Amino acid metabolic shifts in rice: responses to elevated CO2, cyanide, and nitrogen sources

Abstract

Background

Amino acids (AAs) play multiple roles in plant development, and their reorientation is crucial strategy for plants in metabolic adaptation to various abiotic stresses. The incorporation of exogenous CN⁻ into the N fertilization in plants is evident, wherein elevated CO₂ increases utilization and assimilation of biodegradable N-containing pollutants, consequently reduce phytotoxicity. In this study, a hydroponic system was employed to investigate the effects of different nitrogen (N) forms (nitrate: NO₃⁻ and ammonium: NH₄⁺), CO₂ concentrations (ambient at 350 ppm and elevated at 700 ppm), and exogenous cyanide (KCN at 3.0 mg CN/L) on rice plants using metabonomics analysis.

Results

Elevated [CO₂] (700 ppm) significantly enhanced the growth rate of rice seedlings, particularly under NH₄⁺ nutrition combined with CN⁻ treatment, compared to ambient [CO₂] (350 ppm). Under elevated [CO₂] both NO₃⁻ and NH₄⁺-fed plants exhibited significantly higher CN⁻ uptake and assimilation rates, with NH₄⁺-fed plants showing a greater response. Metabolomic analysis revealed distinct alteration in AA profiles, where elevated [CO₂] and exogenous CN⁻ significantly influenced the proportions of the glutamate (Glu) pathway and aspartate (Asp) pathway under both N treatments. Notably, NH₄⁺-fed plants under CN⁻ stress demonstrated a 5.75-fold increase in total AA content in shoots under elevated [CO₂], while NO₃⁻-fed plants CN⁻ stress showed a smaller increase of 1.81-fold. These results suggest that elevated [CO₂] coupled with NH⁴⁺ nutrition optimizes rice metabolic adaptation to CN⁻ stress.

Conclusions

This study highlights the strategic alteration of AA profiles as a key adaptive mechanism in rice plants facing elevated [CO₂] and exogenous CN⁻ stress. These shifts in AA pathways facilitate enhanced nutrient assimilation and stress resilience, offering insights into plant metabolic adaptation under changing environmental conditions.

Graphical abstract