Everolimus decreases [U-13C]glucose utilization by pyruvate carboxylase in breast cancer cells in vitro and in vivo.

Reprogrammed metabolism is a hallmark of cancer, but notoriously difficult to target due to metabolic plasticity, especially in response to single metabolic interventions. Combining mTOR inhibitor everolimus and mitochondrial complex 1 inhibitor metformin results in metabolic synergy in in vitro models of triple-negative breast cancer. Here, we investigated whether the effect of this drug combination on tumor size is reflected in changes in tumor metabolism using [U-13C]glucose labeling in an MDA-MB-231 triple negative breast cancer xenograft model. The in vitro effects of everolimus and metformin treatment on oxidative phosphorylation and glycolysis reflected changes in 13C-labeling of metabolites in MDA-MB-231 cells. Treatment of MDA-MB-231 xenografts in SCID/Beige mice with everolimus resulted in slower tumor growth and reduced tumor size and tumor viability by 35%. Metformin treatment moderately inhibited tumor growth but did not enhance everolimus-induced effects. High serum levels of everolimus were reached, whereas levels of metformin were relatively low. Everolimus decreased TCA cycle metabolite labeling and inhibited pyruvate carboxylase activity. Metformin only caused a mild reduction in glycolytic metabolite labeling and did not affect pyruvate carboxylase activity or TCA cycle metabolite labeling. In conclusion, treatment with everolimus, but not metformin, decreased tumor size and viability. Furthermore, the efficacy of everolimus was reflected in reduced 13C-labeling of TCA cycle intermediates and reduced pyruvate carboxylase activity. By using in-depth analysis of drug-induced changes in glucose metabolism in combination with measurement of drug levels in tumor and plasma, effects of metabolically targeted drugs can be explained, and novel targets can be identified.

Development of targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry method for acyl-Coenzyme A covering short- to long-chain species in a single analytical run.

Acyl-CoAs play a significant role in numerous physiological and metabolic processes making it important to assess their concentration levels for evaluating metabolic health. Considering the important role of acyl-CoAs, it is crucial to develop an analytical method that can analyze these compounds. Due to the structural variations of acyl-CoAs, multiple analytical methods are often required for comprehensive analysis of these compounds, which increases complexity and the analysis time. In this study, we have developed a method using a zwitterionic HILIC column that enables the coverage of free CoA and short- to long-chain acyl-CoA species in one analytical run. Initially, we developed the method using an LC-QTOF instrument for the identification of acyl-CoA species and optimizing their chromatography. Later, a targeted HILIC-MS/MS method was created in scheduled multiple reaction monitoring mode using a QTRAP MS detector. The performance of the method was evaluated based on various parameters such as linearity, precision, recovery and matrix effect. This method was applied to identify the difference in acyl-CoA profiles in HepG2 cells cultured in different conditions. Our findings revealed an increase in levels of acetyl-CoA, medium- and long-chain acyl-CoA while a decrease in the profiles of free CoA in the starved state, indicating a clear alteration in the fatty acid oxidation process.

Kinetic data for modeling the dynamics of the enzymes involved in animal fatty acid synthesis.

The synthesis and modification of fatty acids (FAs) from carbohydrates are paramount for the production of lipids. Simultaneously, lipids are pivotal energy storage in human health. They are associated with various metabolic diseases and their production pathways are for instance candidate therapeutic targets for cancer treatments. The fatty acid de novo synthesis (FADNS) occurs in the cytoplasm, while the microsomal modification of fatty acids (MMFA) happens at the surface of the endoplasmic reticulum (ER). The kinetics and regulation of these complex processes involve several enzymes. In mammals, the main ones are the acetyl-CoA carboxylase (ACC), the fatty acid synthase (FAS), the very-long-chain fatty acid elongases (ELOVL 1-7), and the desaturases (delta family). Their mechanisms and expression in different organs have been studied for more than 50 years. However, modeling them in the context of complex metabolic pathways is still a challenge. Distinct modeling approaches can be implemented. Here, we focus on dynamic modeling using ordinary differential equations (ODEs) based on kinetic rate laws. This requires a combination of knowledge on the enzymatic mechanisms and their kinetics, as well as the interactions between the metabolites, and between enzymes and metabolites. In the present review, after recalling the modeling framework, we support the development of such a mathematical approach by reviewing the available kinetic information of the enzymes involved.

Inhibition of the succinyl dehydrogenase complex in acute myeloid leukemia leads to a lactate-fuelled respiratory metabolic vulnerability.

