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There is increasing interest in the potential for metabolic profiling to evaluate the progression of pulmonary hypertension (PH). However, a detailed analysis of the metabolic changes in lungs at the early stage of PH, characterized by increased pulmonary artery pressure but prior to the development of right ventricle hypertrophy and failure, is lacking in a preclinical animal model of PH. Thus, we undertook a study using rats 14 days after exposure to monocrotaline (MCT), to determine whether we could identify early stage metabolic changes prior to the manifestation of developed PH. We observed changes in multiple pathways associated with the development of PH, including activated glycolysis, increased markers of proliferation, disruptions in carnitine homeostasis, increased inflammatory and fibrosis biomarkers, and a reduction in glutathione biosynthesis. Further, our global metabolic profile data compare favorably with prior work carried out in humans with PH. We conclude that despite the MCT-model not recapitulating all the structural changes associated with humans with advanced PH, including endothelial cell proliferation and the formation of plexiform lesions, it is very similar at a metabolic level. Thus, we suggest that despite its limitations it can still serve as a useful preclinical model for the study of PH.

TRAP1 (TNF receptor-associated protein), a member of the HSP90 chaperone family, is found predominantly in mitochondria. TRAP1 is broadly considered to be an anticancer molecular target. However, current inhibitors cannot distinguish between HSP90 and TRAP1, making their utility as probes of TRAP1-specific function questionable. Some cancers express less TRAP1 than do their normal tissue counterparts, suggesting that TRAP1 function in mitochondria of normal and transformed cells is more complex than previously appreciated. We have used TRAP1-null cells and transient TRAP1 silencing/overexpression to show that TRAP1 regulates a metabolic switch between oxidative phosphorylation and aerobic glycolysis in immortalized mouse fibroblasts and in human tumor cells. TRAP1-deficiency promotes an increase in mitochondrial respiration and fatty acid oxidation, and in cellular accumulation of tricarboxylic acid cycle intermediates, ATP and reactive oxygen species. At the same time, glucose metabolism is suppressed. TRAP1-deficient cells also display strikingly enhanced invasiveness. TRAP1 interaction with and regulation of mitochondrial c-Src provide a mechanistic basis for these phenotypes. Taken together with the observation that TRAP1 expression is inversely correlated with tumor grade in several cancers, these data suggest that, in some settings, this mitochondrial molecular chaperone may act as a tumor suppressor.

Naive [CD8.sup.+] T cells rely upon oxidation of fatty acids as a primary source of energy. After antigen encounter, T cells shift to a glycolytic metabolism to sustain effector function. [...]

Purpose To determine the global metabolomic profile as measured in circulating plasma from surviving and non-surviving patients with community-acquired pneumonia (CAP) and sepsis. Methods Random, outcome-stratified case-control sample from a prospective study of 1,895 patients hospitalized with CAP and sepsis. Cases (n = 15) were adults who died before 90 days, and controls (n = 15) were adults who survived, matched on demographics, infection type, and procalcitonin. We determined the global metabolomic profile in the first emergency department blood sample using non-targeted mass-spectrometry. We derived metabolite-based prognostic models for 90-day mortality. We determined if metabolites stimulated cytokine production by differentiated Thp1 monocytes in vitro, and validated metabolite profiles in mouse liver and kidney homogenates at 8 h in cecal ligation and puncture (CLP) sepsis. Results We identified 423 small molecules, of which the relative levels of 70 (17 %) were different between survivors and non-survivors (p [less than or equal to] 0.05). Broad differences were present in pathways of oxidative stress, bile acid metabolism, and stress response. Metabolite-based prognostic models for 90-day survival performed modestly (AUC = 0.67, 95 % CI 0.48, 0.81). Five nucleic acid metabolites were greater in non-survivors (p [less than or equal to] 0.05). Of these, pseudouridine increased monocyte expression of TNF[alpha] and IL1[beta] versus control (p < 0.05). Pseudouridine was also increased in liver and kidney homogenates from CLP mice versus sham (p < 0.05 for both). Conclusions Although replication is required, we show the global metabolomic profile in plasma broadly differs between survivors and non-survivors of CAP and sepsis. Metabolite-based prognostic models had modest performance, though metabolites of oxidative stress may act as putative damage-associated molecular patterns., Author(s): Christopher W. Seymour [sup.1] [sup.2], Sachin Yende [sup.2] [sup.3], Melanie J. Scott [sup.2] [sup.4], John Pribis [sup.4], Robert P. Mohney [sup.5], Lauren N. Bell [sup.5], Yi-Fan Chen [sup.6], Brian [...]

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research., Understanding the role of genetic predispositions and their interaction with environmental factors in complex chronic diseases is key to the development of safe and efficient therapies, to diagnosis and to [...]

As part of an overall systems approach to generating highly accurate screening data across large numbers of compounds and biological targets, we have developed and implemented streamlined methods for purifying and quantitating compounds at various stages of the screening process, coupled with automated 'traditional' storage methods (DMSO, -20 [degrees]C). Specifically, all of the compounds in our druglike library are purified by LC/MS/ UV and are then controlled for identity and concentration in their respective DMSO stock solutions by chemiluminescent nitrogen detection (CLND)/evaporative light scattering detection (ELSD) and MS/UV. In addition, the compound--buffer solutions used in the various biological assays are quantitated by LC/UV/CLND to determine the concentration of compound actually present during screening. Our results show that LC/UV/CLND/ELSD/MS is a widely applicable method that can be used to purify, quantitate, and identify most small organic molecules from compound libraries. The LC/UV/CLND technique is a simple and sensitive method that can be easily and cost-effectively employed to rapidly determine the concentrations of even small amounts of any N-containing compound in aqueous solution. We present data to establish error limits for concentration determination that are well within the overall variability of the screening process. This study demonstrates that there is a significant difference between the predicted amount of soluble compound from stock DMSO solutions following dilution into assay buffer and the actual amount present in assay buffer solutions, even at the low concentrations employed for the assays. We also demonstrate that knowledge of the concentrations of compounds to which the biological target is exposed is critical for accurate potency determinations. Accurate potency values are in turn particularly important for drug discovery, for understanding structure--activity relationships, and for building useful empirical models of protein--ligand interactions. Our new understanding of relative solubility demonstrates that most, if not all, decisions that are made in early discovery are based upon missing or inaccurate information. Finally, we demonstrate that careful control of compound handling and concentration, coupled with accurate assay methods, allows the use of both positive and negative data in analyzing screening data sets for structure--activity relationships that determine potency and selectivity.