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

Abstract

Introduction: 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.

Methods: 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.

Results: Across 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.

Discussion: 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.

Keywords: India; One Health; antimicrobial resistance (AMR); low- and middle-income countries; resistome; wastewater metagenomics; wastewater surveillance.