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Expanded flux variability analysis on metabolic network of Escherichia coli

ISSN号：1000-3258
期刊名称：《低温物理学报》
时间：0
分类：TQ920.1[轻工技术与工程—发酵工程;化学工程] TV871[水利工程—水利水电工程]
作者机构：[1]Center for Theoretical Biology and School of Physics, Peking University, Beijing 100871, China, [2]Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
相关基金：Supported by the National Natural Science Foundation of China （Grant No. 10721403）, National Basic Research Program of China （Grant Nos. 2006CB910706, 2007CB814800, 2009CB918500）, Chun-Tsung endowment at Peking University and National Fund for Fostering Talents of Basic Science （Grant No. J0630311）The authors thank M, Ni and S.Y. Wang for their valuable suggestions and critical reading of the manuscript.

作者： CHEN Tong[1], XIE ZhengWei[1], OUYANG Qi[1,2]

关键词：代谢网络, 变异性分析, 大肠杆菌, 通量, 代谢反应, 质量守恒定律, 细胞代谢, 增长速度, metabolic network, flux balance analysis, modularity, essentiality

中文摘要：

基于在一个细胞的有机体的集体能量守恒定律，流动平衡分析广泛地被采用了学习在细胞的新陈代谢的网络的结构和功能之间的相互影响。因而，新陈代谢的显型能很好被阐明。在这篇论文，我们介绍扩展流动可变性分析(EFVA ) 描绘新陈代谢的反应的内在的性质，例如灵活性，模块化和本性，由探索范围，最大值和反应的最小的流动的趋势。我们作为一个例子拿了 Escherichia 关口 i 的新陈代谢的网络并且在不同生长率限制下面分析了反应流动的可变性。当生长率增加时，所有反应的平均可变性戏剧性地减少。在新陈代谢的系统上考虑噪音效果，我们因此主张微生物可以实际上在一个非最优的状态下面成长。而且在 EFVA 框架下面，反应是容易被组织进分解代谢、 anabolism 的组。并且 anabolism 的组能进一步被分到特定的生物资源组成。我们也发现了反应的生长率依赖者本性。增补材料为在 10.1007/s11434-009-0341-x 的这篇文章是可得到的并且为授权的用户是可存取的。

英文摘要：

Flux balance analysis, based on the mass conservation law in a cellular organism, has been extensively employed to study the interplay between structures and functions of cellular metabolic networks. Consequently, the phenotypes of the metabolism can be well elucidated. In this paper, we introduce the Expanded Flux Variability Analysis （EFVA） to characterize the intrinsic nature of metabolic reactions, such as flexibility, modularity and essentiality, by exploring the trend of the range, the maximum and the minimum flux of reactions. We took the metabolic network of Escherichia coli as an example and analyzed the variability of reaction fluxes under different growth rate constraints. The average variability of all reactions decreases dramatically when the growth rate increases. Consider the noise effect on the metabolic system, we thus argue that the microorganism may practically grow under a suboptimal state. Besides, under the EFVA framework, the reactions are easily to be grouped into catabolic and anabolic groups. And the anabolic groups can be further assigned to specific biomass constitute. We also discovered the growth rate dependent essentiality of reactions.

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