bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒01‒05
thirty-five papers selected by
Giovanny Rodriguez Blanco
The Beatson Institute for Cancer Research

  1. Methods Mol Biol. 2020 ;2088 73-92
      The recently developed deep labeling method allows for large-scale profiling of metabolic activities in human cells or tissues using isotope tracing with a highly 13C enriched culture medium in combination with liquid chromatography-high resolution mass spectrometry. This method generates mass spectrometry data sets where endogenous cellular products can be identified, and active pathways can be determined from observed 13C mass isotopomers of the various metabolites measured. Here we describe in detail the experimental procedures for deep labeling experiments in cultured mammalian cells, including synthesis of the deep labeling medium, experimental considerations for cell culture, metabolite extractions and sample preparation, and liquid chromatography-mass spectrometry. We also outline a workflow for the downstream data analysis using publicly available software.
    Keywords:  Cell culture; LC-HRMS; Metabolism; Metabolomics; Stable isotope tracing experiments
  2. J Biomol Tech. 2019 Dec;30(Suppl): S25-S26
      Lipid metabolism is complex and involves a large number of metabolic reactions resulting in an enormous number and variety of actual lipids within living cells. LIPIDMAPS currently stores more than 40000 lipid structures. The dynamic range of lipid concentrations in biological systems can vary by 106 or more (from nanomolar fatty acids to attomolar eicosanoid lipid mediators). The level of precision of most systems-wide measurements is not yet sufficient to detail specific levels or concentrations of cellular components. Comparing lipidomic data across laboratories requires absolute quantification since relative values can vary widely not only between laboratories and between instruments due to various factors including: analyst errors, sample preparation differences (e.g. extraction methods) and ion suppression when using ESI MS. The lack of accurate characterisation of the lipid species also severely hinders interpretation of lipid metabolism associated with disease and physiological states. The proposed platform involves integrated high throughput analytical tool for accurate and robust measurement (>1500 injections) of lipid from sample preparation through to data handling and pathway elucidation. The platform can also be used for more in depth targeting of specific class of lipids of interest. Validation of the chromatographic method is performed at multiple sites by different analysts to show robustness and ease of method transfer. A rapid total lipid extraction method involving IPA and MTBE for plasma shows promising results. This will grant researchers more flexibility depending on their specific needs and requirements. The calibration, system suitability and QC standards used in this platform is sourced pre-mixed from commercial vendors (Avanti Lipids). SymphonyTM Software is used to automate the entire workflow and integrated with Skyline for data processing to enhance efficiency and flexibility. Once quantitative data has been generated and processed, pathway mapping tools can be used to determine the biological relevance of changes in concentration, and make data comparisons between laboratories.
  3. Methods Mol Biol. 2020 ;2088 17-32
      Gas chromatography coupled with mass spectrometry can provide an extensive overview of the metabolic state of a biological system. Analysis of raw mass spectrometry data requires powerful data processing software to generate interpretable results. Here we describe a data processing workflow to generate metabolite levels, mass isotopomer distribution, similarity and variability analysis of metabolites in a nontargeted manner, using stable isotope labeling. Using our data analysis software, no bioinformatic or programming background is needed to generate results from raw mass spectrometry data.
    Keywords:  Data analysis; GCMS; Gas chromatography; Mass isotopomer distribution; Mass spectrometry; Metabolism; Nontargeted metabolomics; Stable isotope labeling
  4. J Hepatol. 2019 Dec 30. pii: S0168-8278(19)30760-3. [Epub ahead of print]
      BACKGROUND & AIMS: Mitochondrial dysfunction and subsequent metabolic deregulation are commonly observed in cancers including hepatocellular carcinoma (HCC). When mitochondrial function is impaired, reductive glutamine metabolism is a major cellular carbon source for de novo lipogenesis to support cancer cell growth. The underlying regulators of reductively metabolized glutamine in mitochondrial dysfunction are not completely understood in tumorigenesis including in HCC.METHODS: We systematically investigated the role of oxoglutarate dehydrogenase-like (OGDHL), one of the rate-limiting components of the key mitochondrial multi-enzyme OGDH complex (OGDHC), in the regulation of lipid metabolism in hepatoma cells and explored the underlying molecular mechanisms.
