Work

Next-Generation Wastewater Treatment: Omics and AI-Driven Microbial Strategies for Xenobiotic Bioremediation and Circular Resource Recovery

Year: 2025

Type: article

Abstract: Wastewater treatment plants (WWTPs) function as engineered ecosystems in which microbial consortia mediate nutrient cycling, xenobiotic degradation, and heavy metal detoxification. This review discusses a forward-looking roadmap that integrates microbial ecology, multi-omics diagnostics, and artificial intelligence (AI) for next-generation treatments. Meta-analyses suggest that a globally conserved core microbiome indicates sludge functions, with high predictive value for treatment stability. Multi-omics approaches, including metagenomics, metatranscriptomics, and environmental DNA (eDNA) profiling, have integrated microbial composition with greenhouse gas (GHG) emissions, showing that WWTPs contribute 2–5% of anthropogenic nitrous oxide (N2O) emissions. Emerging AI-enhanced eDNA models have achieved >90% predictive accuracy for effluent quality and antibiotic resistance gene (ARG) prevalence, facilitating near-real-time monitoring and adaptive control of effluent quality. Key advances include microbial strategies for degrading organic pollutants, pesticides, and heavy metals and monitoring industrial effluents. This review highlights both translational opportunities, including engineered microbial consortia, AI-driven digital twins and molecular indices, and persistent barriers, including ARG dissemination, resilience under environmental stress and regulatory integration. Future WWTPs are envisioned as adaptive, climate-conscious biorefineries that recover resources, mitigate ecological risks, and reduce their carbon footprint.

Source: Processes

DOI: 10.3390/pr13103218

Authors: Prabhaharan Renganathan, Lira A. Gaysina

Institutions: M. Akmullah Bashkir State Pedagogical University, Moscow Institute of Physics and Technology, Russian Research Institute for Phytopathology

Language: English

Topic: Wastewater Treatment and Nitrogen Removal

Subfield: Pollution

Field: Environmental Science

Domain: Physical Sciences

SDGs: Clean water and sanitation, Responsible consumption and production, Climate action, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,896