Metabolic programs can differ substantially across genetically distinct subtypes of acute myeloid leukemia (AML). These programs are not static entities but can change swiftly as a consequence of extracellular changes or in response to pathway-inhibiting drugs. Here, we uncover that AML patients with FLT3 internal tandem duplications (FLT3-ITD+) are characterized by a high expression of succinate-CoA ligases and high activity of mitochondrial electron transport chain (ETC) complex II, thereby driving high mitochondrial respiration activity linked to the Krebs cycle. While inhibition of ETC complex II enhances apoptosis in FLT3-ITD+ AML, cells also quickly adapt by importing lactate from the extracellular microenvironment. 13C3-labelled lactate metabolic flux analyses reveal that AML cells use lactate as a fuel for mitochondrial respiration. Inhibition of lactate transport by blocking Monocarboxylic Acid Transporter 1 (MCT1) strongly enhances sensitivity to ETC complex II inhibition in vitro as well as in vivo. Our study highlights a metabolic adaptability of cancer cells that can be exploited therapeutically.

Pyruvate Dehydrogenase Kinase Inhibition by Dichloroacetate in Melanoma Cells Unveils Metabolic Vulnerabilities.

Melanoma is characterized by high glucose uptake, partially mediated through elevated pyruvate dehydrogenase kinase (PDK), making PDK a potential treatment target in melanoma. We aimed to reduce glucose uptake in melanoma cell lines through PDK inhibitors dichloroacetate (DCA) and AZD7545 and through PDK knockdown, to inhibit cell growth and potentially unveil metabolic co-vulnerabilities resulting from PDK inhibition. MeWo cells were most sensitive to DCA, while SK-MEL-2 was the least sensitive, with IC50 values ranging from 13.3 to 27.0 mM. DCA strongly reduced PDH phosphorylation and increased the oxygen consumption rate:extracellular acidification rate (OCR:ECAR) ratio up to 6-fold. Knockdown of single PDK isoforms had similar effects on PDH phosphorylation and OCR:ECAR ratio as DCA but did not influence sensitivity to DCA. Growth inhibition by DCA was synergistic with the glutaminase inhibitor CB-839 (2- to 5-fold sensitization) and with diclofenac, known to inhibit monocarboxylate transporters (MCTs) (3- to 8-fold sensitization). CB-839 did not affect the OCR:ECAR response to DCA, whereas diclofenac strongly inhibited ECAR and further increased the OCR:ECAR ratio. We conclude that in melanoma cell lines, DCA reduces proliferation through reprogramming of cellular metabolism and synergizes with other metabolically targeted drugs.

Simultaneous Quantification of the Concentration and Carbon Isotopologue Distribution of Polar Metabolites in a Single Analysis by Gas Chromatography and Mass Spectrometry.

13C-isotope tracing is a frequently employed approach to study metabolic pathway activity. When combined with the subsequent quantification of absolute metabolite concentrations, this enables detailed characterization of the metabolome in biological specimens and facilitates computational time-resolved flux quantification. Classically, a 13C-isotopically labeled sample is required to quantify 13C-isotope enrichments and a second unlabeled sample for the quantification of metabolite concentrations. The rationale for a second unlabeled sample is that the current methods for metabolite quantification rely mostly on isotope dilution mass spectrometry (IDMS) and thus isotopically labeled internal standards are added to the unlabeled sample. This excludes the absolute quantification of metabolite concentrations in 13C-isotopically labeled samples. To address this issue, we have developed and validated a new strategy using an unlabeled internal standard to simultaneously quantify metabolite concentrations and 13C-isotope enrichments in a single 13C-labeled sample based on gas chromatography-mass spectrometry (GC/MS). The method was optimized for amino acids and citric acid cycle intermediates and was shown to have high analytical precision and accuracy. Metabolite concentrations could be quantified in small tissue samples (≥20 mg). Also, we applied the method on 13C-isotopically labeled mammalian cells treated with and without a metabolic inhibitor. We proved that we can quantify absolute metabolite concentrations and 13C-isotope enrichments in a single 13C-isotopically labeled sample.

Quantitative analysis of amino acid metabolism in liver cancer links glutamate excretion to nucleotide synthesis.

Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for in-depth analysis. We find that up to 30% of the glutamine is metabolized in the cytosol, primarily for nucleotide synthesis, producing cytosolic glutamate. We hypothesize that excreting glutamate helps the cell to increase the nucleotide synthesis rate to sustain growth. Indeed, we show experimentally that partial inhibition of glutamate excretion reduces cell growth. Our integrative approach thus links glutamine addiction to glutamate excretion in cancer and points toward potential drug targets.

Targeted Proteomics to Study Mitochondrial Biology.

