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

Area of Science:

• Environmental toxicology
• Plant molecular biology
• Computational biology

Background:

• Co-occurring environmental stressors, such as nanoplastics (NPs) and arsenic (As), pose complex challenges to plant health.
• Conventional methods often fail to capture the distinct molecular strategies plants employ to manage multiple simultaneous environmental insults.
• Understanding organ-specific responses is crucial for accurate risk assessment of contaminant mixtures in crops.

Purpose of the Study:

• To develop and validate a unified statistical model, the Spatially-Dependent Interaction Framework (SDIF), for analyzing complex multi-stressor interactions.
• To investigate the distinct molecular responses of rice (Oryza sativa) roots and leaves to co-exposure of nanoplastics and arsenic.
• To identify key molecular regulators of organ-specific stress responses using high-resolution transcriptomic data.

Main Methods:

• Development and application of the Spatially-Dependent Interaction Framework (SDIF) statistical model.
• Analysis of high-resolution transcriptomic data from rice plants exposed to environmentally relevant levels of nanoplastics and arsenic (As(III)).
• Direct testing for three-way interactions (Stressor A × Stressor B × Tissue) to pinpoint regulatory mechanisms.

Main Results:

• Rice roots primarily exhibited additive defense strategies against nanoplastics and arsenic, with minimal non-additive molecular interactions.
• Rice leaves displayed significant antagonistic interactions, suggesting a role in systemic damage control.
• The iron homeostasis protein Ferritin 1 (OsFer1) was identified as a key regulator, showing synergistic amplification in roots and antagonistic suppression in leaves.

Conclusions:

• The Spatially-Dependent Interaction Framework (SDIF) effectively reveals nuanced, organ-specific toxicodynamic strategies obscured by traditional analyses.
• Plant roots and leaves employ distinct molecular strategies to manage co-occurring environmental stressors.
• A root-centric perspective is essential for the accurate risk assessment of contaminant mixtures in food crops.