bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2019‒05‒26
forty-nine papers selected by
Giovanny Rodriguez Blanco
The Beatson Institute for Cancer Research


  1. Methods Mol Biol. 2019 ;1978 219-241
    Cordes T, Metallo CM.
      Metabolism plays a central role in virtually all diseases, including diabetes, cancer, and neurodegeneration. Detailed analysis is required to identify the specific metabolic pathways dysregulated in the context of a given disease or biological perturbation. Measurement of metabolite concentrations can provide some insights into altered pathway activity or enzyme function, but since most biochemicals are metabolized by various enzymes in distinct pathways within cells and tissues, these approaches are somewhat limited. By applying metabolic tracers to a biological system, one can visualize pathway-specific information depending on the tracer used and analytes measured. To this end, stable isotope tracers and mass spectrometry are emerging as important tools for the examination of metabolic pathways and fluxes in cultured mammalian cells and other systems. Here, we describe a detailed workflow for quantifying metabolic processes in mammalian cell cultures using stable isotopes and gas chromatography coupled to mass spectrometry (GC-MS). As a case study, we apply 13C isotopic labeled glucose and glutamine to a cancer cell line to quantify substrate utilization for TCA metabolism and lipogenesis. Guidelines are also provided for interpretation of data and considerations for application to other cell systems. Ultimately, this approach provides a robust and precise method for quantifying stable isotope labeling in metabolite pools that can be applied to diverse biological systems.
    Keywords:  Fragment; Gas chromatography mass spectrometry (GC-MS); Isotopologue distribution; Isotopomer spectral analysis (ISA); MTBSTFA; Metabolic flux; Metabolism; Metabolite extraction; Stable isotope tracer; TBDMS
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_14
  2. Metabolites. 2019 May 17. pii: E99. [Epub ahead of print]9(5):
    Wagner-Golbs A, Neuber S, Kamlage B, Christiansen N, Bethan B, Rennefahrt U, Schatz P, Lind L.
      High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term storage on the metabolome, human ethylenediaminetetraacetic acid (EDTA) plasma samples stored for up to 16 years were analyzed by gas and liquid chromatography-tandem mass spectrometry-based metabolomics. Only 2% of 231 tested plasma metabolites were altered in the first seven years of storage. However, upon longer storage periods of up to 16 years and more time differences of few years significantly affected up to 26% of the investigated metabolites when analyzed within subject age groups. Ontology classes that were most affected included complex lipids, fatty acids, energy metabolism molecules, and amino acids. In conclusion, the human plasma metabolome is adequately stable to long-term storage at -80 °C for up to seven years but significant changes occur upon longer storage. However, other biospecimens may display different sensitivities to long-term storage. Therefore, in retrospective studies on EDTA plasma samples, analysis is best performed within the first seven years of storage.
    Keywords:  biomarker; long-term stability; mass spectrometry; metabolomics; plasma; storage
    DOI:  https://doi.org/10.3390/metabo9050099
  3. Methods Mol Biol. 2019 ;1978 107-120
    Fu X, Anderson M, Wang Y, Zimring JC.
      LC-MS/MS with multiple reaction monitoring (MRM) is a powerful tool for targeted metabolomics analysis including screening and quantification of known metabolites. Given the complexity of biological samples, the difference in ionization efficiency, and signal intensity of each metabolite, isotopically labeled internal standards are often used for accurate quantification. In this chapter, we describe a detailed protocol for the quantitative analysis of polyunsaturated fatty acids (PUFAs) and their oxidized products (oxylipins) by LC-MS/MS-MRM with isotope dilution. PUFAs are very susceptible to oxidation by both enzymatic and nonenzymatic pathways. Free PUFAs and corresponding oxylipins, known as bioactive lipids, are involved in many processes with varying biological functions depending on their chemical structure and concentration. Accurate quantification is thus becoming crucial to understanding the role of these bioactive lipids in health, disease(s), and other settings.
    Keywords:  Docosanoids; Eicosanoids; Hydroxyeicosatetraenoic acids (HETEs); Hydroxyoctadecadienoic acids (HODEs); Isotope dilution; LC-MS; Lipid mediators; Lipid oxidation; MRM; Oxylipins; Polyunsaturated fatty acid
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_7
  4. Methods Mol Biol. 2019 ;1978 259-268
    Kalucka J, Ghesquière B, Fendt SM, Carmeliet P.
      Blood vessels are lined by a streamlined monolayer of quiescent endothelial cells (ECs). Although these cells can remain quiescent for years, different stimuli (ischemia, inflammation) and growth factors can activate them and drive a process of new vessel formation (angiogenesis). Emerging evidence reveals that cellular metabolism is a key determinant of the EC subtype specification. The use of stable isotope tracing and mass spectrometry analysis has been essential for the discovery that fatty acid metabolism contributes to EC proliferation and lymphatic EC differentiation. This chapter describes the methodology for setting up palmitate-based tracer metabolomics and the subsequent liquid chromatography-mass spectrometry (LC-MS)-based analysis. As such, tracer metabolomics can be used: (1) to identify the different metabolic pathways relying on carbons provided by fatty acid oxidation and (2) to quantify the relative contributions of palmitate-derived carbons. We begin by providing a background and general principles regarding the use of stable isotopes to study fatty acid metabolism. We then proceed with detailed procedures for the labeling conditions, sample preparation, and subsequent LC-MS analysis.
    Keywords:  Angiogenesis; EC metabolism; Fatty acids; Mass spectrometry; Stable isotopes
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_16
  5. Methods Mol Biol. 2019 ;1978 81-105
    Zarini S, Barkley RM, Gijón MA, Murphy RC.
      Mass spectrometry has played a critical role in the identification and quantitation of lipids present in biological extracts. Various strategies have emerged in order to carry out lipidomic studies. These include both shotgun approaches as well as those engaging liquid chromatographic separation of lipid species prior to mass spectrometric analysis. Nonetheless challenges remain at every level of the lipidomic experiment, including extraction of lipids, identification of specific species, and quantitation of the vast array of lipids present in the sample extract. New strategies have emerged to address some of these issues; however, precise quantitation remains a significant challenge. The use of the ratio of the abundance of the molecular ion species to that of an internal standard enables quite accurate assessment of fold changes within complex lipid species without the need for exact quantitation. Challenges continue to remain in terms of availability of reference standard material as well as relevant internal standards.
    Keywords:  Identification; Lipidomics; Mass spectrometry; Quantitation
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_6
  6. Methods Mol Biol. 2019 ;1978 13-26
    Nemkov T, Reisz JA, Gehrke S, Hansen KC, D'Alessandro A.
      Metabolomics has emerged in the past decade as a highly attractive and impactful technique for phenotype-level profiling in diverse biological applications. Most recently, the dual developments of high-throughput analytical techniques along with dramatically increased sensitivity of high-resolution mass spectrometers have enabled the routine analysis of hundreds of unique samples per day. We have previously reported a robust 3 min isocratic metabolomics platform for the quantification of amino acids and the key pathways of central carbon and nitrogen metabolism. Building on this work, we describe here a 5 min reverse phase gradient followed by global, untargeted profiling of the hydrophilic metabolome. In addition to observing those metabolites measured in the 3 min run, the use of the longer gradient run here also allows for coverage of less polar compounds such as fatty acids and acylcarnitines, both key players in mitochondrial and lipid metabolism, without a significant sacrifice in throughput.
    Keywords:  Gradient; High-throughput; Isocratic; Mass spectrometry; Untargeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_2
  7. Metabolomics. 2019 May 23. 15(6): 83
    Wilkins J, Sakrikar D, Petterson XM, Lanza IR, Trushina E.
      INTRODUCTION: Patient-derived skin fibroblasts offer a unique translational model to study molecular mechanisms of multiple human diseases. Metabolomics profiling allows to track changes in a broad range of metabolites and interconnected metabolic pathways that could inform on molecular mechanisms involved in disease development and progression, and on the efficacy of therapeutic interventions. Therefore, it is important to establish standardized protocols for metabolomics analysis in human skin fibroblasts for rigorous and reliable metabolic assessment.OBJECTIVES: We aimed to develop an optimized protocol for concurrent measure of the concentration of amino acids, acylcarnitines, and components of the tricarboxylic acid (TCA) cycle in human skin fibroblasts using gas (GC) and liquid chromatography (LC) coupled with mass spectrometry (MS).
