Metabolic reprogramming driven by EZH2 inhibition depends on cell-matrix interactions.

EZH2 (Enhancer of Zeste Homolog 2), a subunit of Polycomb Repressive Complex 2 (PRC2), catalyzes the trimethylation of histone H3 at lysine 27 (H3K27me3), which represses expression of genes. It also has PRC2-independent functions, including transcriptional coactivation of oncogenes, and is frequently overexpressed in lung cancers. Clinically, EZH2 inhibition can be achieved with the FDA-approved drug EPZ-6438 (tazemetostat). To realize the full potential of EZH2 blockade, it is critical to understand how cell-cell/cell-matrix interactions present in 3D tissue and cell culture systems influences this blockade in terms of growth-related metabolic functions. Here, we show that EZH2 suppression reduced growth of human lung adenocarcinoma A549 cells in 2D cultures but stimulated growth in 3D cultures. To understand the metabolic underpinnings, we employed [13C6]-glucose stable isotope-resolved metabolomics to determine the effect of EZH2 suppression on metabolic networks in 2D versus 3D A549 cultures. The Krebs cycle, neoribogenesis, γ-aminobutyrate metabolism, and salvage synthesis of purine nucleotides were activated by EZH2 suppression in 3D spheroids but not in 2D cells, consistent with the growth effect. Using simultaneous 2H7-glucose + 13C5,15N2-Gln tracers and EPZ-6438 inhibition of H3 trimethylation, we delineated the effects on the Krebs cycle, γ-aminobutyrate metabolism, gluconeogenesis, and purine salvage to be PRC2-dependent. Furthermore, the growth/metabolic effects differed for mouse Matrigel versus self-produced A549 extracellular matrix. Thus, our findings highlight the importance of the presence and nature of extracellular matrix in studying the function of EZH2 and its inhibitors in cancer cells for modeling the in vivo outcomes.

Stable isotope-resolved metabolomics analyses of metabolic phenotypes reveal variable glutamine metabolism in different patient-derived models of non-small cell lung cancer from a single patient.

INTRODUCTION: Stable isotope tracers have been increasingly used in preclinical cancer model systems, including cell culture and mouse xenografts, to probe the altered metabolism of a variety of cancers, such as accelerated glycolysis and glutaminolysis and generation of oncometabolites. Comparatively little has been reported on the fidelity of the different preclinical model systems in recapitulating the aberrant metabolism of tumors. OBJECTIVES: We have been developing several different experimental model systems for systems biochemistry analyses of non-small cell lung cancer (NSCLC1) using patient-derived tissues to evaluate appropriate models for metabolic and phenotypic analyses. METHODS: To address the issue of fidelity, we have carried out a detailed Stable Isotope-Resolved Metabolomics study of freshly resected tissue slices, mouse patient derived xenografts (PDXs), and cells derived from a single patient using both 13C6-glucose and 13C5,15N2-glutamine tracers. RESULTS: Although we found similar glucose metabolism in the three models, glutamine utilization was markedly higher in the isolated cell culture and in cell culture-derived xenografts compared with the primary cancer tissue or direct tissue xenografts (PDX). CONCLUSIONS: This suggests that caution is needed in interpreting cancer biochemistry using patient-derived cancer cells in vitro or in xenografts, even at very early passage, and that direct analysis of patient derived tissue slices provides the optimal model for ex vivo metabolomics. Further research is needed to determine the generality of these observations.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action.

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.

NMR-based isotope editing, chemoselection and isotopomer distribution analysis in stable isotope resolved metabolomics.

NMR is a very powerful tool for identifying and quantifying compounds within complex mixtures without the need for individual standards or chromatographic separation. Stable Isotope Resolved Metabolomics (or SIRM) is an approach to following the fate of individual atoms from precursors through metabolic transformation, producing an atom-resolved metabolic fate map. However, extracts of cells or tissue give rise to very complex NMR spectra. While multidimensional NMR experiments may partially overcome the spectral overlap problem, additional tools may be needed to determine site-specific isotopomer distributions. NMR is especially powerful by virtue of its isotope editing capabilities using NMR active nuclei such as 13C, 15N, 19F and 31P to select molecules containing just these atoms in a complex mixture, and provide direct information about which atoms are present in identified compounds and their relative abundances. The isotope-editing capability of NMR can also be employed to select for those compounds that have been selectively derivatized with an NMR-active stable isotope at particular functional groups, leading to considerable spectral simplification. Here we review isotope analysis by NMR, and methods of chemoselection both for spectral simplification, and for enhanced isotopomer analysis.

