Stacey N. Reinke

A glycolytic burst drives glucose induction of global histone acetylation by picNuA4 and SAGA

Little is known about what enzyme complexes or mechanisms control global lysine acetylation in the amino-terminal tails of the histones. Here, we show that glucose induces overall acetylation of H3 K9, 18, 27 and H4 K5, 8, 12 in quiescent yeast cells mainly by stimulating two KATs, Gcn5 and Esa1. Genetic and pharmacological perturbation of carbon metabolism, combined with 1H-NMR metabolic profiling, revealed that glucose induction of KAT activity directly depends on increased glucose catabolism. Glucose-inducible Esa1 and Gcn5 activities predominantly reside in the picNuA4 and SAGA complexes, respectively, and act on chromatin by an untargeted mechanism. We conclude that direct metabolic regulation of globally acting KATs can be a potent driving force for reconfiguration of overall histone acetylation in response to a physiological cue.

Ubiquinone-binding site mutations in the Saccharomyces cerevisiae succinate dehydrogenase generate superoxide and lead to the accumulation of succinate

The mitochondrial succinate dehydrogenase (SDH) is an essential component of the electron transport chain and of the tricarboxylic acid cycle. Also known as complex II, this tetrameric enzyme catalyzes the oxidation of succinate to fumarate and reduces ubiquinone. Mutations in the human SDHB, SDHC, and SDHD genes are tumorigenic, leading to the development of several types of tumors, including paraganglioma and pheochromocytoma. The mechanisms linking SDH mutations to oncogenesis are still unclear. In this work, we used the yeast SDH to investigate the molecular and catalytic effects of tumorigenic or related mutations. We mutated Arg47 of the Sdh3p subunit to Cys, Glu, and Lys and Asp88 of the Sdh4p subunit to Asn, Glu, and Lys. Both Arg47 and Asp88 are conserved residues, and Arg47 is a known site of cancer causing mutations in humans. All of the mutants examined have reduced ubiquinone reductase activities. The SDH3 R47K, SDH4 D88E, and SDH4 D88N mutants are sensitive to hyperoxia and paraquat and have elevated rates of superoxide production in vitro and in vivo.We also observed the accumulation and secretion of succinate. Succinate can inhibit prolyl hydroxylase enzymes, which initiate a proliferative response through the activation of hypoxia-inducible factor 1α. We suggest that SDH mutations can promote tumor formation by contributing to both reactive oxygen species production and to a proliferative response normally induced by hypoxia via the accumulation of succinate.

Caenorhabditis elegans diet significantly affects metabolic profile, mitochondrial DNA levels, lifespan and brood size.

Diet can have profound effects on an organisms health. Metabolic studies offer an effective way to measure and understand the physiological effects of diet or disease. The metabolome is very sensitive to dietary, lifestyle and genetic changes. Caenorhabditis elegans, a soil nematode, is an attractive model organism for metabolic studies because of the ease with which genetic and environmental factors can be controlled. In this work, we report significant effects of diet, mutation and RNA interference on the C.elegans metabolome. Two strains of Escherichia coli, OP50 and HT115 are commonly employed as food sources for maintaining and culturing the nematode. We studied the metabolic and phenotypic effects of culturing wild-type and mutant worms on these two strains of E. coli. We report significant effects of diet on metabolic profile, on mitochondrial DNA copy number and on phenotype. The dietary effects we report are similar in magnitude to the effects of mutations or RNA interference-mediated gene suppression. This is the first critical evaluation of the physiological and metabolic effects on C.elegans of two commonly used culture conditions.

Metabolomic profiling in multiple sclerosis: insights into biomarkers and pathogenesis

Metabolomics enables the provision of sensitive bio-markers of disease. We performed 800 MHz 1H-nuclear magnetic resonance (NMR) spectroscopic analyses of cerebrospinal fluid (CSF) specimens to identify biomarkers of multiple sclerosis (MS), yielding reproducible detection of 15 metabolites from MS (n=15) and non-MS (n=17) patients. Mean levels of choline, myo-inositol and threonate were increased, whereas 3-hydroxybutyrate, citrate, phenylalanine, 2-hydroxyisovalerate and mannose were decreased in MS-derived CSF (p<0.05), suggesting alterations to energy and phospholipid metabolism. Multivariate hierarchal cluster analysis indicated a high correlation within the metabolite profiles, significantly clustering samples into the two clinical groups, which was corroborated using principal components analysis. CSF metabolomics have the capacity to yield quantitative biomarkers and insights into the pathogenesis of MS.

