title: Integration of enzyme activities into metabolic flux distributions by elementary mode analysis.
abstract: BACKGROUND
  In systems biology, network-based pathway analysis facilitates understanding or designing metabolic systems and enables prediction of metabolic flux distributions. Network-based flux analysis requires considering not only pathway architectures but also the proteome or transcriptome to predict flux distributions, because recombinant microbes significantly change the distribution of gene expressions. The current problem is how to integrate such heterogeneous data to build a network-based model.
  
  
  RESULTS
  To link enzyme activity data to flux distributions of metabolic networks, we have proposed Enzyme Control Flux (ECF), a novel model that integrates enzyme activity into elementary mode analysis (EMA). ECF presents the power-law formula describing how changes in enzyme activities between wild-type and a mutant are related to changes in the elementary mode coefficients (EMCs). To validate the feasibility of ECF, we integrated enzyme activity data into the EMCs of Escherichia coli and Bacillus subtilis wild-type. The ECF model effectively uses an enzyme activity profile to estimate the flux distribution of the mutants and the increase in the number of incorporated enzyme activities decreases the model error of ECF.
  
  
  CONCLUSIONS
  The ECF model is a non-mechanistic and static model to link an enzyme activity profile to a metabolic flux distribution by introducing the power-law formula into EMA, suggesting that the change in an enzyme profile rather reflects the change in the flux distribution. The ECF model is highly applicable to the central metabolism in knockout mutants of E. coli and B. subtilis.
authors.affiliation: Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan. kurata@bio.kyutech.ac.jp
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Kurata
authors.forename: Quanyu
authors.initials: Q
authors.lastname: Zhao
authors.forename: Ryuichi
authors.initials: R
authors.lastname: Okuda
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Shimizu
mesh_terms: D000465:Algorithms; D001412:Bacillus subtilis / Q000201:enzymology / Q000235:genetics / Q000378:metabolism; D004798:Enzymes / Q000235:genetics / Q000378:metabolism*; D004926:Escherichia coli / Q000201:enzymology / Q000235:genetics / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D011770:Pyruvate Kinase / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D017384:Sequence Deletion; D049490:Systems Biology
chemical_list: D004798:Enzymes; D011770:Pyruvate Kinase