Systemic metabolic reactions are obtained by singular value decomposition of genome-scale stoichiometric matrices
Systemic metabolic reactions are obtained by singular value decomposition of genome-scale stoichiometric matrices
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DOI：
10.1016/s0022-5193(03)00146-2
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发表时间：
2003-09-07
影响因子：
2
通讯作者：
Palsson, BO
中科院分区：
文献类型：
--
作者：
Famili, I;Palsson, BO
可以重建基因组规模的代谢网络。现在可以研究这些网络的系统生化特性。在这里，使用奇异值分解（SVD）分析基因组规模的重建代谢网络。包含在重构的代谢网络中的所有个体生化转化由化学计量矩阵（S）描述。S的SVD导致了基本模式的定义，这些模式表征了网络中发生的整体生化转化，并对其重要性进行了排序。这些模式被证明对应于系统的生化反应，它们可以用来识别驱动它们的个体生化反应的组和簇。对大肠杆菌、流感嗜血杆菌和幽门螺杆菌基因组规模代谢网络的比较分析表明，所有三种网络中的四种主导模式对应于：（1）ATP转化为ADP，（2）NADP的氧化还原代谢，（3）质子动力，和（4）无机磷酸盐代谢。然而，这三种生物体之间的个体代谢反应集产生这些全身转化。因此，我们现在可以定义系统代谢反应或特征反应，用于代谢的系统生物学研究，并为比较基因组特异性代谢网络的整体特性奠定基础。(C)2003 Elsevier Ltd.保留所有权利。
Genome-scale metabolic networks can be reconstructed. The systemic biochemical properties of these networks can now be studied. Here, genome-scale reconstructed metabolic networks were analysed using singular value decomposition (SVD). All the individual biochemical conversions contained in a reconstructed metabolic network are described by a stoichiometric matrix (S). SVD of S led to the definition of the underlying modes that characterize the overall biochemical conversions that take place in a network and rank-ordered their importance. The modes were shown to correspond to systemic biochemical reactions and they could be used to identify the groups and clusters of individual biochemical reactions that drive them. Comparative analysis of the Escherichia coli, Haemophilus influenzae, and Helicobacter pylori genome-scale metabolic networks showed that the four dominant modes in all three networks correspond to: (1) the conversion of ATP to ADP, (2) redox metabolism of NADP, (3) proton-motive force, and (4) inorganic phosphate metabolism. The sets of individual metabolic reactions deriving these systemic conversions, however, differed among the three organisms. Thus, we can now define systemic metabolic reactions, or eigen-reactions, for the study of systems biology of metabolism and have a basis for comparing the overall properties of genome-specific metabolic networks. (C) 2003 Elsevier Ltd. All rights reserved.