Mutations in the Saccharomyces cerevisiae succinate dehydrogenase result in distinct metabolic phenotypes revealed through (1)H NMR-based metabolic footprinting.

Metabolomics is a powerful method of examining the intricate connections between mutations, metabolism, and disease. Metabolic footprinting examines the extracellular metabolome or exometabolome. We employed NMR-based metabolic footprinting and multivariate statistical analysis to examine a yeast model of mitochondrial dysfunction. Succinate dehydrogenase (SDH) is a component of both the tricarboxylic acid cycle and the mitochondrial respiratory chain. Mutations in the human SDH are linked to a variety of cancers or neurodegenerative disorders, highlighting the genotype/phenotype complexity associated with SDH dysfunction. To gain insight into the underlying global metabolic consequences of SDH dysfunction, we examined the metabolic footprints of SDH3 and SDH4 mutants. We identified and quantified 36 metabolites in the exometabolome. Our results indicate that SDH mutations cause significant alterations to several areas of yeast metabolism. Multivariate statistical analysis allowed us to discriminate between the different metabotypes of individual mutants, including mutants that were phenotypically indistinguishable. Metabotypes were highly correlated to mutant growth yields, suggesting that the characterization of metabotypes offers a rapid means of investigating the phenotype of a new mutation. Our study provides novel insight into the metabolic effects of SDH dysfunction and highlights the effectiveness of metabolic footprinting for examining complex disorders, such as mitochondrial diseases.

Formate can differentiate between hyperhomocysteinemia due to impaired remethylation and impaired transsulfuration.

Formate can differentiate between hyperhomocysteinemia due to impaired remethylation and impaired transsulfuration. Am J Physiol Endocrinol Metab 301: E000-E000, 2011. First published September 20, 2011; 10.1152/ajpendo.00345.2011.-We carried out a (1)H-NMR metabolomic analysis of sera from vitamin B(12)-deficient rats. In addition to the expected increases in methylmalonate and homocysteine (Hcy), we observed an approximately sevenfold increase in formate levels, from 64 μM in control rats to 402 μM in vitamin B(12)-deficient rats. Urinary formate was also elevated. This elevation of formate could be attributed to impaired one-carbon metabolism since formate is assimilated into the one-carbon pool by incorporation into 10-formyl-THF via the enzyme 10-formyl-THF synthase. Both plasma and urinary formate were also increased in folate-deficient rats. Hcy was elevated in both the vitamin B(12)- and folate-deficient rats. Although plasma Hcy was also elevated, plasma formate was unaffected in vitamin B(6)-deficient rats (impaired transsulfuration pathway). These results were in accord with a mathematical model of folate metabolism, which predicted that reduction in methionine synthase activity would cause increased formate levels, whereas reduced cystathionine β-synthase activity would not. Our data indicate that formate provides a novel window into cellular folate metabolism, that elevated formate can be a useful indicator of deranged one-carbon metabolism and can be used to discriminate between the hyperhomocysteinemia caused by defects in the remethylation and transsulfuration pathways.

Metabolomics analysis identifies different metabotypes of asthma severity

In this study, we sought to determine whether asthma has a metabolic profile and whether this profile is related to disease severity. We characterised the serum from 22 healthy individuals and 54 asthmatics (12 mild, 20 moderate, 22 severe) using liquid chromatography–high-resolution mass spectrometry-based metabolomics. Selected metabolites were confirmed by targeted mass spectrometry assays of eicosanoids, sphingolipids and free fatty acids. We conclusively identified 66 metabolites; 15 were significantly altered with asthma (p≤0.05). Levels of dehydroepiandrosterone sulfate, cortisone, cortisol, prolylhydroxyproline, pipecolate and N-palmitoyltaurine correlated significantly (p<0.05) with inhaled corticosteroid dose, and were further shifted in individuals treated with oral corticosteroids. Oleoylethanolamide increased with asthma severity independently of steroid treatment (p<0.001). Multivariate analysis revealed two patterns: 1) a mean difference between controls and patients with mild asthma (p=0.025), and 2) a mean difference between patients with severe asthma and all other groups (p=1.7×10−4). Metabolic shifts in mild asthma, relative to controls, were associated with exogenous metabolites (e.g. dietary lipids), while those in moderate and severe asthma (e.g. oleoylethanolamide, sphingosine-1-phosphate, N-palmitoyltaurine) were postulated to be involved in activating the transient receptor potential vanilloid type 1 (TRPV1) receptor, driving TRPV1-dependent pathogenesis in asthma. Our findings suggest that asthma is characterised by a modest systemic metabolic shift in a disease severity-dependent manner, and that steroid treatment significantly affects metabolism. Mild asthma is metabolically distinct from both moderate and severe asthma, and steroid treatment affects metabolism http://ow.ly/EHo7306DwmN