    METHODS: The suitability of four different methods of cell harvesting on the recovery of amino acids, acylcarnitines, and TCA cycle metabolites was established using GC/MS and LC/MS analytical platforms. For each method, metabolite stability was determined after 48 h, 2 weeks and 1 month of storage at - 80 °C.
    RESULTS: Harvesting cells in 80% methanol solution allowed the best recovery and preservation of metabolites. Storage of samples in 80% methanol up to 1  month at - 80 °C did not significantly impact metabolite concentrations.
    CONCLUSION: We developed a robust workflow for metabolomics analysis in human skin fibroblasts suitable for a high-throughput multiplatform analysis. This method allows a direct side-by-side comparison of metabolic changes in samples collected at different time that could be used for studies in large patient cohorts.
    Keywords:  Acylcarnitines; Amino acids; Cell harvesting; Metabolomics; Skin fibroblasts; TCA cycle
    DOI:  https://doi.org/10.1007/s11306-019-1544-z
  8. Methods Mol Biol. 2019 ;1996 259-272
    Puchalska P, Crawford PA.
      The progression of nonalcoholic fatty liver disease (NAFLD) increases the risks of cirrhosis and cardiovascular disease. Marked alteration of both cytosolic and mitochondrial metabolism, and in combination with insulin resistance, increases hepatic glucose production. Utilization of stable isotope tracers to study liver metabolism offers deep insight into rearrangements of metabolic pathways and substrate-product relationships under the conditions leading to fatty liver and induced by diseases, drugs, toxins, or genetic manipulations. Isotope tracing untargeted metabolomics (ITUM) recently emerged as a powerful platform in which the label can be tracked in an untargeted fashion, revealing the penetration of substrates into metabolic pathways, even at low abundance. Here, we describe a protocol that can be utilized to study the changes in utilization of any labeled substrate toward a wide range of metabolites either in isolated liver cells or whole liver tissue under conditions mimicking various stages of fatty liver disease. Furthermore, a routine protocol for extraction, separation, and mass spectrometric detection of isotopically labeled metabolites in an untargeted or targeted fashion. An informatic approach to analyze stable isotope untargeted metabolomic datasets is also described.
    Keywords:  Fatty liver disease; Isotope tracking untargeted metabolomics; Mass spectrometry; Stable isotopes; Untargeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_20
  9. Eur Rev Med Pharmacol Sci. 2019 May;pii: 17823. [Epub ahead of print]23(9): 3940-3950
    Li SS, Liu Y, Li H, Wang LP, Xue LF, Yin GS, Wu XS.
      OBJECTIVE: The aim of the study was to investigate the endogenous metabolites of patients with psoriasis vulgaris which will be helpful for the diagnosis of the disease and to provide the evidence of pathogenesis and the formulation for the individualized dosage regimen.PATIENTS AND METHODS: This study investigated the plasma metabolomic profiling between the psoriasis vulgaris patients (N=12) and the healthy volunteers (N=12) using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) metabolomic techniques. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to identify and visualize the metabolic data clusters.
    RESULTS: A total of 22 differential metabolites contributing to the clusters were identified, among which the levels of threonine (p<0.001), leucine (p<0.001), phenylalanine (p<0.001), tryptophan (p=0.018), palmitamide (p<0.001), Linoleic amide (p<0.001), oleamide (p<0.001), stearamide (p<0.001), cis-11- eicosenamide (p< 0.001), trans-13-Docosenamide (p<0.001), uric acid (p=0.034), LysoPC (16:0) (p<0.001), LysoPC (18:3) (p<0.001), LysoPC (18:2) (p=0.024), LysoPC (18:1) (P=0.012) and LysoPC (18:0) (p=0.002) were significantly higher in the plasma of psoriasis vulgaris patients compared with the healthy controls, whereas oleic acid (p<0.001), arachidonic acid (p<0.001) and N-linoleoyl taurine (p<0.001) were significantly lower. These biomarkers are related to glucose metabolism, lipid metabolism, amino acid metabolism, nucleic acid metabolism and so on.
    CONCLUSIONS: The data suggest that psoriasis vulgaris patients may have disrupted lipid and amino acid metabolism, as well as inflammation and functional lesions in the liver and kidney. This study deepens the understanding of psoriasis vulgaris pathogenesis and proposes novel ideas and methods for auxiliary diagnosis and treatment of the disease.
    DOI:  https://doi.org/10.26355/eurrev_201905_17823
  10. Methods Mol Biol. 2019 ;1994 119-130
    Artati A, Prehn C, Adamski J.
      Metabolomics, a comprehensive analysis of metabolites in biological specimens (e.g., cells, body fluids, tissues, exhaled air, plants), offers promising tools in health, nutrition, biotechnology, and food sciences. Here we describe methods of LC-MS/MS-based analyses for cell metabolomics. Using methods employed in this section, over 1000 endogenous and exogenous metabolites can be detected, annotated, and quantified relatively by nontargeted analysis approach, whereas targeted metabolomics analysis enables us to quantify 188 endogenous metabolites.
    Keywords:  Cell culture metabolomics; LC-MS/MS-based metabolomics; Mass spectrometry; Metabolomics; Nontargeted metabolomics; Targeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-4939-9477-9_10
  11. Biomolecules. 2019 May 23. pii: E200. [Epub ahead of print]9(5):
    Khadka M, Todor A, Maner-Smith KM, Colucci JK, Tran V, Gaul DA, Anderson EJ, Natrajan MS, Rouphael N, Mulligan MJ, McDonald CE, Suthar M, Li S, Ortlund EA.
      Liquid-chromatography mass spectrometry is commonly used to identify and quantify metabolites from biological samples to gain insight into human physiology and pathology. Metabolites and their abundance in biological samples are labile and sensitive to variations in collection conditions, handling and processing. Variations in sample handling could influence metabolite levels in ways not related to biology, ultimately leading to the misinterpretation of results. For example, anticoagulants and preservatives modulate enzyme activity and metabolite oxidization. Temperature may alter both enzymatic and non-enzymatic chemistry. The potential for variation induced by collection conditions is particularly important when samples are collected in remote locations without immediate access to specimen processing. Data are needed regarding the variation introduced by clinical sample collection processes to avoid introducing artifact biases. In this study, we used metabolomics and lipidomics approaches paired with univariate and multivariate statistical analyses to assess the effects of anticoagulant, temperature, and time on healthy human plasma samples collected to provide guidelines on sample collection, handling, and processing for vaccinology. Principal component analyses demonstrated clustering by sample collection procedure and that anticoagulant type had the greatest effect on sample metabolite variation. Lipids such as glycerophospholipids, acylcarnitines, sphingolipids, diacylglycerols, triacylglycerols, and cholesteryl esters are significantly affected by anticoagulant type as are amino acids such as aspartate, histidine, and glutamine. Most plasma metabolites and lipids were unaffected by storage time and temperature. Based on this study, we recommend samples be collected using a single anticoagulant (preferably EDTA) with sample processing at <24 h at 4 °C.
    Keywords:  anticoagulants; lipidomics; metabolomics; sample collection; storage conditions; vaccine
    DOI:  https://doi.org/10.3390/biom9050200
  12. J Biol Chem. 2019 May 24. pii: jbc.RA119.007784. [Epub ahead of print]
    Lypova N, Telang S, Chesney J, Imbert-Fernandez Y.
      Constitutive activation of the epidermal growth factor receptor (EGFR) due to somatic mutations of the EGFR gene is commonly observed in tumors of non-small cell lung cancer (NSCLC) patients. Consequently, tyrosine kinase inhibitors (TKI) targeting the EGFR are among the most effective therapies for patients with sensitizing EGFR mutations. Clinical responses to the EGFR-targeting TKIs are evaluated through 2-[18F]-fluoro-2-deoxy-glucose (18FDG-PET) uptake, which is decreased in patients responding favorably to therapy and is positively correlated with survival. Recent studies have reported that EGFR signaling drives glucose metabolism in NSCLC cells; however, the precise downstream effectors required for this EGFR-driven metabolic effect are largely unknown. 6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase  (PFKFB3) is an essential glycolytic regulator that is consistently overexpressed in lung cancer. Here, we found that PFKFB3 is an essential target of EGFR signaling and that PFKFB3 activation is required for glycolysis stimulation upon EGFR activation. We demonstrate that exposing NSCLC cells harboring either wildtype or mutated EGFR to EGF rapidly increases PFKFB3 phosphorylation, expression, and activity, and that PFKFB3 inhibition markedly reduces the EGF-mediated increase in glycolysis. Furthermore, we found that prolonged NSCLC cell exposure to the TKI erlotinib drives PFKFB3 expression and that chemical PFKFB3 inhibition synergizes with erlotinib in increasing erlotinib's anti-proliferative activity in NSCLC cells. We conclude that PFKFB3 has a key role in mediating glucose metabolism and survival of NSCLC cells in response to EGFR signaling. These results support the potential clinical utility of using PFKFB3 inhibitors in combination with EGFR-TKIs to manage NSCLC.
