Literature DB >> 1497632

Metabolic control analysis using transient metabolite concentrations. Determination of metabolite concentration control coefficients.

J Delgado1, J C Liao.   

Abstract

The methodology previously developed for determining the Flux Control Coefficients [Delgado & Liao (1992) Biochem. J. 282, 919-927] is extended to the calculation of metabolite Concentration Control Coefficients. It is shown that the transient metabolite concentrations are related by a few algebraic equations, attributed to mass balance, stoichiometric constraints, quasi-equilibrium or quasi-steady states, and kinetic regulations. The coefficients in these relations can be estimated using linear regression, and can be used to calculate the Control Coefficients. The theoretical basis and two examples are discussed. Although the methodology is derived based on the linear approximation of enzyme kinetics, it yields reasonably good estimates of the Control Coefficients for systems with non-linear kinetics.

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Year:  1992        PMID: 1497632      PMCID: PMC1132889          DOI: 10.1042/bj2850965

Source DB:  PubMed          Journal:  Biochem J        ISSN: 0264-6021            Impact factor:   3.857


  6 in total

1.  Determination of Flux Control Coefficients from transient metabolite concentrations.

Authors:  J Delgado; J C Liao
Journal:  Biochem J       Date:  1992-03-15       Impact factor: 3.857

2.  Metabolic control theory: a structural approach.

Authors:  C Reder
Journal:  J Theor Biol       Date:  1988-11-21       Impact factor: 2.691

3.  A linear steady-state treatment of enzymatic chains. General properties, control and effector strength.

Authors:  R Heinrich; T A Rapoport
Journal:  Eur J Biochem       Date:  1974-02-15

4.  Metabolic control and its analysis. Extensions to the theory and matrix method.

Authors:  H M Sauro; J R Small; D A Fell
Journal:  Eur J Biochem       Date:  1987-05-15

5.  Metabolic control and its analysis. Additional relationships between elasticities and control coefficients.

Authors:  D A Fell; H M Sauro
Journal:  Eur J Biochem       Date:  1985-05-02

6.  The control of flux.

Authors:  H Kacser; J A Burns
Journal:  Symp Soc Exp Biol       Date:  1973
  6 in total
  7 in total

1.  Combined use of fluorescent dyes and flow cytometry to quantify the physiological state of Pichia pastoris during the production of heterologous proteins in high-cell-density fed-batch cultures.

Authors:  Petr Hyka; Thomas Züllig; Claudia Ruth; Verena Looser; Christian Meier; Joachim Klein; Karel Melzoch; Hans-Peter Meyer; Anton Glieder; Karin Kovar
Journal:  Appl Environ Microbiol       Date:  2010-05-14       Impact factor: 4.792

2.  Metabolic control analysis of biochemical pathways based on a thermokinetic description of reaction rates.

Authors:  J Nielsen
Journal:  Biochem J       Date:  1997-01-01       Impact factor: 3.857

3.  On the identifiability of metabolic network models.

Authors:  Sara Berthoumieux; Matteo Brilli; Daniel Kahn; Hidde de Jong; Eugenio Cinquemani
Journal:  J Math Biol       Date:  2012-11-15       Impact factor: 2.259

4.  Influence of experimental errors on the determination of flux control coefficients from transient metabolite concentrations.

Authors:  M Ehlde; G Zacchi
Journal:  Biochem J       Date:  1996-02-01       Impact factor: 3.857

5.  Structure identifiability in metabolic pathways: parameter estimation in models based on the power-law formalism.

Authors:  A Sorribas; M Cascante
Journal:  Biochem J       Date:  1994-03-01       Impact factor: 3.857

6.  Optimization of a blueprint for in vitro glycolysis by metabolic real-time analysis.

Authors:  Matthias Bujara; Michael Schümperli; René Pellaux; Matthias Heinemann; Sven Panke
Journal:  Nat Chem Biol       Date:  2011-03-20       Impact factor: 15.040

7.  Dynamic Bayesian sensitivity analysis of a myocardial metabolic model.

Authors:  D Calvetti; R Hageman; R Occhipinti; E Somersalo
Journal:  Math Biosci       Date:  2007-11-01       Impact factor: 2.144

  7 in total

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