bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2019–09–01
thirty papers selected by
Giovanny Rodriguez Blanco, The Beatson Institute for Cancer Research



  1. Int Rev Cell Mol Biol. 2019 ;pii: S1937-6448(19)30066-8. [Epub ahead of print]347 191-223
      Altered metabolism is one of the defining features of cancer. Since the discovery of the Warburg effect in 1924, research into the metabolic aspects of cancer has been reinvigorated over the past decade. Metabolomics is an invaluable tool for gaining insights into numerous biochemical processes including those related to cancer metabolism and metabolic aspects of other diseases. The combination of untargeted and targeted metabolomics approaches has greatly facilitated the discovery of many cancer biomarkers with prognostic potential. Using mass spectrometry-based stable isotope-resolved metabolomics (SIRM) with isotopic labeling, a powerful tool used in pathway analysis, researchers have discovered novel cancer metabolic pathways and metabolic targets for therapeutic application. Metabolomics technologies provide invaluable metabolic insights reflecting cancer progression in coordination with genomics and proteomics aspects. The systematic study of metabolite levels in the metabolome and their dynamics within a biological organism has been, in recent years, applied across a wide range of fields. Metabolomics technologies have been applied to both early clinical trials and pre-clinical research in several essential aspects of human health. This chapter will give an overview of metabolomics technologies and their application in the discovery of novel pathways using isotopic labeled and non-labeled metabolomics.
    Keywords:  Cancer metabolism; Glucose metabolism; Glutamine metabolism; Isotopic labeling; Metabolomics technologies
    DOI:  https://doi.org/10.1016/bs.ircmb.2019.07.003
  2. Chem Phys Lipids. 2019 Aug 23. pii: S0009-3084(19)30089-1. [Epub ahead of print] 104802
      Microwave radiation can lead to some biological effects, mainly involving the nervous and reproductive systems. However, its lipid metabolic mechanism remains unclear. Here, we performed an untargeted metabolomics approach to analyze lipid metabolic changes caused by microwave radiation using ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). Then, multivariate analysis was used to reveal the different lipid metabolites and metabolic pathways. Compared with the sham group, biochemical parameters of the microwave group had significant changes in triglyceride (TG) and high-density lipoprotein (HDL) levels. Sixty-eight abnormal lipids were identified, which were mainly distributed in linoleic acid metabolism, glycerophospholipid metabolism, glycerolipid metabolism and glycosylphosphatidylinositol (GPI)-anchor biosynthesis. Among them, phosphatidylethanolamine (PE), lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC) and linoleic acid showed mainly upregulated expression, while sphingomyelin (SM), cholesterol esters (CE) and some free fatty acids (FFAs) showed downregulated expression. Phosphatidylcholine (PC) and triacylglycerol (TG) were increased or decreased. Furthermore, we obtained significant links between lipid metabolic changes and cognitive damage caused by microwave radiation. Together, our results suggested that microwave radiation could cause changes in lipid metabolism and provided a novel insight into the role of lipids in microwave radiation. Targeting lipid metabolism may provide a new therapeutic strategy for microwave radiation injury.
    Keywords:  UPLC-MS; glycerolipid; glycerophospholipid; linoleic acid; lipid metabolism; microwave radiation
    DOI:  https://doi.org/10.1016/j.chemphyslip.2019.104802
  3. Phys Biol. 2019 Aug 29.
      The glycolytic enzyme pyruvate kinase M2 (PKM2) exists in both catalytically inactive dimeric and active tetrameric forms. In cancer cells, PKM2 dimer predominance contributes to tumor growth by triggering glycolytic reprogramming. However, the mechanism that promotes PKM2 dimer predominance over tetramer in cancer cells remains elusive. Here, we show that pulsatile phosphofructokinase (PFK-1) activity results in PKM2 dimer predominance. Mathematical simulations predict that pulsatile PFK-1 activity prevents the formation of PKM2 tetramer even under high levels of fructose-1,6-bisphosphate (FBP), a PKM2 tetramer-promoting metabolite produced by PFK-1. We experimentally confirm these predictions at the single-molecule level by providing evidence for pulsatile PFK-1 activity-induced synchronized dissociation of PKM2 tetramers and the subsequent accumulation of PKM2 dimers under high levels of FBP in HeLa cells. Moreover, we show that pulsatile PFK-1 activity-induced PKM2 dimer predominance also controls cell proliferation. Thus, our study reveals the significance of pulsatile PFK-1 activity in cancer cell metabolism.
