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...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 variabil-ity 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.展开更多
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)
文摘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 variabil-ity 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.
