Energy-linked transhydrogenase. Effects of valinomycin and nigericin on the ATP-driven transhydrogenase reaction catalyzed by reconstituted transhydrogenase-ATPase vesicles

Reconstituted transhydrogenase-ATPase vesicles obtained with purified beef heart transhydrogenase and oligomycin-sensitive ATPase were investigated with respect to the mode of interaction between the two proton pumps, with special reference to the relative contributions of the membrane potential and proton gradient using valinomycin and nigericin in the presence of potassium. In the absence of ionophores and at low ATP concentrations, below 20 microM, the ATPase generated a proton motive force which was predominantly due to a membrane potential, whereas at saturating concentrations of ATP the proton gradient was the predominant component. The ATP-dependence of the rate of the ATP-driven transhydrogenase reaction showed apparent Km values in the low and high ATP concentration range of about 3 and 56 microM, respectively, with a corresponding difference in Vmax of about 3-fold. It is concluded that the reconstituted transhydrogenase can utilize both a membrane potential and a proton gradient, separately or combined, where the relative contributions of these components depend on the activity of the ATPase. In the reconstituted vesicles, the maximally active transhydrogenase is apparently driven by an electrochemical proton gradient where the membrane potential and the proton gradient contribute one-third and two-thirds, respectively. The rate-dependent relative generation of a membrane potential and pH gradient presumably reflects the proton pump characteristics of the ATPase and/or buffering/permeability characteristics of the vesicles rather than the properties of the transhydrogenase per se. These results are discussed in relation to current models for transhydrogenase-linked proton translocation.     

Arrangement of the subunits in solubilized and membrane-bound cytochrome c oxidase from bovine heart.

The arrangement of the six cytochrome c oxidase subunits in the inner membrane of bovine heart mitochondria was investigated. The experiments were carried out in three steps. In the first step, exposed subunits were coupled to the membrane-impermeant reagent p-diazonium benzene [32S]sulfonate. In the second step, the membranes were lysed with cholate anc cytochrome c oxidase was isolated by immunoprecipitation. In the third step, the six cytochrome c oxidase subunits were separated from each other by dodecyl sulfate-acrylamide gel electrophoresis and scanned for radioactivity. Exposed subunits on the outer side of the mitochondrial inner membrane were identified by labeling intact mitochondria. Exposed subunits on the matrix side of the inner membrane were identified by labeling sonically prepared submitochondrial particles in which the matrix side of the inner membrane is exposed to the suspending medium. Since sonic irradiation leads to a rearrangement of cytochrome c oxidase in a large fraction of the resulting submitochondrial particles, an immunochemical procedure was developed for isolating particles with a low content of displaced cytochrome c oxidase. With mitochondria, subunits II, V, and VI were labeled, whereas in purified submitochondrial particles most of the label was in subunit III. The arrangement of cytochrome c oxidase in the mitochondrial inner membrane is thus transmembraneous and asymmetric; subunits II, V, and VI are situated on the outer side, subunit III is situated on the matrix side, and subunits I and IV are buried in the interior of the membrane. In a study of purified cytochrome c oxidase labeled with p-diazonium benzene [32S]sulfonate, the results were similar to those obtained with the membrane-bound enzyme. Subunits I and IV were inaccessible to the reagent, whereas the other four subunits were accessible. In contrast, all six subunits became labeled if the enzyme was dissociated with dodecyl sulfate before being exposed to the labeling reagent.     

Cytochrome c oxidase from bakers' yeast. V. Arrangement of the subunits in the isolated and membrane-bound enzyme.

Cytochrome c oxidase from baker's yeast contains three mitochondrially made subunits (I to III) which are relatively hydrophobic and four cytoplasmically made subunits (IV to VII) which are relatively hydrophilic (Mason, T. L., Poyton, R. O., Wharton, D.C., and Schatz, G. (1973) J. Biol. Chem. 248, 1346-1354 and Poyton, R. O., and Schatz, G. (1975) J. Biol. Chem. 250, 752-761). In order to explore the arrangement of these subunits in the holoenzyme, the reactivity of each subunit with a variety of "surface probes" was tested with isolated cytochrome c oxidase, with cytochrome c oxidase incorporated into liposomes, and with mitochondrially bound cytochrome c oxidase. The surface probes included iodination with lactoperoxidase and coupling with p-diazonium benzenesulfonate. In addition, external subunits were identified by linking them to bovine serum albumin carrying a covalently bound isocyanate group. In the membrane-bound enzyme, Subunit I was almost completely inaccessible and Subunit II was partly inaccessible to all surface probes. All of the other subunits were accessible. Similar results were obtained with the solubilized enzyme, except that the differences in reactivity between the individual subunits were less clear-cut. The results obtained with liposome-bound cytochrome c oxidase resembled those obtained with the mitochondrially bound enzyme. These data suggest that the two largest mitochondrially made subunits are localized in the interior of the enzyme and that they are genuine components of cytochrome c oxidase.     