    Keywords:  Cancer cell metabolism; Glycolytic reprogramming; Pulsatile PFK-1 activity; Quantitative Biology
    DOI:  https://doi.org/10.1088/1478-3975/ab3f5a
  4. Methods Mol Biol. 2019 ;2037 3-14
      The fast-growing field of metabolomics is impacting numerous areas of basic and life sciences. In metabolomics, analytical methods play a pivotal role, and nuclear magnetic resonance (NMR) and mass spectrometry (MS) have proven to be the most suitable and powerful methods. Although NMR exhibits lower sensitivity and resolution compared to MS, NMR's numerous important characteristics far outweigh its limitations. Some of its characteristics include excellent reproducibility and quantitative accuracy, the capability to analyze intact biospecimens, an unparalleled ability to identify unknown metabolites, the ability to trace in-cell and in-organelle metabolism in real time, and the capacity to trace metabolic pathways atom by atom using 2H, 13C, or 15N isotopes. Each of these characteristics has been exploited extensively in numerous studies. In parallel, the field has witnessed significant progress in instrumentation, methods development, databases, and automation that are focused on higher throughput and alleviating the limitations of NMR, in particular, resolution and sensitivity. Despite the advances, however, the high complexity of biological mixtures combined with the limitations in sensitivity and resolution continues to pose major challenges. These challenges need to be dealt with effectively to better realize the potential of metabolomics, in general. As a result, multifaceted efforts continue to focus on addressing the challenges as well as reaping the benefits of NMR-based metabolomics. This chapter highlights the current status with emphasis on the opportunities and challenges in NMR-based metabolomics.
    Keywords:  Biomarkers; Historical perspective; Metabolomics; NMR; Pathways
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_1
  5. Methods Mol Biol. 2019 ;2037 35-47
      Lipid profiling, which includes fatty acids, phospholipids, glycerides, and cholesterols is extremely important because of the essential role lipids play in the regulation of metabolism in animals. 1H-NMR-based protocols for high-throughput lipid analysis in complex mixtures have been developed and applied to biological systems. Many classes of lipids can be quantitatively analyzed in many sample matrices including serum, cells, and tissues using a simple 1H NMR experiment. In this chapter, we provide protocols for NMR-based lipid profiling including sample preparation, NMR experiments, and quantification using the LipSpin software tool.
    Keywords:  1H NMR spectroscopy; Lipid extracts; Lipid profiling
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_3
  6. Int Rev Cell Mol Biol. 2019 ;pii: S1937-6448(19)30063-2. [Epub ahead of print]347 145-190
      Autophagy is an ancient catabolic process used by cells to clear excess or dysfunctional organelles and large subcellular structures and thus performs an important housekeeping role for the cell. Autophagy is acutely sensitive to nutrient availability and is upregulated at a transcriptional and posttranslational level in response to nutrient deprivation. This serves to promote turnover of cellular content and recycling of nutrients for continued growth and survival. While important for most normal tissues, tumor cells appear to be particularly dependent on autophagy for survival under ischemic or therapeutic stress, and in response to loss of matrix attachment; autophagy is upregulated markedly in cancers as they progress to malignancy. Ras-driven tumors appear to be particularly dependent on autophagy and thus inhibition of autophagy is being pursued as a productive clinical approach for such cancers. However, this enthusiasm needs to be offset against possible negative effects of autophagy inhibition on normal tissue function and on limiting antitumor immune responses. In addressing all of these topics, we focus in on understanding how autophagy is induced by nutrient stress, its role in recycling metabolites for growing tumors, how selective forms of autophagy, such as mitophagy and ribophagy contribute specifically to tumorigenesis, how autophagy in the tumor microenvironment and throughout the animal affects access of the tumor to nutrients, and finally how different oncogenic pathways may determine which tumors respond to autophagy inhibition and which ones will not.
    Keywords:  AMPK; ATF4; Amino acids; Autophagy; FoxO; Glycolysis; Lipophagy; MYC; Mitochondria; Mitophagy; RAS; Ribophagy; TFEB/MiTF; Therapeutic vulnerabilities; mTOR
    DOI:  https://doi.org/10.1016/bs.ircmb.2019.06.002
  7. Methods Mol Biol. 2019 ;2037 113-133
      Metabolomics represents a powerful, complementary approach for studying biological system responses to various biotic and abiotic stimuli. A major challenge in metabolomics is the lack of reliable annotations for all metabolites detected in complex MS and/or NMR data. To meet this challenge, we have developed an integrated UHPLC-QTOF-MS/MS-SPE-NMR system for higher-throughput metabolite identifications, which provides advanced biological context and enhances the scientific value of metabolomics data for understanding systems biology. This integrated instrumental method is less labor-intensive and more cost-effective than conventional individual methods (LC; MS; SPE; NMR). It enables the simultaneous purification and identification of primary and secondary metabolites present in biological samples. In this chapter, we describe the configuration and use of UHPLC-MS/MS-SPE-NMR in metabolite analyses ranging from sample extraction to higher-throughput metabolite annotation. With the integrated UHPLC-QTOF-MS/MS-SPE-NMR method, we have purified and confidently identified more than 100 previously known as well as unknown triterpene and flavonoid glycosides while noting that most of the identified compounds are not commercially available.
