Understanding antimicrobial resistance phenotype in Indian clinical isolates through genomic lens

Antimicrobial Resistance (AMR) poses a global health crisis, with a disproportionately higher burden in developing countries. Yet, the genome-wide exploration of bacterial resistance in high-burden countries like India remains limited due to underrepresentation of high-quality data in publicly available resources. Integrating whole-genome sequencing (WGS) data with standardised phenotypic data, , enables characterization of local resistome patterns. In this study, a systematic workflow was implemented to curate WGS and associated AST data from Indian isolates of critical WHO bacterial priority pathogens. Assembled genomes and curated data were evaluated as per global standards of EUCAST and CLSI. Genomic analyses were performed to identify insertion elements and antibiotic resistance genes (ARGs), correlate presence of ARGs with AST phenotype, and compare the resistomes with global genome datasets for the priority drug-bug combinations. A total of 871 non-redundant AST-linked isolates were curated including A. baumannii (n = 119), E. coli (n = 305) and K. pneumoniae (n = 447) from 75 literature studies, BV-BRC and AST browser. The curated Indian isolates were resistant to many ‘Watch’ category antibiotics indicating strong reliance on last-resort antibiotics. It was observed that Indian samples are enriched in a small set of resistance determinants like bla NDM-5 , bla CTX-M-15 , and bla OXA-48-like genes, while the global dataset has a broader diversity of ARGs. It is also observed that isolates have more than one resistance mechanisms, pointing to AMR being a complex phenotype. This study highlights the local AMR trends in Indian clinical isolates and provides recommendations for standardized data reporting that are also applicable globally.