Stable Isotope-Resolved Metabolomics Studies on Corticosteroid-Induced PC12 Cells: A Strategy for Evaluating Glucose Catabolism in an in Vitro Model of Depression.

Depression is a common psychopathological state or mood disorder syndrome. The serious risks to human life and the inadequacy of the existing antidepressant drugs have driven us to understand the pathogenesis of depression from a new perspective. Our research group has found disturbances in glucose catabolism in both depression and nephrotic syndrome. What are the specific metabolic pathways and specificities of glucose catabolism disorders caused by depression? To address the above scientific questions, we creatively combined traditional metabolomics technology with stable isotope-resolved metabolomics to research the glucose catabolism of the corticosterone-induced PC12 cell damage model and the adriamycin-induced glomerular podocyte damage model. The results showed an increased flux of pyruvate metabolism in depression. The increased flux of pyruvate metabolism led to an activation of gluconeogenesis in depression. The disturbed upstream metabolism of succinate caused the tricarboxylic acid cycle (TCA cycle) to be blocked in depression. In addition, there were metabolic disturbances in the purine metabolism and pentose phosphate pathways in depression. Compared with nephrotic syndrome, pyruvate metabolism, the TCA cycle, and gluconeogenesis metabolism in depression were specific. The metabolic pathways researched above are likely to be important targets for the efficacy of antidepressants.

Stable Isotope-Resolved Metabolomics Reveals the Abnormal Brain Glucose Catabolism in Depression Based on Chronic Unpredictable Mild Stress Rats.

The severe harm of depression to human life has attracted great attention to neurologists, but its pathogenesis is extremely complicated and has not yet been fully elaborated. Here, we provided a new strategy for revealing the specific pathways of abnormal brain glucose catabolism in depression, based on the supply of energy substrates and the evaluation of the mitochondrial structure and function. By using stable isotope-resolved metabolomics, we discovered that the tricarboxylic acid cycle (TCA cycle) is blocked and gluconeogenesis is abnormally activated in chronic unpredictable mild stress (CUMS) rats. In addition, our results showed an interesting phenomenon that the brain attempted to activate all possible metabolic enzymes in energy-producing pathways, but CUMS rats still exhibited a low TCA cycle activity due to impaired mitochondria. Depression caused the mitochondrial structure and function to be impaired and then led to abnormal brain glucose catabolism. The combination of the stable isotope-resolved metabolomics and mitochondrial structure and function analysis can accurately clarify the mechanism of depression. The mitochondrial pyruvate carrier and acetyl-CoA may be the key targets for depression treatment. The strategy provides a unique insight for exploring the mechanism of depression, the discovery of new targets, and the development of ideal novel antidepressants. Data are available via ProteomeXchange with identifier PXD025548.

Inhibiting PHGDH with NCT-503 reroutes glucose-derived carbons into the TCA cycle, independently of its on-target effect.

The small-molecule inhibitor of phosphoglycerate dehydrogenase, NCT-503, reduces incorporation of glucose-derived carbons into serine in vitro. Here we describe an off-target effect of NCT-503 in neuroblastoma cell lines expressing divergent phosphoglycerate dehydrogenase (PHGDH) levels and single-cell clones with CRISPR-Cas9-directed PHGDH knockout or their respective wildtype controls. NCT-503 treatment strongly reduced synthesis of glucose-derived citrate in all cell models investigated compared to the inactive drug control and independent of PHGDH expression level. Incorporation of glucose-derived carbons entering the TCA cycle via pyruvate carboxylase was enhanced by NCT-503 treatment. The activity of citrate synthase was not altered by NCT-503 treatment. We also detected no change in the thermal stabilisation of citrate synthase in cellular thermal shift assays from NCT-503-treated cells. Thus, the direct cause of the observed off-target effect remains enigmatic. Our findings highlight off-target potential within a metabolic assessment of carbon usage in cells treated with the small-molecule inhibitor, NCT-503.