    Keywords:  6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase; PFKFB3; epidermal growth factor (EGF); epidermal growth factor receptor (EGFR); erlotinib; glycolysis; lung cancer; metabolism; tumorigenesis; tyrosine kinase inhibitor
    DOI:  https://doi.org/10.1074/jbc.RA119.007784
  13. Methods Mol Biol. 2019 ;1978 121-135
    Reisz JA, Zheng C, D'Alessandro A, Nemkov T.
      Liquid chromatography coupled to mass spectrometry (LC-MS)-based metabolomics and lipidomics offers invaluable tools to qualitatively and quantitatively study biological systems. Historically, unbiased (or discovery) analysis has been performed independently of targeted, quantitative analysis such as multiple reaction monitoring (MRM). These practices have been aptly carried out based on technical limitations of each assay. The wide mass scanning ranges typical of discovery approaches limit assay sensitivity, while targeted methods that improve analyte detection do not acquire data on ions not included in the targeted assay design. Recent improvements to quadrupole-Orbitrap technology have improved both scan speed as well as sensitivity, thus making these instruments more robust. By combining the improved robustness and coverage with stable isotope dilution (SID) techniques, advantages of the separate assays can now be realized in a single run, thereby improving the throughput of this type of analysis.
    Keywords:  Absolute quantification; Bile acids; Gradient; High-throughput; Mass spectrometry; Oxylipids; Untargeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_8
  14. Methods Mol Biol. 2019 ;1978 55-77
    López-Gonzálvez Á, Godzien J, García A, Barbas C.
      Although capillary electrophoresis (CE) coupled to mass spectrometry (MS) is a separation technique not extensively implemented, it offers differential possibilities in the study of polar and ionic metabolites in complex matrices with minimum sample treatment. However, in order to get successful results, some efforts at early stages and following specific recommendations are necessary.In this chapter, we describe our updated and well-tested methods for untargeted metabolomics using CE-MS-TOF for common biological samples: urine, serum or plasma, feces, tissues, and cells. Sample treatment, as well as separation and detection conditions are described in detail and other steps in the workflow for untargeted metabolomics are also explained. Special attention is paid to instrumental setup and advices for daily practice.Characteristic electropherograms obtained with each type of sample are depicted as well as groups of metabolites easily measured by this technique. Their global or individual comparisons have been given undoubtedly important information to unveil altered metabolic pathways, diagnosis, and prognosis or biomarker discovery in the study of diseases or conditions over decades.
    Keywords:  Biological samples; CE-MS; Fingerprinting; Polar metabolites; Untargeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_5
  15. J Steroid Biochem Mol Biol. 2019 May 18. pii: S0960-0760(19)30123-2. [Epub ahead of print]
    Denver N, Khan S, Homer NZM, MacLean MR, Andrew R.
      Estrogens and their bioactive metabolites play key roles in regulating diverse processes in health and disease. In particular, estrogen and estrogenic metabolites have shown both protective and non-protective effects on disease pathobiology, implicating the importance of this steroid pathway in disease diagnostics and monitoring. All estrogens circulate in a wide range of concentrations, which in some patient cohorts can be extremely low. However, elevated levels of E2 are also reported in disease. For example, in pulmonary arterial hypertension (PAH) levels are elevated in men with idiopathic PAH and in postmenopausal women with PAH. Conventional immunoassay techniques have been under scrutiny for some time with their selectivity, accuracy and precision coming into question. Analytical methodologies such as gas and liquid chromatography coupled to single and tandem mass spectrometric approaches (GC-MS, GC-MS/MS, LC-MS and LC-MS/MS) have been developed to quantify endogenous estrogens and in some cases their bioactive metabolites in biological fluids such as urine, serum, plasma and saliva. Liquid-liquid or solid-phase extraction approaches are favoured with derivatization remaining a necessity for lower volumes of sample. The limits of quantitation of individual assays vary but are commonly in the range of 0.5 - 5 pg/mL for estrone and estradiol, with limits of their bioactive metabolites being higher. This review provides an overview of current approaches for measurement of estrogens in biological matrices by MS, highlighting the advances in this field and the challenges remaining for routine use in the clinical and research environment.
    Keywords:  derivatization; estrogen; extraction; gas chromatography tandem mass spectrometry; liquid chromatography tandem mass spectrometry
    DOI:  https://doi.org/10.1016/j.jsbmb.2019.04.022
  16. Methods Mol Biol. 2019 ;1978 287-299
    Yao L, Sheflin AM, Broeckling CD, Prenni JE.
      Gas chromatography and liquid chromatography coupled to mass spectrometry are used extensively in untargeted metabolomics, which involves the profiling of small metabolites in biological samples. The complex raw dataset produced from untargeted metabolomics requires proper processing before it can be statistically analyzed and interpreted. This chapter describes a high-throughput data processing workflow routinely used in our laboratory, including feature detection and alignment, data reduction, and spectral-matching-based annotation. This semiautomated workflow uses vendor neutral data file formats and freely available data processing tools and therefore can be readily implemented on datasets acquired from instruments of different vendors.
    Keywords:  GC-MS; LC-MS; RAMClustR; RAMSearch; Untargeted metabolomics; XCMS
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_18
  17. Methods Mol Biol. 2019 ;1996 41-46
    Mendez R, Del Carmen Piqueras M, Raskind A, de Jong FA, Beecher C, Bhattacharya SK, Banerjee S.
      Various research strategies involving biomarker discovery and mechanistic studies in system biology depend on reproducible and reliable quantification of all metabolites from tissue(s) of interest. Contemporary analytical methods rely on mass spectrometry-based targeted and/or untargeted metabolomics platforms. The robustness of these analyses depends on the cleanliness of the samples, accuracy of the database, resolution of the instrument, and, the most variable of the list, the personal preferences of the researcher and the instrument operator. In this chapter, we introduce a simple method to prepare murine liver samples and carry it through the Isotope Ratio Outlier Analysis (IROA®) pipeline. This pipeline encompasses sample preparation, LC-MS-based peak acquisition, proprietary software-based library creation, normalization, and quantification of metabolites. IROA® offers a unique platform to create and normalize a local library and account for run-to-run variability over years of acquisition using the internal standards (IROA®-IS) and long-term reference standards (IROA®-LTRS).
    Keywords:  IS; Isotope ratio outlier analysis; LC-MS; LTRS; Mass spectrometry; Metabolomics; Quantitative metabolomics; Variability
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_4
  18. J Biol Chem. 2019 May 19. pii: jbc.RA119.007983. [Epub ahead of print]
    Yam M, Engel AL, Wang Y, Zhu S, Hauer A, Zhang R, Lohner D, Huang J, Dinterman M, Zhao C, Chao JR, Du J.
      The retinal pigment epithelium (RPE) is a monolayer of pigmented cells between the choroid and the retina. RPE dysfunction underlies many retinal degenerative diseases, including age-related macular degeneration, the leading cause of age-related blindness. To perform its various functions in nutrient transport, phagocytosis of the outer segment, and cytokine secretion, the RPE relies on an active energy metabolism. We previously reported that human RPE cells prefer proline as a nutrient and transport proline-derived metabolites to the apical, or retinal, side. In this study, we investigated how RPE utilizes proline in vivo and why proline is a preferred substrate. By using 13C proline labeling both ex vivo and in vivo, we found that the retina rarely uses proline directly, whereas the RPE utilizes it at a high rate, exporting proline-derived mitochondrial intermediates for use by the retina. We observed that in primary human RPE cell culture, proline is the only amino acid whose uptake increases with cellular maturity. In human RPE, proline was sufficient to stimulate de novo serine synthesis, increase reductive carboxylation, and protect against oxidative damage. Blocking proline catabolism in RPE impaired glucose metabolism and glutathione production. Notably, in an acute model of RPE-induced retinal degeneration, dietary proline improved visual function. In conclusion, proline is an important nutrient that supports RPE metabolism and the metabolic demand of the retina.
