title: Flux-coupled genes and their use in metabolic flux analysis.
abstract: As large volumes of omics data have become available, systems biology is playing increasingly important roles in elucidating new biological phenomena, especially through genome-scale metabolic network modeling and simulation. Much effort has been exerted on integrating omics data with metabolic flux simulation, but further development is necessary for more accurate flux estimation. To move one step forward, we adopted the concept of flux-coupled genes (FCGs), which show that their expression transition patterns upon perturbations are correlated with their corresponding flux values, as additional constraints in metabolic flux analysis. It was found that gnd, pfkB, rpe, sdhB, sdhD, sucA, and zwf genes, mostly associated with pentose phosphate pathway and TCA cycle, were the most consistent FCGs in Escherichia coli based on its transcriptome and (13) C-flux data obtained from the chemostat cultivation at five different dilution rates. Consequently, constraints-based flux analyses with FCGs as additional constraints were conducted for the seven single-gene knockout mutants, compared with those obtained without using FCGs. This strategy of constraining the metabolic flux analysis with FCGs is expected to be useful due to the relative ease in obtaining transcriptional information in the functional genomics era.
authors: Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 program), Center for Systems and Synthetic Biotechnology, Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea; BioInformatics Research Center, KAIST, Daejeon, Republic of Korea.
authors: Hyun Uk
authors: HU
authors: Kim
authors: Won Jun
authors: WJ
authors: Kim
authors: Sang Yup
authors: SY
authors: Lee
mesh_terms: D000465:Algorithms; D002952:Citric Acid Cycle / Q000235:genetics*; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism; D055785:Gene Knockdown Techniques; D005798:Genes, Bacterial; D064688:Metabolic Flux Analysis; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D010427:Pentose Phosphate Pathway / Q000235:genetics*; D049490:Systems Biology; D059467:Transcriptome
keywords: Constraints-based flux analysis; Data integration; Flux-coupled genes; Genome-scale metabolic model; Systems biology