De novo synthesis of serine and glycine fuels purine nucleotide biosynthesis in human lung cancer tissues.

Nucleotide synthesis is essential to proliferating cells, but the preferred precursors for de novo biosynthesis are not defined in human cancer tissues. We have employed multiplexed stable isotope-resolved metabolomics to track the metabolism of [13C6]glucose, D2-glycine, [13C2]glycine, and D3-serine into purine nucleotides in freshly resected cancerous and matched noncancerous lung tissues from nonsmall cell lung cancer (NSCLC) patients, and we compared the metabolism with established NSCLC PC9 and A549 cell lines in vitro Surprisingly, [13C6]glucose was the best carbon source for purine synthesis in human NSCLC tissues, in contrast to the noncancerous lung tissues from the same patient, which showed lower mitotic indices and MYC expression. We also observed that D3-Ser was preferentially incorporated into purine rings over D2-glycine in both tissues and cell lines. MYC suppression attenuated [13C6]glucose, D3-serine, and [13C2]glycine incorporation into purines and reduced proliferation in PC9 but not in A549 cells. Using detailed kinetic modeling, we showed that the preferred use of glucose as a carbon source for purine ring synthesis in NSCLC tissues involves cytoplasmic activation/compartmentation of the glucose-to-serine pathway and enhanced reversed one-carbon fluxes that attenuate exogenous serine incorporation into purines. Our findings also indicate that the substrate for de novo nucleotide synthesis differs profoundly between cancer cell lines and fresh human lung cancer tissues; the latter preferred glucose to exogenous serine or glycine but not the former. This distinction in substrate utilization in purine synthesis in human cancer tissues should be considered when targeting one-carbon metabolism for cancer therapy.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks.

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Inhibition of Anaplerotic Glutaminolysis Underlies Selenite Toxicity in Human Lung Cancer.

Large clinical trials and model systems studies suggest that the chemical form of selenium dictates chemopreventive and chemotherapeutic efficacy. Selenite induces excess ROS production, which mediates autophagy and eventual cell death in non-small cell lung cancer adenocarcinoma A549 cells. As the mechanisms underlying these phenotypic effects are unclear, the clinical relevance of selenite for cancer therapy remains to be determined. The authors' previous stable isotope-resolved metabolomics and gene expression analysis showed that selenite disrupts glycolysis, the Krebs cycle, and polyamine metabolism in A549 cells, potentially through perturbed glutaminolysis, a vital anaplerotic process for proliferation of many cancer cells. Herein, the role of the glutaminolytic enzyme glutaminase 1 (GLS1) in selenite's toxicity in A549 cells and in patient-derived lung cancer tissues is investigated. Using [13 C6 ]-glucose and [13 C5 ,15 N2 ]-glutamine tracers, selenite's action on metabolic networks is determined. Selenite inhibits glutaminolysis and glutathione synthesis by suppressing GLS1 expression, and blocks the Krebs cycle, but transiently activates pyruvate carboxylase activity. Glutamate supplementation partially rescues these anti-proliferative and oxidative stress activities. Similar metabolic perturbations and necrosis are observed in selenite-treated human patients' cancerous lung tissues ex vivo. The results support the hypothesis that GLS1 suppression mediates part of the anti-cancer activity of selenite both in vitro and ex vivo.

Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues.

