Integrating Metagenomics in Environmental Monitoring: Co-Selection of Heavy Metal and Antimicrobial Resistance Genes in Contaminated Aquatic Systems

Heavy metal pollution and antimicrobial resistance genes (ARGs) are global challenges in aquatic ecosystems. They are commonly produced from agricultural waste, industrial effluents, and untreated sewage. Heavy metals, including cadmium, copper, and zinc, can exert pressure on microbial communities, leading to the co-selection of antimicrobial resistance genes (ARGs) and metal resistance genes (MRGs). This occurs through cross-resistance mechanisms, shared mobile genetic elements, and co-regulation under selective pressure. Metagenomics is known for its effectiveness and culture- independent nature, providing an advanced way to detect and profile ARGs and MRGs in environmental samples to facilitate the identification of functional genes and uncultured microorganisms. Findings from case studies from the Yamuna River (India) and Pear River (China) demonstrate strong relationships between concentrations of heavy metals and abundance of ARG/MRG, which supports the assumption that heavy metal contamination plays an integral role in sustaining antimicrobial resistance genes in aquatic systems. This paper also highlights metagenomics as a key tool for defining dynamics of co-selection, integrating biological indicators into monitoring water quality, and informing risk assessment. It establishes that standardized protocols, cross-sectoral frameworks, and long-term monitoring are vital for mitigating spread of antimicrobial resistance genes. Embedding genomics data with environmental parameters suggests that metagenomics support early interventions while strengthening environmental governance and minimizing public health risks for its environmental dissemination.