Collaborative Research: Predictive Modeling of Maize Metabolism

合作研究：玉米代谢的预测模型

• 批准号: 1517671
• 负责人: Ganesh Sriram
• 金额: $ 32.61万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1517671&HistoricalAwards=false
• 关键词: Collaborative; Research; Predictive; Modeling; Maize

This project will develop and test predictive mathematical models of the chemical reactions (metabolism) by which maize (corn) transforms the sugars produced during photosynthesis into compounds such as starch that are stored in the seeds. The goal is to understand starch metabolism better and provide the means for enhancing food production. This study will reveal fundamental principles of metabolic function and dynamics, and provide interdisciplinary training (in mathematical modeling, genetic engineering and metabolic biochemistry) to students engaged in this project.Starchy endosperm (SE) is the major site of carbohydrate and protein storage in cereals, but atypical constraints complicate detailed resolution of the system. These include a steady state carbon dioxide level of essentially zero, coincident with energy-expensive breakdown and re-synthesis of building blocks prior to storage polymer formation. A major question in SE metabolism is how ATP is generated to support starch and protein synthesis, and how the photo-assimilate is divided between catabolic and anabolic pathways. This project will expand upon existing flux models to account for bio-energetic parameters, and probe the system by directed genetic modifications that impair specific metabolic nodes. Metabolite levels and flux maps will be compared between SE from unaltered and mutant lines. These data will be applied to refine the mathematical models and test hypotheses of how the system diverts chemical resources for storage compound accumulation.

该项目将开发和测试化学反应(新陈代谢)的预测数学模型，玉米(玉米)通过该模型将光合作用过程中产生的糖转化为储存在种子中的淀粉等化合物。其目标是更好地了解淀粉代谢，并为提高粮食产量提供手段。这项研究将揭示代谢功能和动力学的基本原理，并为从事这一项目的学生提供跨学科的培训(数学建模、基因工程和代谢生物化学)。星状胚乳(SE)是谷物中碳水化合物和蛋白质储存的主要部位，但非典型的限制因素使系统的详细解析复杂化。其中包括基本为零的稳态二氧化碳水平，这与能源成本高昂的分解和在存储聚合物形成之前重新合成积木相一致。SE代谢的一个主要问题是如何产生ATP来支持淀粉和蛋白质的合成，以及光同化产物是如何在分解代谢和合成代谢途径之间分配的。该项目将扩展现有的流量模型以解释生物能量参数，并通过损害特定新陈代谢节点的定向遗传修改来探索该系统。我们将比较未改变品系和突变品系的SE代谢物水平和通量图。这些数据将被用来改进数学模型，并测试系统如何将化学资源转移到储存化合物积累的假设。