Prospects for Using Multi-omics to Advance the Bioremediation of Organic Micropollutants in Aquatic Environments: A Review

The continued rise in concentrations of organic micropollutants (OMPs) in aquatic ecosystems and the significant risks posed by OMPs to environmental and human health emphasize the dire need for effective, mechanism‑based mitigation strategies. Multi‑omics technologies now provide essential insights into how complex microbial communities mediate OMP removal and transformation. Here, we review recent advances in metagenomics, metatranscriptomics, metaproteomics, metabolomics, and stable isotope probing, and outline how their integration can be used to systematically identify key OMPs‑degrading microorganisms, resolve primary and co‑metabolic pathways, and characterize the functional enzymes and transformation products involved. We also summarize database resources and predictive computational tools that support genome‑ and pathway‑level interpretations of multi‑omics data in the context of OMP bioremediation. Finally, we propose a multi‑level analytical framework that integrates metagenomics, metaproteomics, metabolomics, and stable isotope probing to enable the systematic identification of key degrading microorganisms, functional enzymes, and transformation pathways involved in OMP remediation. Together, these recent advances demonstrate that multi-omics studies are beginning to successfully merge data obtained from individual omics layers into an integrated picture of the microbial networks, pathways, and transformation products that underpin OMPs bioremediation in aquatic environments. Overall, the synthesis of current case studies and methodology developments presented indicates that the prospects are highly promising for multi-omics-guided frameworks to improve the reliability, efficiency, and adaptability of OMPs remediation compared with approaches that rely on single omics technologies alone. • Multi-omics are increasingly applied to aquatic OMPs bioremediation studies. • Multi-omics combined with stable isotope tracing uncovers bioremediation processes of OMPs. • Database of OMPs biodegradation enhances the predictability of degradation products. • Multi-omics combined with AI promote modelling and optimizing microbial performances.