A Novel Method for Flux Distribution Computation in Metabolic Networks

Abstract

In recent years, the study on metabolic networks has attracted considerable attention from the research community. Though the topological structures of genome-scale metabolic networks of some organisms have been investigated, their metabolic flux distributions still remain unclear. The understanding of flux distributions in metabolic networks, especially when it comes to the gene-knockout mutants, is helpful for suggesting potential ways to improve strain design. The traditional method of flux distribution computation, i.e., flux balance analysis (FBA) method, is based on the idea of maximizing biomass yield. However, this method overestimates the production of biomass. In this paper, we develop a novel approach to overcome the drawback of the FBA method. First, we adopt a series of extended equations to model reaction flux; Second, we build the stoichiometric matrix of a metabolic network by using a more complex but accurate model - carbon mole balance - rather than mass balance used in FBA. Computation results with real-world data of Escherichia coli show that our approach outperforms FBA in the accuracy of flux distribution computation.