Antimicrobial resistance (AMR) is increasingly recognised as a One Health challenge in which environmental reservoirs play an important role in the persistence and dissemination of resistance genes. Despite growing recognition that environmental antimicrobial resistance is a critical component of the One Health challenge, the pathways through which antimicrobial resistance genes (ARGs) move between environmental systems and human populations remain incompletely characterised, particularly in low- and middle-income countries where environmental exposures are greatest and surveillance capacity is limited. This review synthesises current knowledge on environmental resistomes across soil, water, sediment and groundwater systems, with a focus on metagenomic and quantitative analytical approaches that have transformed environmental AMR surveillance. Unlike traditional culture-based methods, metagenomics enables comprehensive, culture-independent profiling of microbial communities and their associated resistomes, allowing detection of both known and previously uncharacterised resistance genes, as well as insights into their genetic context and mobility. This has significantly advanced our ability to characterise environmental reservoirs and infer potential transmission pathways at ecosystem scale. Using Bangladesh as an illustrative example of environmental exposure dynamics in rapidly urbanising low- and middle-income settings, we examine how contaminated urban waterways, wastewater discharge, agricultural practices, and seasonal hydrological processes-including monsoon-driven flooding-create interconnected transmission pathways linking environmental, animal, and human microbiomes. We also consider how co-selection pressures from heavy metals and other environmental contaminants contribute to the persistence and amplification of antimicrobial resistance beyond antibiotic-driven selection alone. These dynamics are further intensified by dense surface water networks, strong hydrological connectivity, and limited wastewater treatment infrastructure, which together create high-intensity human-environment interfaces and facilitate large-scale redistribution of antimicrobial resistance genes across environmental compartments. Taken together, these features make Bangladesh an analytically distinctive and tractable model system for understanding environmental AMR dynamics, with relevance to comparable deltaic and monsoon-influenced regions in South and Southeast Asia. Key methodological challenges-including the gap between ARG detection and clinical risk interpretation, biases in resistance gene databases, sampling limitations, and the lack of harmonised environmental surveillance frameworks-are examined alongside emerging tools such as long-read sequencing, functional metagenomics and artificial intelligence-assisted bioinformatic analysis. Finally, we propose an integrated One Health framework linking environmental metagenomics, global surveillance systems and policy interventions to support harmonised, data-driven monitoring and mitigation of environmental AMR across interconnected ecosystems.
Mitra et al. (Tue,) studied this question.