    RESULTS: Lower expression of OGDHL was associated with advanced tumor stage, significantly worse survival and more frequent tumor recurrence in three independent cohorts totaling 681 postoperative HCC patients. Promoter hypermethylation and DNA copy deletion of OGDHL were independently correlated with reduced OGDHL expression in HCC specimens. Additionally, OGDHL overexpression significantly inhibited the growth of hepatoma cells as mouse xenografts while knockdown of OGDHL promoted proliferation in hepatoma cells. Mechanistically, OGDHL downregulation upregulated the α-ketoglutarate (αKG):citrate ratio by reducing OGDHC activity, which subsequently drove reductive carboxylation (RC) of glutamine-derived αKG for lipogenesis via retrograde TCA cycling in hepatoma cells. Notably, silencing of OGDHL activated the mTORC1 signaling pathway in an α-KG-dependent manner, which in turn transcriptionally induced expression of SCD1 and FASN, thus, enhancing de novo lipogenesis. Meanwhile, metabolic reprogramming in OGDHL-negative hepatoma cells provided an abundant supply of NADPH and GSH to support the cellular antioxidant system. The reduction of reductive glutamine metabolism through OGDHL overexpression or through use of glutaminase inhibitors sensitized tumor cells to sorafenib, a molecular-targeted therapy for HCC.
    CONCLUSION: Our findings established that silencing of OGDHL contributed to HCC development and survival by regulating glutamine metabolic pathways, and suggest OGDHL as a promising prognostic biomarker and therapeutic target for HCC.
    Keywords:  Glutamine metabolism; Liver cancer; OGDHL; Tricarboxylic acid cycle
  5. Cancer Metab. 2019 ;7 13
      Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with limited treatment options. Pyruvate kinase, especially the M2 isoform (PKM2), is highly expressed in PDAC cells, but its role in pancreatic cancer remains controversial. To investigate the role of pyruvate kinase in pancreatic cancer, we knocked down PKM2 individually as well as both PKM1 and PKM2 concurrently (PKM1/2) in cell lines derived from a Kras G12D/- ; p53 -/- pancreatic mouse model.Methods: We used liquid chromatography tandem mass spectrometry (LC-MS/MS) to determine metabolic profiles of wildtype and PKM1/2 knockdown PDAC cells. We further used stable isotope-labeled metabolic precursors and LC-MS/MS to determine metabolic pathways upregulated in PKM1/2 knockdown cells. We then targeted metabolic pathways upregulated in PKM1/2 knockdown cells using CRISPR/Cas9 gene editing technology.
    Results: PDAC cells are able to proliferate and continue to produce pyruvate despite PKM1/2 knockdown. The serine biosynthesis pathway partially contributed to pyruvate production during PKM1/2 knockdown: knockout of phosphoglycerate dehydrogenase in this pathway decreased pyruvate production from glucose. In addition, cysteine catabolism generated ~ 20% of intracellular pyruvate in PDAC cells. Other potential sources of pyruvate include the sialic acid pathway and catabolism of glutamine, serine, tryptophan, and threonine. However, these sources did not provide significant levels of pyruvate in PKM1/2 knockdown cells.
    Conclusion: PKM1/2 knockdown does not impact the proliferation of pancreatic cancer cells. The serine biosynthesis pathway supports conversion of glucose to pyruvate during pyruvate kinase knockdown. However, direct conversion of serine to pyruvate was not observed during PKM1/2 knockdown. Investigating several alternative sources of pyruvate identified cysteine catabolism for pyruvate production during PKM1/2 knockdown. Surprisingly, we find that a large percentage of intracellular pyruvate comes from cysteine. Our results highlight the ability of PDAC cells to adaptively rewire their metabolic pathways during knockdown of a key metabolic enzyme.
