Tissue-specific metabolite profiling reveals diverse metabolic response under N deficiency and high temperature stress in soybean.
Journal:
Journal of advanced research
Published Date:
Aug 7, 2026
Abstract
INTRODUCTION: Climate change has increased the incidence of compound stresses, including the co-occurrence of nitrogen deficiency (-N) and high temperature (HT), which severely reduce plant productivity. Studies have primarily focused on single plant tissues to decipher tolerance mechanisms; however, tissue-specific metabolic reprogramming remains poorly examined. OBJECTIVES: This work aimed to examine the distinct metabolic reprogramming in roots and leaves under whole-plant nitrogen deficiency (-N) and high temperature (HT), applied individually or combined. We hypothesized that roots and leaves exhibit complementary metabolic profiles, while combined stress triggers a unique metabolic signature associated with plant growth regulation. METHODS: Soybean plants were subjected to control, -N, HT, and HT-N conditions, and later whole-plant physiological assessment and untargeted metabolites profiling of roots and leaves were performed and analyzed by machine learning analyses (e.g., t-SNE, UMAP, WGCNA, and random forest regression), qPCR and absolute quantification of identified key metabolites. RESULTS: Combined HT-N stress caused severe growth inhibition, reduced shoot length (67%), root fresh weight (52%), and photosynthetic efficiency (Fv/Fm; by 51%) compared to control. Metabolomic analysis revealed stress specific responses in different tissues, with roots prioritizing N assimilation (accumulating glutamate, proline and aspartate) under -N, while leaves enhanced osmo-protection (accumulating flavonoids) under HT. Under combined HT-N, tissue-specific responses were additive, with roots focusing on amino acid and proline metabolism and leaves on phenylpropanoid and glutathione metabolism. Our machine learning analyses (t-SNE, UMAP), WGCNA and RFR showed distinct tissue-specific metabolic signatures for each stress, and identified glucose, flavonoids, proline, and specific amino acids among key candidate metabolites associated with physiological resilience. Later, exogenous application of proline, quercetin, and L-arginine recovered soybean growth under stress, but in a stress-specific manner. CONCLUSION: Soybean employs distinct metabolic strategies in roots and leaves to manage multiple stresses. The identified key metabolites represent candidate hubs in the stress response network, offering candidate targets that warrant further investigation for breeding climate-resilient crops.
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