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稳态代谢的综合化学计量学、热力学和动力学建模。

Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.

机构信息

Center for Chromosome Biology, School of Natural Sciences, National University of Ireland, Galway, Ireland.

出版信息

J Theor Biol. 2010 Jun 7;264(3):683-92. doi: 10.1016/j.jtbi.2010.02.044. Epub 2010 Mar 15.

Abstract

The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis.

摘要

生物化学反应用于生物科学前沿的定量分析。最近,生物学中高通量技术数据集的出现为各种复杂程度的新建模方法铺平了道路,包括细胞或生物体的代谢组。理解单细胞和多细胞生物的新陈代谢将为合理设计生长条件提供知识,以在生物技术中生产具有商业价值的试剂。在这里,我们展示了如何将代表稳态质量守恒、能量守恒、热力学第二定律和可逆酶动力学的方程表示为一个单一的线性等式和不等式系统,除了指数变量的线性等式。尽管可行集是非凸的,但该重述是准确的,并且适用于大规模数值分析,这是计算上可行的基因组规模建模的前提。在统一的基于约束的公式中集成通量、浓度和动力学变量,旨在提高通量平衡分析的定量预测能力。将热力学和动力学变量的实验和理论边界纳入其中,可确保预测的稳态通量在热力学和生物化学上都是可行的。所得的计算预测结果与大肠杆菌中心代谢的通量组学数据进行了比较,并且与通量平衡分析的计算预测结果相比具有优势。

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本文引用的文献

2
Metabolic capabilities of Escherichia coli: I. synthesis of biosynthetic precursors and cofactors.
J Theor Biol. 1993 Dec 21;165(4):477-502. doi: 10.1006/jtbi.1993.1202.
3
A protocol for generating a high-quality genome-scale metabolic reconstruction.
Nat Protoc. 2010 Jan;5(1):93-121. doi: 10.1038/nprot.2009.203. Epub 2010 Jan 7.
4
Quantitative assignment of reaction directionality in constraint-based models of metabolism: application to Escherichia coli.
Biophys Chem. 2009 Dec;145(2-3):47-56. doi: 10.1016/j.bpc.2009.08.007. Epub 2009 Sep 1.
6
Group contribution method for thermodynamic analysis of complex metabolic networks.
Biophys J. 2008 Aug;95(3):1487-99. doi: 10.1529/biophysj.107.124784.
7
Something from nothing: bridging the gap between constraint-based and kinetic modelling.
FEBS J. 2007 Nov;274(21):5576-85. doi: 10.1111/j.1742-4658.2007.06076.x. Epub 2007 Oct 8.
8
Estimation of the number of extreme pathways for metabolic networks.
BMC Bioinformatics. 2007 Sep 27;8(1):363. doi: 10.1186/1471-2105-8-363.
9
Storing and annotating of kinetic data.
In Silico Biol. 2007;7(2 Suppl):S37-44.

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