Multi-omics approaches to assess the impact of emerging contaminants in soil ecosystems

Abstract

Emerging contaminants (ECs), such as pharmaceuticals, microplastics (MPs), per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAH), endocrine-disrupting compounds (EDC) and heavy metals, are progressively affecting soil ecosystems through multiple inputs such as wastewater irrigation, biosolid amendment, agricultural runoff and atmospheric deposition. Despite their widespread occurrence, ECs are rarely incorporated into regular soil monitoring frameworks and remain mainly unregulated. Their persistent accumulation disrupts fundamental soil physicochemical characteristics, microbial community composition, soil-plant interactions, ultimately threatening ecosystem functions. Conventional ecotoxicological techniques lack the mechanistic precision necessary to capture the systemic, multi-scale changes that ECs cause throughout biological hierarchies. Multi-omics approaches, integrating metagenomics, metatranscriptomics, metaproteomics and metabolomics, have enabled comprehensive, system-level insights into EC-induced perturbations at the genetic, transcriptional, protein and metabolic levels. This review synthesises recent advances in the application of multi-omics to unravel the impacts of ECs on soil microbial communities, with a particular focus on changes in taxonomic structure, functional gene expression, enzymatic activities and metabolic pathways. Despite the transformative potential of multi-omics for ecological risk assessment and bioremediation, challenges such as data integration and dimensionality, standardisation and interpretation persist. Furthermore, substantial variability in analytical workflows and dependence on non-soil reference databases restrict inter-study comparability and practical application. Continued advancements will hinge on standardised methodologies, open-access soil databases, artificial intelligence (AI) driven data integration and long-term field investigations to enhance the reproducibility and ecological relevance. Integrating multi-omics with geospatial modelling and decision-support systems provides a pathway for translating molecular insights into actionable strategies for sustainable soil management and ecosystem restoration in the face of ECs.