Literature DB >> 1879427

Quantitative assessment of regulation in metabolic systems.

J H Hofmeyr1, A Cornish-Bowden.   

Abstract

We show how metabolic regulation as commonly understood in biochemistry can be described in terms of metabolic control analysis. The steady-state values of the variables of metabolic systems (fluxes and concentrations) are determined by a set of parameters. Some of these parameters are concentrations that are set by the environment of the system; they can act as external regulators by communicating changes in the environment to the metabolic system. How effectively a system is regulated depends both on the degree to which the activity of the regulatory enzyme with which a regulator interacts directly can be altered by the regulator (its regulability) and on the ability of the regulatory enzyme to transmit the changes to the rest of the system (its regulatory capacity). The regulatory response of a system also depends on its internal organisation around key variable metabolites that act as internal regulators. The regulatory performance of the system can be judged in terms of how sensitivity the fluxes respond to the external stimulus and to what degree homeostasis in the concentrations of the internal regulators is maintained. We show how, on the level of both external and internal regulation, regulability can be quantified in terms of an elasticity coefficient and regulatory capacity in terms of a control coefficient. Metabolic regulation can therefore be described in terms of metabolic control analysis. The combined response relationship of control analysis relates regulability and regulatory capacity and allows quantification of the regulatory importance of the various interactions of regulators with enzymes in the system. On this basis we propose a quantitative terminology and analysis of metabolic regulation that shows what we should measure experimentally and how we should interpret the results. Analysis and numerical simulation of a simple model system serves to demonstrate our treatment.

Mesh:

Year:  1991        PMID: 1879427     DOI: 10.1111/j.1432-1033.1991.tb21071.x

Source DB:  PubMed          Journal:  Eur J Biochem        ISSN: 0014-2956


  25 in total

1.  Product dependence and bifunctionality compromise the ultrasensitivity of signal transduction cascades.

Authors:  Fernando Ortega; Luis Acerenza; Hans V Westerhoff; Francesc Mas; Marta Cascante
Journal:  Proc Natl Acad Sci U S A       Date:  2002-02-05       Impact factor: 11.205

2.  Elasticity analysis and design for large metabolic responses produced by changes in enzyme activities.

Authors:  Fernando Ortega; Luis Acerenza
Journal:  Biochem J       Date:  2002-10-01       Impact factor: 3.857

3.  Protein phosphorylation can regulate metabolite concentrations rather than control flux: the example of glycogen synthase.

Authors:  James R A Schafer; David A Fell; Douglas Rothman; Robert G Shulman
Journal:  Proc Natl Acad Sci U S A       Date:  2004-01-26       Impact factor: 11.205

Review 4.  Metabolic control analysis: a survey of its theoretical and experimental development.

Authors:  D A Fell
Journal:  Biochem J       Date:  1992-09-01       Impact factor: 3.857

5.  Is the regulation of galactose 1-phosphate tuned against gene expression noise?

Authors:  Pedro de Atauri; David Orrell; Stephen Ramsey; Hamid Bolouri
Journal:  Biochem J       Date:  2005-04-01       Impact factor: 3.857

Review 6.  Elusive control.

Authors:  H V Westerhoff; B N Kholodenko; M Cascante; K Van Dam
Journal:  J Bioenerg Biomembr       Date:  1995-10       Impact factor: 2.945

Review 7.  Metabolic regulation: a control analytic perspective.

Authors:  J H Hofmeyr
Journal:  J Bioenerg Biomembr       Date:  1995-10       Impact factor: 2.945

Review 8.  Control and regulation of pathways via negative feedback.

Authors:  Herbert M Sauro
Journal:  J R Soc Interface       Date:  2017-02       Impact factor: 4.118

Review 9.  Control strategies in systemic metabolism.

Authors:  Jessica Ye; Ruslan Medzhitov
Journal:  Nat Metab       Date:  2019-10-07

10.  Human liver rate-limiting enzymes influence metabolic flux via branch points and inhibitors.

Authors:  Min Zhao; Hong Qu
Journal:  BMC Genomics       Date:  2009-12-03       Impact factor: 3.969

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