Cationic amphiphiles induce fusion of acidic liposomes

Decylamine, dodecylamine and tetradecylamine induced aggregation and fusion of acidic liposomes at concentrations of about 1 mM, 75 μM and 75 μM, respectively. Aggregation was assayed as increase in turbidity. Fusion was assayed as intermixing of membranes and contents, and was observed in the electron-microscope to form large liposomes. Only at higher concentrations did these amphiphiles induce massive leakage of the liposomes' contents. Similar effects were caused by hexadecylpyridinium bromide (CP) and hexadecyltrimethylammonium bromide (CTAB). The trivalent cation 4-dodecyldiethylenetriamine and the more hydrophobic amphiphile, trioctylmethylammonium chloride, induced fusion at concentrations of about 10–20 μM. Octylamine and heptylamine induced size increase at mM concentrations. They induced membrane intermixing but little or no content intermixing. Thus, these amphiphiles seem to promote size increase either by transfer of lipid or mainly by ‘cracking and annealing’.     

A supervised approach for identifying discriminating genotype patterns and its application to breast cancer data

MOTIVATION: Large-scale association studies, investigating the genetic determinants of a phenotype of interest, are producing increasing amounts of genomic variation data on human cohorts. A fundamental challenge in these studies is the detection of genotypic patterns that discriminate individuals exhibiting the phenotype under study from individuals that do not possess it. The difficulty stems from the large number of single nucleotide polymorphism (SNP) combinations that have to be tested. The discrimination problem becomes even more involved when additional high-throughput data, such as gene expression data, are available for the same cohort. RESULTS: We have developed a graph theoretic approach for identifying discriminating patterns (DPs) for a given phenotype in a genotyped population. The method is based on representing the SNP data as a bipartite graph of individuals and their SNP states, and identifying fully connected subgraphs of this graph that relate individuals enriched for a given phenotypic group. The method can handle additional data types such as expression profiles of the genotyped population. It is reminiscent of biclustering approaches with the crucial difference that its search process is guided by the phenotype under consideration in a supervised manner. We tested our approach in simulations and on real data. In simulations, our method was able to retrieve planted patterns with high success rate. We then applied our approach to a dataset of 72 breast cancer patients with available gene expression profiles, genotyped over 695 SNPs. We detected several DPs that were highly significant with respect to various clinical phenotypes, and investigated the groups of patients and the groups of genes they defined. We found the patient groups to be highly enriched for other phenotypes and to display expression coherency among their profiles. The gene groups displayed functional coherency and involved genes with known role in cancer, providing additional support to their involvement. AVAILABILITY: The program is available upon request.     

Proteomics-Based Metabolic Modeling Reveals That Fatty Acid Oxidation (FAO) Controls Endothelial Cell (EC) Permeability