    Keywords:  Liquid chromatography mass spectrometry; Metabolism; PKM; Pancreatic cancer; Pyruvate kinase
  6. Methods Mol Biol. 2020 ;2088 271-298
      Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.
    Keywords:  Central energy metabolism; Computational analysis; Isotopolog distribution; Kinetic models of metabolism; Mass spectrometry; Metabolic fluxes; Stable isotope tracing; Stable isotope-resolved metabolomics
  7. Cancers (Basel). 2019 Dec 16. pii: E2028. [Epub ahead of print]11(12):
      IDH1R132H (isocitrate dehydrogenase 1) mutations play a key role in the development of low-grade gliomas. IDH1wt converts isocitrate to α-ketoglutarate while reducing nicotinamide adenine dinucleotide phosphate (NADP+), whereas IDH1R132H uses α-ketoglutarate and NADPH to generate the oncometabolite 2-hydroxyglutarate (2-HG). While the effects of 2-HG have been the subject of intense research, the 2-HG independent effects of IDH1R132H are still ambiguous. The present study demonstrates that IDH1R132H expression but not 2-HG alone leads to significantly decreased tricarboxylic acid (TCA) cycle metabolites, reduced proliferation, and enhanced sensitivity to irradiation in both glioblastoma cells and astrocytes in vitro. Glioblastoma cells, but not astrocytes, showed decreased NADPH and NAD+ levels upon IDH1R132H transduction. However, in astrocytes IDH1R132H led to elevated expression of the NAD-synthesizing enzyme nicotinamide phosphoribosyltransferase (NAMPT). These effects were not 2-HG mediated. This suggests that IDH1R132H cells utilize NAD+ to restore NADP pools, which only astrocytes could compensate via induction of NAMPT. We found that the expression of NAMPT is lower in patient-derived IDH1-mutant glioma cells and xenografts compared to IDH1-wildtype models. The Cancer Genome Atlas (TCGA) data analysis confirmed lower NAMPT expression in IDH1-mutant versus IDH1-wildtype gliomas. We show that the IDH1 mutation directly affects the energy homeostasis and redox state in a cell-type dependent manner. Targeting the impairments in metabolism and redox state might open up new avenues for treating IDH1-mutant gliomas.
    Keywords:  IDH-mutation; IDH1; NAD-synthesis; glioma; metabolism; redox state
  8. J Pharm Biomed Anal. 2019 Dec 23. pii: S0731-7085(19)31859-X. [Epub ahead of print]180 113069
      Malignant pleural effusion (MPE) is an important hallmark for late-stage lung cancer with metastasis. Current clinical diagnosis methods require tedious work to distinguish MPE from benign pleural effusion (BPE). The objective of this study was to characterize the metabolic signatures in MPE of lung cancer, and identify potential metabolite biomarkers for diagnosis of MPE. MPE from lung cancer (n = 46) and BPE from tuberculosis patients (n = 32) were investigated by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based global metabolomic and lipidomic profiling. Multivariate partial least-square discriminative analysis models exhibited distinct metabolic profiles between MPE and BPE. A total of 25 ether lipids, including phosphatidylcholines (PC), lysophosphatidylcholines (LPC) and phosphatidylethanolamines (PE), were observed to be significantly downregulated in MPE with excellent diagnostic potential. Plasmalogen PC(40:3p) showed highest AUC value of 0.953 in receiver operating characteristic (ROC) model. Oxidized polyunsaturated fatty acids (PUFA) were upregulated in MPE. The obtained results implied a high oxidative stress and peroxisome disorder in lung cancer patients. Combined metabolomic and lipidomic profiling have discovered potential biomarkers in MPE with excellent clinical diagnostic capability. Dysregulated ether lipids and oxidized PUFAs have implied an aberrant redox metabolism, which provides novel insights into the pathology of MPE in lung cancer.
