Functional centrality as a predictor of shifts in metabolic flux states.
BACKGROUND
The 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.


RESULTS
We 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.


CONCLUSIONS
The 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.
Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Am Mühlenweg 1, 14476, Potsdam, Germany. sajitz@mpimp-golm.mpg.de.
Max
M
Sajitz-Hermstein
Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Am Mühlenweg 1, 14476, Potsdam, Germany.
Zoran
Z
Nikoloski
D000255:Adenosine Triphosphate / Q000378:metabolism; D000332:Aerobiosis; D000465:Algorithms; D004734:Energy Metabolism; D004926:Escherichia coli / Q000378:metabolism*; D005285:Fermentation; D005947:Glucose / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D010101:Oxygen Consumption
D000255:Adenosine Triphosphate; D005947:Glucose
Cooperative game theory; Elementary flux mode; Flux balance analysis; Functional centrality; Metabolic control; Metabolic flux; Metabolic network; Reaction stoichiometry; Shapley value; Structural modeling