Deciphering soil microbial dynamics in response to pollution stress: A multi-omic perspective

Soils harbor complex microbial communities that underpin the One Health continuum, sustaining ecosystem functions and human well-being. Nonetheless, heavy metal and organic pollutant contamination perturbs these communities, leading to functional impairments and ecological imbalance. Unlike previous reviews that broadly surveyed omics applications, this review focuses on three specific advances: (i) synthesizing recent breakthroughs in metagenomics, meta­­transcriptomics, metaproteomics, metabolomics, and viromics specifically under pollution stress; (ii) highlighting recurring cross-omic patterns, particularly the distinction between functional potential and realized activity, as well as temporal mismatches among molecular layers under pollution stress; and (iii) highlighting how multi-omics integration can link soil microbial dynamics to human health risks—particularly by identifying pollutant-driven antibiotic resistance genes (ARGs), virulence factors, and pathogen reservoirs that may enter the food chain or water systems. Nevertheless, the success of multi-omics has also exposed critical bottlenecks: data heterogeneity across omic layers, limited functional annotation of the “microbial dark matter,” and the inability to establish causal links between molecular potential and ecosystem outcomes. Addressing these challenges requires standardized pipelines, machine-learning architectures, and integration with single-cell and spatial omics. Ultimately, multi-omics frameworks empower evidence-based interventions to mitigate environmental contamination and its cascading effects on public health.