Computational prediction of changes in brain metabolic fluxes during Parkinson's disease from mRNA expression.

BACKGROUND: Parkinson's disease is a widespread neurodegenerative disorder which affects brain metabolism. Although changes in gene expression during disease are often measured, it is difficult to predict metabolic fluxes from gene expression data. Here we explore the hypothesis that changes in gene expression for enzymes tend to parallel flux changes in biochemical reaction pathways in the brain metabolic network. This hypothesis is the basis of a computational method to predict metabolic flux changes from post-mortem gene expression measurements in Parkinson's disease (PD) brain. RESULTS: We use a network model of central metabolism and optimize the correspondence between relative changes in fluxes and in gene expression. To this end we apply the Least-squares with Equalities and Inequalities algorithm integrated with Flux Balance Analysis (Lsei-FBA). We predict for PD (1) decreases in glycolytic rate and oxygen consumption and an increase in lactate production in brain cortex that correspond with measurements (2) relative flux decreases in ATP synthesis, in the malate-aspartate shuttle and midway in the TCA cycle that are substantially larger than relative changes in glucose uptake in the substantia nigra, dopaminergic neurons and most other brain regions (3) shifts in redox shuttles between cytosol and mitochondria (4) in contrast to Alzheimer's disease: little activation of the gamma-aminobutyric acid shunt pathway in compensation for decreased alpha-ketoglutarate dehydrogenase activity (5) in the globus pallidus internus, metabolic fluxes are increased, reflecting increased functional activity. CONCLUSION: Our method predicts metabolic changes from gene expression data that correspond in direction and order of magnitude with presently available experimental observations during Parkinson's disease, indicating that the hypothesis may be useful for some biochemical pathways. Lsei-FBA generates predictions of flux distributions in neurons and small brain regions for which accurate metabolic flux measurements are not yet possible.

The dynamic side of the Warburg effect: glycolytic intermediate storage as buffer for fluctuating glucose and O 2 supply in tumor cells.

Background: Tumor cells show the Warburg effect: high glucose uptake and lactate production despite sufficient oxygen supply. Otto Warburg found this effect in tissue slices and in suspensions of Ehrlich ascites tumor cells. Remarkably, these ascites tumor cells can transiently take up glucose an order of magnitude faster than the steady high rate measured by Warburg for hours. Methods: The purpose of the transiently very high glucose uptake is investigated here with a computational model of glycolysis, oxidative phosphorylation and ATP consumption which reproduces short kinetic experiments on the ascites tumor cells as well as the long-lasting Warburg, Crabtree and Pasteur effects. The model, extended with equations for glucose and O 2 transport in tissue, is subsequently used to predict metabolism in tumor cells during fluctuations of tissue blood flow resulting in cycling hypoxia. Results: The model analysis suggests that the head section of the glycolytic chain in the tumor cells is partially inhibited in about a minute when substantial amounts of glucose have been taken up intracellularly; this head section of the glycolytic chain is subsequently disinhibited slowly when concentrations of glycolytic intermediates are low. Based on these dynamic characteristics, simulations of tissue with fluctuating O 2 and glucose supply predict that tumor cells greedily take up glucose when this periodically becomes available, leaving very little for other cells. The glucose is stored as fructose 1,6-bisphosphate and other glycolytic intermediates, which are used for ATP production during   O 2 and glucose shortages. Conclusions: The head section of glycolysis which phosphorylates glucose may be dynamically regulated and takes up glucose at rates exceeding the Warburg effect if glucose levels have been low for some time. The hypothesis is put forward here that dynamic regulation of the powerful glycolytic enzyme system in tumors is used to buffer oxygen and nutrient fluctuations in tissue.

Understanding the physiology of the ageing individual: computational modelling of changes in metabolism and endurance.

