Literature DB >> 11289790

The organization of metabolic reaction networks. II. Signal processing in hierarchical structured functional units.

A Kremling1, E D Gilles.   

Abstract

Based on the analysis of molecular interactions of proteins with DNA binding sites, a new approach to developing mathematical models describing gene expression is introduced. Detection of hierarchical structures in metabolic networks can be used to decompose complex reaction schemes. This will be achieved by assigning each regulator protein to one level in the hierarchy. Signals are then transduced from the top level to the lower level, but not vice versa. The method is shown by a simple example with two interacting proteins. A comparison of simulation results shows good agreement between a model taking all interactions into account and a model developed with the new approach. Finally, the method is applied to the crpA modulon in Escherichia coli, which controls uptake and metabolism for a number of carbohydrates. Here, RNA polymerase represents the top level, CrpA the second level, and the lactose-specific repressor LacI the lowest level, respectively. Besides the lactose operon, the method is applied to the adenylate cyclase gene and the gene for the regulator CrpA. Copyright 2001 Academic Press.

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Year:  2001        PMID: 11289790     DOI: 10.1006/mben.2000.0175

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  5 in total

1.  Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks.

Authors:  Jacek Puchałka; Andrzej M Kierzek
Journal:  Biophys J       Date:  2004-03       Impact factor: 4.033

2.  A computational framework for the topological analysis and targeted disruption of signal transduction networks.

Authors:  Madhukar S Dasika; Anthony Burgard; Costas D Maranas
Journal:  Biophys J       Date:  2006-04-14       Impact factor: 4.033

3.  Detailed map of a cis-regulatory input function.

Authors:  Y Setty; A E Mayo; M G Surette; U Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2003-06-12       Impact factor: 11.205

4.  Catabolic regulation analysis of Escherichia coli and its crp, mlc, mgsA, pgi and ptsG mutants.

Authors:  Ruilian Yao; Yuki Hirose; Dayanidhi Sarkar; Kenji Nakahigashi; Qin Ye; Kazuyuki Shimizu
Journal:  Microb Cell Fact       Date:  2011-08-11       Impact factor: 5.328

Review 5.  Importance of understanding the main metabolic regulation in response to the specific pathway mutation for metabolic engineering of Escherichia coli.

Authors:  Yu Matsuoka; Kazuyuki Shimizu
Journal:  Comput Struct Biotechnol J       Date:  2013-01-16       Impact factor: 7.271

  5 in total

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