BACKGROUND: Stable isotope tracing can follow individual atoms through metabolic transformations through the detection of the incorporation of stable isotope within metabolites. This resulting data can be interpreted in terms related to metabolic flux. However, detection of a stable isotope in metabolites by mass spectrometry produces a profile of isotopologue peaks that requires deconvolution to ascertain the localization of isotope incorporation. RESULTS: To aid the interpretation of the mass spectroscopy isotopologue profile, we have developed a moiety modeling framework for deconvoluting metabolite isotopologue profiles involving single and multiple isotope tracers. This moiety modeling framework provides facilities for moiety model representation, moiety model optimization, and moiety model selection. The moiety_modeling package was developed from the idea of metabolite decomposition into moiety units based on metabolic transformations, i.e. a moiety model. The SAGA-optimize package, solving a boundary-value inverse problem through a combined simulated annealing and genetic algorithm, was developed for model optimization. Additional optimization methods from the Python scipy library are utilized as well. Several forms of the Akaike information criterion and Bayesian information criterion are provided for selecting between moiety models. Moiety models and associated isotopologue data are defined in a JSONized format. By testing the moiety modeling framework on the timecourses of 13C isotopologue data for uridine diphosphate N-acetyl-D-glucosamine (UDP-GlcNAc) in human prostate cancer LnCaP-LN3 cells, we were able to confirm its robust performance in isotopologue deconvolution and moiety model selection. CONCLUSIONS: SAGA-optimize is a useful Python package for solving boundary-value inverse problems, and the moiety_modeling package is an easy-to-use tool for mass spectroscopy isotopologue profile deconvolution involving single and multiple isotope tracers. Both packages are freely available on GitHub and via the Python Package Index.

Probing the metabolic phenotype of breast cancer cells by multiple tracer stable isotope resolved metabolomics.

Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using 13C6-glucose, 13C-1+2-glucose, 13C5,15N2-Gln, 13C3-glycerol, and 13C8-octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment.

NMR-based Stable Isotope Resolved Metabolomics in systems biochemistry.

Metabolism is the basic activity of live cells, and monitoring the metabolic state provides a dynamic picture of the cells or tissues, and how they respond to external changes, for in disease or treatment with drugs. NMR is an extremely versatile analytical tool that can be applied to a wide range of biochemical problems. Despite its modest sensitivity its versatility make it an ideal tool for analyzing biochemical dynamics both in vitro and in vivo, especially when coupled with its isotope editing capabilities, from which isotope distributions can be readily determined. These are critical for any analyses of flux in live organisms. This review focuses on the utility of NMR spectroscopy in metabolomics, with an emphasis on NMR applications in stable isotope-enriched tracer research for elucidating biochemical pathways and networks with examples from nucleotide biochemistry. The knowledge gained from this area of research provides a ready link to genomic, epigenomic, transcriptomic, and proteomic information to achieve systems biochemical understanding of living cells and organisms.

Quantitative Analysis of Cancer Metabolism: From pSIRM to MFA.

Metabolic reprogramming is a required step during oncogenesis and essential for cellular proliferation. It is triggered by activation of oncogenes and loss of tumor suppressor genes. Beside the combinatorial events leading to cancer, common changes within the central metabolism are reported. Increase of glycolysis and subsequent lactic acid formation has been a focus of cancer metabolism research for almost a century. With the improvements of bioanalytical techniques within the last decades, a more detailed analysis of metabolism is possible and recent studies demonstrate a wide range of metabolic rearrangements in various cancer types. However, a systematic and mechanistic understanding is missing thus far. Therefore, analytical and computational tools have to be developed allowing for a dynamic and quantitative analysis of cancer metabolism. In this chapter, we outline the application of pulsed stable isotope resolved metabolomics (pSIRM) and describe the interface toward computational analysis of metabolism.

Challenges of Spatially Resolved Metabolism in Cancer Research.

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.

A unique insight for Xiaoyao San exerts antidepressant effects by modulating hippocampal glucose catabolism using stable isotope-resolved metabolomics.

