Wagner Clemens, Urbanczik Robert
Institute of Pharmacology, Bern, Switzerland.
Biophys J. 2005 Dec;89(6):3837-45. doi: 10.1529/biophysj.104.055129. Epub 2005 Sep 23.
The analysis of metabolic networks has become a major topic in biotechnology in recent years. Applications range from the enhanced production of selected outputs to the prediction of genotype-phenotype relationships. The concepts used are based on the assumption of a pseudo steady-state of the network, so that for each metabolite inputs and outputs are balanced. The stoichiometric network analysis expands the steady state into a combination of nonredundant subnetworks with positive coefficients called extremal currents. Based on the unidirectional representation of the system these subnetworks form a convex cone in the flux-space. A modification of this approach allowing for reversible reactions led to the definition of elementary modes. Extreme pathways are obtained with the same method but splitting up internal reactions into forward and backward rates. In this study, we explore the relationship between these concepts. Due to the combinatorial explosion of the number of elementary modes in large networks, we promote a further set of metabolic routes, which we call the minimal generating set. It is the smallest subset of elementary modes required to describe all steady states of the system. For large-scale networks, the size of this set is of several magnitudes smaller than that of elementary modes and of extreme pathways.
近年来,代谢网络分析已成为生物技术领域的一个主要课题。其应用范围从提高特定产物的产量到预测基因型与表型的关系。所使用的概念基于网络伪稳态的假设,从而使每种代谢物的输入和输出达到平衡。化学计量网络分析将稳态扩展为具有正系数的非冗余子网络的组合,这些正系数称为极值电流。基于系统的单向表示,这些子网络在通量空间中形成一个凸锥。对该方法进行修改以允许可逆反应,从而引出了基本模式的定义。通过相同的方法获得极端途径,但将内部反应分为正向和反向速率。在本研究中,我们探讨了这些概念之间的关系。由于大型网络中基本模式数量的组合爆炸式增长,我们提出了另一组代谢途径,我们称之为最小生成集。它是描述系统所有稳态所需的基本模式的最小子集。对于大规模网络,该集合的规模比基本模式和极端途径的规模小几个数量级。