    Keywords:  age-related macular degeneration (AMD); amino acid; cell metabolism; glucose metabolism; mitochondrial metabolism; oxidative stress; retinal metabolism; tricarboxylic acid cycle (TCA cycle) (Krebs cycle); visual function
    DOI:  https://doi.org/10.1074/jbc.RA119.007983
  19. Methods Mol Biol. 2019 ;1996 61-73
    Petucci C, Culver JA, Kapoor N, Sessions EH, Divlianska D, Gardell SJ.
      Pyridine nucleotides which include NAD+, NADH, NADP, and NADPH play vital roles in many different biological processes. These metabolites can be accurately quantified in a wide variety of biological samples using LC-MS/MS. The quality and precision of these measurements was enhanced using heavy isotope-labeled internal standards and carefully crafted protocols for sample processing.
    Keywords:  Mass spectrometry; NAD+; NADH; NADP; NADPH; Pyridine nucleotides
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_7
  20. Biochim Biophys Acta Gen Subj. 2019 May 20. pii: S0304-4165(19)30132-1. [Epub ahead of print]
    Willems AP, Sun L, Schulz MA, Tian W, Ashikov A, van Scherpenzeel M, Hermans E, Clausen H, Yang Z, Lefeber DJ.
      BACKGROUND: Sialylation of glycoproteins and glycolipids is important for biological processes such as cellular communication, cell migration and protein function. Biosynthesis of CMP-sialic acid, the essential substrate, comprises five enzymatic steps, involving ManNAc and sialic acid and their phosphorylated forms as intermediates. Genetic diseases in this pathway result in different and tissue-restricted phenotypes, which is poorly understood.METHODS AND RESULTS: We aimed to study the mechanisms of sialic acid metabolism in knockouts (KO) of the sialic acid pathway in two independent cell lines. Sialylation of cell surface glycans was reduced by KO of GNE (UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase), NANS (sialic acid synthase) and CMAS (N-acylneuraminate cytidylyltransferase) genes, but was largely unaffected in NANP (N-acylneuraminate-9-phosphatase) KO, as studied by MAA and PNA lectin binding. NANP is the third enzyme in sialic acid biosynthesis and dephosphorylates sialic acid 9-phosphate to free sialic acid. LC-MS analysis of sialic acid metabolites showed that CMP-sialic acid was dramatically reduced in GNE and NANS KO cells and undetectable in CMAS KO. In agreement with normal cell surface sialylation, CMP-sialic acid levels in NANP KO were comparable to WT cells, even though sialic acid 9-phosphate, the substrate of NANP accumulated. Metabolic flux analysis with 13C6-labelled ManNAc showed a lower, but significant conversion of ManNAc into sialic acid.
    CONCLUSIONS: Our data provide evidence that NANP activity is not essential for de novo sialic acid production and point towards an alternative phosphatase activity, bypassing NANP.
    GENERAL SIGNIFICANCE: This report contributes to a better understanding of sialic acid biosynthesis in humans.
    Keywords:  Carbohydrate metabolism; Glycosylation; Inborn errors of metabolism; Nucleotide sugars; Sialic acid
    DOI:  https://doi.org/10.1016/j.bbagen.2019.05.011
  21. Methods Mol Biol. 2019 ;1978 403-430
    Herrero P, Rodríguez MÁ, Ras MR, Del Pino A, Arola L, Canela N.
      The metabolic and physiologic responses to healthy dietary habits and physical exercise have become an increasingly interesting research area, since equilibrated diet and regular physical activity are commonly recommended for their antioxidant capacity and for the prevention and treatment of several disorders as insulin resistance, dyslipidemia, obesity, and hypertension that may result in cardiovascular disease and type II diabetes.Nutritional and exercise-induced responses and the biological mechanisms that explain these associations have been tackled by several researchers using metabolomic approaches that have emerged as a powerful tool to comprehensively evaluate individual metabolic signatures, analyzing metabolome composition in serum, urine, stool, or tissue samples.The overview of the wide range of metabolites related to dietary and to physical training interventions reported from numerous human or animal studies endorses the complexity for assessing metabolic changes and compound identification, and a combination of targeted and non-targeted global profiling studies is recommended for increasing the understanding of nutrition and exercise metabolic mechanisms.The present protocol attempt to identify variations in human blood circulating metabolites with a multiplatform global analysis based on LC-MS, GC-MS, and NMR, combining targeted and untargeted strategies, to complete the holistic understanding of the serum metabolome.
    Keywords:  Diet; Gas chromatography; Liquid chromatography; Mass spectrometry; Metabolomics; Nuclear magnetic resonance; Nutrition; Physical training
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_25
  22. Neoplasia. 2019 May 17. pii: S1476-5586(18)30666-3. [Epub ahead of print]21(7): 665-675
    Chen S, Yang X, Yu M, Wang Z, Liu B, Liu M, Liu L, Ren M, Qi H, Zou J, Vucenik I, Zhu WG, Luo J.
      SIRT3 is a major mitochondrial deacetylase, which regulates various metabolic pathways by deacetylation; however, the effect of SIRT3 on proline metabolism is not reported. Pyrroline-5-carboxylate reductase 1 (PYCR1) participates in proline synthesis process by catalyzing the reduction of P5C to proline with concomitant generation of NAD+ and NADP+. PYCR1 is highly expressed in various cancers, and it can promote the growth of tumor cells. Here, through immunoprecipitation and mass spectrometry, we found that PYCR1 is in SIRT3's interacting network. PYCR1 directly binds to SIRT3 both in vivo and in vitro. CBP is the acetyltransferase for PYCR1, whereas SIRT3 deacetylates PYCR1. We further identified that K228 is the major acetylation site for PYCR1. Acetylation of PYCR1 at K228 reduced its enzymatic activity by impairing the formation of the decamer of PYCR1. As a result, acetylation of PYCR1 at K228 inhibits cell proliferation, while deacetylation of PYCR1 mediated by SIRT3 increases PYCR1's activity. Our findings on the regulation of PYCR1 linked proline metabolism with SIRT3, CBP and cell growth, thus providing a potential approach for cancer therapy.
    DOI:  https://doi.org/10.1016/j.neo.2019.04.008
  23. Methods Mol Biol. 2019 ;1978 269-283
    Violante S, Berisa M, Thomas TH, Cross JR.
      Stable isotope tracing allows a metabolic substrate to be followed through downstream biochemical reactions, thereby providing unparalleled insights into the metabolic wiring of cells. This approach stops short of modeling absolute fluxes but is relatively straightforward and has become increasingly accessible due to the widespread adoption of high-resolution mass spectrometers. Analysis of both dynamic and steady-state labeling patterns in downstream metabolites provides valuable qualitative information as to their origin and relative rates of production. Stable isotope tracing is, therefore, a powerful way to understand the impact of genetic alterations and defined perturbations on metabolism. In this chapter, we describe a liquid chromatography-mass spectrometry (LC-MS) protocol for stable isotope tracing using 13C-L-arginine in a macrophage cell line. A similar approach can be used to follow other stable isotope tracers, and notes are provided with advice on how this protocol can be generalized for use in other settings.
    Keywords:  Fluxomics; Metabolomics; Stable isotope; Tracing experiments
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_17
  24. Metabolites. 2019 May 22. pii: E102. [Epub ahead of print]9(5):
    Silva C, Perestrelo R, Silva P, Tomás H, Câmara JS.
      Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and environmental factors. Nowadays, the available diagnostic tools have aided in the early detection of BC leading to the improvement of survival rates. However, better detection tools for diagnosis and disease monitoring are still required. In this sense, metabolomic NMR, LC-MS and GC-MS-based approaches have gained attention in this field constituting powerful tools for the identification of potential biomarkers in a variety of clinical fields. In this review we will present the current analytical platforms and their applications to identify metabolites with potential for BC biomarkers based on the main advantages and advances in metabolomics research. Additionally, chemometric methods used in metabolomics will be highlighted.
    Keywords:  analytical platforms; breast cancer; chemometric methods; omics
    DOI:  https://doi.org/10.3390/metabo9050102
  25. J Cell Biochem. 2019 May 20.
    Aftab S, Shakoori AR.
