Mg\u3csup\u3e2+\u3c/sup\u3e Differentially Regulates Two Modes of Mitochondrial Ca\u3csup\u3e2+\u3c/sup\u3e Uptake in Isolated Cardiac Mitochondria: Implications for Mitochondrial Ca\u3csup\u3e2+\u3c/sup\u3e Sequestration

The manner in which mitochondria take up and store Ca2+ remains highly debated. Recent experimental and computational evidence has suggested the presence of at least two modes of Ca2+ uptake and a complex Ca2+ sequestration mechanism in mitochondria. But how Mg2+ regulates these different modes of Ca2+ uptake as well as mitochondrial Ca2+ sequestration is not known. In this study, we investigated two different ways by which mitochondria take up and sequester Ca2+ by using two different protocols. Isolated guinea pig cardiac mitochondria were exposed to varying concentrations of CaCl2 in the presence or absence of MgCl2. In the first protocol, A, CaCl2 was added to the respiration buffer containing isolated mitochondria, whereas in the second protocol, B, mitochondria were added to the respiration buffer with CaCl2 already present. Protocol A resulted first in a fast transitory uptake followed by a slow gradual uptake. In contrast, protocol B only revealed a slow and gradual Ca2+ uptake, which was approximately 40 % of the slow uptake rate observed in protocol A. These two types of Ca2+ uptake modes were differentially modulated by extra-matrix Mg2+. That is, Mg2+ markedly inhibited the slow mode of Ca2+ uptake in both protocols in a concentration-dependent manner, but not the fast mode of uptake exhibited in protocol A. Mg2+ also inhibited Na+-dependent Ca2+ extrusion. The general Ca2+ binding properties of the mitochondrial Ca2+ sequestration system were reaffirmed and shown to be independent of the mode of Ca2+ uptake, i.e. through the fast or slow mode of uptake. In addition, extra-matrix Mg2+ hindered Ca2+ sequestration. Our results indicate that mitochondria exhibit different modes of Ca2+ uptake depending on the nature of exposure to extra-matrix Ca2+, which are differentially sensitive to Mg2+. The implications of these findings in cardiomyocytes are discussed

Modeling Mitochondrial Bioenergetics with Integrated Volume Dynamics

Mathematical models of mitochondrial bioenergetics provide powerful analytical tools to help interpret experimental data and facilitate experimental design for elucidating the supporting biochemical and physical processes. As a next step towards constructing a complete physiologically faithful mitochondrial bioenergetics model, a mathematical model was developed targeting the cardiac mitochondrial bioenergetic based upon previous efforts, and corroborated using both transient and steady state data. The model consists of several modified rate functions of mitochondrial bioenergetics, integrated calcium dynamics and a detailed description of the K+-cycle and its effect on mitochondrial bioenergetics and matrix volume regulation. Model simulations were used to fit 42 adjustable parameters to four independent experimental data sets consisting of 32 data curves. During the model development, a certain network topology had to be in place and some assumptions about uncertain or unobserved experimental factors and conditions were explicitly constrained in order to faithfully reproduce all the data sets. These realizations are discussed, and their necessity helps contribute to the collective understanding of the mitochondrial bioenergetics

A pH-Dependent Kinetic Model of Dihydrolipoamide Dehydrogenase from Multiple Organisms

AbstractDihydrolipoamide dehydrogenase is a flavoenzyme that reversibly catalyzes the oxidation of reduced lipoyl substrates with the reduction of NAD+ to NADH. In vivo, the dihydrolipoamide dehydrogenase component (E3) is associated with the pyruvate, α-ketoglutarate, and glycine dehydrogenase complexes. The pyruvate dehydrogenase (PDH) complex connects the glycolytic flux to the tricarboxylic acid cycle and is central to the regulation of primary metabolism. Regulation of PDH via regulation of the E3 component by the NAD+/NADH ratio represents one of the important physiological control mechanisms of PDH activity. Furthermore, previous experiments with the isolated E3 component have demonstrated the importance of pH in dictating NAD+/NADH ratio effects on enzymatic activity. Here, we show that a three-state mechanism that represents the major redox states of the enzyme and includes a detailed representation of the active-site chemistry constrained by both equilibrium and thermodynamic loop constraints can be used to model regulatory NAD+/NADH ratio and pH effects demonstrated in progress-curve and initial-velocity data sets from rat, human, Escherichia coli, and spinach enzymes. Global fitting of the model provides stable predictions to the steady-state distributions of enzyme redox states as a function of lipoamide/dihydrolipoamide, NAD+/NADH, and pH. These distributions were calculated using physiological NAD+/NADH ratios representative of the diverse organismal sources of E3 analyzed in this study. This mechanistically detailed, thermodynamically constrained, pH-dependent model of E3 provides a stable platform on which to accurately model multicomponent enzyme complexes that implement E3 from a variety of organisms