Metagenomic and Metabolomic Characterization of Rabies Encephalitis: New Insights into the Treatment of an Ancient Disease

Rabies virus (RV) infection is a fatal nervous system disorder. We describe a patient who died of rabies despite a neuroprotective intervention. Neuropathology showed neuronal loss with abundant RV antigen, genome, and Negri bodies, accompanied by intense neuroinflammation, including by CD8(+) T lymphocyte infiltrates. Deep sequencing and real-time reverse-transcription polymerase chain reaction revealed RNA encoding a bat RV strain together with inflammatory gene induction. RV-infected brain demonstrated reduced neuronal metabolites with an anaerobic metabolic profile by nuclear magnetic resonance (NMR) spectroscopy. These multiplatform studies highlight the extent of ongoing viral replication coupled with inflammation in treated rabies, indicative of a neurological immune reconstitution inflammatory syndrome.

Development of a Liquid Chromatography–High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition

High-resolution mass spectrometry (HRMS)-based metabolomics approaches have made significant advances. However, metabolite identification is still a major challenge with significant bottleneck in translating metabolomics data into biological context. In the current study, a liquid chromatography (LC)-HRMS metabolomics method was developed using an all ion fragmentation (AIF) acquisition approach. To increase the specificity in metabolite annotation, four criteria were considered: (i) accurate mass (AM), (ii) retention time (RT), (iii) MS/MS spectrum, and (iv) product/precursor ion intensity ratios. We constructed an in-house mass spectral library of 408 metabolites containing AMRT and MS/MS spectra information at four collision energies. The percent relative standard deviations between ion ratios of a metabolite in an analytical standard vs sample matrix were used as an additional metric for establishing metabolite identity. A data processing method for targeted metabolite screening was then created, merging m/z, RT, MS/MS, and ion ratio information for each of the 413 metabolites. In the data processing method, the precursor ion and product ion were considered as the quantifier and qualifier ion, respectively. We also included a scheme to distinguish coeluting isobaric compounds by selecting a specific product ion as the quantifier ion instead of the precursor ion. An advantage of the current AIF approach is the concurrent collection of full scan data, enabling identification of metabolites not included in the database. Our data acquisition strategy enables a simultaneous mixture of database-dependent targeted and nontargeted metabolomics in combination with improved accuracy in metabolite identification, increasing the quality of the biological information acquired in a metabolomics experiment.

The effect of haemolysis on the metabolomic profile of umbilical cord blood

OBJECTIVES Metabolomics is defined as the comprehensive study of all low molecular weight biochemicals, (metabolites) present in an organism. Using a systems biology approach, metabolomics in umbilical cord blood (UCB) may offer insight into many perinatal disease processes by uniquely detecting rapid biochemical pathway alterations. In vitro haemolysis is a common technical problem affecting UCB sampling in the delivery room, and can hamper metabolomic analysis. The extent of metabolomic alteration which occurs in haemolysed samples is unknown. DESIGN AND METHODS Visual haemolysis was designated by the laboratory technician using a standardised haemolysis index colour chart. The metabolomic profile of haemolysed and non-haemolysed UCB serum samples from 69 healthy term infants was compared using both (1)H-NMR and targeted DI and LC-MS/MS approach. RESULTS We identified 43 metabolites that are significantly altered in visually haemolysed UCB samples, acylcarnitines (n=2), glycerophospholipids (n=23), sphingolipids (n=7), sugars (n=3), amino acids (n=4) and Krebs cycle intermediates (n=4). CONCLUSION This information will be useful for researchers in the field of neonatal metabolomics to avoid false findings in the presence of haemolysis, to ensure reproducible and credible results.