Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks

Areejit Samal

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arXiv · 0905.2709

Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks

Areejit Samal

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Abstract

Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a give metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.

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Areejit Samal. 2009-05-17. Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks. https://arxiv.org/abs/0905.2709

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