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Data-driven integrative modeling of photorespiratory metabolism

数据驱动的光呼吸代谢综合建模

基本信息

批准号：
246607488
负责人：
Professor Dr. Zoran Nikoloski, Ph.D.
金额：
--
依托单位：
Arbeitsgruppe Bioinformatik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2016-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/246607488?language=en
关键词：
Data driven integrative modeling photorespiratory

项目摘要

Biological processes involved in photorespiratory and photosynthetic metabolisms operate concurrently and affect the interplay between carbon and nitrogen assimilation reflected in plant growth. Experimental evidence has indicated that photorespiratory metabolism has a wide-ranging influence not only on other principal metabolic pathways but also on a multitude of signaling cascades. Therefore, accurate quantitative models of photorespiration can provide the means for predicting and in silico probing of behavior on various levels of the plant system. The goal of this project is threefold: First, we plan to devise both structural and kinetic models of photorespiration which will be used to in silico investigate the effects of photorespiratory metabolism under different environmental conditions on genome-scale metabolic network of C3 plants. Second, the high-throughput transcriptomics and metabolomics data from experiments with wild type and mutant plants will be integrated with the models to characterize the cellular metabolic state, described by reaction fluxes and metabolite levels, and determine key pathway components. The integration of data and models will be performed by using constraint-based approaches for estimating fluxes and metabolite turnover. With the help of these approaches, we will consider photoresipratory metabolism in the context of tightly linked carbon and nitrogen metabolisms. Third, the kinetic and structural models will be employed to design and investigate in silico metabolic engineering strategy to improve the plant biomass production. The proposed framework will allow assessing the still controversial role of photorespiration in plant growth and yield by confronting the devised models with high-throughput data.

参与光呼吸和光合代谢的生物过程同时进行，并影响植物生长中反映的碳和氮同化之间的相互作用。实验证据表明，光呼吸代谢不仅对其他主要代谢途径，而且对众多的信号级联具有广泛的影响。因此，精确的光呼吸定量模型可以提供预测和在计算机上探测植物系统的各个层面上的行为的手段。本项目的目标有三个方面：首先，我们计划设计光呼吸的结构和动力学模型，这些模型将用于在计算机上研究不同环境条件下光呼吸代谢对C3植物基因组尺度代谢网络的影响。其次，来自野生型和突变体植物实验的高通量转录组学和代谢组学数据将与模型集成，以表征细胞代谢状态，通过反应通量和代谢物水平描述，并确定关键途径组分。数据和模型的整合将通过使用基于约束的方法来估计通量和代谢物周转。在这些方法的帮助下，我们将在紧密联系的碳和氮代谢的背景下考虑光合作用代谢。第三，动力学和结构模型将被用来设计和研究计算机代谢工程策略，以提高植物生物量的生产。建议的框架将允许评估仍然有争议的作用，光呼吸在植物生长和产量面对设计的模型与高通量的数据。