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Title: Mapping the landscape of metabolic goals of a cell

Abstract

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.

Authors:
 [1];  [1];  [2];  [1];  [1]
  1. Boston Univ., Boston, MA (United States)
  2. Boston Univ., Boston, MA (United States); Memorial Sloan Kettering Cancer Center, New York, NY (United States)
Publication Date:
Research Org.:
Boston Univ., MA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1310268
Grant/Contract Number:  
SC0012627
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Genome Biology (Online)
Additional Journal Information:
Journal Name: Genome Biology (Online); Journal Volume: 17; Journal Issue: 1; Journal ID: ISSN 1474-760X
Publisher:
BioMed Central
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; metabolic networks; flux balance analysis; inverse optimization; objective functions; genome-scale stoichiometric models

Citation Formats

Zhao, Qi, Stettner, Arion I., Reznik, Ed, Paschalidis, Ioannis Ch., and Segre, Daniel. Mapping the landscape of metabolic goals of a cell. United States: N. p., 2016. Web. doi:10.1186/s13059-016-0968-2.
Zhao, Qi, Stettner, Arion I., Reznik, Ed, Paschalidis, Ioannis Ch., & Segre, Daniel. Mapping the landscape of metabolic goals of a cell. United States. doi:10.1186/s13059-016-0968-2.
Zhao, Qi, Stettner, Arion I., Reznik, Ed, Paschalidis, Ioannis Ch., and Segre, Daniel. Mon . "Mapping the landscape of metabolic goals of a cell". United States. doi:10.1186/s13059-016-0968-2. https://www.osti.gov/servlets/purl/1310268.
@article{osti_1310268,
title = {Mapping the landscape of metabolic goals of a cell},
author = {Zhao, Qi and Stettner, Arion I. and Reznik, Ed and Paschalidis, Ioannis Ch. and Segre, Daniel},
abstractNote = {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.},
doi = {10.1186/s13059-016-0968-2},
journal = {Genome Biology (Online)},
number = 1,
volume = 17,
place = {United States},
year = {Mon May 23 00:00:00 EDT 2016},
month = {Mon May 23 00:00:00 EDT 2016}
}

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Cited by: 6 works
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Works referenced in this record:

Effect of Escherichia coli biomass composition on central metabolic fluxes predicted by a stoichiometric model
journal, October 1998