    Keywords:  Biomarker; Lipidomics; Lung cancer; Mass spectrometry; Metabolomics; Pleural effusion
  9. Methods Mol Biol. 2020 ;2088 119-160
      Biomass composition is an important input for genome-scale metabolic models and has a big impact on their predictive capabilities. However, researchers often rely on generic data for biomass composition, e.g. collected from similar organisms. This leads to inaccurate predictions, because biomass composition varies between different cell lines, conditions, and growth phases. In this chapter we present protocols for the determination of the biomass composition of Chinese Hamster Ovary (CHO) cells. These methods can easily be adapted to other types of mammalian cells. The protocols include the quantification of cell dry mass and of the main biomass components, namely protein, lipid, DNA, RNA, and carbohydrates. Cell dry mass is determined gravimetrically by weighing a defined number of cells. Amino acid composition and protein content are measured by gas chromatography mass spectrometry. Lipids are quantified by shotgun mass spectrometry, which provides quantities for the different lipid classes and also the distribution of fatty acids. RNA is purified and then quantified spectrophotometrically. The methods for DNA and carbohydrates are simple fluorometric and colorimetric assays adapted to a 96-well plate format. To ensure quantitative results, internal standards or spike-in controls are used in all methods, e.g. to account for possible matrix effects or loss of material. Finally, the last section provides a guide on how to convert the measured data into biomass equations, which can then be integrated into a metabolic model.
    Keywords:  Amino acids; Biomass composition; Carbohydrates; Chinese Hamster Ovary cells; DNA; Lipids; RNA
  10. Cell Metab. 2019 Dec 12. pii: S1550-4131(19)30665-5. [Epub ahead of print]
      Regulatory T cells (Tregs) subdue immune responses. Central to Treg activation are changes in lipid metabolism that support their survival and function. Fatty acid binding proteins (FABPs) are a family of lipid chaperones required to facilitate uptake and intracellular lipid trafficking. One family member, FABP5, is expressed in T cells, but its function remains unclear. We show that in Tregs, genetic or pharmacologic inhibition of FABP5 function causes mitochondrial changes underscored by decreased OXPHOS, impaired lipid metabolism, and loss of cristae structure. FABP5 inhibition in Tregs triggers mtDNA release and consequent cGAS-STING-dependent type I IFN signaling, which induces heightened production of the regulatory cytokine IL-10 and promotes Treg suppressive activity. We find evidence of this pathway, along with correlative mitochondrial changes in tumor infiltrating Tregs, which may underlie enhanced immunosuppression in the tumor microenvironment. Together, our data reveal that FABP5 is a gatekeeper of mitochondrial integrity that modulates Treg function.
    Keywords:  FABP5; IL-10; Treg; cGAS-STING; immunometabolism; lipids; mtDNA; suppression; tumor; type I IFN
  11. Methods Mol Biol. 2020 ;2088 51-71
      Oxidation-reduction (redox) reactions are ubiquitous in biology and typically occur in specific subcellular compartments. In cells, the electron transfer between molecules and organelles is commonly facilitated by pyridine nucleotides such as nicotinamide adenine dinucleotide phosphate (NADPH) and nicotinamide adenine dinucleotide (NADH). While often taken for granted, these metabolic reactions are critically important for maintaining redox homeostasis and biochemical potentials across membranes. While 13C tracing and metabolic flux analysis (MFA) have emerged as powerful tools to study intracellular metabolism, this approach is limited when applied to pathways catalyzed in multiple cellular compartments. To address this issue, we and others have applied 2H (deuterium) tracers to observe transfer of labeled hydride anions, which accompanies electron transfer. Furthermore, we have developed a reporter system for indirectly quantifying NADPH enrichment in specific subcellular compartments. Here, we provide a detailed description of 2H tracing applications and the interrogation of mitochondrial versus cytosolic NAD(P)H metabolism in cultured mammalian cells. Specifically, we describe the generation of reporter cell lines that express epitope-tagged R132H-IDH1 or R172K-IDH2 and produce (D)2-hydroxyglutarate in a doxycycline-dependent manner. These tools and methods allow for quantitation of reducing equivalent turnover rates, the directionality of pathways present in multiple compartments, and the estimation of pathway contributions to NADPH pools.
