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A Spatially‐Resolved Framework Reveals Contrasting Root and Leaf Strategies to Nanoplastic‐Arsenic Stress in Rice

Physiologia Plantarum 2026 Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Chanchan Xu

Summary

This study used a new statistical framework to show that rice roots and leaves respond very differently when exposed to both nanoplastics and arsenic simultaneously: roots mount a straightforward additive defense, while leaves show complex antagonistic molecular interactions centred on iron storage. The finding is important for food safety because it reveals that standard toxicity tests on individual stressors may underestimate the risks posed by contaminant mixtures in food crops.

Understanding how plant roots manage co-occurring environmental stressors like nanoplastics (NPs) and arsenic (As) is critical, yet conventional methods often overlook their distinct strategic responses. Here, we developed and validated the Spatially-Dependent Interaction Framework (SDIF), a unified statistical model designed to deconstruct complex multi-stressor interactions across biological compartments. Applied to a high-resolution transcriptomic dataset from rice (Oryza sativa) co-exposed to environmentally relevant levels of NPs (1 mg L-1) and As (1 mg L-1 As(III)), our analysis revealed that roots employ a predominantly additive defense strategy, with virtually no significant nonadditive molecular interactions (1 gene). This contrasts sharply with the systemic response in leaves, where complex antagonistic interactions were prevalent (40 genes), indicating a distinct role in systemic damage control. Crucially, the SDIF's direct test for three-way interactions (Stressor A × Stressor B × Tissue) pinpointed the iron homeostasis protein Ferritin 1 (OsFer1) as a key regulator of this divergent strategy. OsFer1 exhibited synergistic amplification in roots (interaction log2-fold change [LFC] = +1.27), consistent with a fortified frontline defense, which is reversed to an antagonistic suppression in leaves (LFC = -0.85). This critical finding, obscured by traditional analyses, highlights SDIF's utility in uncovering nuanced, organ-specific toxicodynamic strategies. It underscores the importance of a root-centric perspective for the risk assessment of contaminant mixtures in food crops.

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