      Studying the metabolic pathways of cancer cells is considered as a key to control cancer malignancies and open windows for effective drug discovery against cancer. Of all the properties of a tumor, metastasis potential is a defining characteristic. Metastasis is controlled by a variety of factors that directly control the expression of cell adhesion proteins. In this study we have investigated the expression of cell to cell and cell to matrix adhesion protein genes during the initial phases of attachment of human glioblastoma cancer cell line SF767 (66Y old human female: UCSF Neurosurgery Tissue Bank) to the attachment surface under (Cell culture treated polystyrene plate bottom) glucose-rich and glucose-starved conditions. The aim was to imitate the natural microenvironment of glucose availability to cancer cells inside a tumor that triggers epithelial to mesenchymal transition (EMT). In this study, we have observed the gene expression of epithelial and mesenchymal isoforms of cadherin (E-CAD and N-CAD) and Ig like cell adhesion molecules (E-CAM and N-CAM) along with Integrin family subunits for the initial attachment of cancer cells. We observed that high glucose environments promoted cell survival and cell adhesion, whereas low glucose accelerated EMT by downregulating the expression level of integrin, E-CAD, and N-CAD, and upregulation of N-CAM during early period of cell adhesion. Low glucose availability also downregulated variety of structural and regulatory genes, such as zinc finger E-box binding home box 1A), cytokeratin, Snail, and β catenin, and upregulation of hypoxia-inducible factor 1, matrix metalloprotease 13/Collagenase 3, vimentim, p120, and fructose 1,6 bisphosphatase. Glucose conditions are more efficient for cancer studies in this case glioblastoma cells.
    Keywords:  cancer nutrient tolerance. cross-talk in cell adhesion molecules; cell adhesion molecules; glucose metabolism
    DOI:  https://doi.org/10.1002/jcb.28940
  26. Methods Mol Biol. 2019 ;1978 199-217
    Seim GL, Britt EC, Fan J.
      Arginine metabolism is linked to several important metabolic processes, and reprogramming of arginine metabolism occurs in various physiological and pathological conditions. Here we describe a method, using a LC-MS-based metabolomics and 15N4-arginine tracing approach, to quantitatively analyze arginine metabolism. This method can reliably quantify the abundance of important intermediates and fluxes of major metabolic reactions in arginine metabolism in a variety of cultured mammalian cell models.
    Keywords:  Arginine; Isotopic labeling; LC-MS; Metabolic flux analysis
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_13
  27. Methods Mol Biol. 2019 ;1978 301-321
    Agrawal S, Kumar S, Sehgal R, George S, Gupta R, Poddar S, Jha A, Pathak S.
      Analysis of large metabolomic datasets is becoming commonplace with the increased realization of the role that metabolites play in biology and pathophysiology. While there are many open-source analysis tools to extract peaks from liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and tandem mass spectrometry (LC-MS/MS) data, these tools are not very interactive and are suboptimal when a large number of samples are to be analyzed. El-MAVEN is an open-source analysis platform that extends MAVEN and provides fast, powerful, and interactive analysis capabilities especially for datasets containing over 100 samples. The El-MAVEN workflow is easy to use with just four steps from loading data to exporting of the results. Advanced analysis and software techniques such as multiprocessing, machine learning, and reduction of memory leaks are implemented so as to provide a seamless and interactive user experience. Results from El-MAVEN can be exported in a range of formats allowing continued analysis on other platforms. Additionally, El-MAVEN is also fully integrated with Polly™, a cloud-based analysis platform that provides a range of tools for flux analysis and integrative-omics analysis. El-MAVEN is a powerful tool that enables fast and efficient analysis of large metabolomic datasets to accelerate the process of gaining insight from raw data.
    Keywords:  Bioinformatics; Data analysis; Data processing; Liquid chromatography-mass spectrometry; MAVEN; Mass spectrometry; Metabolic pathways; Metabolomics
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_19
  28. Methods Mol Biol. 2019 ;1978 187-195
    Gevi F, Fanelli G, Zolla L, Rinalducci S.
      Untargeted metabolomics is a useful approach for the simultaneous analysis of a vast array of compounds from a single extract. Metabolomic profiling is the relative multi-parallel quantification of a mixture of low molecular weight compounds, or classes of compounds, and it is most often performed by using ultra performance liquid chromatography (UPLC) coupled with mass spectrometry (MS). Being an extension of the classical targeted methods, this approach allows a broader view of the main biochemical events within a particular sample. This chapter exemplifies and provides experimental details on the basic steps to perform a non-targeted metabolomic analysis on plant leaf tissues: sample collection and homogenization, extraction of metabolites, raw data acquisition, and processing into formats for data mining and informatics. In particular, the approach was applied to two spring wheat varieties with different level of drought tolerance (Kavir, drought-resistant; Bahar, drought-sensitive) developed by the CIMMYT (International Center for the Improvement of Corn and Wheat).
    Keywords:  Mass spectrometry; Metabolomics; Plant metabolite extraction; UPLC; Wheat
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_12
  29. Methods Mol Biol. 2019 ;1978 3-12
    Hayton S, Trengove RD, Maker GL.
      Metabolomics is an analytical technique that investigates the small molecules present within a biological system. Metabolomics of cultured cells allows profiling of the metabolic chemicals involved in a cell type-specific system and the response of that metabolome to external challenges, such as change in environment or exposure to drugs or toxins. The numerous benefits of in vitro metabolomics include a much greater control of external variables and reduced ethical concerns. There is potential for metabolomics of mammalian cells to uncover new information on mechanisms of action for drugs or toxins or to provide a more sensitive, human-specific early risk assessment in drug development or toxicology investigations. One way to achieve stronger biological outcomes from metabolomic data is via the use of these mammalian cultured cell models, particularly in a high-throughput context. With the sensitivity and quantity of data that metabolomics is able to provide, it is important to ensure that the sampling techniques have minimal interference when it comes to interpretation of any observed shifts in the metabolite profile. Here we describe a sampling procedure designed to ensure that the effects seen in metabolomic analyses are explained fully by the experimental factor and not other routine culture-specific activities.
    Keywords:  Adherent cells; Cell culture; Experimental design; Extracellular; Intracellular; Mammalian cells; Metabolite extraction; Metabolomics; Quenching; Sample preparation
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_1
  30. Cancer Immunol Immunother. 2019 May 22.
    Kesarwani P, Prabhu A, Kant S, Chinnaiyan P.
      Glioblastoma (GBM) is one of the most aggressive tumors. Numerous studies in the field of immunotherapy have focused their efforts on identifying various pathways linked with tumor-induced immunosuppression. Recent research has demonstrated that metabolic reprogramming in a tumor can contribute towards immune tolerance. To begin to understand the interface between metabolic remodeling and the immune-suppressive state in GBM, we performed a focused, integrative analysis coupling metabolomics with gene-expression profiling in patient-derived GBM (n = 80) and compared them to low-grade astrocytoma (LGA; n = 28). Metabolic intermediates of tryptophan, arginine, prostaglandin, and adenosine emerged as immuno-metabolic nodes in GBM specific to the mesenchymal and classical molecular subtypes of GBM. Integrative analyses emphasized the importance of downstream metabolism of several of these metabolic pathways in GBM. Using CIBERSORT to analyze immune components from the transcriptional profiles of individual tumors, we demonstrated that tryptophan and adenosine metabolism resulted in an accumulation of Tregs and M2 macrophages, respectively, and was recapitulated in mouse models. Furthermore, we extended these findings to preclinical models to determine their potential utility in defining the biologic and/or immunologic consequences of the identified metabolic programs. Collectively, through integrative analysis, we uncovered multifaceted ways by which metabolic reprogramming may contribute towards immune tolerance in GBM, providing the framework for further investigations designed to determine the specific immunologic consequence of these metabolic programs and their therapeutic potential.
    Keywords:  Adenosine; Arginase; Glioblastoma; Immune metabolism; Prostaglandin; Tryptophan
    DOI:  https://doi.org/10.1007/s00262-019-02347-3
  31. Methods Mol Biol. 2019 ;1978 447-456
    Marciano DP, Snyder MP.
      The human metabolome is the cumulative product of ingested metabolites and those produced by the body and its microbiota. Together these metabolites can dynamically report on the health and disease state of an individual, as well as their response to drug treatments and other external perturbations. Profiling metabolites in human body fluids provides an opportunity to identify biomarkers and stratify patients for personalized treatments but requires the development of high-throughput approaches compatible with large cohort and longitudinal studies. Here we review in detail sample preparation and analytical liquid chromatography-mass spectrometry (LC-MS) methods to measure the broad chemical diversity of metabolites found in human plasma and urine.
