Cracking the code on degrading water contaminants through multi-omics
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Graphic Abstract
view moreCredit: Yujia Zhai
Organic micropollutants (OMPs), including pharmaceuticals, personal care products, industrial chemicals, and pesticides, are harmful to environmental and human health due to their toxicity, persistence, and bioaccumulative properties. Conventional physical and chemical treatment methods often prove impractical due to high costs, waste disposal problems, and generation of toxic byproducts, making biological remediation an economically viable and environmentally friendly alternative. However, much remain unknown, including the identity of key degrading microorganisms, the enzymatic mechanisms underlying primary and co‑metabolic pathways, and the fate of transformation products under environmentally relevant conditions.
In a new study published in Water & Ecology, an international team led by Yujia Zhai from Beijing Normal University addresses the escalating challenge of OMPs in aquatic ecosystems and critically evaluates the transformative potential of multi-omics technologies in advancing bioremediation strategies.
“We reviewed four omics technologies—metagenomics, metatranscriptomics, metaproteomics, metabolomics, combined with stable isotope probing (SIP)—and demonstrated how their integration surpasses the limitations of single‑omics approaches,” shares Zhai.
The team found that metagenomics provides genetic potential and community composition; metatranscriptomics reveals real‑time gene expression; metaproteomics identifies expressed enzymes and catalytic functions; metabolomics captures substrate dynamics and transformation intermediates. “However, each approach in isolation has major constraints, as using certain omics methods independently may cause researchers to miss important links between different genes, proteins, and metabolites and therefore fail to fully understand the underlying OMP degradation mechanisms,” says Zhai.
The integration of omics data at different levels (i.e., genes, proteins, and metabolites), often referred to as “multi-omics”, can aid in the identification of novel pathways and mechanisms involved in the degradation of pollutants. “A multi-omics approach to establish OMP degradation mechanisms should include whole metagenome sequencing (metagenomics), gene expression level analysis (metatranscriptomics), and analysis of expressed pathways and enzymes (metaproteomics), as well as the identification of the degradation and transformation products using metabolomics and bioinformatics tools,” adds Zhai.
To that end, the researchers proposed a multi‑level analytical framework that integrates metagenomics, metaproteomics, metabolomics, and SIP to pinpoint OMP‑degrading microorganisms, functional enzymes, and transformation routes. “By tracking isotopically labeled OMPs into biomass and metabolic products, SIP enables the assignment of degradation functions to specific taxa and the elucidation of metabolic flux within complex communities,” says Zhai. ““The combination of SIP and multi‑omics potentially allows for the reconstruction of degradation and conversion routes within complex microbial communities while also providing insights into the relationships between microorganisms (e.g., cross‑feeding) and the contribution of individual microorganisms to the overall community metabolic function.”
The researchers also assessed current computational tools and databases—such as KEGG, MetaCyc, EAWAG‑BBD, and enviPath—that support pathway prediction and genome‑resolved interpretation. “While these tools are valuable, they remain constrained by incomplete reaction rules and an inability to model microbial interactions, underscoring the necessity of coupling predictions with empirical multi‑omics validation,” says Zhai.
The researchers conclude that the prospects are 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. “Future research should move toward quantitative models that can predict how complex communities will respond to changing OMP loads and identify leverage points for targeted intervention,” Zhai adds.
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Contact the author:
Yujia Zhai, yzhai@bnu.edu.cn
-State Key Laboratory of Regional Environment and Sustainability, School of Environment, Beijing Normal University, Beijing100875, China
The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).
Journal
Water & Ecology
Method of Research
Literature review
Subject of Research
Not applicable
COI Statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Mark van Loosdrecht is an editorial board member for Water & Ecology and was not involved in the editorial review or the decision to publish this article.
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