Abstract Antimicrobial resistance (AMR) is a major public health threat, especially in low- and middle-income countries (LMICs), where large datasets linking antimicrobial susceptibility testing (AST) with genomic data remain limited. We analyzed AST results and whole genomes from 266 resistant bacterial isolates representing diverse species and specimen sources, collected from Northern and Western India between 2022 and 2024. Correlation of genomic resistance predictions with AST data revealed an overprediction of resistance by genomic methods. To our knowledge, this is the first study to systematically examine these discrepancies across multiple antibiotic-pathogen combinations in India and to identify promising targets for genomic resistance prediction. We also investigated the predominant antibiotic resistance genes (ARGs), plasmids, and other mobile genetic elements associated with them. Overall, our findings contribute meaningfully to the genomic epidemiology of AMR in India and support the development of molecular diagnostics for antimicrobial resistance.
Gheewalla et al. (2026) studied this question.