    Keywords:  Deuterium; Isotopomer spectral analysis; Mammalian cell culture; Metabolic flux analysis; Metabolite extraction; NADH; NADPH; Redox metabolism; Stable isotope tracing
  12. J Clin Exp Hepatol. 2019 Nov-Dec;9(6):9(6): 657-675
      Background: Human infection with Opisthorchis viverrini, a carcinogenic liver fluke inhabiting the biliary tree, is endemic in Southeast Asia. Chronic infection is associated with a fatal complication, cholangiocarcinoma (CCA), a late-presenting and aggressive malignancy. Currently, annual mortality rates from CCA mirror trends in incidence, due in part to limited availability of efficient prognostic and early diagnostic biomarkers. With ability to detect thousands of urinary metabolites using metabonomics, the urine metabolome holds great potential in providing an insight into system-level alterations in carcinogenesis and in identifying metabolic markers altered in response to disturbed homoeostasis.Methods: Global molecular profiling using reversed-phase ultraperformance liquid chromatography mass spectrometry was utilised to acquire the urinary spectral profile of 137 Thai subjects (48 at high risk of infection, 41 with O. viverrini infection, 34 periportal fibrosis and 14 CCA) from Khon Kaen, Thailand.
    Results: Multivariate statistical analysis identified perturbation in several molecular classes related to purine metabolism and lipid metabolism in the CCA urine metabolome. These markers mainly reflect changes in energy metabolism to support proliferation (increased fatty acid oxidation and purine recycling), DNA methylation and hepatic injury.
    Conclusions: Several metabolites of biological interest were discovered from this proof-of-principle dataset. Augmenting these findings is essential to accelerate the development of urinary metabolic markers in CCA.
    Keywords:  Opisthorchis viverrini; acetaminophen, APAP; bile duct cancer; carnitine palmitoyltransferase 1, CPT1; carnitine palmitoyltransferase 2, CPT2; carnitine/acylcarnitine translocase, CACT; cholangiocarcinoma screening and care program, CASCAP; cholangiocarcinoma, CCA; data-dependent acquisition, DDA; electrospray ionisation, ESI; hypoxanthine phosphoribosyltransferase 1, HPRT1; hypoxanthine-guanine phosphoribosyltransferase, HPRT; mass spectrometry; metabonomics; orthogonal projections to latent structures discriminant analysis, OPLS-DA; periductal fibrosis, PDF; periportal fibrosis, PPF; primary biliary cholangitis, PBC; primary sclerosing cholangitis, PSC; principal component analysis, PCA; reversed-phase ultra-performance liquid-chromatography mass spectrometry, RP-UPLC-MS; ultra-performance liquid chromatography mass spectrometry, UPLC-MS; variable importance in projection, VIP
  13. J Biol Chem. 2020 Jan 02. pii: jbc.RA119.011083. [Epub ahead of print]
      The maternal embryonic leucine zipper kinase (MELK) has been implicated in the regulation of cancer cell proliferation. RNAi-mediated MELK depletion impairs growth and causes G2/M arrest in numerous cancers, but the mechanisms underlying these effects are poorly understood. Furthermore, the MELK inhibitor OTSSP167 has recently been shown to have poor selectivity for MELK, complicating the use of this inhibitor as a tool compound to investigate MELK function. Here, using a cell-based proteomics technique called multiplexed kinase inhibitor beads/mass spectrometry (MIB/MS), we profiled the selectivity of two additional MELK inhibitors, NVS-MELK8a (8a) and HTH-01-091. Our results revealed that 8a is a highly selective MELK inhibitor, which we further used for functional studies. Resazurin and crystal violet assays indicated that 8a decreases triple-negative breast cancer cell viability, and immunoblotting revealed that impaired growth is due to perturbation of cell cycle progression rather than induction of apoptosis. Using double thymidine synchronization and immunoblotting, we observed that MELK inhibition delays mitotic entry, which was associated with delayed activation of Aurora A, Aurora B, and cyclin-dependent kinase 1 (CDK1). Following this delay, cells entered and completed mitosis. Using live-cell microscopy of cells harboring fluorescent proliferating cell nuclear antigen (PCNA), we confirmed that 8a significantly and dose-dependently lengthens G2 phase. Collectively, our results provide a rationale for using 8a as a tool compound for functional studies of MELK and indicate that MELK inhibition delays mitotic entry, likely via transient G2/M checkpoint activation.
