한빛사 논문
Abstract
aMetabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Program), KAIST, Daejeon 305-701, Republic of Korea;
bCenter for Systems and Synthetic Biotechnology, Institute for the BioCentury, KAIST, Daejeon 305-701, Republic of Korea; and
cDepartment of Bio and Brain Engineering, BioProcess Engineering Research Center and Bioinformatics Research Center, KAIST, Daejeon 305-701, Republic of Korea
Edited* by Bernhard Ø. Palsson, University of California at San Diego, La Jolla, CA, and accepted by the Editorial Board July 6, 2010 (received for review March 26, 2010)
AbstractFlux balance analysis (FBA) of a genome-scale metabolic model allows calculation of intracellular fluxes by optimizing an objective function, such as maximization of cell growth, under given constraints, and has found numerous applications in the field of systems biology and biotechnology. Due to the underdetermined nature of the system, however, it has limitations such as inaccurate prediction of fluxes and existence of multiple solutions for an optimal objective value. Here, we report a strategy for accurate prediction of metabolic fluxes by FBA combined with systematic and condition-independent constraints that restrict the achievable flux ranges of grouped reactions by genomic context and flux-converging pattern analyses. Analyses of three types of genomic contexts, conserved genomic neighborhood, gene fusion events, and co-occurrence of genes across multiple organisms, were performed to suggest a group of fluxes that are likely on or off simultaneously. The flux ranges of these grouped reactions were constrained by flux-converging pattern analysis. FBA of the Escherichia coli genome-scale metabolic model was carried out under several different genotypic (pykF, zwf, ppc, and sucA mutants) and environmental (altered carbon source) conditions by applying these constraints, which resulted in flux values that were in good agreement with the experimentally measured 13C-based fluxes. Thus, this strategy will be useful for accurately predicting the intracellular fluxes of large metabolic networks when their experimental determination is difficult.
Escherichiacoli, flux balance analysis, grouping reaction constraints, 13C-based flux, genome-scale metabolic model
Footnotes
1To whom correspondence should be addressed.
Author contributions: J.M.P., T.Y.K., and S.Y.L. designed research; J.M.P. and T.Y.K. performed research; J.M.P. contributed new reagents/analytic tools; J.M.P., T.Y.K., and S.Y.L. analyzed data; and J.M.P., T.Y.K., and S.Y.L. wrote the paper.
The authors declare no conflict of interest.
*This article is a PNAS Direct Submission. B.Ø.P. is a guest editor invited by the Editorial Board.
This article contains supporting information online at
www.pnas.org/lookup/suppl/doi:10.1073/pnas.1003740107/-/DCSupplemental.
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