Network-based Analysis of Kinetics and Regulation

描述(由申请人提供)：极端途径是代谢途径的一个独特的、基于网络的数学定义，因此可以用来严格定义和研究生物系统的紧急性质。它们直接来自代表生化网络的化学计量矩阵，并完全表征了通过该网络的所有可能的稳态通量分布。极端路径已经给出了许多关于重构反应网络的拓扑性质以及它们与生物功能的关系的有洞察力的结论。然而，极端途径的实用性目前受到这样一个事实的限制，即完全列举基因组规模的极端途径在计算上是具有挑战性的。此外，需要开发新的分析工具来加强极端途径特性和实验数据之间的联系。因此，我们的具体目标是：(1)能够从基因组规模的模型中有效地计算极端路径；(2)应用在特定目标#1中开发的技术来计算极端路径：(A)细胞器(来自酿酒酵母的线粒体和来自拟南芥的叶绿体)，(B)依赖于生长条件的人类病原体(幽门螺杆菌和流感嗜血杆菌以及在本提案期间可能出现的其他病原体)，以及(C)完全自主的生物体大肠杆菌线圈；以及(3)开发分析工具，通过分析极端途径矩阵的奇异值分解(SVD)，并利用测量的浓度(蛋白质组学和代谢组学数据)将通量锥转换为动力学常数锥(K锥)，从而产生更多的生物学意义和极端途径的相关性。到目前为止开发和验证的概念和分析方法必须向前推进，以便将概念直接与生物数据和应用联系起来。如果实施，这项拟议的计划将使我们在研究和表征重建网络的能力以及将电子计算结果与实际蜂窝功能联系起来的能力方面取得重大进展。

DESCRIPTION (provided by applicant): Extreme pathways are a unique, network-based, mathematical definition of metabolic pathways and thus can be used to rigorously define and study the emergent properties of biological systems. They are derived directly from the stoichiometric matrix that represents a biochemical network and completely characterize all possible steady-state flux distributions through the network. Extreme pathways have already given many insightful conclusions about the topological properties of reconstructed reaction networks and their relationships to biological functionalities. However, the utility of extreme pathways is currently limited by the fact that the complete enumeration of genome-scale extreme pathways is computationally challenging. Additionally, the development of new analysis tools is needed to strengthen the link between extreme pathway properties and experimental data. Accordingly, our specific aims are to: (1) enable the efficient calculation of extreme pathways from genome-scale models; (2) apply the techniques developed in Specific Aim #1 to compute the extreme pathways for: (a) organelles (the mitochondria from Saccharomyces cerevisiae and chloroplasts from Arabidopsis thaliana), (b) growth condition dependent human pathogens (Helicobacter pylori and Haemophilus influenzae and others that may become available during the period of this proposal), and (c) a fully autonomous organism Escherichia coil); and (3) develop analysis tools to yield more biological meaning and relevance of extreme pathways by analyzing singular value decomposition (SVD) of extreme pathway matrices and converting the flux cone into a cone of kinetic constants (the K-cone) using measured concentrations (proteomics and metabolomic data). The concepts and analysis methods developed and verified to date must be moved forward to tie concepts directly to biological data and applications. If implemented, this proposed program will result in a significant advancement in our ability to study and characterize the capabilities of reconstructed networks and to relate in silico results to actual cellular functions.