    Keywords:  Mass spectrometry (MS); Nuclear magnetic resonance (NMR) spectroscopy; Online and offline sample transfer; Solid-phase extraction (SPE); Ultrahigh-performance liquid chromatography (UHPLC)
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_7
  8. Metabolites. 2019 Aug 28. pii: E173. [Epub ahead of print]9(9):
      Short chain fatty acids (SCFAs) are the main products of dietary fibers that are not digested by the human body, and they have been shown to affect human metabolism and inflammation. The amount of SCFAs in the body is related to many human diseases, and studies have focused on elucidating their roles and target molecules in both metabolic and immune responses. Thus, the quantitation of SCFAs in biological samples becomes crucial in understanding their important roles in the human body. Herein, a facile profiling method of SCFAs using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and then applied to biological samples. C2-C6 SCFAs were derivatized while using 4-acetamido-7-mercapto-2,1,3-benzoxadiazole for 5 min. at room temperature prior to LC-MS/MS analysis, and characteristic fragmentation patterns and increased hydrophobicity after chemical derivatization enabled specific discrimination among 12 SCFAs. Derivatization was fast and reliable, and the reaction products were stable for a week at 4 °C. The developed method was applied to measure SCFAs in mouse feces, plasma, and human exhaled breath condensates. This fast and simple method can save labor and effort to profile SCFAs from various biological samples.
    Keywords:  4-acetamido-7-mercapto-2,1,3-benzoxadiazole; chemical derivatization; exhaled breath condensate; feces; plasma; short chain fatty acids
    DOI:  https://doi.org/10.3390/metabo9090173
  9. Methods Mol Biol. 2019 ;2037 169-186
      Altered metabolism is considered one of the hallmarks of cancer. The findings that malignant brain tumors and brain metastases utilize acetate as an alternative nutrient are relatively recent and offer new avenues for investigation of altered metabolism in human cancers. Here, we describe comprehensively the details of the 13C NMR-based isotopomer methodology to measure in vivo acetate utilization in brain tumor patients, including the contribution from acetate metabolism of peripheral tissues. Methods described in this chapter can be readily extended to other cancer types.
    Keywords:  13C NMR; 13C–13C spin–spin coupling; Acetyl-CoA; Citric acid cycle; Isotopomer; Pyruvate recycling; [1,2-13C]acetate
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_10
  10. Methods Mol Biol. 2019 ;2037 413-427
      Metabolomics is the study of profiles of small molecules in biological fluids, cells, or organs. These profiles can be thought of as the "fingerprints" left behind from chemical processes occurring in biological systems. Because of its potential for groundbreaking applications in disease diagnostics, biomarker discovery, and systems biology, metabolomics has emerged as a rapidly growing area of research. Metabolomics investigations often, but not always, involve the identification and quantification of endogenous and exogenous metabolites in biological samples. Software tools and databases play a crucial role in advancing the rigor, robustness, reproducibility, and validation of these studies. Specifically, the establishment of a robust library of spectral signatures with unique compound descriptors and atom identities plays a key role in profiling studies based on data from nuclear magnetic resonance (NMR) spectroscopy. Here, we discuss developments leading to a rigorous basis for unique identification of compounds, reproducible numbering of atoms, the compact representation of NMR spectra of metabolites and small molecules, tools for improved compound identification, quantification and visualization, and approaches toward the goal of rigorous analysis of metabolomics data.
    Keywords:  Identification; Metabolomics; NMR; Numbering of atoms; Quantification
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_23
  11. Mol Cell. 2019 Aug 06. pii: S1097-2765(19)30537-4. [Epub ahead of print]
      The rapid proliferation of cancer cells and dysregulated vasculature within the tumor leads to limited nutrient accessibility. Cancer cells often rewire their metabolic pathways for adaption to nutrient stress, and the underlying mechanism remains largely unknown. Glutamate dehydrogenase 1 (GDH1) is a key enzyme in glutaminolysis that converts glutamate to α-ketoglutarate (α-KG). Here, we show that, under low glucose, GDH1 is phosphorylated at serine (S) 384 and interacts with RelA and IKKβ. GDH1-produced α-KG directly binds to and activates IKKβ and nuclear factor κB (NF-κB) signaling, which promotes glucose uptake and tumor cell survival by upregulating GLUT1, thereby accelerating gliomagenesis. In addition, GDH1 S384 phosphorylation correlates with the malignancy and prognosis of human glioblastoma. Our finding reveals a unique role of α-KG to directly regulate signal pathway, uncovers a distinct mechanism of metabolite-mediated NF-κB activation, and also establishes the critical role of α-KG-activated NF-κB in brain tumor development.