ETHNOPHARMACOLOGICAL RELEVANCE: In traditional Chinese medicine (TCM) theory, depression is an emotional disease, which is thought to be related to stagnation of liver qi and dysfunction of the spleen in transport. Xiaoyao San (XYS) is considered to have the effects of soothing liver-qi stagnation and invigorating the spleen. The spleen has the function to transport and transform nutrients. The liver has also termed the center of energy metabolism in the body. Therefore, exploring the antidepressant effects of XYS from the perspective of energy metabolism may reveal new findings. AIM OF THE STUDY: Glucose catabolism is an important part of energy metabolism. In recent years, several researchers have found that XYS can exert antidepressant effects by modulating abnormalities in glucose catabolism-related metabolites. The previous research of our research group found that the hippocampus glucose catabolism was disordered in depression. However, the antidepressant potential of XYS through modulating the disorders of hippocampal glucose catabolism and the specific metabolic pathways and targets of XYS action were still unknown. The aim of this study was to address the above scientific questions. MATERIALS AND METHODS: In this research, the CUMS (chronic unpredictable mild stress) model was used as the animal model of depression. The antidepressant effect of XYS was evaluated by behavioral indicators. The specific pathways and targets of XYS modulating the disorders of glucose catabolism in the hippocampus of CUMS rats were obtained by stable isotope-resolved metabolomics. Further, the isotope tracing results were also verified by molecular biology and electron transmission electron microscopy. RESULTS: The results demonstrated that XYS pretreatment could significantly improve the depressive symptoms induced by CUMS. More importantly, it was found that XYS could modulate the disorders of glucose catabolism in the hippocampus of CUMS rats. Stable isotope-resolved metabolomics and enzyme activity tests showed that Lactate dehydrogenase (LDH), Pyruvate carboxylase (PC), and Pyruvate dehydrogenase (PDH) were targets of XYS for modulating the disorders of glucose catabolism in the hippocampus of CUMS rats. The Succinate dehydrogenase (SDH) and mitochondrial respiratory chain complex V (MRCC-Ⅴ) were targets of XYS to improve abnormal mitochondrial oxidative phosphorylation in the hippocampus of CUMS rats. XYS was also found to have the ability to improve the structural damage of mitochondria and nuclei in the hippocampal caused by CUMS. CONCLUSIONS: This study was to explore the antidepressant effect of XYS from the perspective of glucose catabolism based on a strategy combining stable isotope tracing, molecular biology techniques, and transmission electron microscopy. We not only obtained the specific pathways and targets of XYS to improve the disorders of glucose catabolism in the hippocampus of CUMS rats, but also revealed the specific targets of the pathways of XYS compared with VLF.

A novel insight for high-rate and low-efficiency glucose metabolism in depression through stable isotope-resolved metabolomics in CUMS-induced rats.

BACKGROUND: Existing research has suggested that depression results in disorders of glucose metabolism in the organism which causing insufficient energy supply. However, the overall changes in glucose metabolism that arise from depression have not been clarified. METHODS: In this study, the depression-like behavior in chronically unpredictable mild stressed rats was investigated, and the fate of glucose was tracked through isotope tracing and mass spectrometry, with a focus on metabolite changes in cecal contents. RESULTS: As indicated by the results, the isotopic results of cecal contents can indicate the metabolic end of the organism. Moreover, the TCA cycle activity was notably reduced, and the gluconeogenesis pathway was abnormally up-regulated in the CUMS-induced rats. The organism expedited other glucose metabolism pathways to make up for the insufficiency of energy. As a result, the activity of the inefficient glycolysis pathway was increased. LIMITATIONS: Existing research has only investigated the metabolism of 13C-glucose, and lipids and proteins have been rarely explored. CONCLUSIONS: The chronic unpredictable mild stress can inhibit the entry of pyruvate into mitochondria in SD rats, such that the activity of TCA is reduced, and insufficient energy supply is caused. The organism is capable of expediting other glucose metabolism rate pathways to make up for the insufficiency of energy, whereas it still cannot compensate for the loss of energy. As a result, CUMS-induced rats exhibited high-rate and low-efficiency glucose metabolism.

Differential Inhibition of Anaplerotic Pyruvate Carboxylation and Glutaminolysis-Fueled Anabolism Underlies Distinct Toxicity of Selenium Agents in Human Lung Cancer.