Ageing and lifespan are strongly affected by metabolism. The maximal possible uptake of oxygen is not only a good predictor of performance in endurance sports, but also of life expectancy. Figuratively speaking, healthy ageing is a competitive sport. Although the root cause of ageing is damage to macromolecules, it is the balance with repair processes that is decisive. Reduced or intermittent nutrition, hormones and intracellular signalling pathways that regulate metabolism have strong effects on ageing. Homeostatic regulatory processes tend to keep the environment of the cells within relatively narrow bounds. On the other hand, the body is constantly adapting to physical activity and food consumption. Spontaneous fluctuations in heart rate and other processes indicate youth and health. A (homeo)dynamic aspect of homeostasis deteriorates with age. We are now in a position to develop computational models of human metabolism and the dynamics of heart rhythm and oxygen transport that will advance our understanding of ageing. Computational modelling of the connections between dietary restriction, metabolism and protein turnover may increase insight into homeostasis of the proteins in our body. In this way, the computational reconstruction of human physiological processes, the Physiome, can help prevent frailty and age-related disease.

Progressively heterogeneous mismatch of regional oxygen delivery to consumption during graded coronary stenosis in pig left ventricle.

In normal hearts, myocardial perfusion is fairly well matched to regional metabolic demand, although both are distributed heterogeneously. Nonuniform regional metabolic vulnerability during coronary stenosis would help to explain nonuniform necrosis during myocardial infarction. In the present study, we investigated whether metabolism-perfusion correlation diminishes during coronary stenosis, indicating increasing mismatch of regional oxygen supply to demand. Thirty anesthetized male pigs were studied: controls without coronary stenosis (n = 11); group I, left anterior descending (LAD) coronary stenosis leading to coronary perfusion pressure reduction to 70 mmHg (n = 6); group II, stenosis with perfusion pressure of about 35 mmHg (n = 6); and group III, stenosis with perfusion pressure of 45 mmHg combined with adenosine infusion (n = 7). [2-(13)C]- and [1,2-(13)C]acetate infusion was used to calculate regional O2 consumption from glutamate NMR spectra measured for multiple tissue samples of about 100 mg dry mass in the LAD region. Blood flow was measured with microspheres in the same regions. In control hearts without stenosis, regional oxygen extraction did not correlate with basal blood flow. Average myocardial O2 delivery and consumption decreased during coronary stenosis, but vasodilation with adenosine counteracted this. Regional oxygen extraction was on average decreased during stenosis, suggesting adaptation of metabolism to lower oxygen supply after half an hour of ischemia. Whereas regional O2 delivery correlated with O2 consumption in controls, this relation was progressively lost with graded coronary hypotension but partially reestablished by adenosine infusion. Therefore, coronary stenosis leads to heterogeneous metabolic stress indicated by decreasing regional O2 supply to demand matching in myocardium during partial coronary obstruction.

Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain.

Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer's disease agree with independent measurements of cerebral metabolism in patients. This second version of BiGGR is available from Bioconductor.

Increased expression of matrix extracellular phosphoglycoprotein (MEPE) in cortical bone of the rat tibia after mechanical loading: identification by oligonucleotide microarray.

Skeletal integrity in humans and animals is maintained by daily mechanical loading. It has been widely accepted that osteocytes function as mechanosensors. Many biochemical signaling molecules are involved in the response of osteocytes to mechanical stimulation. The aim of this study was to identify genes involved in the translation of mechanical stimuli into bone formation. The four-point bending model was used to induce a single period of mechanical loading on the right tibia, while the contra lateral left tibia served as control. Six hours after loading, the effects of mechanical loading on gene-expression were determined with microarray analysis. Protein expression of differentially regulated genes was evaluated with immunohistochemistry. Nine genes were found to exhibit a significant differential gene expression in LOAD compared to control. MEPE, Garnl1, V2R2B, and QFG-TN1 olfactory receptor were up-regulated, and creatine kinase (muscle form), fibrinogen-B beta-polypeptide, monoamine oxidase A, troponin-C and kinesin light chain-C were down-regulated. Validation with real-time RT-PCR analysis confirmed the up-regulation of MEPE and the down-regulation of creatine kinase (muscle form) and troponin-C in the loaded tibia. Immunohistochemistry showed that the increase of MEPE protein expression was already detectable six hours after mechanical loading. In conclusion, these genes probably play a role during translation of mechanical stimuli six hours after mechanical loading. The modulation of MEPE expression may indicate a connection between bone mineralization and bone formation after mechanical stimulation.

Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies.

BACKGROUND: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue samples is desirable. Taking tissue biopsies after infusion of substrates labeled with stable carbon isotopes makes this possible in animal experiments. However, the appreciable noise level in NMR spectra of extracted tissue samples makes computational estimation of metabolic fluxes challenging and a good method to define confidence regions was not yet available. RESULTS: Here we present a computational analysis method for nuclear magnetic resonance (NMR) measurements of tricarboxylic acid (TCA) cycle metabolites. The method was validated using measurements on extracts of single tissue biopsies taken from porcine heart in vivo. Isotopic enrichment of glutamate was measured by NMR spectroscopy in tissue samples taken at a single time point after the timed infusion of 13C labeled substrates for the TCA cycle. The NMR intensities for glutamate were analyzed with a computational model describing carbon transitions in the TCA cycle and carbon exchange with amino acids. The model dynamics depended on five flux parameters, which were optimized to fit the NMR measurements. To determine confidence regions for the estimated fluxes, we used the Metropolis-Hastings algorithm for Markov chain Monte Carlo (MCMC) sampling to generate extensive ensembles of feasible flux combinations that describe the data within measurement precision limits. To validate our method, we compared myocardial oxygen consumption calculated from the TCA cycle flux with in vivo blood gas measurements for 38 hearts under several experimental conditions, e.g. during coronary artery narrowing. CONCLUSIONS: Despite the appreciable NMR noise level, the oxygen consumption in the tissue samples, estimated from the NMR spectra, correlates with blood-gas oxygen uptake measurements for the whole heart. The MCMC method provides confidence regions for the estimated metabolic fluxes in single cardiac biopsies, taking the quantified measurement noise level and the nonlinear dependencies between parameters fully into account.

A community-driven global reconstruction of human metabolism.

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.

A vision and strategy for the virtual physiological human: 2012 update.

European funding under Framework 7 (FP7) for the virtual physiological human (VPH) project has been in place now for 5 years. The VPH Network of Excellence (NoE) has been set up to help develop common standards, open source software, freely accessible data and model repositories, and various training and dissemination activities for the project. It is also working to coordinate the many clinically targeted projects that have been funded under the FP7 calls. An initial vision for the VPH was defined by the FP6 STEP project in 2006. In 2010, we wrote an assessment of the accomplishments of the first two years of the VPH in which we considered the biomedical science, healthcare and information and communications technology challenges facing the project (Hunter et al. 2010 Phil. Trans. R. Soc. A 368, 2595-2614 (doi:10.1098/rsta.2010.0048)). We proposed that a not-for-profit professional umbrella organization, the VPH Institute, should be established as a means of sustaining the VPH vision beyond the time-frame of the NoE. Here, we update and extend this assessment and in particular address the following issues raised in response to Hunter et al.: (i) a vision for the VPH updated in the light of progress made so far, (ii) biomedical science and healthcare challenges that the VPH initiative can address while also providing innovation opportunities for the European industry, and (iii) external changes needed in regulatory policy and business models to realize the full potential that the VPH has to offer to industry, clinics and society generally.

Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism.

The human physiological system is stressed to its limits during endurance sports competition events. We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We calculated heat transfer by conduction and blood flow inside the body, and heat transfer from the skin by radiation, convection and sweat evaporation, resulting in temperature changes in 25 body compartments. We simulated a mountain time trial to Alpe d'Huez during the Tour de France. To approach the time realized by Lance Armstrong in 2004, very high oxygen uptake must be sustained by the simulated cyclist. Temperature was predicted to reach 39°C in the brain, and 39.7°C in leg muscle. In addition to the macroscopic simulation, we analysed the buffering of bursts of high adenosine triphosphate hydrolysis by creatine kinase during cyclical muscle activity at the biochemical pathway level. To investigate the low oxygen to carbohydrate ratio for the brain, which takes up lactate during exercise, we calculated the flux distribution in cerebral energy metabolism. Computational modelling of the human body, describing heat exchange and energy metabolism, makes simulation of endurance sports events feasible.

