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◆ Biodegradation2026-09-08

Decoding next-generation heavy metal bioremediation via species-specific Earthworm and its gut microbiome interactions: insights from molecular responses, multi-omics, synthetic biology, and artificial intelligence.

Inrikynti Mary Kharmawphlang, María Gómez-Brandón, Nazneen Hussain

原始摘要(英文原文)· Original abstract
Heavy metal (HM) contamination represents a persistent global threat, demanding bioremediation strategies that are both mechanistically robust and ecologically sustainable. This review provides a next-generation perspective on vermiremediation by integrating species-level physiology, gut microbiome functionality, molecular detoxification pathways, synthetic biology innovations, multi-omics insights, and artificial intelligence (AI)-driven modeling into a unified framework. A central novelty of this work lies in the detailed elucidation of earthworm-microbe consortia and their synergistic contributions to metal sequestration, transformation, and detoxification-moving beyond traditional organism-centric views toward eco-engineered host-symbiont systems. We synthesize species-specific bioaccumulation patterns, toxicological responses, and detoxification mechanisms, supported by enrichment kinetic models. At the molecular scale, we highlight antioxidant defense pathways involving catalase, glutathione-S-transferase, and superoxide dismutase, alongside oxidative stress signaling, macromolecular damage, and thresholds that differentiate adaptive resilience from system failure. Advancements in synthetic biology includes gene editing, pathway reconstruction, and designer symbiotic microbes which are examined as emerging tools to enhance gut microbial functionality and engineer targeted metal-binding pathways. Multi-omics approaches provide a systems-level view of detoxification networks, revealing previously uncharacterized genes, enzymes, and metabolic signatures associated with HM tolerance and early biomarkers of sub-lethal stress. The incorporation of AI-based models introduces a data-driven dimension, enabling accurate prediction of remediation outcomes and optimization of vermiremediation strategies. Overall, this review advances vermiremediation from an empirical practice to a programmable, systems-biotechnology platform for sustainable HM bioremediation.
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Decoding next-generation heavy metal bioremediation via species-specific Earthworm and its gut microbiome interactions: insights from molecular responses, multi-omics, synthetic biology, and artificial intelligence. — 科研速览 Science Skim