A genome-scale model of Arabidopsis metabolism

拟南芥代谢的基因组规模模型

• 批准号: BB/E00203X/1
• 负责人: David Fell
• 金额: $ 23.66万
• 依托单位: Oxford Brookes University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FE00203X%2F1
• 关键词: genome; scale; model; Arabidopsis; metabolism

The molecules that make up the cells of biological organisms do not function in isolation but do so by interacting with other molecules. Cells thus consist of a complex network of interacting molecules. Because the behaviour of an individual molecule is influenced not only by its own properties but also by those of interacting molecules, networks display emergent properties - that is the behaviour of the network as a whole cannot be simply predicted from the properties of its components in isolation. One way of getting to grips with network behaviour is to construct mathematical models that allow network parameters to be computed. This proposal aims to generate a mathematical model that will provide insight into the metabolic network of the model plant species, Arabidopsis thaliana. Metabolism is one of the best described and most studied of all biological networks and yet our understanding of the behaviour of metabolism as a whole remains rather limited. A mathematical model will not only provide new insight into fundamental aspects of control of the plant metabolic network, but it will also be a useful tool to allow predictions to be made about the best way to manipulate the flow of metabolic intermediates. Such metabolic engineering is an important part of attempts to generate new varieties of crop plants that are better equipped to deal with challenges imposed by a changing global climate and the requirements for increased yield.

构成生物有机体细胞的分子不是孤立地发挥作用，而是通过与其他分子相互作用来发挥作用。因此，细胞是由相互作用的分子组成的复杂网络。由于单个分子的行为不仅受到其自身性质的影响，而且还受到相互作用分子的性质的影响，因此网络显示出涌现的性质--也就是说，网络作为一个整体的行为不能简单地从其组成部分的性质孤立地预测出来。掌握网络行为的一种方法是构建数学模型，以计算网络参数。该建议旨在生成一个数学模型，该模型将提供对模式植物物种拟南芥的代谢网络的深入了解。新陈代谢是所有生物网络中描述最好、研究最多的网络之一，但我们对新陈代谢行为的整体理解仍然相当有限。数学模型不仅将为植物代谢网络控制的基本方面提供新的见解，而且它也将是一个有用的工具，可以预测操纵代谢中间体流动的最佳方式。这种代谢工程是产生作物新品种的尝试的重要组成部分，这些作物新品种更好地应对全球气候变化带来的挑战和提高产量的要求。

项目成果

Modular decomposition of metabolic systems via null-space analysis

• DOI: 10.1016/j.jtbi.2007.08.005
• 发表时间: 2007-12-21
• 期刊: JOURNAL OF THEORETICAL BIOLOGY
• 影响因子: 2
• 作者: Poolman, Mark G.;Sebu, Cristiana;Fell, David A.
• 通讯作者: Fell, David A.

Metabolic trade-offs between biomass synthesis and photosynthate export at different light intensities in a genome-scale metabolic model of rice.

• DOI: 10.3389/fpls.2014.00656
• 发表时间: 2014
• 期刊: Frontiers in plant science
• 影响因子: 5.6
• 作者: Poolman MG;Kundu S;Shaw R;Fell DA
• 通讯作者: Fell DA

A Diel Flux Balance Model Captures Interactions between Light and Dark Metabolism during Day-Night Cycles in C3 and Crassulacean Acid Metabolism Leaves

• DOI: 10.1104/pp.113.234468
• 发表时间: 2014-06-01
• 期刊: PLANT PHYSIOLOGY
• 影响因子: 7.4
• 作者: Cheung, C. Y. Maurice;Poolman, Mark G.;Sweetlove, Lee J.
• 通讯作者: Sweetlove, Lee J.