Analyzing the functional properties of the creatine kinase system with multiscale 'sloppy' modeling.

In this study the function of the two isoforms of creatine kinase (CK; EC 2.7.3.2) in myocardium is investigated. The 'phosphocreatine shuttle' hypothesis states that mitochondrial and cytosolic CK plays a pivotal role in the transport of high-energy phosphate (HEP) groups from mitochondria to myofibrils in contracting muscle. Temporal buffering of changes in ATP and ADP is another potential role of CK. With a mathematical model, we analyzed energy transport and damping of high peaks of ATP hydrolysis during the cardiac cycle. The analysis was based on multiscale data measured at the level of isolated enzymes, isolated mitochondria and on dynamic response times of oxidative phosphorylation measured at the whole heart level. Using 'sloppy modeling' ensemble simulations, we derived confidence intervals for predictions of the contributions by phosphocreatine (PCr) and ATP to the transfer of HEP from mitochondria to sites of ATP hydrolysis. Our calculations indicate that only 15±8% (mean±SD) of transcytosolic energy transport is carried by PCr, contradicting the PCr shuttle hypothesis. We also predicted temporal buffering capabilities of the CK isoforms protecting against high peaks of ATP hydrolysis (3750 µM*s(-1)) in myofibrils. CK inhibition by 98% in silico leads to an increase in amplitude of mitochondrial ATP synthesis pulsation from 215±23 to 566±31 µM*s(-1), while amplitudes of oscillations in cytosolic ADP concentration double from 77±11 to 146±1 µM. Our findings indicate that CK acts as a large bandwidth high-capacity temporal energy buffer maintaining cellular ATP homeostasis and reducing oscillations in mitochondrial metabolism. However, the contribution of CK to the transport of high-energy phosphate groups appears limited. Mitochondrial CK activity lowers cytosolic inorganic phosphate levels while cytosolic CK has the opposite effect.

Endotoxemia decreases matching of regional blood flow and O2 delivery to O2 uptake in the porcine left ventricle.

Heterogeneity of regional coronary blood flow is caused in part by heterogeneity in O(2) demand in the normal heart. We investigated whether myocardial O(2) supply/demand mismatching is associated with the myocardial depression of sepsis. Regional blood flow (microspheres) and O(2) uptake ([(13)C]acetate infusion and analysis of resultant NMR spectra) were measured in about nine contiguous tissue samples from the left ventricle (LV) in each heart. Endotoxemic pigs (n = 9) showed hypotension at unchanged cardiac output with a fall in LV stroke work and first derivative of LV pressure relative to controls (n = 4). Global coronary blood flow and O(2) delivery were maintained. Lactate accumulated in arterial blood, but net lactate extraction across the coronary bed was unchanged during endotoxemia. When LV O(2) uptake based on blood gas versus NMR data were compared, the correlation was 0.73 (P = 0.007). While stable over time in controls, regional blood flows were strongly redistributed during endotoxin shock, with overall flow heterogeneity unchanged. A stronger redistribution of blood flow with endotoxin was associated with a larger fall in LV function parameters. Moreover, the correlation of regional O(2) delivery to uptake fell from r = 0.73 (P < 0.001) in control to r = 0.18 (P = 0.25, P = 0.009 vs. control) in endotoxemic hearts. The results suggest a redistribution of LV regional coronary blood flow during endotoxin shock in pigs, with regional O(2) delivery mismatched to O(2) demand. Mismatching may underlie, at least in part, the myocardial depression of sepsis.

Electron density fingerprints (EDprints): virtual screening using assembled information of electron density.