The Inferred Cardiogenic Gene Regulatory Network in the Mammalian Heart

Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from the developing mouse heart. Approximately 200 genes of interest were input into the algorithm to generate putative network topologies that are capable of explaining the experimental data via model simulation. To cull specious network interactions, thousands of putative networks are merged and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene interactions and used to predict regulatory pathways important for the developing mammalian heart. Area under the precision-recall curve and receiver operator characteristic curve are 9% and 58%, respectively. Of the top 10 ranked predicted interactions, 4 have already been validated. The algorithm is further tested using a network enriched with known interactions and another depleted of them. The inferred networks contained more interactions for the enriched network versus the depleted network. In all test cases, maximum performance of the algorithm was achieved when the purely data-driven method of network inference was combined with a data-independent, functional-based association method. Lastly, the network generated from the list of approximately 200 genes of interest was expanded using gene-profile uniqueness metrics to include approximately 900 additional known mouse genes and to form the most likely cardiogenic gene regulatory network. The resultant network supports known regulatory interactions and contains several novel cardiogenic regulatory interactions. The method outlined herein provides an informative approach to network inference and leads to clear testable hypotheses related to gene regulation

Temporal and regional intestinal changes in permeability, tight junction, and cytokine gene expression following ovariectomy-induced estrogen deficiency

The work presented within this study was funded in part by NCCIH (R01AT007695) and NIDDK (R01DK101050Peer reviewedPublisher PD

The feasibility of genome-scale biological network inference using Graphics Processing Units

Abstract Systems research spanning fields from biology to finance involves the identification of models to represent the underpinnings of complex systems. Formal approaches for data-driven identification of network interactions include statistical inference-based approaches and methods to identify dynamical systems models that are capable of fitting multivariate data. Availability of large data sets and so-called ‘big data’ applications in biology present great opportunities as well as major challenges for systems identification/reverse engineering applications. For example, both inverse identification and forward simulations of genome-scale gene regulatory network models pose compute-intensive problems. This issue is addressed here by combining the processing power of Graphics Processing Units (GPUs) and a parallel reverse engineering algorithm for inference of regulatory networks. It is shown that, given an appropriate data set, information on genome-scale networks (systems of 1000 or more state variables) can be inferred using a reverse-engineering algorithm in a matter of days on a small-scale modern GPU cluster.https://deepblue.lib.umich.edu/bitstream/2027.42/136186/1/13015_2017_Article_100.pd

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

An integrated bioenergetics modeling approach to mitochondrial permeability transition

Acute myocardial infarctions are a result of the cessation of blood carrying vital nutrients and oxygen to the myocardium. This ischemic insult is detrimental to the affected tissue and resupplying the starved tissue with blood may result in a paradoxical response. This phenomenon is known as ischemia/reperfusion injury and is estimated contribute up to 50% of the infarct size. It often leads to a lethal reperfusion injury known as mitochondrial permeability transition (MPT). MPT is an event when a pore known as the mitochondrial permeability transition pore (PTP) opens and likely results in devastating bioenergetic consequences, namely cytochrome c mediated apoptosis and necrosis. Current therapies for MPT remain inadequate, and this fact highlights the need for understanding this ischemic/reperfusion injury in order to develop better therapeutic and preventative measures. The work presented in this thesis takes a step forward in this process and begins to unravel the MPT phenomenon at a bioenergetic mechanistic level in a mathematical modeling intensive manner. Three objectives of this work will be discussed: i) the development and corroboration of a mitochondrial bioenergetics model capable of modeling Ca2+ dynamics and volume regulation, ii) the extension of the bioenergetics model to include PTP regulation and analyze its affect on bioenergetics and iii) the development of a sampling based model-driven experiment design algorithm and its implementation in designing novel experiments to identify critical parameters for the adenine nucleotide translocase-based PTP voltage-sensor hypothesis