    Keywords:  GDH1; NF-κB; glucose deficiency; tumorigenesis; α-ketoglutarate
    DOI:  https://doi.org/10.1016/j.molcel.2019.07.007
  12. Mol Cell Proteomics. 2019 Aug 26. pii: mcp.RA119.001625. [Epub ahead of print]
      Protein methylation has been implicated in many important biological contexts including signaling, metabolism, and transcriptional control. Despite the importance of this post-translational modification, the global analysis of protein methylation by mass spectrometry-based proteomics has not been extensively studied due to the lack of robust, well-characterized techniques for methyl peptide enrichment. Here, to better investigate protein methylation, we compared two methods for methyl peptide enrichment: immunoaffinity purification (IAP) and high pH strong cation exchange (SCX). Using both methods, we identified 1,720 methylation sites on 778 proteins. Comparison of these methods revealed that they are largely orthogonal, suggesting that the usage of both techniques is required to provide a global view of protein methylation. Using both IAP and SCX, we then investigated changes in protein methylation downstream of protein arginine methyltransferase 1 (PRMT1). PRMT1 knockdown resulted in significant changes to 127 arginine methylation sites on 78 proteins. In contrast, only a single lysine methylation site was significantly changed upon PRMT1 knockdown. In PRMT1 knockdown cells, we found 114 MMA sites that were either significantly downregulated or upregulated on proteins enriched for mRNA metabolic processes. PRMT1 knockdown also induced significant changes in both asymmetric dimethyl arginine (ADMA) and symmetric dimethyl arginine (SDMA). Using characteristic neutral loss fragmentation ions, we annotated dimethylarginines as either ADMA or SDMA. Through integrative analysis of methyl forms, we identified 18 high confidence PRMT1 substrates and 12 methylation sites that are scavenged by other non-PRMT1 arginine methyltransferases in the absence of PRMT1 activity. We also identified one methylation site, HNRNPA1 R206, which switched from ADMA to SDMA upon PRMT1 knockdown. Taken together, our results suggest that deep protein methylation profiling by mass spectrometry requires orthogonal enrichment techniques to identify novel PRMT1 methylation targets and highlight the dynamic interplay between methyltransferases in mammalian cells.
    Keywords:  Affinity proteomics; Immunoaffinity; Label-free quantification; Methylation*; Post-translational modifications*; Systems biology*; Tandem Mass Spectrometry; arginine; lysine; strong cation exchange
    DOI:  https://doi.org/10.1074/mcp.RA119.001625
  13. Methods Mol Biol. 2019 ;2037 49-67
      High-resolution magic angle spinning (HRMAS) NMR spectroscopy enables the evaluation of metabolite profiles of intact tissue with high spectral resolution. The ability to preserve the tissue after analysis permits subsequent histopathological examination and enables the analyses of correlations between tissue metabolites and pathologies, thus making HRMAS NMR spectroscopy a powerful tool in the metabolomics field. Improved methods for the elimination of spinning sidebands that appear at low spinning rates preserve the integrity of tissue structures better and allow measurement of delicate tissues, such as clinical biopsy core samples. In the metabolomics field, HRMAS NMR has been established as a valuable tool for both untargeted and targeted metabolite profiling. In this chapter, we present protocols to perform HRMAS NMR spectroscopy experiments, including sample preparation, acquisition procedures, measurement parameters, histopathological examination techniques, spectral processing, and metabolite quantification and statistical analyses.
    Keywords:  High-resolution magic angle spinning; Intact tissue; Metabolite quantification; Metabolomics; NMR spectroscopy
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_4
  14. Methods Mol Biol. 2019 ;2037 345-362
      The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic exploration and natural products discovery. To achieve this goal, plant metabolomics relies on accurate and selective acquisition of all possible chemical information, which includes maximization of the number of detected metabolites and their correct molecular assignment. Nuclear magnetic resonance (NMR) spectroscopy has been recognized as a powerful platform for obtaining the metabolite profiles of plant extracts. In this chapter, we provide a workflow for targeted and untargeted metabolite profiling of plant extracts using both 1D and 2D NMR methods. The protocol includes sample preparation, instrument operation, data processing, multivariate analysis, biomarker elucidation, and metabolite quantitation. It also addresses the annotation of plant metabolite peaks considering NMR's capabilities to cover a broad range of metabolites and elucidate structures for unknown compounds.
    Keywords:  Metabolite annotation; NMR spectroscopy; Natural products; Plant metabolomics; Quantitative NMR
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_19
  15. Cell Metab. 2019 Aug 19. pii: S1550-4131(19)30385-7. [Epub ahead of print]
      Lipid metabolism is frequently perturbed in cancers, but the underlying mechanism is unclear. We present comprehensive evidence that oncogene MYC, in collaboration with transcription factor sterol-regulated element-binding protein (SREBP1), regulates lipogenesis to promote tumorigenesis. We used human and mouse tumor-derived cell lines, tumor xenografts, and four conditional transgenic mouse models of MYC-induced tumors to show that MYC regulates lipogenesis genes, enzymes, and metabolites. We found that MYC induces SREBP1, and they collaborate to activate fatty acid (FA) synthesis and drive FA chain elongation from glucose and glutamine. Further, by employing desorption electrospray ionization mass spectrometry imaging (DESI-MSI), we observed in vivo lipidomic changes upon MYC induction across different cancers, for example, a global increase in glycerophosphoglycerols. After inhibition of FA synthesis, tumorigenesis was blocked, and tumors regressed in both xenograft and primary transgenic mouse models, revealing the vulnerability of MYC-induced tumors to the inhibition of lipogenesis.