Targeted mass spectrometry in the selected or parallel reaction monitoring (SRM or PRM) mode is a widely used methodology to quantify proteins based on so-called signature or proteotypic peptides. SRM has the advantage of being able to quantify a range of proteins in a single analysis, for example, to measure the level of enzymes comprising a biochemical pathway. In this chapter, we will detail how to set up an SRM assay on the example of the mitochondrial protein succinate dehydrogenase [ubiquinone] flavoprotein subunit (mouse UniProt-code Q8K2B3). First, we will outline the in silico assay design including the choice of peptides based on a range of properties. We will further delineate different quantification strategies and introduce the reader to LC-MS assay development including the selection of the optimal peptide charge state and fragment ions as well as a discussion of the dynamic range of detection. The chapter will close with an application from the area of mitochondrial biology related to the quantification of a set of proteins isolated from mouse liver mitochondria in a study on mitochondrial respiratory flux decline in aging mouse muscle.

Running wheel access fails to resolve impaired sustainable health in mice feeding a high fat sucrose diet.

Diet and physical activity are thought to affect sustainable metabolic health and survival. To improve understanding, we studied survival of mice feeding a low-fat (LF) or high-saturated fat/high sugar (HFS) diet, each with or without free running wheel (RW) access. Additionally several endocrine and metabolic health indices were assessed at 6, 12, 18 and 24 months of age. As expected, HFS feeding left-shifted survival curve of mice compared to LF feeding, and this was associated with increased energy intake and increased (visceral/total) adiposity, liver triglycerides, and increased plasma cholesterol, corticosterone, HOMA-IR, and lowered adiponectin levels. Several of these health parameters improved (transiently) by RW access in HFS and LF fed mice (i.e., HOMA-IR, plasma corticosterone), others however deteriorated (transiently) by RW access only in HFS-fed mice (i.e., body adiposity, plasma resistin, and free cholesterol levels). Apart from these multiple and sometimes diverging health effects of RW access, RW access did not affect survival curves. Important to note, voluntary RW activity declined with age, but this effect was most pronounced in the HFS fed mice. These results thus challenge the hypothesis that voluntary wheel running can counteract HFS-induced deterioration of survival and metabolic health.

Cofactors revisited - Predicting the impact of flavoprotein-related diseases on a genome scale.

Flavin adenine dinucleotide (FAD) and its precursor flavin mononucleotide (FMN) are redox cofactors that are required for the activity of more than hundred human enzymes. Mutations in the genes encoding these proteins cause severe phenotypes, including a lack of energy supply and accumulation of toxic intermediates. Ideally, patients should be diagnosed before they show symptoms so that treatment and/or preventive care can start immediately. This can be achieved by standardized newborn screening tests. However, many of the flavin-related diseases lack appropriate biomarker profiles. Genome-scale metabolic models can aid in biomarker research by predicting altered profiles of potential biomarkers. Unfortunately, current models, including the most recent human metabolic reconstructions Recon and HMR, typically treat enzyme-bound flavins incorrectly as free metabolites. This in turn leads to artificial degrees of freedom in pathways that are strictly coupled. Here, we present a reconstruction of human metabolism with a curated and extended flavoproteome. To illustrate the functional consequences, we show that simulations with the curated model - unlike simulations with earlier Recon versions - correctly predict the metabolic impact of multiple-acyl-CoA-dehydrogenase deficiency as well as of systemic flavin-depletion. Moreover, simulations with the new model allowed us to identify a larger number of biomarkers in flavoproteome-related diseases, without loss of accuracy. We conclude that adequate inclusion of cofactors in constraint-based modelling contributes to higher precision in computational predictions.

Targeting pathogen metabolism without collateral damage to the host.

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this 'network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells.

Malnutrition-associated liver steatosis and ATP depletion is caused by peroxisomal and mitochondrial dysfunction.