    Keywords:  G2/M checkpoint; cell cycle; cell proliferation; inhibitor; kinome profiling; mass spectrometry (MS); maternal embryonic leucine zipper kinase (MELK); mitotic delay; multiplexed kinase inhibitor beads/mass spectrometry (MIB/MS); protein kinase
  14. Free Radic Biol Med. 2019 Dec 25. pii: S0891-5849(19)31737-X. [Epub ahead of print]
      High fidelity and effective adaptive changes of the cell and tissue metabolism to changing environments requires strict coordination of numerous biological processes. Multicellular organisms developed sophisticated signaling systems of monitoring and responding to these different contexts. Among these systems, oxygenated lipids play a significant role realized via a variety of re-programming mechanisms. Some of them are enacted as a part of pro-survival pathways that eliminate harmful or unnecessary molecules or organelles by a variety of degradation/hydrolytic reactions or specialized autophageal processes. When these "partial" intracellular measures are insufficient, the programs of cells death are triggered with the aim to remove irreparably damaged members of the multicellular community. These regulated cell death mechanisms are believed to heavily rely on signaling by a highly diversified group of molecules, oxygenated phospholipids (PLox). Out of thousands of detectable individual LPox species, redox phospholipidomics deciphered several specific molecules that seem to be diagnostic of specialized death programs. Oxygenated cardiolipins (CLs) and phosphatidylethanolamines (PEs) have been identified as predictive biomarkers of apoptosis and ferroptosis, respectively. This has led to decoding of the enzymatic mechanisms of their formation involving mitochondrial oxidation of CLs by cytochrome c and endoplasmic reticulum-associated oxidation of PE by lipoxygenases. Understanding of the specific biochemical radical-mediated mechanisms of these oxidative reactions opens new avenues for the design and search of highly specific regulators of cell death programs. This review emphasizes the usefulness of such selective lipid peroxidation mechanisms in contrast to the concept of random poorly controlled free radical reactions as instruments of non-specific damage of cells and their membranes. Detailed analysis of two specific examples of phospholipid oxidative signaling in apoptosis and ferroptosis along with their molecular mechanisms and roles in reprogramming has been presented.
  15. Methods Mol Biol. 2020 ;2088 93-118
      Metastasis formation is the leading cause of death in cancer patients. It has recently emerged that cancer cells adapt their metabolism to successfully transition through the metastatic cascade. Consequently, measuring and analyzing the in vivo metabolism of metastases has the potential to reveal novel treatment strategies to prevent metastasis formation. Here, we describe two different metastasis mouse models and how their metabolism can be analyzed with metabolomics and 13C tracer analysis.
    Keywords:  13C tracer analysis; In vivo metabolism; Metabolism; Metabolomics; Metastasis; Mouse infusions
  16. Methods Mol Biol. 2020 ;2088 205-221
      Extracellular vesicles (EVs) are ubiquitous nanoscale particles released from many different types of cells. They have been shown to contain proteins, DNA, RNA, miRNA, and, most recently, metabolites. These particles can travel through the intercellular space and bloodstream to have regulatory effects on distant recipients. When an EV reaches a target cell, it is taken up and degraded to release its contents for utilization within the cell. In addition to regulatory effects, EVs have been shown to supplement the high metabolic demands of recipient cells in a nutrient-deprived tumor microenvironment. We developed an integrated empirical and computational platform to quantify metabolic contribution of source cell-derived EVs to recipient cells. The versatile Exo-MFA software tool utilizes 13C stable-isotope tracing data to quantify the metabolic contributions of EVs from a source cell type on a recipient cell type. This is accomplished by creating EV-depleted culture medium, producing isotope-labeled EVs from the source cells, isolating the labeled EVs from the culture supernatant, culturing the recipient cells in the presence of the labeled EVs, and measuring the resulting metabolite levels across several time points.
