Antimicrobial resistance (AMR) is a global public health crisis with a disproportionate burden in developing countries. The study addresses limited genome-wide exploration of bacterial resistance in high-burden settings such as India, where high-quality, linked whole-genome sequencing (WGS) and phenotypic data are underrepresented in public resources. By integrating WGS with standardized antimicrobial susceptibility testing (AST) data, the authors aimed to characterize local resistome patterns in clinically relevant WHO priority pathogens and to place Indian isolates in a global context.
A systematic workflow was implemented to curate WGS data together with associated AST results from Indian clinical isolates. The curated dataset comprised 871 non-redundant, AST-linked isolates drawn from 75 literature studies, the BV-BRC resource, and the AST browser. The collection included three priority pathogens: Acinetobacter baumannii (n = 119), Escherichia coli (n = 305) and Klebsiella pneumoniae (n = 447). The authors reported that genomes and phenotypic data were assembled and evaluated following international standards to ensure comparability.
To harmonize phenotype interpretation and genomic data quality, assembled genomes and curated AST results were evaluated against global reference standards from EUCAST and CLSI. The application of these standards enabled consistent categorization of susceptibility and facilitated comparison across isolates and with global datasets. The source states that this standardization was a key component of the workflow, though detailed procedural steps were not reported in the abstract.
Genomic analyses focused on identifying antibiotic resistance genes (ARGs) and insertion elements within the assembled genomes. Detection of these genetic determinants allowed the authors to describe the dominant molecular mechanisms present in the Indian isolates. The study also used the genomic data to construct ARG co-occurrence networks to examine associations among resistance determinants.
The curated resource enabled correlation of the presence of specific ARGs with AST phenotypes. The authors reported such correlations as part of their effort to link genotype to phenotype in the Indian isolates. The abstract indicates that multiple resistance mechanisms were often found within the same isolate, emphasizing that AMR is a complex phenotype arising from combinations of determinants rather than single genes alone.
Comparative analyses with global genome datasets for priority drug–bug combinations revealed differences in resistome composition. Indian isolates were observed to be enriched in a relatively small set of resistance determinants. For A. baumannii this included blaOXA-23, blaOXA-66 and blaOXA-51-like genes. For E. coli and K. pneumoniae, the Indian collection was enriched for blaCTX-M-15, blaNDM-5 and blaTEM-1. In contrast, the global dataset showed a broader diversity of ARGs, suggesting geographical or sampling differences in resistome structure.
The authors note that isolates frequently carried more than one resistance mechanism, which supports the view of AMR as a multifactorial phenotype. To probe these relationships, ARG co-occurrence networks were generated; the abstract presents these networks as a framework to analyze complex molecular interactions that may contribute to the emergence and spread of AMR. Specific network topology or quantitative network results were not detailed in the source abstract.
Phenotypic data in the curated Indian collection indicated resistance to multiple WHO “Watch” category antibiotics, reflecting substantial reliance on last-resort agents in clinical settings. The enrichment of a limited set of ARGs in Indian isolates and the presence of multiple mechanisms per isolate have implications for treatment choices, infection control, and surveillance strategies. The study underscores the utility of paired WGS and AST data to inform local resistome trends and to situate those trends within a global context.
Based on their findings, the authors provide recommendations for standardized reporting of WGS and AST data to improve the value of genomic surveillance. The abstract highlights that such standardization is applicable not only to India but also to global AMR monitoring efforts. Detailed recommendations and implementation steps were not provided in the abstract and would require consultation of the full text for specifics.
Conflict of interest
The authors declared no competing interests in the source.