Mapping the landscape of metabolic goals of a cell. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Zhao, Qi; Stettner, Arion; Reznik, Ed; Paschalidis, Ioannis; Segrè, Daniel
• Is Part Of: Genome biology. Volume 17:Issue 1(2016)
• Page Start: 1
• Page End: 11
• Publication Date: 2016-12
• Subjects: Metabolic networks -- Flux balance analysis -- Inverse optimization -- Objective functions -- Genome-scale stoichiometric models; Genomes -- Periodicals; Biology -- Periodicals; Molecular biology -- Periodicals; 572.8633
• DOI: 10.1186/s13059-016-0968-2
• Languages: English
• ISSNs: 1474-760X

Abstract

Abstract Genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulatedE. coli data and time-dependentS. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolvedE. coli strains, revealing objective functions that provide insight into metabolic adaptation trajectories.