Shaw Rahul, Cheung C Y Maurice
Division of Science, Yale-NUS College, Singapore, Singapore.
Front Plant Sci. 2018 Jun 26;9:884. doi: 10.3389/fpls.2018.00884. eCollection 2018.
Plant metabolism is highly adapted in response to its surrounding for acquiring limiting resources. In this study, a dynamic flux balance modeling framework with a multi-tissue (leaf and root) diel genome-scale metabolic model of was developed and applied to investigate the reprogramming of plant metabolism through multiple growth stages under different nutrient availability. The framework allowed the modeling of optimal partitioning of resources and biomass in leaf and root over diel phases. A qualitative flux map of carbon and nitrogen metabolism was identified which was consistent across growth phases under both nitrogen rich and limiting conditions. Results from the model simulations suggested distinct metabolic roles in nitrogen metabolism played by enzymes with different cofactor specificities. Moreover, the dynamic model was used to predict the effect of physiological or environmental perturbation on the growth of Arabidopsis leaves and roots.
植物代谢高度适应其周围环境以获取有限资源。在本研究中,开发了一个具有多组织(叶和根)昼夜基因组规模代谢模型的动态通量平衡建模框架,并将其应用于研究不同养分有效性下多个生长阶段植物代谢的重编程。该框架允许对昼夜阶段叶和根中资源和生物量的最佳分配进行建模。确定了碳和氮代谢的定性通量图,该图在富氮和氮限制条件下的各个生长阶段都是一致的。模型模拟结果表明,具有不同辅因子特异性的酶在氮代谢中发挥着不同的代谢作用。此外,该动态模型用于预测生理或环境扰动对拟南芥叶和根生长的影响。