We have designed a method to encode properties related to the electron densities of molecules (calculated (1)H and (13)C NMR shifts and atomic partial charges) in molecular fingerprints (EDprints). EDprints was evaluated in terms of their retrospective virtual screening accuracy against the Directory of Useful Decoys (DUD) and compared to the established ligand-based similarity search methods MOLPRINT 2D and FCFP-4. Although there are no significant differences in the overall virtual screening accuracies of the three methods, specific examples highlight interesting differences between the new EDprints fingerprint method and the atom-centered circular fingerprint methods of MOLPRINT 2D and FCFP-4. On one hand, EDprints similarity searches can be biased by the molecular protonation state, especially when reference ligands contain multiple ionizable groups. On the other hand, EDprints models are more robust toward subtle rearrangements of chemical groups and more suitable for screening against reference molecules with fused ring systems than MOLPRINT 2D and FCFP-4. EDprints is furthermore the fastest method under investigation in comparing fingerprints (average 56-233-fold increase in speed), which makes it highly suitable for all-against-all similarity searches and for repetitive virtual screening against large chemical databases of millions of compounds.

A vision and strategy for the virtual physiological human in 2010 and beyond.

European funding under framework 7 (FP7) for the virtual physiological human (VPH) project has been in place now for nearly 2 years. The VPH network of excellence (NoE) is helping in the development of common standards, open-source software, freely accessible data and model repositories, and various training and dissemination activities for the project. It is also helping to coordinate the many clinically targeted projects that have been funded under the FP7 calls. An initial vision for the VPH was defined by framework 6 strategy for a European physiome (STEP) project in 2006. It is now time to assess the accomplishments of the last 2 years and update the STEP vision for the VPH. We consider the biomedical science, healthcare and information and communications technology challenges facing the project and we propose the VPH Institute as a means of sustaining the vision of VPH beyond the time frame of the NoE.

Computational quantification of metabolic fluxes from a single isotope snapshot: application to an animal biopsy.

MOTIVATION: Quantitative determination of metabolic fluxes in single tissue biopsies is difficult. We report a novel analysis approach and software package for in vivo flux quantification using stable isotope labeling. RESULTS: We developed a protocol based on brief, timed infusion of (13)C isotope-enriched substrates for the tricarboxylic acid (TCA) cycle followed by quick freezing of tissue biopsies. NMR measurements of tissue extracts were used for flux estimation based on a computational model of carbon transitions between TCA cycle metabolites and related amino acids. To this end, we developed a computational framework in which metabolic systems can be flexibly assembled, simulated and analyzed. Flux parameters were quantified from NMR multiplets by a partial grid search followed by repeated Nelder-Mead optimizations implemented on a computer grid. We implemented a model of the TCA cycle and showed by extensive simulations that the timed infusion protocol reliably quantitates multiple fluxes. Experimental validation of the method was done in vivo on hearts of anesthetized pigs under two different conditions: basal state (n = 7) and cardiac stress caused by infusion of dobutamine (n = 7). About nine tissue samples (40-200 mg dry-weight) were taken per heart. TCA cycle flux was 6.11 +/- 0.28 (SEM) micromol/min x gdw at baseline versus 9.29 +/- 1.03 micromol/min x gdw for dobutamine stress. Oxygen consumption calculated from the TCA cycle flux and from 'gold standard' blood gas-based measurements were close, correlating with r=0.88 (P < 10(-4)). Spatial heterogeneity in metabolic fluxes is detectable amongst the small samples. We propose that our novel isotope snapshot methodology is suitable for flux measurements in biopsies in vivo. AVAILABILITY: Non-profit organizations will, upon request, be granted a non-exclusive license to use the software for internal research and teaching purposes at no charge. A web interface for using the software on our computer grid is available under http://www.ibi.vu.nl/programs/

Robust modelling, measurement and analysis of human and animal metabolic systems.

