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Updated: Jun 14, 2026

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
Understanding antimicrobial resistance phenotype in Indian clinical isolates through genomic lens
Rupali Aggarwal1, Ankita Das1, Jasleen Kaur1
1Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, 160036, India.
Abstract:
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 has been 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 blaOXA-23, blaOXA-66and blaOXA-51-likeinA. baumannii and blaCTX-M-15, blaNDM-5, blaTEM-1 in E. coli and K. pneumoniae, while the global dataset has a broader diversity of ARGs. It is also observed that isolates have more than one resistance mechanism, pointing to AMR being a complex phenotype. ARG co-occurrence networks provide a framework to analyze the complex molecular interactions leading to emergence of AMR. This study highlights the local AMR trends in Indian clinical isolates and provides recommendations for standardized data reporting that are also applicable globally.
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