    Keywords:  HILIC; LC-MS; Liquid chromatography-mass spectrometry; Metabolites; Personalized metabolomics; Plasma; Reverse phase; Urine
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_27
  32. Methods Mol Biol. 2019 ;1996 1-15
    Najdekr L, Blanco GR, Dunn WB.
      Ultra performance liquid chromatography-mass spectrometry (UPLC-MS) is the most frequently applied analytical platform in the untargeted metabolomic study of mammalian urine. Here we describe two complementary UPLC-MS methods for metabolomic analysis or urine, a reversed phase C18 method and a hydrophilic interaction liquid chromatography (HILIC) method. We discuss the inclusion of pooled quality control (QC) samples and a recommended analysis list construction. Up to 96 injections can be performed every 24 h, and up to 2000 metabolites can be routinely detected.
    Keywords:  HILIC; Metabolic phenotyping; QC samples; Reversed phase C18; Ultra performance liquid chromatography-mass spectrometry; Untargeted metabolomics; Urine
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_1
  33. Methods Mol Biol. 2019 ;1978 155-165
    Li H, Tennessen JM.
      The fruit fly Drosophila melanogaster has emerged as an ideal system in which to study 2-hydroxyglutarate (2HG) metabolism. Unlike many mammalian tissues and cell lines, which primarily accumulate D- or L-2HG as the result of genetic mutations or metabolic stress, Drosophila larvae accumulate high concentrations of L-2HG during normal larval growth. As a result, flies represent one of the few model systems that allows for studies of endogenous L-2HG metabolism. Moreover, the Drosophila genome not only encodes key enzymes involved in the synthesis and degradation of D-2HG, but the fly has also been used as to investigate the in vivo effects of oncogenic isocitrate dehydrogenase 1 and 2 (IDH1/2) mutations. All of these studies, however, rely on mass spectrometry-based methods to distinguish between the D- and L-2HG enantiomers. While such approaches are common among labs studying mammalian cell culture, few Drosophila studies have attempted to resolve and measure the individual 2HG enantiomers. Here we describe a highly reproducible gas chromatography-mass spectrometry (GC-MS)-based protocol that allows for quantitative measurements of both 2HG enantiomers in Drosophila homogenates.
    Keywords:  2-Hydroxyglutarate; Drosophila; Gas chromatography-mass spectrometry; Metabolomics; Oncometabolite
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_10
  34. Int J Mol Sci. 2019 May 22. pii: E2524. [Epub ahead of print]20(10):
    Kalita-de Croft P, Straube J, Lim M, Al-Ejeh F, Lakhani SR, Saunus JM.
      Patients with brain-metastatic breast cancer face a bleak prognosis marked by morbidity and premature death. A deeper understanding of molecular interactions in the metastatic brain tumour microenvironment may inform the development of new therapeutic strategies. In this study, triple-negative MDA-MB-231 breast cancer cells or PBS (modelling traumatic brain injury) were stereotactically injected into the cerebral cortex of NOD/SCID mice to model metastatic colonization. Brain cells were isolated from five tumour-associated samples and five controls (pooled uninvolved and injured tissue) by immunoaffinity chromatography, and proteomic profiles were compared using the Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) discovery platform. Ontology and cell type biomarker enrichment analysis of the 125 differentially abundant proteins (p < 0.05) showed the changes largely represent cellular components involved in metabolic reprogramming and cell migration (min q = 4.59 × 10-5), with high-throughput PubMed text mining indicating they have been most frequently studied in the contexts of mitochondrial dysfunction, oxidative stress and autophagy. Analysis of mouse brain cell type-specific biomarkers suggested the changes were paralleled by increased proportions of microglia, mural cells and interneurons. Finally, we orthogonally validated three of the proteins in an independent xenograft cohort, and investigated their expression in craniotomy specimens from triple-negative metastatic breast cancer patients, using a combination of standard and fluorescent multiplex immunohistochemistry. This included 3-Hydroxyisobutyryl-CoA Hydrolase (HIBCH), which is integral for gluconeogenic valine catabolism in the brain, and was strongly induced in both graft-associated brain tissue (13.5-fold by SWATH-MS; p = 7.2 × 10-4), and areas of tumour-associated, reactive gliosis in human clinical samples. HIBCH was also induced in the tumour compartment, with expression frequently localized to margins and haemorrhagic areas. These observations raise the possibility that catabolism of valine is an effective adaptation in metastatic cells able to access it, and that intermediates or products could be transferred from tumour-associated glia. Overall, our findings indicate that metabolic reprogramming dominates the proteomic landscape of graft-associated brain tissue in the intracranial MDA-MB-231 xenograft model. Brain-derived metabolic provisions could represent an exploitable dependency in breast cancer brain metastases.
    Keywords:  brain metastasis; metabolism; proteomics; tumour microenvironment
    DOI:  https://doi.org/10.3390/ijms20102524
  35. Oncotarget. 2019 Apr 26. 10(31): 2959-2972
    James NE, Cantillo E, Yano N, Chichester CO, DiSilvestro PA, Hovanesian V, Rao RSP, Kim KK, Moore RG, Ahsan N, Ribeiro JR.
      Epithelial Ovarian Cancer (EOC) is associated with dismal survival rates due to the fact that patients are frequently diagnosed at an advanced stage and eventually become resistant to traditional chemotherapeutics. Hence, there is a crucial need for new and innovative therapies. Septin-2, a member of the septin family of GTP binding proteins, has been characterized in EOC for the first time and represents a potential future target. Septin-2 was found to be overexpressed in serous and clear cell human patient tissue compared to benign disease. Stable septin-2 knockdown clones developed in an ovarian cancer cell line exhibited a significant decrease in proliferation rates. Comparative label-free proteomic analysis of septin-2 knockdown cells revealed differential protein expression of pathways associated with the TCA cycle, acetyl CoA, proteasome and spliceosome. Further validation of target proteins indicated that septin-2 plays a predominant role in post-transcriptional and translational modifications as well as cellular metabolism, and suggested the potential novel role of septin-2 in promoting EOC tumorigenesis through these mechanisms.
    Keywords:  metabolic proteins; ovarian cancer; proteomics; septin-2
    DOI:  https://doi.org/10.18632/oncotarget.26836
  36. Cancer Cell. 2019 Apr 26. pii: S1535-6108(19)30197-7. [Epub ahead of print]
    Hassannia B, Vandenabeele P, Vanden Berghe T.
      One of the key challenges in cancer research is how to effectively kill cancer cells while leaving the healthy cells intact. Cancer cells often have defects in cell death executioner mechanisms, which is one of the main reasons for therapy resistance. To enable growth, cancer cells exhibit an increased iron demand compared with normal, non-cancer cells. This iron dependency can make cancer cells more vulnerable to iron-catalyzed necrosis, referred to as ferroptosis. The identification of FDA-approved drugs as ferroptosis inducers creates high expectations for the potential of ferroptosis to be a new promising way to kill therapy-resistant cancers.
    Keywords:  GPX4; HMOX1; Iron; anti-cancer therapy; ferroptosis; lipid peroxidation; nanomedicine; p53
    DOI:  https://doi.org/10.1016/j.ccell.2019.04.002
  37. Elife. 2019 May 20. pii: e45572. [Epub ahead of print]8
    Kang YP, Torrente L, Falzone A, Elkins CM, Liu M, Asara JM, Dibble CC, DeNicola G.
      NRF2 is emerging as a major regulator of cellular metabolism. However, most studies have been performed in cancer cells, where co-occurring mutations and tumor selective pressures complicate the influence of NRF2 on metabolism. Here we use genetically engineered, non-transformed primary murine cells to isolate the most immediate effects of NRF2 on cellular metabolism. We find that NRF2 promotes the accumulation of intracellular cysteine and engages the cysteine homeostatic control mechanism mediated by cysteine dioxygenase 1 (CDO1), which catalyzes the irreversible metabolism of cysteine to cysteine sulfinic acid (CSA). Notably, CDO1 is preferentially silenced by promoter methylation in human non-small cell lung cancers (NSCLC) harboring mutations in KEAP1, the negative regulator of NRF2. CDO1 silencing promotes proliferation of NSCLC by limiting the futile metabolism of cysteine to the wasteful and toxic byproducts CSA and sulfite (SO32-), and depletion of cellular NADPH. Thus, CDO1 is a metabolic liability for NSCLC cells with high intracellular cysteine, particularly NRF2/KEAP1 mutant cells.