    Keywords:  ChIP; MYC; MYC conditional transgenic mouse models; RNA-seq; SREBP1; acetyl-CoA carboxylase A inhibition; carbon tracing; fatty acid synthesis; glycerophosphoglycerols; mass spectrometry imaging; nuclear run-on
    DOI:  https://doi.org/10.1016/j.cmet.2019.07.012
  16. J Exp Clin Cancer Res. 2019 Aug 27. 38(1): 377
       BACKGROUND: Cardamonin, a chalcone isolated from Alpiniae katsumadai, has anti-inflammatory and anti-tumor activities. However, the molecular mechanism by which cardamonin inhibits breast cancer progression largely remains to be determined.
    METHODS: CCK-8 and Hoechst 33258 staining were used to detect cell growth and apoptosis, respectively. HIF-1α driven transcription was measured by luciferase reporter assay. Glucose uptake and lactate content were detected with 2-NBDG and L-Lactate Assay Kit. Cell metabolism assays were performed on Agilent's Seahorse Bioscience XF96 Extracellular Flux Analyzer. Mitochondrial membrane potential was measured with JC-1 probe. DCFH-DA was used to measure ROS level. Protein expression was detected by western blotting assay. Immunohistochemistry was performed to measure the expression of HIF-1α, LDHA and CD31 in tumor tissues.
    RESULTS: Cardamonin inhibited growth of the triple negative breast cancer cell line MDA-MB-231 in vitro and in vivo by suppressing HIF-1α mediated cell metabolism. Cardamonin inhibited the expression of HIF-1α at mRNA and protein levels by repressing the mTOR/p70S6K pathway, and subsequently enhanced mitochondrial oxidative phosphorylation and induced reactive oxygen species (ROS) accumulation. We also found that cardamonin inhibited the Nrf2-dependent ROS scavenging system which further increased intracellular ROS levels. Eventually, accumulation of the intracellular ROS induced apoptosis in breast cancer cells. In addition, cardamonin treatment reduced glucose uptake as well as lactic acid production and efflux, suggesting its function in repressing the glycolysis process.
    CONCLUSIONS: These results reveal novel function of cardamonin in modulating cancer cell metabolism and suppressing breast cancer progression, and suggest its potential for breast cancer treatment.
    Keywords:  Apoptosis; Breast cancer; Cardamonin; Cell metabolism; Mitochondrial oxidative phosphorylation; Reactive oxygen species
    DOI:  https://doi.org/10.1186/s13046-019-1351-4
  17. Int Rev Cell Mol Biol. 2019 ;pii: S1937-6448(19)30070-X. [Epub ahead of print]347 1-26
      As compared to their normal counterparts, neoplastic cells exhibit a variety of metabolic changes that reflect not only genetic and epigenetic defects underlying malignant transformation, but also the nutritional and immunobiological conditions of the tumor microenvironment. Such alterations, including the so-called Warburg effect (an increase in glucose uptake largely feeding anabolic and antioxidant metabolism), have attracted considerable attention as potential targets for the development of novel anticancer therapeutics. However, very few drugs specifically conceived to target bioenergetic cancer metabolism are currently approved by regulatory agencies for use in humans. This reflects the elevated degree of heterogeneity and redundancy in the metabolic circuitries exploited by neoplastic cells from different tumors (even of the same type), as well as the resemblance of such metabolic pathways to those employed by highly proliferating normal cells. Here, we summarize the major metabolic alterations that accompany oncogenesis, the potential of targeting bioenergetic metabolism for cancer therapy, and the obstacles that still prevent the clinical translation of such a promising therapeutic paradigm.
    Keywords:  Glutamine; Krebs cycle; Oxidative phosphorylation; Pentose phosphate pathway; Reductive carboxylation; Serine
    DOI:  https://doi.org/10.1016/bs.ircmb.2019.07.007
  18. Methods Mol Biol. 2019 ;2037 195-213
      Continued progress is being made in understanding the breast cancer metabolism using analytical magnetic resonance (MR)-based methods like nuclear magnetic resonance (NMR) and in-vivo MR spectroscopy (MRS). Analyses using these methods have enhanced the knowledge of altered biochemical pathways associated with breast cancer progression, regression, and pathogenesis. Comprehensive metabolic profiling of biological samples like tissues, cell lines, fine needle aspirate, and biofluids such as sera and urine enables identification of new biomarkers and abnormalities in biochemical pathways. These methods are not only useful for diagnosis, therapy monitoring, disease progression, and staging of cancer but also for the identification of new therapeutic targets and designing new treatment strategies. Additionally, in-vivo MRS studies have established choline-containing compounds (tCho) as biomarkers of malignancy, which is useful for enhancing the diagnostic specificity of magnetic resonance imaging (MRI). Recent technological developments related to in-vivo MRS such as increased magnetic field strength, multichannel phased array breast coils, and absolute quantification of tCho have provided a better understanding of the tumor heterogeneity, metabolism, and pathogenesis. This chapter focuses on providing the experimental aspects of in-vitro, ex-vivo, and in-vivo MR spectroscopy methods used for metabolomics studies of breast cancer.
