Beilstein-Institut Symbolic Control Analysis of Cellular Systems

Metabolic Control Analysis (MCA) is a powerful quantitative framework for understanding and explaining the relationships between the global steady-state properties of a cellular system in terms of control coefficients, and the local properties of the individual components of the system in terms of elasticities. The elasticities are apparent kinetic orders, which derive directly from the kinetic properties of the enzymes. Since MCA relates elasticities to control coefficients through a matrix inversion, it allows one to predict and to quantify how the kinetics of individual enzymes affect the systemic behaviour of biological pathways. Most often this problem has been solved numerically, with algebraic and symbolic control analysis having been tackled less frequently. We present here a general implementation of the symbolic matrix inversion of MCA through symbolic algebraic computation. The algebraic expressions thus generated allow an in-depth analysis of where the control within a system lies and which parameters have the greatest effect on this control distribution, even if the exact values of the elasticities or control coefficients are unknown. 137 http://www.beilstein-institut.de/escec2007/proceedings/Rohwer/Rohwer.pdf ESCEC, September 23 – 26, 2007, Rüdesheim/Rhein, Germany

[1]  Jacky L. Snoep,et al.  BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems , 2005, Nucleic Acids Res..

[2]  Jan-Hendrik S. Hofmeyr,et al.  Modelling cellular systems with PySCeS , 2005, Bioinform..

[3]  Jacky L. Snoep,et al.  Web-based kinetic modelling using JWS Online , 2004, Bioinform..

[4]  Michiel Kleerebezem,et al.  Metabolic engineering of lactic acid bacteria, the combined approach: kinetic modelling, metabolic control and experimental analysis. , 2002, Microbiology.

[5]  A. Cornish-Bowden,et al.  Co-response analysis: a new experimental strategy for metabolic control analysis. , 1996, Journal of theoretical biology.

[6]  R. Heinrich,et al.  The Regulation of Cellular Systems , 1996, Springer US.

[7]  D. Fell Understanding the Control of Metabolism , 1996 .

[8]  H. Kacser,et al.  The control of flux. , 1995, Biochemical Society transactions.

[9]  H V Westerhoff,et al.  Getting to the inside of cells using metabolic control analysis. , 1994, Biophysical chemistry.

[10]  D A Fell,et al.  A computer program for the algebraic determination of control coefficients in Metabolic Control Analysis. , 1993, The Biochemical journal.

[11]  J. Hofmeyr,et al.  Control-pattern analysis of metabolic pathways. Flux and concentration control in linear pathways. , 1989, European journal of biochemistry.

[12]  D. Fell,et al.  The matrix method of metabolic control analysis: its validity for complex pathway structures. , 1989, Journal of theoretical biology.

[13]  D. Fell,et al.  Metabolic control and its analysis. Extensions to the theory and matrix method. , 1987, European journal of biochemistry.

[14]  Leslie Lamport,et al.  Latex : A Document Preparation System , 1985 .

[15]  H. Westerhoff,et al.  How do enzyme activities control metabolite concentrations? An additional theorem in the theory of metabolic control. , 1984, European journal of biochemistry.

[16]  H. Westerhoff,et al.  Quantification of the contribution of various steps to the control of mitochondrial respiration. , 1982, The Journal of biological chemistry.

[17]  Reinhart Heinrich,et al.  A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. , 1974, European journal of biochemistry.

[18]  J. Hofmeyr,et al.  Metabolic control analysis in a nutshell , 2001 .