers. Further, a user-friendly AI/ML-based tool (TB-AMRpred) has been developed to predict antibiotic resistance using genomic data and is currently being validated.
Preliminary analysis of these clinical isolates has revealed previously unreported mutations associated with drug resistance, underscoring the need for revised diagnostic panels. The insights gained from this data have the potential to accelerate the development of rapid diagnostic tools, leading to faster detection of drug-resistant TB cases and improved treatment outcomes.
This achievement by the InTGS consortium marks a significant step toward strengthening India's TB control efforts. By mapping the genetic diversity of Mycobacterium tuberculosis strains across the country, we can pave the way for precision medicine approaches and innovative therapeutic strategies. The InTGS initiative is a testament to India's commitment to tackling tuberculosis through cutting-edge genomics and translational research. As the project advances, it will continue to provide crucial insights into drug resistance mechanisms, strain lineage distribution, and novel targets for intervention.