    Keywords:  biochemistry; cancer biology; chemical biology; human; mouse
    DOI:  https://doi.org/10.7554/eLife.45572
  38. Methods Mol Biol. 2019 ;1996 101-111
    Hernandez DR, Del Carmen Piqueras M, Macias AE, Martinez L, Vazquez-Padron R, Bhattacharya SK.
      Different methodologies for collagen quantification have been described in the past. Introduction of mass spectrometry combined with high-performance liquid chromatography (HPLC) is a high-resolution tool, which has generated novel applications in biomedical research. In this study, HPLC coupled to electrospray ionization (ESI) tandem mass spectrometry (HPLC-ESI-MS/MS) was used to characterize tissue samples from AVFs done in rats. These findings helped create a protocol for identifying and quantifying components of immature and mature collagen crosslink moieties. Two different internal standards were used: epinephrine and pyridoxine. Quantification curves were drawn by means of these standards. The goal of the experiment was to achieve accurate quantification with the minimum amount of sample. Time and cost of experiment were considerably minimized. Up to date, this method has not been tested for crosslinking quantification.
    Keywords:  Amino acids; Arteriovenous fistula; Collagen; Crosslinking; Orbitrap; Q Exactive
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_10
  39. Methods Mol Biol. 2019 ;1978 323-340
    Reinhold D, Pielke-Lombardo H, Jacobson S, Ghosh D, Kechris K.
      Metabolomics is the science of characterizing and quantifying small molecule metabolites in biological systems. These metabolites give organisms their biochemical characteristics, providing a link between genotype, environment, and phenotype. With these opportunities also come data challenges, such as compound annotation, missing values, and batch effects. We present the steps of a general pipeline to process untargeted mass spectrometry data to alleviate the latter two challenges. We assume to have a matrix with metabolite abundances, with metabolites in rows and samples in columns. The steps in the pipeline include summarizing technical replicates (if available), filtering, imputing, transforming, and normalizing the data. In each of these steps, a method and parameters should be chosen based on assumptions one is willing to make, the question of interest, and diagnostic tools. Besides giving a general pipeline that can be adapted by the reader, our goal is to review diagnostic tools and criteria that are helpful when making decisions in each step of the pipeline and assessing the effectiveness of normalization and batch correction. We conclude by giving a list of useful packages and discuss some alternative approaches that might be more appropriate for the reader's data.
    Keywords:  Filtering; Imputation; Mass spectrometry; Metabolomics; Normalization; Pre-analytic; Processing; Technical replicates; Untargeted
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_20
  40. Methods Mol Biol. 2019 ;1996 207-216
    Kesh K, Banerjee S.
      Cancer stem cells (CSCs) or tumor-initiating cells (TICs) are a population of cells present within tumor that have increased self-renewal, chemoresistance, and aggressiveness, thereby contributing to tumor relapse. Literature shows that CSCs or TICs typically originate within the hypoxic niches of the tumor, making hypoxia one of the driving factors for generation of this population. Hypoxic stress promotes adaptation to low oxygen tension in the tissues by altering metabolic properties of the CSCs. This leads to a number of altered enzymatic activities in the CSC population that further contribute to the survival of the CSCs leading to resistance to standard therapy. Hence, understanding this altered metabolic pathways as well as targeting key nodes in these may pave the way for cancer management.Glucose and glutamine are the major substrates utilized by cancer cells and feed into multiple biosynthetic pathways. Hence, labeling and tracking these compounds may reveal some novel metabolic pathways exploited by cancer stem cells to acquire survival advantage. In these current book chapters, we elaborately summarized the basic steps required for isolation, characterization, and metabolic labeling (13C6 glucose and 13C5 glutamine) of CSC for flux analysis.
    Keywords:  CD133; Cancer stem cells; Hypoxia; Isotope labeling; Metabolic flux
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_18
  41. Anal Chim Acta. 2019 Sep 06. pii: S0003-2670(19)30430-1. [Epub ahead of print]1070 51-59
    Zheng J, Zheng SJ, Cai WJ, Yu L, Yuan BF, Feng YQ.
      Short-chain fatty acids (SCFAs) are one class of bacterial metabolites mainly formed by gut microbiota from undigested fibers and proteins. These molecules are able to mediate signal conduction processes of cells, acting as G protein-coupled receptors (GPR) activators and histone deacetylases (HDAC) inhibitors. It was reported that SCFAs were closely associated with various human diseases. However, it is still challenging to analyze SCFAs because of their diverse structures and broad range of concentrations. In this study, we developed a highly sensitive method for simultaneous detection of 34 SCFAs by stable isotope labeling coupled with ultra-high performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS/MS) analysis. In this respect, a pair of isotope labeling reagents, N-(4-(aminomethyl)benzyl)aniline (4-AMBA) and N-(4-(aminomethyl)benzyl)aniline-d5 (4-AMBA-d5), were synthesized to label SCFAs from the feces of mice and SCFA standards, respectively. The 4-AMBA-d5 labeled SCFAs were used as internal standards to compensate the ionization variances resulting from matrix effect and thus minimize quantitation deviation in MS detection. After 4-AMBA labeling, the retention of SCFAs on the reversed-phase column increased and the separation resolution of isomers were improved. In addition, the MS responses of most SCFAs were enhanced by up to three orders of magnitude compared to unlabeled SCFAs. The limits of detection (LODs) of SCFAs were as low as 0.005 ng/mL. Moreover, good linearity for 34 SCFAs was obtained with the coefficient of determination (R2) ranging from 0.9846 to 0.9999 and the intra- and inter-day relative standard deviations (RSDs) were <17.8% and 15.4%, respectively, indicating the acceptable reproducibility of the developed method. Using the developed method, we successfully quantified 21 SCFAs from the feces of mice. Partial least squares discriminant analysis (PLS-DA) and t-test analysis showed that the contents of 9 SCFAs were significantly different between Alzheimer's disease (AD) and wide type (WT) mice fecal samples. Compared to WT mice, the contents of propionic acid, isobutyric acid, 3-hydroxybutyric acid, and 3-hydroxyisocaleric acid were decreased in AD mice, while lactic acid, 2-hydroxybutyric acid, 2-hydroxyisobutyric acid, levulinic acid, and valpronic acid were increased in AD mice. These significantly changed SCFAs in the feces of AD mice may afford to a better understanding of the pathogenesis of AD. Taken together, the developed UHPLC-ESI-MS/MS method could be applied for the sensitive and comprehensive determination of SCFAs from complex biological samples.
    Keywords:  Alzheimer's disease; Liquid chromatography-tandem mass spectrometry; Quantification; Short-chain fatty acids; Stable isotope labeling
    DOI:  https://doi.org/10.1016/j.aca.2019.04.021
  42. Genome Res. 2019 May 23. pii: gr.247353.118. [Epub ahead of print]
    Sidoli S, Kori Y, Lopes M, Yuan ZF, Kim HJ, Kulej K, Janssen KA, Agosto LM, Cunha JPC, Andrews AJ, Garcia BA.
      DNA and histone proteins define the structure and composition of chromatin. Histone post-translational modifications (PTMs) are covalent chemical groups capable of modeling chromatin accessibility, mostly due to their ability in recruiting enzymes responsible for DNA readout and remodeling. Mass spectrometry (MS)-based proteomics is the methodology of choice for large-scale identification and quantification of protein PTMs, including histones. High sensitive proteomics requires online MS coupling with relatively low throughput and poorly robust nano-liquid chromatography (nanoLC) and, for histone proteins, a 2-day sample preparation that includes histone purification, derivatization and digestion. We present a new protocol that achieves quantitative data on about 200 histone PTMs from tissue or cell lines in 7 hours from start to finish. This protocol includes 4 hours of histone extraction, 3 hours of derivatization and digestion, and only 1 minute of MS analysis via direct injection (DI-MS). We demonstrate that this sample preparation can be parallelized for 384 samples by using multichannel pipettes and 96-well plates. We also engineered the sequence of a synthetic "histone-like" peptide to spike into the sample, of which derivatization and digestion benchmarks the quality of the sample preparation. We ensure that DI-MS does not introduce biases in histone peptide ionization as compared to nanoLC-MS/MS by producing and analyzing a library of synthetically modified histone peptides mixed in equal molarity. Finally, we introduce EpiProfileLite for comprehensive analysis of this new data type. Altogether, our workflow is suitable for high throughput screening of >1,000 samples per day using a single mass spectrometer.