BACKGROUND & AIMS: Severe malnutrition in young children is associated with signs of hepatic dysfunction such as steatosis and hypoalbuminemia, but its etiology is unknown. Peroxisomes and mitochondria play key roles in various hepatic metabolic functions including lipid metabolism and energy production. To investigate the involvement of these organelles in the mechanisms underlying malnutrition-induced hepatic dysfunction we developed a rat model of malnutrition. METHODS: Weanling rats were placed on a low protein or control diet (5% or 20% of calories from protein, respectively) for four weeks. Peroxisomal and mitochondrial structural features were characterized using immunofluorescence and electron microscopy. Mitochondrial function was assessed using high-resolution respirometry. A novel targeted quantitative proteomics method was applied to analyze 47 mitochondrial proteins involved in oxidative phosphorylation, tricarboxylic acid cycle and fatty acid ß-oxidation pathways. RESULTS: Low protein diet-fed rats developed hypoalbuminemia and hepatic steatosis, consistent with the human phenotype. Hepatic peroxisome content was decreased and metabolomic analysis indicated peroxisomal dysfunction. This was followed by changes in mitochondrial ultrastructure and increased mitochondrial content. Mitochondrial function was impaired due to multiple defects affecting respiratory chain complex I and IV, pyruvate uptake and several ß-oxidation enzymes, leading to strongly reduced hepatic ATP levels. Fenofibrate supplementation restored hepatic peroxisome abundance and increased mitochondrial ß-oxidation capacity, resulting in reduced steatosis and normalization of ATP and plasma albumin levels. CONCLUSIONS: Malnutrition leads to severe impairments in hepatic peroxisomal and mitochondrial function, and hepatic metabolic dysfunction. We discuss the potential future implications of our findings for the clinical management of malnourished children. LAY SUMMARY: Severe malnutrition in children is associated with metabolic disturbances that are poorly understood. In order to study this further, we developed a malnutrition animal model and found that severe malnutrition leads to an impaired function of liver mitochondria which are essential for energy production and a loss of peroxisomes, which are important for normal liver metabolic function.

Drug target identification through systems biology.

To rationalise drug target selection, we should understand the role of putative targets in biological pathways quantitatively. We review here how experimental and computational network-based approaches can aid more rational drug target selection and illustrate this with results obtained for microbes and for cancer. Comparison of the drug response of biochemical networks in target cells and (healthy) host cells can reveal network-selective targets.

Short-Chain Fatty Acids Protect Against High-Fat Diet-Induced Obesity via a PPARγ-Dependent Switch From Lipogenesis to Fat Oxidation.

Short-chain fatty acids (SCFAs) are the main products of dietary fiber fermentation and are believed to drive the fiber-related prevention of the metabolic syndrome. Here we show that dietary SCFAs induce a peroxisome proliferator-activated receptor-γ (PPARγ)-dependent switch from lipid synthesis to utilization. Dietary SCFA supplementation prevented and reversed high-fat diet-induced metabolic abnormalities in mice by decreasing PPARγ expression and activity. This increased the expression of mitochondrial uncoupling protein 2 and raised the AMP-to-ATP ratio, thereby stimulating oxidative metabolism in liver and adipose tissue via AMPK. The SCFA-induced reduction in body weight and stimulation of insulin sensitivity were absent in mice with adipose-specific disruption of PPARγ. Similarly, SCFA-induced reduction of hepatic steatosis was absent in mice lacking hepatic PPARγ. These results demonstrate that adipose and hepatic PPARγ are critical mediators of the beneficial effects of SCFAs on the metabolic syndrome, with clearly distinct and complementary roles. Our findings indicate that SCFAs may be used therapeutically as cheap and selective PPARγ modulators.

A kinetic model of catabolic adaptation and protein reprofiling in Saccharomyces cerevisiae during temperature shifts.

In this article, we aim to find an explanation for the surprisingly thin line, with regard to temperature, between cell growth, growth arrest and ultimately loss of cell viability. To this end, we used an integrative approach including both experimental and modelling work. We measured the short- and long-term effects of increases in growth temperature from 28 °C to 37, 39, 41, 42 or 43 °C on the central metabolism of Saccharomyces cerevisiae. Based on the experimental data, we developed a kinetic mathematical model that describes the metabolic and energetic changes in growing bakers' yeast when exposed to a specific temperature upshift. The model includes the temperature dependence of core energy-conserving pathways, trehalose synthesis, protein synthesis and proteolysis. Because our model focuses on protein synthesis and degradation, the net result of which is important in determining the cell's capacity to grow, the model includes growth, i.e. glucose is consumed and biomass and adenosine nucleotide cofactors are produced. The model reproduces both the observed initial metabolic response and the subsequent relaxation into a new steady-state, compatible with the new ambient temperature. In addition, it shows that the energy consumption for proteome reprofiling may be a major determinant of heat-induced growth arrest and subsequent recovery or cell death.

Dissecting the catalytic mechanism of Trypanosoma brucei trypanothione synthetase by kinetic analysis and computational modeling.

