Metagenomic insights into the urban-rural variation of antimicrobial resistance and pathogen reservoirs in untreated wastewater from central India

<h4>Introduction</h4>Rapid and scalable surveillance of antimicrobial resistance (AMR) is urgently needed in resource-constrained countries where routine monitoring is limited. Wastewater-based metagenomics offers a potential solution for early detection and geographic mapping of AMR.<h4>Methods</h4>We conducted a retrospective DNA shotgun metagenomic analysis of untreated wastewater collected across Nagpur, India (February-April 2021). A total of 422 grab samples were pooled into 138 composite samples from 10 urban zones and rural catchments. The bacterial microbiota and resistome were profiled, and urban-rural patterns were compared using diversity metrics and correlation analyses.<h4>Results</h4>Across all samples, 871 bacterial genera were detected, dominated by Proteobacteria, with frequent presence of <i>Pseudomonas</i>, <i>Acinetobacter</i>, <i>Aeromonas</i>, <i>Acidovorax</i> and <i>Bacteroides</i>. Beta diversity revealed statistically significant but subtle urban-rural compositional shifts. Of 33 globally important pathogens examined, 13 were detected at generally low relative abundance (<1%). <i>Vibrio cholerae</i> appeared in one sample, while <i>Aeromonas</i> spp. were most prevalent. Seven pathogens occurred in ≥10% of samples, with <i>Aeromonas</i>, <i>Citrobacter</i>, and <i>Enterobacter</i> differing significantly between locations (<i>p</i> < 0.05). The resistome comprised 606 unique antimicrobial resistance genes (ARGs), dominated by drug/biocide efflux determinants, followed by macrolide-lincosamide-streptogramin B genes driven largely by 23S rRNA mutations. Carbapenemases (<i>blaNDM</i>, <i>blaKPC</i>) and colistin resistance (<i>mcr</i>) were detected at lower abundance. Correlation analyses linked <i>Pseudomonas</i> with <i>mexEF</i>/<i>emhABC</i> efflux and <i>copBCDRS</i> copper resistance operon, <i>Acinetobacter</i> with <i>oxa</i> and <i>dfrA</i>, and <i>Aeromonas</i> with <i>ctx</i>, <i>tetA</i>, <i>sul1</i>, <i>dfrB/F</i>, and <i>gyrA/parC</i>.<h4>Discussion</h4>These findings show that wastewater metagenomics sensitively resolved clinically relevant pathogens and ARGs in an Indian urban-rural setting, capturing nuanced geographic structure. Integrating routine DNA metagenomics into One Health environmental surveillance could strengthen AMR early warning and guide interventions in resource-constrained contexts.