    Keywords:  Acetonitrile extraction; Breast cancer; Chloroform-methanol extraction; Choline; Ex-vivo NMR; In-vitro NMR; In-vivo MRS; Metabolomics; Perchloric acid extraction
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_12
  19. Methods Mol Biol. 2019 ;2037 97-110
      Cellular coenzymes including coenzyme A (CoA), acetyl coenzyme A (acetyl-CoA), coenzymes of redox reactions and of energy, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. The redox coenzymes include NAD+ (oxidized nicotinamide adenine dinucleotide), NADH (reduced nicotinamide adenine dinucleotide), NADP+ (oxidized nicotinamide adenine dinucleotide phosphate), and NADPH (reduced nicotinamide adenine dinucleotide phosphate); the energy coenzymes include ATP (adenosine triphosphate), ADP (adenosine diphosphate), and AMP (adenosine monophosphate); and the antioxidants include GSSG (oxidized glutathione) and GSH (reduced glutathione). Their measurement is important to better understand cellular metabolism. Recent advances have pushed the limit of metabolite quantitation using NMR methods to an unprecedented level, which offer a new avenue for analysis of the coenzymes and antioxidants. Unlike the conventional enzyme assays, which need separate protocols for analysis, a simple 1D 1H NMR experiment enables analysis of all these molecular species in one step. In this chapter, we describe protocols for their identification and quantitation in tissue and whole blood using NMR spectroscopy.
    Keywords:  1D NMR; ADP; AMP; ATP; Acetyl-CoA; Antioxidants; Blood; CoA; Coenzymes; GSH; GSSG; NAD+; NADH; NADP+; NADPH; Quantitation; Tissue
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_6
  20. Methods Mol Biol. 2019 ;2037 243-262
      NMR-based metabolomics has shown promise in the diagnosis of diseases as it enables identification and quantification of metabolic biomarkers. Using high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy, metabolic profiles from intact tissue specimens can be obtained with high spectral resolution. In addition, HR-MAS NMR requires minimal sample preparation and the sample is kept intact for subsequent analyses. In this chapter, we describe a typical protocol for NMR-based metabolomics of tissue samples. We cover all major steps ranging from tissue sample collection to determination of biomarkers, including experimental precautions taken to ensure reproducible and reliable reporting of data in the area of clinical application.
    Keywords:  Biomarkers; Biopsies; High-resolution magic-angle-spinning MR spectroscopy; Metabolism; Metabolomics; Protocols; Tissue analysis
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_15
  21. Aging Cell. 2019 Aug 28. e13034
      Methionine restriction (MetR) extends lifespan across different species and exerts beneficial effects on metabolic health and inflammatory responses. In contrast, certain cancer cells exhibit methionine auxotrophy that can be exploited for therapeutic treatment, as decreasing dietary methionine selectively suppresses tumor growth. Thus, MetR represents an intervention that can extend lifespan with a complementary effect of delaying tumor growth. Beyond its function in protein synthesis, methionine feeds into complex metabolic pathways including the methionine cycle, the transsulfuration pathway, and polyamine biosynthesis. Manipulation of each of these branches extends lifespan; however, the interplay between MetR and these branches during regulation of lifespan is not well understood. In addition, a potential mechanism linking the activity of methionine metabolism and lifespan is regulation of production of the methyl donor S-adenosylmethionine, which, after transferring its methyl group, is converted to S-adenosylhomocysteine. Methylation regulates a wide range of processes, including those thought to be responsible for lifespan extension by MetR. Although the exact mechanisms of lifespan extension by MetR or methionine metabolism reprogramming are unknown, it may act via reducing the rate of translation, modifying gene expression, inducing a hormetic response, modulating autophagy, or inducing mitochondrial function, antioxidant defense, or other metabolic processes. Here, we review the mechanisms of lifespan extension by MetR and different branches of methionine metabolism in different species and the potential for exploiting the regulation of methyltransferases to delay aging.
