title: Mapping the landscape of metabolic goals of a cell.
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 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.affiliation: Department of Electrical and Computer Engineering, and Division of Systems Engineering, Boston University, Boston, MA, 02215, USA.
authors.forename: Qi
authors.initials: Q
authors.lastname: Zhao
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
authors.forename: Arion I
authors.initials: AI
authors.lastname: Stettner
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.|Current address: Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
authors.forename: Ed
authors.initials: E
authors.lastname: Reznik
authors.affiliation: Department of Electrical and Computer Engineering, and Division of Systems Engineering, Boston University, Boston, MA, 02215, USA. yannisp@bu.edu.
authors.forename: Ioannis Ch
authors.initials: ICh
authors.lastname: Paschalidis
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA. dsegre@bu.edu.|Department of Biology and Bioinformatics Program, Boston University, Boston, MA, 02215, USA. dsegre@bu.edu.
authors.forename: Daniel
authors.initials: D
authors.lastname: Segrè
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism*; D015964:Gene Expression Regulation, Bacterial; D016680:Genome, Bacterial; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008962:Models, Theoretical; D020592:Shewanella / Q000235:genetics* / Q000378:metabolism
keywords: Flux balance analysis; Genome-scale stoichiometric models; Inverse optimization; Metabolic networks; Objective functions