Modelling human and animal metabolism is impeded by the lack of accurate quantitative parameters and the large number of biochemical reactions. This problem may be tackled by: (i) study of modules of the network independently; (ii) ensemble simulations to explore many plausible parameter combinations; (iii) analysis of 'sloppy' parameter behaviour, revealing interdependent parameter combinations with little influence; (iv) multiscale analysis that combines molecular and whole network data; and (v) measuring metabolic flux (rate of flow) in vivo via stable isotope labelling. For the latter method, carbon transition networks were modelled with systems of ordinary differential equations, but we show that coloured Petri nets provide a more intuitive graphical approach. Analysis of parameter sensitivities shows that only a few parameter combinations have a large effect on predictions. Model analysis of high-energy phosphate transport indicates that membrane permeability, inaccurately known at the organellar level, can be well determined from whole-organ responses. Ensemble simulations that take into account the imprecision of measured molecular parameters contradict the popular hypothesis that high-energy phosphate transport in heart muscle is mostly by phosphocreatine. Combining modular, multiscale, ensemble and sloppy modelling approaches with in vivo flux measurements may prove indispensable for the modelling of the large human metabolic system.

Multiscale and modular analysis of cardiac energy metabolism: repairing the broken interfaces of isolated system components.

Computational models of large molecular systems can be assembled from modules representing biological function emerging from interactions among a small subset of molecules. Experimental information on isolated molecules can be integrated with the response of the network as a whole to estimate crucial missing parameters. As an example, a "skeleton" model is analyzed for the module regulating dynamic adaptation of myocardial oxidative phosphorylation (OxPhos) to fluctuating cardiac energy demand. The module contains adenine nucleotides, creatine, and phosphate groups. Enzyme kinetic equations for two creatine kinase (CK) isoforms were combined with the response time of OxPhos (t mito; generalized time constant) to steps in the cardiac pacing rate to identify all module parameters. To obtain t mito, the time course of O2 uptake was measured for the whole heart. An O2 transport model was used to deconvolute the whole-heart response to the mitochondrial level. By optimizing mitochondrial outer membrane permeability to 21 microm/s the experimental t mito = 3.7 s was reproduced. This in vivo value is about four times larger, or smaller, respectively, than conflicting values obtained from two different in vitro studies. This demonstrates an important rule for multiscale analysis: experimental responses and modeling of the system at the larger scale allow one to estimate essential parameters for the interfaces of components which may have been altered during physical isolation. The model correctly predicts a smaller t mito when CK activity is reduced. The model further predicts a slower response if the muscle CK isoform is overexpressed and a faster response if mitochondrial CK is overexpressed. The CK system is very effective in decreasing maximum levels of ADP during systole and reducing average Pi levels over the whole cardiac cycle.

Adenine nucleotide-creatine-phosphate module in myocardial metabolic system explains fast phase of dynamic regulation of oxidative phosphorylation.

Computational models of a large metabolic system can be assembled from modules that represent a biological function emerging from interaction of a small subset of molecules. A "skeleton model" is tested here for a module that regulates the first phase of dynamic adaptation of oxidative phosphorylation (OxPhos) to demand in heart muscle cells. The model contains only diffusion, mitochondrial outer membrane (MOM) permeation, and two isoforms of creatine kinase (CK), in cytosol and mitochondrial intermembrane space (IMS), respectively. The communication with two neighboring modules occurs via stimulation of mitochondrial ATP production by ADP and P(i) from the IMS and via time-varying cytosolic ATP hydrolysis during contraction. Assuming normal cytosolic diffusion and high MOM permeability for ADP, the response time of OxPhos (t(mito); generalized time constant) to steps in cardiac pacing rate is predicted to be 2.4 s. In contrast, with low MOM permeability, t(mito) is predicted to be 15 s. An optimized MOM permeability of 21 mum/s gives t(mito) = 3.7 s, in agreement with experiments on rabbit heart with blocked glycolytic ATP synthesis. The model correctly predicts a lower t(mito) if CK activity is reduced by 98%. Among others, the following predictions result from the model analysis: 1) CK activity buffers large ADP oscillations; 2) ATP production is pulsatile in beating heart, although it adapts slowly to demand with "time constant" approximately 14 heartbeats; 3) if the muscle isoform of CK is overexpressed, OxPhos reacts slower to changing workload; and 4) if mitochondrial CK is overexpressed, OxPhos reacts faster.

