Data Sheet 1_Metagenomic insights into the urban–rural variation of antimicrobial resistance and pathogen reservoirs in untreated wastewater from central India.zip

IntroductionRapid 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.
MethodsWe 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.
ResultsAcross all samples, 871 bacterial genera were detected, dominated by Proteobacteria, with frequent presence of Pseudomonas, Acinetobacter, Aeromonas, Acidovorax and Bacteroides. 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%). Vibrio cholerae appeared in one sample, while Aeromonas spp. were most prevalent. Seven pathogens occurred in ≥10% of samples, with Aeromonas, Citrobacter, and Enterobacter differing significantly between locations (p < 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 (blaNDM, blaKPC) and colistin resistance (mcr) were detected at lower abundance. Correlation analyses linked Pseudomonas with mexEF/emhABC efflux and copBCDRS copper resistance operon, Acinetobacter with oxa and dfrA, and Aeromonas with ctx, tetA, sul1, dfrB/F, and gyrA/parC.
DiscussionThese 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.