Mapping the landscape of metabolic goals of a cell

Zhao, Qi; Stettner, Arion I.; Reznik, Ed; Paschalidis, Ioannis Ch.; Segrè, Daniel

doi:10.1186/s13059-016-0968-2

Title: Mapping the landscape of metabolic goals of a cell

Journal Article · 23 May 2016 · Genome Biology (Online)

DOI: https://doi.org/10.1186/s13059-016-0968-2 · OSTI ID:1618921

Zhao, Qi; Stettner, Arion I.; Reznik, Ed; Paschalidis, Ioannis Ch.; Segrè, Daniel

Here, 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 simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptation trajectories.

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Research Organization:: Boston Univ., MA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0012627

OSTI ID:: 1618921

Alternate ID(s):: OSTI ID: 1310268

Journal Information:: Genome Biology (Online), Journal Name: Genome Biology (Online) Vol. 17 Journal Issue: 1; ISSN 1474-760X

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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Cited by: 23 works

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