Regional sympathetic denervation affects the relation between canine local myocardial blood flow and oxygen consumption.

Myocardial blood flow and oxygen consumption are heterogeneously distributed. Perfusion and myocardial oxygen consumption are closely correlated in the normal heart. It is unknown how this metabolism-perfusion relation is influenced by sympathetic denervation. We investigated this question in seven chloralose-anaesthetized dogs, 3-4 weeks after regional sympathetic denervation of the left circumflex coronary artery area of supply of the left ventricle. Measurements were made of local myocardial blood flow (MBF, in ml min(-1) (g dry wt)(-1)), measured with microspheres, and myocardial oxygen consumption ( , in mumol min(-1) (g dry wt)(-1)) in the same location, calculated from the (13)C spectrum of tissue extracts after intracoronary infusion of 3-(13)C-lactate. Since both innervated and denervated regions are subject to the same arterial pressure, lower blood flow indicates higher resistance. Mean MBF was 5.56 ml min(-1) (g dry wt)(-1) (heterogeneity of 3.47 ml min(-1) (g dry wt)(-1)) innervated, 7.48 ml min(-1) (g dry wt)(-1) (heterogeneity of 3.62 ml min(-1) (g dry wt)(-1)) denervated (n.s.). Significant linear relations were found between MBF and M Vo2 of individual samples within the innervated and denervated regions. The slopes of these relations were not significantly different, but the adjusted mean was significantly higher in the denervated regions (+1.92 ml min(-1) (g dry wt)(-1), an increase of 38% of the mean MBF at the pooled mean M Vo2, P = 0.028, ANCOVA). The ratio MBF/M Vo2(in ml micromol(-1)) was significantly higher, being 0.296 +/- 0.167 ml micromol(-1) in the denervated region compared with the innervated region, 0.216 +/- 0.126 ml micromol(-1), P = 0.0182, Mann-Whitney U test. These results indicate that sympathetic tone under chloralose anaesthesia imposes a moderate vasoconstrictive effect in the myocardium that is not detected by comparison of the mean blood flow or resistance.

Myocardial O2 consumption in porcine left ventricle is heterogeneously distributed in parallel to heterogeneous O2 delivery.

Myocardial blood flow is unevenly distributed, but the cause of this heterogeneity is unknown. Heterogeneous blood flow may reflect heterogeneity of oxygen demand. The aim of the present study was to assess the relation between oxygen consumption and blood flow in small tissue regions in porcine left ventricle. In seven male, anesthetized, open-chest pigs, local oxygen consumption was quantitated by computational model analysis of the incorporation of 13C in glutamate via the tricarboxylic acid cycle during timed infusion of [13C]acetate into the left anterior descending coronary artery. Blood flow was measured with radioactive microspheres before and during acetate infusion. High-resolution nuclear magnetic resonance 13C spectra were obtained from extracts of tissue samples (159 mg mean dry wt) taken at the end of the acetate infusion. Mean regional myocardial blood flow was stable [5.0 +/- 1.6 (SD) and 5.0 +/- 1.4 ml.min(-1).g dry wt(-1) before and after 30 min of acetate infusion, respectively]. Mean left ventricular oxygen consumption measured with the NMR method was 18.6 +/- 7.7 micromol.min(-1).g dry wt(-1) and correlated well (r = 0.85, P = 0.02, n = 7) with oxygen consumption calculated from blood flow, hemoglobin, and blood gas measurements (mean 22.8 +/- 4.7 micromol.min(-1).g dry wt(-1)). Local blood flow and oxygen consumption were significantly correlated (r = 0.63 for pooled normalized data, P < 0.0001, n = 60). We calculate that, in the heart at normal workload, the variance of left ventricular oxygen delivery at submilliliter resolution is explained for 43% by heterogeneity in oxygen demand.