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通量总和分析:一种以代谢物为中心理解代谢网络的方法。

Flux-sum analysis: a metabolite-centric approach for understanding the metabolic network.

作者信息

Chung Bevan Kai Sheng, Lee Dong-Yup

机构信息

NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 28 Medical Drive, #05-01, 117456, Singapore.

出版信息

BMC Syst Biol. 2009 Dec 19;3:117. doi: 10.1186/1752-0509-3-117.

Abstract

BACKGROUND

Constraint-based flux analysis of metabolic network model quantifies the reaction flux distribution to characterize the state of cellular metabolism. However, metabolites are key players in the metabolic network and the current reaction-centric approach may not account for the effect of metabolite perturbation on the cellular physiology due to the inherent limitation in model formulation. Thus, it would be practical to incorporate the metabolite states into the model for the analysis of the network.

RESULTS

Presented herein is a metabolite-centric approach of analyzing the metabolic network by including the turnover rate of metabolite, known as flux-sum, as key descriptive variable within the model formulation. By doing so, the effect of varying metabolite flux-sum on physiological change can be simulated by resorting to mixed integer linear programming. From the results, we could classify various metabolite types based on the flux-sum profile. Using the iAF1260 in silico metabolic model of Escherichia coli, we demonstrated that this novel concept complements the conventional reaction-centric analysis.

CONCLUSIONS

Metabolite flux-sum analysis elucidates the roles of metabolites in the network. In addition, this metabolite perturbation analysis identifies the key metabolites, implicating practical application which is achievable through metabolite flux-sum manipulation in the areas of biotechnology and biomedical research.

摘要

背景

基于约束的代谢网络模型通量分析可量化反应通量分布,以表征细胞代谢状态。然而,代谢物是代谢网络中的关键参与者,由于模型构建的固有局限性,当前以反应为中心的方法可能无法解释代谢物扰动对细胞生理学的影响。因此,将代谢物状态纳入模型以进行网络分析是切实可行的。

结果

本文提出了一种以代谢物为中心的代谢网络分析方法,通过将代谢物的周转率(即通量总和)作为模型构建中的关键描述变量。通过这样做,可以借助混合整数线性规划来模拟代谢物通量总和变化对生理变化的影响。从结果中,我们可以根据通量总和概况对各种代谢物类型进行分类。使用大肠杆菌的iAF1260计算机代谢模型,我们证明了这一新颖概念补充了传统的以反应为中心的分析。

结论

代谢物通量总和分析阐明了代谢物在网络中的作用。此外,这种代谢物扰动分析确定了关键代谢物,暗示了在生物技术和生物医学研究领域通过代谢物通量总和操纵可实现的实际应用。

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