In silico metabolic modeling has enabled systematic study of complicated metabolic processes underlying phenotypes of organisms. Modeling of plant metabolism is often hampered by the network complexity and lack of adequate knowledge. The existing metabolic networks of cassava only cover broad metabolism and are not compartmentalized to truly represent metabolism in photosynthetic tissues. To address the aforementioned limitations and develop a robust metabolic network, physiological and genomic data derived from cassava and leaf models of Arabidopsis and rice were to extend the scope of the existing model. The proposed compartmentalized network of metabolism in photosynthetic tissues of cassava, ph-MeRecon (photosynthetic-Manihot esculenta Metabolic Pathway Reconstruction) was developed based on the information resulting of the comparative study of multiple model plants and cassava genome. The ph-MeRecon covers primary carbon metabolism and comprises 461 metabolites, 550 reactions, and 1,037 metabolic genes. Enzymatic genes on the network were validated using RNA-expression data, and the reactions and pathways were compartmentalized into cytoplasm, chloroplast, mitochondria, and peroxisome. To ensure network connectivity, metabolic gaps were filled using gap reactions obtained from literature and metabolic pathway omnibus. In addition, information on plant physiology, including photosynthetic light-dependent reactions, carboxylase and oxygenase activity of RuBisCO enzyme, and phosphoenolpyruvate carboxylase enzyme activity was incorporated into ph-MeRecon to mimic cellular metabolism in cassava leaves. Thus, ph-MeRecon offers a multi-level platform for system analysis of cellular mechanisms underlying phenotypes of interest in cassava. The ph-MeRecon metabolic model is available at http://bml.sbi.kmutt.ac.th/ph-MeRecon/.
Cassava is a staple crop that acclimatizes well to dry weather and limited water availability. The drought response mechanism of quick stomatal closure observed in cassava has no explicit link to the metabolism connecting its physiological response and yield. Here, a genome-scale metabolic model of cassava photosynthetic leaves (leaf-MeCBM) was constructed to study on the metabolic response to drought and stomatal closure. As demonstrated by leaf-MeCBM, leaf metabolism reinforced the physiological response by increasing the internal CO2 and then maintaining the normal operation of photosynthetic carbon fixation. We found that phosphoenolpyruvate carboxylase (PEPC) played a crucial role in the accumulation of the internal CO2 pool when the CO2 uptake rate was limited during stomatal closure. Based on the model simulation, PEPC mechanistically enhanced drought tolerance in cassava by providing sufficient CO2 for carbon fixation by RuBisCO, resulting in high production of sucrose in cassava leaves. The metabolic reprogramming decreased leaf biomass production, which may lead to maintaining intracellular water balance by reducing the overall leaf area. This study indicates the association of metabolic and physiological responses to enhance tolerance, growth, and production of cassava in drought conditions.
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