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Microbial Remediation of Agrochemical-Contaminated Soils: Enzymatic Mechanisms, Quorum Sensing, and Emerging
1UCD School of Agriculture and Food Science, University College Dublin, Dublin, D04 V1W8 Ireland.
Abstract:
The intensive and repeated use of agrochemicals, including synthetic pesticides, herbicides, and fertilisers, has led to persistent contamination of agricultural soils, endangering soil health, ecosystem services, biodiversity, and sustainable food production. Soil microbiomes, with their remarkable metabolic versatility, represent a promising resource for in situ remediation of these pollutants. This review provides an integrated overview of the enzymatic and regulatory mechanisms underpinning microbial remediation, placing greater emphasis on enzymatic degradation as the central process driving pollutant breakdown. The biodegradation of soil pollutants is orchestrated by a network of microbial enzymes, including organophosphorus hydrolases, dehalogenases, oxidoreductases, dioxygenases, plastic-degrading and alkane-catabolising enzymes, that catalyse oxidation, hydrolysis, and dehalogenation reactions, transforming toxic compounds into less harmful intermediates that feed into metabolic pathways. Understanding the relationship between these enzymes, their encoding genes, and microbial hosts is crucial for designing robust bioremediation strategies. Complementing these biochemical processes, quorum sensing (QS) is discussed as a regulatory system that modulates microbial cooperation, biofilm formation, and catabolic gene expression during degradation. Emerging strategies, including microbial consortia design and synthetic biology-based engineering, are evaluated with a focus on the integration of QS-mediated interactions. Critical challenges, including soil heterogeneity, abiotic inhibition of QS signals, enzyme instability, biosafety concerns related to engineered strains, and horizontal gene transfer, are discussed. Future perspectives highlight enzyme engineering, QS-based biosensors, artificial intelligence-driven modelling, and synthetic QS circuits as tools to optimise bioremediation outcomes. Collectively, these insights outline pathways for advancing ecologically sound and sustainable approaches to the remediation of agrochemical-contaminated soils.
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