Computational identification of significantly regulated metabolic reactions by integration of data on enzyme activity and gene expression

Hojung Nam, Taewoo Ryu, Ki Young Lee, Sangwoo Kim, Doheon Lee*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The concentrations and catalytic activities of enzymes control metabolic rates. Previous studies have focused on enzyme concentrations because there are no genome-wide techniques used for the measurement of enzyme activity. We propose a method for evaluating the significance of enzyme activity by integrating metabolic network topologies and genome-wide microarray gene expression profiles. We quantified the enzymatic activity of reactions and report the 388 significant reactions in five perturbation datasets. For the 388 enzymatic reactions, we identified 70 that were significantly regulated (P-value < 0.001). Thirty-one of these reactions were part of anaerobic metabolism, 23 were part of low-pH aerobic metabolism, 8 were part of high-pH anaerobic metabolism, 3 were part of low-pH aerobic reactions, and 5 were part of high-pH anaerobic metabolism.

Original languageEnglish (US)
Pages (from-to)609-614
Number of pages6
JournalJournal of Biochemistry and Molecular Biology
Volume41
Issue number8
StatePublished - Aug 2008
Externally publishedYes

Keywords

  • Enzyme activity
  • Gene expression
  • Metabolic reaction
  • Metabolism regulation

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

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