Top-down elasticity analysis and its application to energy metabolism in isolated mitochondria and intact cells.

This paper reviews top-down elasticity analysis, which is a subset of metabolic control analysis. Top-down elasticity analysis provides a systematic yet simple experimental method to identify all the primary sites of action of an effector in complex systems and to distinguish them from all the secondary, indirect, sites of action. In the top-down approach, the complex system (for example, a mitochondrion, cell, organ or organism) is first conceptually divided into a small number of blocks of reactions interconnected by one or more metabolic intermediates. By changing the concentration of one intermediate when all others are held constant and measuring the fluxes through each block of reactions, the overall kinetic response of each block to each intermediate can be established. The concentrations of intermediates can be changed by adding new branches to the system or by manipulating the activities of blocks of reactions whose kinetics are not under investigation. To determine how much an effector alters the overall kinetics of a block of reactions, the overall kinetic response of the block to the intermediate is remeasured in the presence of the effector. Blocks that contain significant primary sites of action will display altered kinetics; blocks that change rate only because of secondary alterations in the concentrations of other metabolites will not. If desired, this elasticity analysis can be repeated with the primary target blocks subdivided into simpler blocks so that the primary sites of action can be defined with more and more precision until, with sufficient subdivision, they are mapped onto individual kinetic steps. Top-down elasticity analysis has been used to identify the targets of effectors of oxygen consumption in mitochondria, hepatocytes and thymocytes. Effectors include poisons such as cadmium and hormones such as triiodothyronine. However, the method is more general than this; in principle it can be applied to any metabolic or other steady-state system.