Analysis on relationship between eztreme pathways and correlated reaction sets
Background: Constraint-based modeling of reconstructed genome-scale metabolic networks has been successfully applied on several microorganisms. In constraint-based modeling, in order to characterize all allowable phenotypes, network-based pathways, such as extreme pathways and elementary flux modes, are defined. However, as the scale of metabolic network rises, the number of extreme pathways and elementary flux modes increases exponentially.Uniform random sampling solves this problem to some extent to study the contents of the available phenotypes. After uniform random sampling, correlated reaction sets can be identified by the dependencies between reactions derived from sample phenotypes. In this paper,we study the relationship between extreme pathways and correlated reaction sets.Results: Correlated reaction sets are identified for E.coli core, red blood cell and Saccharomyces cerevisiae metabolic networks respectively. All extreme pathways are enumerated for the former two metabolic networks. As for Saccharomyces cerevisiae metabolic network,because of the large scale, we get a set of extreme pathways by sampling the whole extreme pathway space. In most cases, an extreme pathway covers a correlated reaction set in an all or none manner, which means either all reactions in a correlated reaction set or none is used by some extreme pathway. In rare cases, besides the all or none manner, a correlated reaction set may be fully covered by combination of a few extreme pathways with related function, which may bring redundancy and flexibility to improve the survivability of a cell. In a word, extreme pathways show strong complementary relationship on usage of reactions in the same correlated reaction set.Conclusions: Both extreme pathways and correlated reaction sets are derived from the topology information of metabolic networks. The strong relationship between correlated reaction sets and extreme pathways suggests a possible mechanism: as a controllable unit, an extreme pathway is regulated by its corresponding correlated reaction sets, and a correlated reaction set is further regulated by the organisms regulatory network.
Yanping Xi Yi-Ping Phoebe Chen Ming Cao Weirong Wang Fei Wang
School of computer science and technology, Fudan University, Shanghai, China Faculty of Science and Technology, Deakin University, Melbourne Australia Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai, China
国际会议
The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)
北京
英文
619-630
2009-01-01（万方平台首次上网日期，不代表论文的发表时间）