Getting to the inside of cells using metabolic control analysis

European Journal of Biochemistry, 2002

Traditional analyses of the control and regulation of steady-state concentrations and fluxes assume the activities of the enzymes to be constant. In living cells, a hierarchical control structure connects metabolic pathways to signal-transduction and gene-expression. Consequently, enzyme activities are not generally constant. This would seem to compromise analyses of control and regulation at the metabolic level. Here, we investigate the concept of metabolic quasi-steady state kinetics as a means of applying metabolic control analysis to hierarchical biochemical systems. We discuss four methods that enable the experi-mental determination of metabolic control coefficients, and demonstrate these by computer simulations. The best method requires extra measurement of enzyme activities, two others are simpler but are less accurate and one method is bound only to work under special conditions. Our results may assist in evaluating the relative importance of transcriptomics and metabolomics for functional genomics. Abbreviations: IPTG, isopropyl thio-b-D-galactoside; MCA, metabolic control analysis; HCA, hierarchical control analysis.

Journal of Theoretical Biology, 2008

The effect that an increase in the activity of an enzyme has on its flux normally decreases with activity increase. To achieve a large increase in flux by manipulating a single step would therefore require a high initial effect that maintains or increases when the activity is increased, what has been called sustained or paradoxical control. Using metabolic control analysis for large responses, we derive conditions for sustained or paradoxical control in terms of elasticity coefficients. These are used to characterise types of rate laws contributing to this behaviour. The result that simple pathways, with normal kinetics, subject to large activity changes can lead to paradoxical control behaviour suggests that this type of pattern may be much more ubiquitous than could have, in principle, been suspected.

Biochemical Journal, 2002

Metabolic control analysis has been extensively used to describe how the sensitivity properties of the component enzymes in a metabolic pathway (represented by the elasticity coefficients) determine the way in which metabolic variables respond (described by the control coefficients). Similarly, metabolic control design addresses the inverse problem of obtaining the sensitivity properties of the component enzymes that are required for the system to show a pre-established pattern of responses. These formalisms, including what is called elasticity analysis and design, were developed for small, strictly speaking infinitesimal, changes. Here we extend them to large metabolic responses. The new approach can be applied to simple two-step pathways or to any arbitrary metabolic system divided into two groups linked by one intermediate. General expressions that relate control and elasticity coefficients for large changes are derived. Concentration and flux connectivity relationships are obtai...

Bioscience Reports, 1984

Existing, qualitative notions with respect to the way in which enzyme properties control metabolism are discussed in the light of the control analysis developed by H. Kacser and J. A. Burns ((1973) in: Rate Control of Biological Processes, Davies DD, ed., Cambridge University Press, pp. 63–104) and R. Heinrich and T. A. Rapoport ((1974) Eur. 3. Biochem.42, 89–95), and recent

FEBS Letters, 1995

This paper shows that under some conditions the control exerted by a part of a metabolic network (a pathway) on a flux or concentration in any other part can be described through a single (overall) control coefficient. This has the following implications: (i) the relative contributions of a pathway enzyme to the regulation of the pathway (output) flux and of any flux or concentration outside are identical; therefore, the control analysis of the pathway 'in isolation' allows one to determine the control exerted by any pathway enzyme on the rest of the cell by estimation of the control efficient of just one, arbitrarily chosen enzyme; (ii) the relative control of any two metabolic variables outside the pathway (measured as the ratio of the control coefficients over these two variables outside) is the same for all pathway enzymes. These properties allow one to substitute effectively a pathway by a single (super)reaction and make it possible to consider such a pathway as a metabolic unit within the cellular enzyme network.

Journal of Bioenergetics and Biomembranes, 1995

A possible basis for a quantitative theory of metabolic regulation is outlined. Regulation is defined here as the alteration of reaction properties to augment or counteract the mass-action trend in a network reactions. In living systems the enzymes that catalyze these reactions are the “handles” through which such alteration is effected. It is shown how the elasticity coefficients of an enzyme-catalyzed reaction with respect to substrates and products are the sum of a massaction term and a regulatory kinetic term; these coefficients therefore distinguish between massaction effects and regulatory effects and are recognized as the key to quantifying regulation. As elasticity coefficients are also basic ingredients of metabolic control analysis, it is possible to relate regulation to such concepts as control, signalling, stability, and homeostasis. The need for care in the choice of relative or absolute changes when considering questions of metabolic regulation is stressed. Although the concepts are illustrated in terms of a simple coupled reaction system, they apply equally to more complex systems. When such systems are divided into reaction blocks, co-response coefficients can be used to measure the elasticities of these blocks.

Metabolic control analysis is a powerful quantitative framework for understanding the relationship between the steadystate properties of a (bio)chemical reaction network as a whole and the properties of its component reactions. Although in essence it is a typical sensitivity analysis of a dynamical system, the stoichiometric structure of reaction networks gives it a character of its own. It has proved very useful for both theoretical and experimental analysis of cellular systems, leading to deep insights into matters of control and regulation. This paper attempts to capture in a nutshell the detailed derivation from first principles of all of the important theorems of control analysis starting with the general kinetic model of a reaction network.

The Journal of Physical Chemistry B, 2010

This paper develops concepts for assessing and quantifying the regulation of the rate of an enzyme-catalyzed reaction. We show how generic reversible rate equations can be recast in two ways, one making the distance from equilibrium explicit, thereby allowing the distinction between kinetic and thermodynamic control of reaction rate, as well as near-equilibrium and far-from-equilibrium reactions. Recasting in the second form separates mass action from rate capacity and quantifies the degree to which intrinsic mass action contributes to reaction rate and how regulation of an enzyme-catalyzed reaction either enhances or counteracts this mass-action behavior. The contribution of enzyme binding to regulation is analyzed in detail for a number of enzyme-kinetic rate laws, including cooperative reactions.

Applied Mathematics and Computation, 2005

For practical purposes the calculation of rate constants is not particularly valuable, since their physical significance is not clear. Of greater practical use are metabolic control coefficients and elasticities. Given the definition of the flux control coefficients C J E , concentration control coefficient C X E and elasticity v 1 X . We can calculate symbolic formulae for these using computer algebra techniques. These are then functions of V max , K m , K i enzyme and concentrations. Having derived estimates of V max , K m , K i using the fitting method we can then calculate values of the control coefficients and elasticities. Furthermore we can calculate the metabolic control parameters using symbolic values for the conventional kinetic parameters. Using these we have verified the summation and connectivity theorems. This is a useful cross check on the reliability of the calculations. .tr (M. Bayram). www.elsevier.com/locate/amc

European Journal of Biochemistry, 1991