    DOI:  https://doi.org/10.1101/gr.247353.118
  43. Metabolites. 2019 May 22. pii: E101. [Epub ahead of print]9(5):
    Barupal DK, Zhang Y, Shen T, Fan S, Roberts BS, Fitzgerald P, Wancewicz B, Valdiviez L, Wohlgemuth G, Byram G, Choy YY, Haffner B, Showalter MR, Vaniya A, Bloszies CS, Folz JS, Kind T, Flenniken AM, McKerlie C, Nutter LMJ, Lloyd KC, Fiehn O.
      Mouse knockouts facilitate the study ofgene functions. Often, multiple abnormal phenotypes are induced when a gene is inactivated. The International Mouse Phenotyping Consortium (IMPC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples from 30 unique mouse gene knockouts and corresponding wildtype mice from the IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases, and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.
    Keywords:  GC-MS; IMPC; LC-MS; Metabolic phenotyping; functional genomics; lipidomics; metabolomics; mouse knockouts
    DOI:  https://doi.org/10.3390/metabo9050101
  44. Methods Mol Biol. 2019 ;1996 217-257
    Bhinderwala F, Lei S, Woods J, Rose J, Marshall DD, Riekeberg E, Leite AL, Morton M, Dodds ED, Franco R, Powers R.
      Metabolomics has been successfully applied to study neurological and neurodegenerative disorders including Parkinson's disease for (1) the identification of potential biomarkers of onset and disease progression; (2) the identification of novel mechanisms of disease progression; and (3) the assessment of treatment prognosis and outcome. Reproducible and efficient extraction of metabolites is imperative to the success of any metabolomics investigation. Unlike other omics techniques, the composition of the metabolome can be negatively impacted by the preparation, processing, and handling of these samples. The proper choice of data collection, preprocessing, and processing protocols is similarly important to the design of an effective metabolomics experiment. Likewise, the correct application of univariate and multivariate statistical methods is essential for providing biologically relevant insights. In this chapter, we have outlined a detailed metabolomics workflow that addresses all of these issues. A step-by-step protocol from the preparation of neuronal cells and metabolomic tissue samples to their metabolic analyses using nuclear magnetic resonance, mass spectrometry, and chemometrics is presented.
    Keywords:  Chemometrics; Mass spectrometry; Metabolomics; NMR; Neurodegeneration; Parkinson’s disease
    DOI:  https://doi.org/10.1007/978-1-4939-9488-5_19
  45. Methods Mol Biol. 2019 ;1978 431-446
    San-Millán I.
      The field of sports medicine and performance has undergone an important transformation in the past years where the scientific approach is becoming increasingly more important for teams and athletes. Physical and physiological fitness, nutrition, fatigue and recovery, as well as injury prevention are key elements of the scientific monitoring of athletes nowadays. Many different methods are used nowadays as part of the scientific monitoring and testing of the competitive athlete. Among them, physiological and metabolic testing, biomechanical and movement assessments, GPS-based tracking systems, heart rate monitors, power meters, and training software are an integrative part of the scientific monitor program of many teams and athletes.Blood biomarkers through traditional blood analysis have been used for over three decades (mainly in Europe) to monitor athletic performance. In the same manner that different cells in the body respond to the stress of an infection or a disease, cells in athletes respond to the stress of competition and training. Nowadays, the area of blood biomarkers is an emerging field in the US offering important level of possibilities to monitor athletes. The field of metabolomics can offer a significantly higher level of blood biomarkers for sports medicine and performance monitoring.
    Keywords:  Biomarkers; Metabolism; Performance; Sports medicine
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_26
  46. Biochim Biophys Acta Mol Cell Biol Lipids. 2019 May 17. pii: S1388-1981(19)30075-7. [Epub ahead of print]
    Balla T, Sengupta N, Kim YJ.
      Structural lipids are mostly synthesized in the endoplasmic reticulum (ER), from which they are actively transported to the membranes of other organelles. Lipids can leave the ER through vesicular trafficking or non-vesicular lipid transfer and, curiously, both processes can be regulated either by the transported lipid cargos themselves or by different secondary lipid species. For most structural lipids, transport out of the ER membrane is a key regulatory component controlling their synthesis. Distribution of the lipids between the two leaflets of the ER bilayer or between the ER and other membranes is also critical for maintaining the unique membrane properties of each cellular organelle. How cells integrate these processes within the ER depends on fine spatial segregation of the molecular components and intricate metabolic channeling, both of which we are only beginning to understand. This review will summarize some of these complex processes and attempt to identify the organizing principles that start to emerge. This article is part of a Special Issue entitled Endoplasmic reticulum platforms for lipid dynamics edited by Shamshad Cockcroft and Christopher Stefan.
    Keywords:  Endoplasmic reticulum; Lipid transfer protein; Membrane contact sites; Non-vesicular lipid transfer; Phosphatidylcholine; Phosphatidylinositol; Phosphatidylserine
    DOI:  https://doi.org/10.1016/j.bbalip.2019.05.005
  47. Methods Mol Biol. 2019 ;1978 137-152
    Harrison KA, Bergman BC.
      HPLC-MS/MS has enabled the quantitative analysis of complex mixtures of lipid molecular species. Several separate analyses, using methods that have been optimized for individual lipid classes, provide good lipidomic profiles, but may not be desirable for laboratories constrained by available instrumentation and wanting a higher throughput. Here we describe two methods using binary gradient HiLiC HPLC and triple quadrupole MS that together provide a lipidomic profile for lipids of interest in type 2 diabetes research. Methods for analysis of molecular species of diacylglycerol, ceramide, dihydroceramide, sphingosine, glucosyl- and lactosylceramide, sphingomyelin, and acylcarnitine from skeletal muscle and primary culture cells are described.
    Keywords:  Acylcarnitines; Ceramides; Diacylglycerols; Dihydroceramides; Glucosylceramides; HPLC-MS/MS; HiLiC; Lactosylceramides; Lipidomics; Sphingomyelins; Sphingosine
    DOI:  https://doi.org/10.1007/978-1-4939-9236-2_9
  48. Clin Chim Acta. 2019 May 16. pii: S0009-8981(19)31863-7. [Epub ahead of print]
    Tang Y, Li Z, Lazar L, Fang Z, Tang C, Zhao J.
      Lung cancer is one of the most common cancers in the world. Due to the limitations of current diagnostic techniques and methods, most lung cancers are diagnosed at the advanced stage, which is not conducive to early treatment. The rise of metabolomics has provided new ideas for the early diagnosis of lung cancer. As a method for the comprehensive analysis of endogenous metabolites of the biological system, metabolomics has shown significant application potential for the early diagnosis and individualized treatment of various cancers including lung cancers. Via advanced analytical techniques and bioinformatics tools, the metabolome was excavated to find biomarkers related to cancer and its prognosis. In this review, the research methods and workflow of metabolomics are summarized, with an emphasis on the recent discovery of biomarkers and major metabolic pathways for lung cancers.
    Keywords:  Biomarker; Lung cancer; Metabolic pathways; Metabolomics; Workflow
    DOI:  https://doi.org/10.1016/j.cca.2019.05.012
  49. Anal Chem. 2019 May 24.
    Neumann EK, Ellis JF, Triplett AE, Rubakhin SS, Sweedler JV.
      Single cell measurements aid our understanding of chemically heterogeneous systems such as the brain. Lipids are one of the least studied chemical classes and their cell-to-cell heterogeneity remains largely unexplored. We adapted microscopy guided single cell profiling using matrix assisted laser desorption / ionization ion cyclotron resonance mass spectrometry to profile the lipid composition of over 30,000 individual rat cerebral cells. We detected 520 lipid features, many of which were found in subsets of cells; Louvain clustering identified 101 distinct groups that can be correlated to neuronal and astrocytic classifications and lipid classes. Overall, the two most common lipids found were [PC(32:0)+H]+ and [PC(34:1)+H]+, which were present within 98.9% and 89.5% of cells, respectively; lipid signals present in <1% of cells were also detected, including [PC(34:1)+K]+ and [PG(40:2(OH))+Na]+. These results illustrate the vast lipid heterogeneity found within rodent cerebral cells and hint at the distinct functional consequences of this heterogeneity.
    DOI:  https://doi.org/10.1021/acs.analchem.9b01689