    Keywords:  13-Carbon metabolic flux analysis; Exo-MFA; Exosomes; Extracellular vesicles; Multicellular metabolic flux analysis; Stable-isotope tracing
  17. J Biomol Tech. 2019 Dec;30(Suppl): S39
      Metabolomics plays an indispensable role in the growing systems biology approaches to identify biomarkers for complex diseases such as cancer. Liquid chromatography coupled to mass spectrometry (LC-MS) and gas chromatography coupled to mass spectrometry (GC-MS) have been extensively used for high-throughput comparison of the levels of thousands of metabolites among biological samples. However, the potential values of many disease-associated analytes discovered by these platforms have been inadequately explored in systems biology research due to lack of computational tools. Partly due to these limitations, poor reproducibility of previously identified metabolite biomarker candidates has been observed, especially when they are evaluated through independent platforms and validation sets. Our goal is to provide metabolomics core facilities and research scientists with bioinformatics platforms and expertise that enable them to search for disease-associated metabolites at the systems level through integrative systems metabolomics. To this end, we developed a new browser friendly cloud-based tool (SysMet) to help uncover the relationship of diseases and metabolites by investigating the rewiring and conserved interactions among metabolites and through integrative analysis of multi-omic data. Developed via a modular design and a user-friendly graphical user interface (GUI), SysMet allows users to: (1) import preprocessed metabolomic data for differential analysis of metabolite profiles using a network-based method; (2) import other preprocessed omic data for selection of disease-associated metabolites based on network-based integrative analysis; and (3) visually evaluate the outcome of network-based differential analysis and multi-omic data integration through high-quality figures. We believe SysMet will contribute to improving the ability of researchers to discover disease-associated metabolites by enhancing the role of metabolomics in systems biology research.
  18. Cancer Metab. 2019 ;7 12
      Background: Increased flux through both glycolytic and oxidative metabolic pathways is a hallmark of breast cancer cells and is critical for their growth and survival. As such, targeting this metabolic reprograming has received much attention as a potential treatment approach. However, the heterogeneity of breast cancer cell metabolism, even within classifications, suggests a necessity for an individualised approach to treatment in breast cancer patients.Methods: The metabolic phenotypes of a diverse panel of human breast cancer cell lines representing the major breast cancer classifications were assessed using real-time metabolic flux analysis. Flux linked to ATP production, pathway reserve capacities and specific macromolecule oxidation rates were quantified. Suspected metabolic vulnerabilities were targeted with specific pathway inhibitors, and relative cell viability was assessed using the crystal violet assay. Measures of AMPK and mTORC1 activity were analysed through immunoblotting.
    Results: Breast cancer cells displayed heterogeneous energy requirements and utilisation of non-oxidative and oxidative energy-producing pathways. Quantification of basal glycolytic and oxidative reserve capacities identified cell lines that were highly dependent on individual pathways, while assessment of substrate oxidation relative to total oxidative capacity revealed cell lines that were highly dependent on individual macromolecules. Based on these findings, mild mitochondrial inhibition in ESH-172 cells, including with the anti-diabetic drug metformin, and mild glycolytic inhibition in Hs578T cells reduced relative viability, which did not occur in non-transformed MCF10a cells. The effects on viability were associated with AMPK activation and inhibition of mTORC1 signalling. Hs578T were also found to be highly dependent on glutamine oxidation and inhibition of this process also impacted viability.