    Keywords:  S-adenosylmethionine; aging; lifespan; methionine restriction; methylation; methyltransferases
    DOI:  https://doi.org/10.1111/acel.13034
  22. Cancers (Basel). 2019 Aug 23. pii: E1231. [Epub ahead of print]11(9):
      Glioblastoma (GBM) is the most common and aggressive primary brain tumor and is nearly universally fatal. Targeted therapy and immunotherapy have had limited success in GBM, leaving surgery, alkylating chemotherapy and ionizing radiation as the standards of care. Like most cancers, GBMs rewire metabolism to fuel survival, proliferation, and invasion. Emerging evidence suggests that this metabolic reprogramming also mediates resistance to the standard-of-care therapies used to treat GBM. In this review, we discuss the noteworthy metabolic features of GBM, the key pathways that reshape tumor metabolism, and how inhibiting abnormal metabolism may be able to overcome the inherent resistance of GBM to radiation and chemotherapy.
    Keywords:  glioblastoma; glioma; metabolic remodeling; metabolic targeting; metabolism; radiation
    DOI:  https://doi.org/10.3390/cancers11091231
  23. Sci Rep. 2019 Aug 26. 9(1): 12370
      In the past few years, the gut microbiome has been shown to play an important role in various disorders including in particular cardiovascular diseases. Especially the metabolite trimethylamine-N-oxide (TMAO), which is produced by gut microbial metabolism, has repeatedly been associated with an increased risk for cardiovascular events. Here we report a fast liquid chromatography tandem mass spectrometry (LC-MS/MS) method that can analyze the five most important gut metabolites with regards to TMAO in three minutes. Fast liquid chromatography is unconventionally used in this method as an on-line cleanup step to remove the most important ion suppressors leaving the gut metabolites in a cleaned flow through fraction, also known as negative chromatography. We compared different blood matrix types to recommend best sampling practices and found citrated plasma samples demonstrated lower concentrations for all analytes and choline concentrations were significantly higher in serum samples. We demonstrated the applicability of our method by investigating the effect of a standardized liquid meal (SLM) after overnight fasting of 25 healthy individuals on the gut metabolite levels. The SLM did not significantly change the levels of gut metabolites in serum.
    DOI:  https://doi.org/10.1038/s41598-019-48876-w
  24. Front Chem. 2019 ;7 558
      Acetaminophen (APAP)-induced hepatotoxicity is the most common cause of acute liver failure in the Western world. APAP is bioactivated to N-acetyl p-benzoquinone imine (NAPQI), a reactive metabolite, which can subsequently covalently bind to glutathione and protein thiols. In this study, we have used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to characterize NAPQI binding to human glutathione S-transferases (GSTs) in vitro. GSTs play a crucial role in the detoxification of reactive metabolites and therefore are interesting target proteins to study in the context of APAP covalent binding. Recombinantly-expressed and purified GSTs were used to assess NAPQI binding in vitro. APAP biotransformation to NAPQI was achieved using rat liver microsomes or human cytochrome P450 Supersomes in the presence of GSTA1, M1, M2, or P1. Resulting adducts were analyzed using bottom-up proteomics, with or without LC fractionation prior to LC-MS/MS analysis on a quadrupole-time-of-flight instrument with data-dependent acquisition (DDA). Targeted methods using multiple reaction monitoring (MRM) on a triple quadrupole platform were also developed by quantitatively labeling all available cysteine residues with a labeling reagent yielding isomerically-modified peptides following enzymatic digestion. Seven modified cysteine sites were confirmed, including Cys112 in GSTA1, Cys78 in GSTM1, Cys115 and 174 in GSTM2, as well as Cys15, 48, and 170 in GSTP1. Most modified peptides could be detected using both untargeted (DDA) and targeted (MRM) approaches, however the latter yielded better detection sensitivity with higher signal-to-noise and two sites were uniquely found by MRM.
    Keywords:  acetaminophen; bottom-up proteomics; covalent binding; data-dependent acquisition; glutathione S-transferase; high-resolution tandem mass spectrometry; multiple reaction monitoring; reactive metabolite
    DOI:  https://doi.org/10.3389/fchem.2019.00558
  25. Methods Mol Biol. 2019 ;2037 385-393
      Metabolite profiles and their isotopomer distributions can be studied noninvasively in complex mixtures with NMR. The advent of hyperpolarized 13C-NMR using quantitative dissolution Dynamic Nuclear Polarization (qdDNP) and isotope enrichment add sensitivity to such metabolic studies, enabling mapping and quantification of metabolic pathways and networks. Here we describe a sample preparation method, including cell incubation, extraction, and signal enhancement, for reproducible and quantitative analysis of hyperpolarized 13C-NMR metabolite spectra. We further illustrate how qdDNP can be applied to gain metabolic insights into living cells.
    Keywords:  13C-NMR; Glucose; Hyperpolarization; dDNP
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_21
  26. Metabolomics. 2019 Aug 28. 15(9): 120
       INTRODUCTION: Non-targeted metabolic profiling using high-resolution mass spectrometry (HRMS) is a standard approach for pathway identification despite technical limitations.