Past chemopreventive human trials on dietary selenium supplements produced controversial outcomes. They largely employed selenomethionine (SeM)-based diets. SeM was less toxic than selenite or methylseleninic acid (MSeA) to lung cancer cells. We thus investigated the toxic action of these Se agents in two non-small cell lung cancer (NSCLC) cell lines and ex vivo organotypic cultures (OTC) of NSCLC patient lung tissues. Stable isotope-resolved metabolomics (SIRM) using 13C6-glucose and 13C5,15N2-glutamine tracers with gene knockdowns were employed to examine metabolic dysregulations associated with cell type- and treatment-dependent phenotypic changes. Inhibition of key anaplerotic processes, pyruvate carboxylation (PyC) and glutaminolysis were elicited by exposure to MSeA and selenite but not by SeM. They were accompanied by distinct anabolic dysregulation and reflected cell type-dependent changes in proliferation/death/cell cycle arrest. NSCLC OTC showed similar responses of PyC and/or glutaminolysis to the three agents, which correlated with tissue damages. Altogether, we found differential perturbations in anaplerosis-fueled anabolic pathways to underlie the distinct anti-cancer actions of the three Se agents, which could also explain the failure of SeM-based chemoprevention trials.

Investigating the role of GLUL as a survival factor in cellular adaptation to glutamine depletion via targeted stable isotope resolved metabolomics.

Cellular glutamine synthesis is thought to be an important resistance factor in protecting cells from nutrient deprivation and may also contribute to drug resistance. The application of ?targeted stable isotope resolved metabolomics" allowed to directly measure the activity of glutamine synthetase in the cell. With the help of this method, the fate of glutamine derived nitrogen within the biochemical network of the cells was traced. The application of stable isotope labelled substrates and analyses of isotope enrichment in metabolic intermediates allows the determination of metabolic activity and flux in biological systems. In our study we used stable isotope labelled substrates of glutamine synthetase to demonstrate its role in the starvation response of cancer cells. We applied 13C labelled glutamate and 15N labelled ammonium and determined the enrichment of both isotopes in glutamine and nucleotide species. Our results show that the metabolic compensatory pathways to overcome glutamine depletion depend on the ability to synthesise glutamine via glutamine synthetase. We demonstrate that the application of dual-isotope tracing can be used to address specific reactions within the biochemical network directly. Our study highlights the potential of concurrent isotope tracing methods in medical research.

A Micro-Scale Analytical Method for Determining Glycogen Turnover by NMR and FTMS.

Glycogen is a readily deployed intracellular energy storage macromolecule composed of branched chains of glucose anchored to the protein glycogenin. Although glycogen primarily occurs in the liver and muscle, it is found in most tissues, and its metabolism has been shown to be important in cancers and immune cells. Robust analysis of glycogen turnover requires stable isotope tracing plus a reliable means of quantifying total and labeled glycogen derived from precursors such as 13C6-glucose. Current methods for analyzing glycogen are time- and sample-consuming, at best semi-quantitative, and unable to measure stable isotope enrichment. Here we describe a microscale method for quantifying both intact and acid-hydrolyzed glycogen by ultra-high-resolution Fourier transform mass spectrometric (UHR-FTMS) and/or NMR analysis in stable isotope resolved metabolomics (SIRM) studies. Polar metabolites, including intact glycogen and their 13C positional isotopomer distributions, are first measured in crude biological extracts by high resolution NMR, followed by rapid and efficient acid hydrolysis to glucose under N2 in a focused beam microwave reactor, with subsequent analysis by UHR-FTMS and/or NMR. We optimized the microwave digestion time, temperature, and oxygen purging in terms of recovery versus degradation and found 10 min at 110−115 °C to give >90% recovery. The method was applied to track the fate of 13C6-glucose in primary human lung BEAS-2B cells, human macrophages, murine liver and patient-derived tumor xenograft (PDTX) in vivo, and the fate of 2H7-glucose in ex vivo lung organotypic tissue cultures of a lung cancer patient. We measured the incorporation of 13C6-glucose into glycogen and its metabolic intermediates, UDP-Glucose and glucose-1-phosphate, to demonstrate the utility of the method in tracing glycogen turnover in cells and tissues. The method offers a quantitative, sensitive, and convenient means to analyze glycogen turnover in mg amounts of complex biological materials.