In pathogenic trypanosomes, trypanothione synthetase (TryS) catalyzes the synthesis of both glutathionylspermidine (Gsp) and trypanothione (bis(glutathionyl)spermidine (T(SH)2)). Here we present a thorough kinetic analysis of Trypanosoma brucei TryS in a newly developed phosphate buffer system at pH 7.0 and 37 °C, mimicking the physiological environment of the enzyme in the cytosol of bloodstream parasites. Under these conditions, TryS displays Km values for GSH, ATP, spermidine, and Gsp of 34, 18, 687, and 32 µm, respectively, as well as Ki values for GSH and T(SH)2 of 1 mm and 360 µm, respectively. As Gsp hydrolysis has a Km value of 5.6 mm, the in vivo amidase activity is probably negligible. To obtain deeper insight in the molecular mechanism of TryS, we have formulated alternative kinetic models, with elementary reaction steps represented by linear kinetic equations. The model parameters were fitted to the extensive matrix of steady-state data obtained for different substrate/product combinations under the in vivo-like conditions. The best model describes the full kinetic profile and is able to predict time course data that were not used for fitting. This system's biology approach to enzyme kinetics led us to conclude that (i) TryS follows a ter-reactant mechanism, (ii) the intermediate Gsp dissociates from the enzyme between the two catalytic steps, and (iii) T(SH)2 inhibits the enzyme by remaining bound at its product site and, as does the inhibitory GSH, by binding to the activated enzyme complex. The newly detected concerted substrate and product inhibition suggests that TryS activity is tightly regulated.

A new regulatory principle for in vivo biochemistry: pleiotropic low affinity regulation by the adenine nucleotides--illustrated for the glycolytic enzymes of Saccharomyces cerevisiae.

Enzymology tends to focus on highly specific effects of substrates, allosteric modifiers, and products occurring at low concentrations, because these are most informative about the enzyme's catalytic mechanism. We hypothesized that at relatively high in vivo concentrations, important molecular monitors of the state of living cells, such as ATP, affect multiple enzymes of the former and that these interactions have gone unnoticed in enzymology. We test this hypothesis in terms of the effect that ATP, ADP, and AMP might have on the major free-energy delivering pathway of the yeast Saccharomyces cerevisiae. Assaying cell-free extracts, we collected a comprehensive set of quantitative kinetic data concerning the enzymes of the glycolytic and the ethanol fermentation pathways. We determined systematically the extent to which the enzyme activities depend on the concentrations of the adenine nucleotides. We found that the effects of the adenine nucleotides on enzymes catalysing reactions in which they are not directly involved as substrate or product, are substantial. This includes effects on the Michaelis-Menten constants, adding new perspective on these, 100 years after their introduction.

Proliferating bloodstream-form Trypanosoma brucei use a negligible part of consumed glucose for anabolic processes.

Our quantitative knowledge of carbon fluxes in the long slender bloodstream form (BSF) Trypanosoma brucei is mainly based on non-proliferating parasites, isolated from laboratory animals and kept in buffers. In this paper we present a carbon balance for exponentially growing bloodstream form trypanosomes. The cells grew with a doubling time of 5.3h, contained 46 µ mol of carbon (10(8) cells)(-1) and had a glucose consumption flux of 160 nmol min(-1) (10(8) cells)(-1). The molar ratio of pyruvate excreted versus glucose consumed was 2.1. Furthermore, analysis of the (13)C label distribution in pyruvate in (13)C-glucose incubations of exponentially growing trypanosomes showed that glucose was the sole substrate for pyruvate production. We conclude that the glucose metabolised in glycolysis was hardly, if at all, used for biosynthetic processes. Carbon flux through glycolysis in exponentially growing trypanosomes was 10 times higher than the incorporation of carbon into biomass. This biosynthetic carbon is derived from other precursors present in the nutrient rich growth medium. Furthermore, we found that the glycolytic flux was unaltered when the culture went into stationary phase, suggesting that most of the ATP produced in glycolysis is used for processes other than growth.

The fluxes through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscriptional levels.

Metabolic fluxes may be regulated "hierarchically," e.g., by changes of gene expression that adjust enzyme capacities (V(max)) and/or "metabolically" by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the approximately 10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50-20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75-100% of the regulation of protein levels.

Metabolic control analysis to identify optimal drug targets.

This chapter describes the basic principles of Metabolic Control Analysis (MCA) which is a quantitative methodology to evaluate the importance and relative contribution of individual metabolic steps in the overall functioning of a particular system. The control on the flux through a metabolic pathway or subsystem can be quantified by the control coefficients of the individual enzymes or components which reflects the extent to which the component is rate-limiting. The perturbation of an individual step is measured by its elasticity coefficient. The effect of perturbation of a single step on the entire pathway or subsystem is, in turn, measured by the response coefficient. Differential control analysis can be used to compare flux through a single metabolic pathway in a pathogen with the same pathway in its host to identify uniquely vulnerable steps with the greatest potential for specifically inhibiting flux through the pathogen metabolic pathway. The utility of this methodology is illustrated with the glycolysis in Trypanosomes and with oncogenic signaling.