Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Dynamic Behavior of Regulatory Elements in the Hierarchical Regulatory Network of Various Carbon Sources-Grown Escherichia coli

  • Lee, Sung-Gun (Department of Chemical Engineering, College of Engineering, Pusan National University) ;
  • Hwang, Kyu-Suk (Department of Chemical Engineering, College of Engineering, Pusan National University) ;
  • Kim, Cheol-Min (Department of Biochemistry, College of Medicine, Medical Research Institute, Pusan National University)
  • Published : 2005.06.01
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Abstract

The recent rapid increase in genomic data related to many microorganisms and the development of computational tools to accurately analyze large amounts of data have enabled us to design several kinds of simulation approaches for the complex behaviors of cells. Among these approaches, dFBA (dynamic flux balance analysis), which utilizes FBA, differential equations, and regulatory events, has correctly predicted cellular behaviors under given environmental conditions. However, until now, dFBA has centered on substrate concentration, cell growth, and gene on/off, but a detailed hierarchical structure of a regulatory network has not been taken into account. The use of Boolean rules for regulatory events in dFBA has limited the representation of interactions between specific regulatory proteins and genes and the whole transcriptional regulation mechanism with environmental change. In this paper, we adopted the operon as the basic structure, constructed a hierarchical structure for a regulatory network with defined fundamental symbols, and introduced a weight between symbols in order to solve the above problems. Finally, the total control mechanism of regulatory elements (operons, genes, effectors, etc.) with time was simulated through the linkage of dFBA with regulatory network modeling. The lac operon, trp operon, and tna operon in the central metabolic network of E. coli were chosen as the basic models for control patterns. The suggested modeling method in this study can be adopted as a basic framework to describe other transcriptional regulations, and provide biologists and engineers with useful information on transcriptional regulation mechanisms under extracellular environmental change.

Keywords

References

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