Edward K. Ainscow

The causes and functions of mitochondrial proton leak

The non-linear relationship between respiration rate and protonmotive force in isolated mitochondria is explained entirely by delta p-dependent changes in the proton conductance of the mitochondrial inner membrane and is not caused by redox slip in the proton pumps. Mitochondrial proton leak occurs in intact cells and tissues: the futile cycle of proton pumping and proton leak accounts for 26% +/- 7% of the total oxygen consumption rate or 33% +/- 7% of the mitochondrial respiration rate of isolated hepatocytes (mean +/- S.D. for 43 rats); 52% of the oxygen consumption rate of resting perfused muscle and up to 38% of the basal metabolic rate of a rat, suggesting that heat production may be an important function in the proton leak in homeotherms. Together with non-mitochondrial oxygen consumption, it lowers the effective P/O ratio in cells from maximum possible values of 2.33 (palmitate oxidation) or 2.58 (glucose oxidation) to as low as 1.1 in liver or 0.8 in muscle. The effective P/O ratio increases in response to ATP demand; the ability to allow rapid switching of flux from leak to ATP turnover may be an even more important function of the leak reaction than heat production. The mitochondrial proton conductance in isolated mitochondria and in hepatocytes is greatly modulated by thyroid hormones, by phylogeny and by body mass. Usually the reactions of ATP turnover change in parallel so that the coupling ratio is not greatly affected. Changes in proton leak in tissues are brought about in the short term by changes in mitochondrial protonmotive force and in the longer term by changes in the surface area and proton permeability of the mitochondrial inner membrane. Permeability changes are probably caused by changes in the fatty acid composition of the membrane phospholipids.

Calcium regulation of oxidative phosphorylation in rat skeletal muscle mitochondria.

Activation of oxidative phosphorylation by physiological levels of calcium in mitochondria from rat skeletal muscle was analysed using top-down elasticity and regulation analysis. Oxidative phosphorylation was conceptually divided into three subsystems (substrate oxidation, proton leak and phosphorylation) connected by the membrane potential or the protonmotive force. Calcium directly activated the phosphorylation subsystem and (with sub-saturating 2-oxoglutarate) the substrate oxidation subsystem but had no effect on the proton leak kinetics. The response of mitochondria respiring on 2-oxoglutarate at two physiological concentrations of free calcium was quantified using control and regulation analysis. The partial integrated response coefficients showed that direct stimulation of substrate oxidation contributed 86% of the effect of calcium on state 3 oxygen consumption, and direct activation of the phosphorylation reactions caused 37% of the increase in phosphorylation flux. Calcium directly activated phosphorylation more strongly than substrate oxidation (78% compared to 45%) to achieve homeostasis of mitochondrial membrane potential during large increases in flux.

Suppressors of superoxide production from mitochondrial complex III

Mitochondrial electron transport drives ATP synthesis but also generates reactive oxygen species (ROS), which are both cellular signals and damaging oxidants. Superoxide production by respiratory complex III is implicated in diverse signaling events and pathologies but its role remains controversial. Using high-throughput screening we identified compounds that selectively eliminate superoxide production by complex III without altering oxidative phosphorylation; they modulate retrograde signaling including cellular responses to hypoxic and oxidative stress.

Quantifying elasticity analysis: how external effectors cause changes to metabolic systems.

The sites of action of external effectors, such as inhibitors or hormones, on metabolic systems can be described qualitatively by elasticity analysis, or quantitatively by regulation analysis. The use of the latter approach has been limited, due to its practical complexity. In this study, we report mathematical relationships that relate the finite changes in system variables (fluxes and metabolite concentrations) to changes in activity of metabolic processes brought about by a single step addition of an effector. The activation or inhibition of a process by an effector is measured from changes in flux and intermediate levels. The changes in activity of each process can be used to describe, semi-quantitatively, which activations or inhibitions of the system processes are important in bringing about the observed levels of system variables.

Regulation of Energy Metabolism in Hepatocytes

Control analysis has been applied experimentally to many pathways (Fell, 1992). However, the effort required to measure the elasticity, control and response coefficients makes a full empirical analysis unrealistic in all but rather simple systems. Consequently, most investigations have considered single enzymes or pathways, ignoring interactions with other cellular pathways. The most experimentally accessible way to measure regulation in complex systems like whole cells is to group reactions together into much larger blocks. The control and regulation of a simplified network of blocks that includes all the reactions in the cell can then be analysed. This is known as the top-down (Brand, 1996) or modular (Schuster et al., 1993) approach to control analysis. Top-down approaches have been used either to analyse the reactions in whole cells or organs around a single intermediate (Brand, 1996; Soboll et al., 1998) or to analyse a limited number of reactions around several intermediates (Groen et al., 1982; Kashiwaya et al., 1994). There has been no analysis of the grouped reactions of a whole cell with multiple intermediates. Such an analysis is necessary if we are to quantify and understand the importance of interactions between different major pathways in the cell, because it is only when we include all of the reactions that the full complexity appears. A great strength of control analysis is that it provides the methodology and language to describe this complexity meaningfully.