Control and Regulation of Integrated Mitochondrial Function in Metabolic and Transport Networks

The pattern of flux and concentration control coefficients in an integrated mitochondrial energetics model is examined by applying a generalized matrix method of control analysis to calculate control coefficients, as well as response coefficients The computational model of Cortassa et al. encompasses oxidative phosphorylation, the TCA cycle, and Ca2+ dynamics. Control of ATP synthesis, TCA cycle, and ANT fluxes were found to be distributed among various mitochondrial processes. Control is shared by processes associated with ATP/ADP production and transport, as well as by Ca2+ dynamics. The calculation also analyzed the control of the concentrations of key regulatory ions and metabolites (Ca2+, NADH, ADP). The approach we have used demonstrates how properties of integrated systems may be understood through applications of computational modeling and control analysis

A Computational Model of Reactive Oxygen Species and Redox Balance in Cardiac Mitochondria

AbstractElevated levels of reactive oxygen species (ROS) play a critical role in cardiac myocyte signaling in both healthy and diseased cells. Mitochondria represent the predominant cellular source of ROS, specifically the activity of complexes I and III. The model presented here explores the modulation of electron transport chain ROS production for state 3 and state 4 respiration and the role of substrates and respiratory inhibitors. Model simulations show that ROS production from complex III increases exponentially with membrane potential (ΔΨm) when in state 4. Complex I ROS release in the model can occur in the presence of NADH and succinate (reverse electron flow), leading to a highly reduced ubiquinone pool, displaying the highest ROS production flux in state 4. In the presence of ample ROS scavenging, total ROS production is moderate in state 3 and increases substantially under state 4 conditions. The ROS production model was extended by combining it with a minimal model of ROS scavenging. When the mitochondrial redox status was oxidized by increasing the proton permeability of the inner mitochondrial membrane, simulations with the combined model show that ROS levels initially decline as production drops off with decreasing ΔΨm and then increase as scavenging capacity is exhausted. Hence, this mechanistic model of ROS production demonstrates how ROS levels are controlled by mitochondrial redox balance

A Reaction-Diffusion Model of ROS-Induced ROS Release in a Mitochondrial Network

Loss of mitochondrial function is a fundamental determinant of cell injury and death. In heart cells under metabolic stress, we have previously described how the abrupt collapse or oscillation of the mitochondrial energy state is synchronized across the mitochondrial network by local interactions dependent upon reactive oxygen species (ROS). Here, we develop a mathematical model of ROS-induced ROS release (RIRR) based on reaction-diffusion (RD-RIRR) in one- and two-dimensional mitochondrial networks. The nodes of the RD-RIRR network are comprised of models of individual mitochondria that include a mechanism of ROS-dependent oscillation based on the interplay between ROS production, transport, and scavenging; and incorporating the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, and Ca2+ handling. Local mitochondrial interaction is mediated by superoxide (O2.−) diffusion and the O2.−-dependent activation of an inner membrane anion channel (IMAC). In a 2D network composed of 500 mitochondria, model simulations reveal ΔΨm depolarization waves similar to those observed when isolated guinea pig cardiomyocytes are subjected to a localized laser-flash or antioxidant depletion. The sensitivity of the propagation rate of the depolarization wave to O2.− diffusion, production, and scavenging in the reaction-diffusion model is similar to that observed experimentally. In addition, we present novel experimental evidence, obtained in permeabilized cardiomyocytes, confirming that ΔΨm depolarization is mediated specifically by O2.−. The present work demonstrates that the observed emergent macroscopic properties of the mitochondrial network can be reproduced in a reaction-diffusion model of RIRR. Moreover, the findings have uncovered a novel aspect of the synchronization mechanism, which is that clusters of mitochondria that are oscillating can entrain mitochondria that would otherwise display stable dynamics. The work identifies the fundamental mechanisms leading from the failure of individual organelles to the whole cell, thus it has important implications for understanding cell death during the progression of heart disease

Large-scale integration of cancer microarray data identifies a robust common cancer signature

<p>Abstract</p> <p>Background</p> <p>There is a continuing need to develop molecular diagnostic tools which complement histopathologic examination to increase the accuracy of cancer diagnosis. DNA microarrays provide a means for measuring gene expression signatures which can then be used as components of genomic-based diagnostic tests to determine the presence of cancer.</p> <p>Results</p> <p>In this study, we collect and integrate ~ 1500 microarray gene expression profiles from 26 published cancer data sets across 21 major human cancer types. We then apply a statistical method, referred to as the <it>T</it>op-<it>S</it>coring <it>P</it>air of <it>G</it>roups (TSPG) classifier, and a repeated random sampling strategy to the integrated training data sets and identify a common cancer signature consisting of 46 genes. These 46 genes are naturally divided into two distinct groups; those in one group are typically expressed less than those in the other group for cancer tissues. Given a new expression profile, the classifier discriminates cancer from normal tissues by ranking the expression values of the 46 genes in the cancer signature and comparing the average ranks of the two groups. This signature is then validated by applying this decision rule to independent test data.</p> <p>Conclusion</p> <p>By combining the TSPG method and repeated random sampling, a robust common cancer signature has been identified from large-scale microarray data integration. Upon further validation, this signature may be useful as a robust and objective diagnostic test for cancer.</p

An integrative model of the cardiac ventricular myocyte incorporating local control of Ca2+ release.

The local control theory of excitation-contraction (EC) coupling in cardiac muscle asserts that L-type Ca(2+) current tightly controls Ca(2+) release from the sarcoplasmic reticulum (SR) via local interaction of closely apposed L-type Ca(2+) channels (LCCs) and ryanodine receptors (RyRs). These local interactions give rise to smoothly graded Ca(2+)-induced Ca(2+) release (CICR), which exhibits high gain. In this study we present a biophysically detailed model of the normal canine ventricular myocyte that conforms to local control theory. The model formulation incorporates details of microscopic EC coupling properties in the form of Ca(2+) release units (CaRUs) in which individual sarcolemmal LCCs interact in a stochastic manner with nearby RyRs in localized regions where junctional SR membrane and transverse-tubular membrane are in close proximity. The CaRUs are embedded within and interact with the global systems of the myocyte describing ionic and membrane pump/exchanger currents, SR Ca(2+) uptake, and time-varying cytosolic ion concentrations to form a model of the cardiac action potential (AP). The model can reproduce both the detailed properties of EC coupling, such as variable gain and graded SR Ca(2+) release, and whole-cell phenomena, such as modulation of AP duration by SR Ca(2+) release. Simulations indicate that the local control paradigm predicts stable APs when the L-type Ca(2+) current is adjusted in accord with the balance between voltage- and Ca(2+)-dependent inactivation processes as measured experimentally, a scenario where common pool models become unstable. The local control myocyte model provides a means for studying the interrelationship between microscopic and macroscopic behaviors in a manner that would not be possible in experiments