Endothelial cells (ECs) play a key role to maintain the functionality of blood vessels. Altered EC permeability causes severe impairment in vessel stability and is a hallmark of pathologies such as cancer and thrombosis. Integrating label-free quantitative proteomics data into genome-wide metabolic modeling, we built up a model that predicts the metabolic fluxes in ECs when cultured on a tridimensional matrix and organize into a vascular-like network. We discovered how fatty acid oxidation increases when ECs are assembled into a fully formed network that can be disrupted by inhibiting CPT1A, the fatty acid oxidation rate-limiting enzyme. Acute CPT1A inhibition reduces cellular ATP levels and oxygen consumption, which are restored by replenishing the tricarboxylic acid cycle. Remarkably, global phosphoproteomic changes measured upon acute CPT1A inhibition pinpointed altered calcium signaling. Indeed, CPT1A inhibition increases intracellular calcium oscillations. Finally, inhibiting CPT1A induces hyperpermeability in vitro and leakage of blood vessel in vivo, which were restored blocking calcium influx or replenishing the tricarboxylic acid cycle. Fatty acid oxidation emerges as central regulator of endothelial functions and blood vessel stability and druggable pathway to control pathological vascular permeability.Endothelial cells (ECs)¹ line the inner layer of the blood vessel wall and constitute a barrier between blood and surrounding tissue. As such, a tight regulation of EC permeability is crucial to maintain vessel functionality and avoid excessive extravasation of fluid and plasma proteins (1). Increased endothelial permeability is typical in inflammatory states and a hallmark of diseases such thrombosis, atherosclerosis, and cancer (2, 3). Because of their unique localization, ECs are constantly exposed to oxygen and nutrients that fuel cell metabolism and whose levels vary in physiological and pathological conditions. Yet, how cell metabolism regulates endothelial permeability remains incompletely understood.Previous studies have reported that EC cultures use glucose as predominant source of energy by producing lactate through glycolysis. However, also fatty acids and glutamine contribute to ATP and metabolic intermediate production (4–7). Recent in vivo studies have shown that glycolysis is necessary for EC proliferation and motility in physiological and pathological angiogenesis (4, 8). Moreover, the peroxisome proliferator-activated receptor gamma coactivator 1-α, which can activate oxidative phosphorylation, blocks EC sprouting in diabetes (9). The intriguing information emerging from these studies is that key metabolic pathways, such as glycolysis and oxidative phosphorylation in the mitochondria, play an important role in ECs and that they are actively involved in the regulation of key cell functions.Mitochondrial fatty acid oxidation (FAO) is the process that converts fatty acids (FAs) into acetyl-CoA, which fuels the tricarboxylic acid cycle (TCAc) and generates reducing factors for producing ATP via oxidative phosphorylation. Cells can incorporate FAs from the culture media or can generate FAs from the hydrolysis of triglycerides or through de novo synthesis. FAs, then, can access the mitochondria according to their length; whereas short and medium-chain FAs (up to 12 carbon atoms) diffuse through the mitochondrial membrane, long-chain FAs (with 13–21 carbon atoms) are actively transported by the carnitine O-palmitoyl transferase (CPT) proteins, which are rate-limiting enzymes for this pathway (10). Previous work suggested that FAO is poorly utilized by EC cultures (4), however, under certain stress conditions such as glucose deprivation, FAO becomes a major source of energy (7). Although it is striking to note how cells can adapt and remodel their metabolism, the role of key FAO enzymes in the control of EC functions is still largely unclear.Because of the complexity of the cell metabolome, global-scale metabolomic studies for in depth and quantitative analysis of metabolic fluxes are still challenging and computational models have provided invaluable help to better understand cell metabolism. Among them, the integrative metabolic analysis tool (iMAT), which integrates gene expression data with genome-scale metabolic network model (GSMM), has been successfully used to predict enzyme metabolic flux in several model systems and diseases (11, 12). Because gene expression and protein levels do not always correlate, and because enzymes levels do not necessarily reflect their enzymatic activity or the flux of the reaction that they are involved in, iMAT uses expression data as cue for the likelihood, but not final determinant, of enzyme activity. Modern MS technology and robust approaches for protein quantification, such as stable-isotope labeling with amino acids in cell culture (SILAC) (13) and advanced label-free algorithms (14), allow global comparative proteomic analysis and accurate measurements of protein and post-translational modification levels (15). We reasoned that the integration of quantitative MS-proteomic data into GSMM could contribute to the study of cell metabolism. Moreover, metabolic changes trigger activation of protein kinases (16, 17) to rapidly remodel the intracellular signaling and enable cells to adapt to these sudden alterations. Protein phosphorylation therefore plays an important role in regulating cell response to metabolic alteration and may hide information on cellular pathways and functions controlled by specific metabolic activities. MS-based proteomic approaches therefore offer an additional opportunity to investigate in an unbiased manner the interplay between cell metabolism and cell function (18).We have previously shown (19) that when human primary ECs are cultured for 1 day on the three-dimensional matrix matrigel and assemble into a complex network, a simplified model that recapitulates some aspects of vascular network assembly in vivo (20), the levels of metabolic enzymes are profoundly regulated. This result suggested an interplay between cell metabolism and EC behavior. Here we investigate further this aspect. Integrating label-free quantitative MS-proteomics, predictive metabolic modeling and metabolomics we discovered increased FAO when ECs are assembled into a fully formed network. Moreover, by inhibiting CPT1 pharmacologically, we elucidated that FAO is a central regulator of EC permeability in vitro and blood vessel stability in vivo. Thus, proteomics significantly contributes to the study of cell metabolism and here we identified FAO as a promising target for therapeutic intervention for the control of pathological vascular permeability.     

Thrombosis during pregnancy: Risks,prevention, and treatment for mother and fetus—harvesting the power of omic technology,biomarkers and in vitro or in vivo models to facilitate the treatment of thrombosis

Maternal thromboembolism and a spectrum of placenta‐mediated complications including the pre‐eclampsia syndromes, fetal growth restriction, fetal loss, and abruption manifest a shared etiopathogenesis and predisposing risk factors. Furthermore, these maternal and fetal complications are often linked to subsequent maternal health consequences that comprise the metabolic syndrome, namely, thromboembolism, chronic hypertension, and type II diabetes. Traditionally, several lines of evidence have linked vasoconstriction, excessive thrombosis and inflammation, and impaired trophoblast invasion at the uteroplacental interface as hallmark features of the placental complications. “Omic” technologies and biomarker development have been largely based upon advances in vascular biology, improved understanding of the molecular basis and biochemical pathways responsible for the clinically relevant diseases, and increasingly robust large cohort and/or registry based studies. Advances in understanding of innate and adaptive immunity appear to play an important role in several pregnancy complications. Strategies aimed at improving prediction of these pregnancy complications are often incorporating hemodynamic blood flow data using non‐invasive imaging technologies of the utero‐placental and maternal circulations early in pregnancy. Some evidence suggests that a multiple marker approach will yield the best performing prediction tools, which may then in turn offer the possibility of early intervention to prevent or ameliorate these pregnancy complications. Prediction of maternal cardiovascular and non‐cardiovascular consequences following pregnancy represents an important area of future research, which may have significant public health consequences not only for cardiovascular disease, but also for a variety of other disorders, such as autoimmune and neurodegenerative diseases. Birth Defects Research (Part C) 105:209–225, 2015. © 2015 Wiley Periodicals, Inc.     

Modeling cancer metabolism on a genome scale

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome‐scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network‐level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field.