Abstract
BackgroundThe flux phenotype describes the entirety of biochemical conversions in a cell, which renders it a key characteristic of metabolic function. To quantify the functional relevance of individual biochemical reactions, functional centrality has been introduced based on cooperative game theory and structural modeling. It was shown to be capable to determine metabolic control properties utilizing only structural information. Here, we demonstrate the capability of functional centrality to predict changes in the flux phenotype.ResultsWe use functional centrality to successfully predict changes of metabolic flux triggered by switches in the environment. The predictions via functional centrality improve upon predictions using control-effective fluxes, another measure aiming at capturing metabolic control using structural information.ConclusionsThe predictions of flux changes via functional centrality corroborate the capability of the measure to gain a mechanistic understanding of metabolic control from the structure of metabolic networks.
Highlights
The flux phenotype describes the entirety of biochemical conversions in a cell, which renders it a key characteristic of metabolic function
Gene expression may not directly be manifested in changes of flux; a more suitable comparison necessitates the usage of changes in fluxes inferred based on labeling data [11]. In this brief research note, we demonstrate that functional centrality performs better than control-effective fluxes in predicting changes in metabolic flux in the central carbon metabolism of Escherichia coli
In accordance with the definition of control-effective fluxes [10], we utilize the mean of normalized functional centralities obtained for the metabolic functions of ATP and biomass production, which are the two dominant metabolic functions shaping the flux phenotype [13]
Summary
The flux phenotype describes the entirety of biochemical conversions in a cell, which renders it a key characteristic of metabolic function. Elucidating the principles of how Functional centrality combines cooperative game theory, in particular a modified version of the Shapley value for arbitrary restricted games [7], with flux balance analysis (FBA) [8] to determine the functional relevance of biochemical reactions [1, 9]. It quantifies the contribution of individual biochemical reactions to metabolic functionality, e.g., to biomass production, based on the structure of a metabolic network together with constraints on internal and exchange fluxes, which mimic internal and external conditions
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