    OBJECTIVES: To assess the performance of combining targeted quadrupole (QQQ) analysis with HRMS for in-depth pathway profiling.
    METHODS: Serum of exercising patients with type 1 diabetes (T1D) was profiled using targeted and non-targeted assays.
    RESULTS: Non-targeted analysis yielded a broad unbiased metabolic profile, targeted analysis increased coverage of purine metabolism (twofold) and TCA cycle (three metabolites).
    CONCLUSION: Our screening strategy combined the benefits of the unbiased full-scan HRMS acquisition with the deeper insight into specific pathways by large-scale QQQ analysis.
    Keywords:  Metabolism; Non-targeted; Pathways; Targeted
    DOI:  https://doi.org/10.1007/s11306-019-1585-3
  27. Cancer Discov. 2019 Aug 27. pii: CD-19-0215. [Epub ahead of print]
      Glioblastomas are highly lethal cancers, containing self-renewing glioblastoma stem cells (GSCs). Here, we show that GSCs, differentiated glioblastoma cells (DGCs), and non-malignant brain cultures all displayed robust circadian rhythms, yet GSCs alone displayed exquisite dependence on core clock transcription factors, BMAL1 and CLOCK, for optimal cell growth. Downregulation of BMAL1 or CLOCK in GSCs induced cell cycle arrest and apoptosis. Chromatin immunoprecipitation revealed BMAL1 preferentially bound at metabolic genes in GSCs, associated with differences in active chromatin regions compared to NSCs. Targeting BMAL1 or CLOCK attenuated mitochondrial metabolic function and reduced expression of the tricarboxylic acid (TCA) cycle enzymes. Small molecule agonists of two independent BMAL1::CLOCK negative regulators, the Cryptochromes and REV-ERBs, downregulated stem cell factors and reduced GSC growth. Combination of Cryptochrome and REV-ERB agonists induced synergistic anti-tumor efficacy. Collectively, GSCs coopt circadian regulators beyond canonical circadian circuitry to promote stemness maintenance and metabolism, offering novel therapeutic paradigms.
    DOI:  https://doi.org/10.1158/2159-8290.CD-19-0215
  28. Methods Mol Biol. 2019 ;2037 365-383
      Nuclear magnetic resonance (NMR) spectroscopy exhibits a great potential for the quantitative analysis of complex biological samples such as those encountered in metabolomics. To overcome the ubiquitous problem of overlapping peaks in 1D NMR spectra of complex mixtures, acquisition of 2D NMR spectra allows a better separation between overlapped resonances while yielding accurate quantitative data when appropriate analytical protocols are implemented. The experiment duration can be made compatible with high-throughput studies on large sample collections by relying on fast acquisition methods. Here, we describe the general metabolomics workflow to acquire fast quantitative 2D NMR data with a focus on targeted or untargeted analyses.
    Keywords:  2D NMR; Fast methods; Metabolomics; Quantitative analysis; Targeted; Untargeted
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_20
  29. Methods Mol Biol. 2019 ;2037 265-311
      Drug discovery is an extremely difficult and challenging endeavor with a very high failure rate. The task of identifying a drug that is safe, selective, and effective is a daunting proposition because disease biology is complex and highly variable across patients. Metabolomics enables the discovery of disease biomarkers, which provides insights into the molecular and metabolic basis of disease and may be used to assess treatment prognosis and outcome. In this regard, metabolomics has evolved to become an important component of the drug discovery process to resolve efficacy and toxicity issues and as a tool for precision medicine. A detailed description of an experimental protocol is presented that outlines the application of NMR metabolomics to the drug discovery pipeline. This includes (1) target identification by understanding the metabolic dysregulation in diseases, (2) predicting the mechanism of action of newly discovered or existing drug therapies, (3) and using metabolomics to screen a chemical lead to assess biological activity. Unlike other OMICS approaches, the metabolome is "fragile" and may be negatively impacted by improper sample collection, storage, and extraction procedures. Similarly, biologically irrelevant conclusions may result from incorrect data collection, preprocessing or processing procedures, or the erroneous use of univariate and multivariate statistical methods. These critical concerns are also addressed in the protocol.
    Keywords:  Chemometrics; Drug discovery; Metabolomics; NMR
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_16
  30. Methods Mol Biol. 2019 ;2037 453-470
      NMR data from large studies combining multiple cohorts is becoming common in large-scale metabolomics. The data size and combination of cohorts with diverse properties leads to special problems for data processing and analysis. These include alignment, normalization, detection and removal of outliers, presence of strong correlations, and the identification of unknowns. Nonetheless, these challenges can be addressed with suitable algorithms and techniques, leading to enhanced data sets ripe for further data mining.
    Keywords:  Data analysis; Data processing; Metabolome-wide significance level (MWSL); Multicohort; NMR; Subset optimization by reference matching (STORM)
    DOI:  https://doi.org/10.1007/978-1-4939-9690-2_25