    Conclusions: Together, these data highlight that systematic flux analysis in breast cancer cells can identify targetable metabolic vulnerabilities, despite heterogeneity in metabolic profiles between individual cancer cell lines.
    Keywords:  AMPK; Breast cancer; Metabolic flux analysis; Metabolism; Metformin; mTORC1
  19. J Chromatogr B Analyt Technol Biomed Life Sci. 2019 Dec 23. pii: S1570-0232(19)31015-3. [Epub ahead of print]1137 121956
      Gangliosides (GG) are glycosphingolipids, composed of a ceramide moiety (fatty acid and long chain base) linked to an oligosaccharide chain containing one (or more) molecule of sialic acid. After lipid extraction from biological matrices, quantification of GG by liquid chromatography coupled to electrospray ionization mass spectrometry (LC-ESI/MS) can be impacted by ion suppression effects due to co-elution with more abundant lipids in the matrix. In this study, a simple, rapid and efficient method to purify GG from biological samples by Phree columns is proposed. This approach proved to be useful in eliminating phospholipids (PL) from the matrix and thus increasing the signal of GG classes and molecular species in rat brain samples during LC-ESI/MS analysis.
    Keywords:  Gangliosides; Ion suppression; Lipids; Liquid chromatography-mass spectrometry; Purification; Quantitative analysis
  20. Mol Cell Proteomics. 2019 Dec 30. pii: mcp.RA119.001705. [Epub ahead of print]
      In bottom-up, label-free discovery proteomics, biological samples are acquired in a data dependent (DDA) or data independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance, and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals for detecting differential abundance could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2 combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g., using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.
    Keywords:  Cancer biomarker(s); Label-free quantification; Lung cancer; Mass Spectrometry; Quantification; SWATH-MS
  21. Methods Mol Biol. 2020 ;2088 33-50
      Accurate quantification of mass isotopolog distribution (MID) of intracellular metabolites is a key requirement for 13C metabolic flux analysis (13C-MFA). Liquid chromatography coupled with mass spectrometry (LC/MS) has emerged as a frontrunner technique that combines two orthogonal separation strategies. While metabolomics requires separation of monoisotopic peaks, 13C-MFA imposes additional demands for chromatographic separation as isotopologs of metabolites significantly add to the number of analytes. In this protocol chapter, we discuss two liquid chromatography methods, namely, reverse phase ion-pairing and hydrophilic interaction chromatography (HILIC) that together can separate a wide variety of metabolites that are typically used for 13C metabolic flux analysis.
    Keywords:  HILIC; Metabolic flux analysis; Nucleotides; Reverse phase ion-pairing; Sugar phosphates
  22. Talanta. 2020 Mar 01. pii: S0039-9140(19)31170-1. [Epub ahead of print]209 120537
      Monitoring pharmacological active compounds in pharmaceutical preparations of medical cannabis and in conventional and non-conventional biological matrices of treated individuals use requires both a wide linear range and sensitive detection. We have developed and validated a fast and sensitive method using ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) for analysis of Δ-9-tetrahydrocannabinol (THC), cannabidiol (CBD), their acidic precursors Δ-9-tetrahydrocannabinolic acid A (THCA-A) and cannabidiolic acid (CBDA) and some major metabolites of THC such as 11-nor-9-carboxy-THC (THC-COOH), 11-hydroxy-THC (11-OH-THC), Δ-9-THC-Glucuronide (THC-GLUC) and THC-COOH-Glucuronide (THC-COOH-GLUC) in conventional (whole blood and urine) and non-conventional (oral fluid and sweat) of individual treated with medical cannabis preparation. Specifically, THC, THCA-A, CBD and CBD-A were determined in cannabis decoction and oil prepared to treat individuals. The method used positive electrospray ionization (ESI) mode to reach the sensitivity needed to detect minimal amounts of analytes under investigations exposure with limits of quantification ranging from 0.2 to 0.5 ng per milliliter (ng/mL) or ng per patch in case of collected sweat. The validation results indicated this method was accurate (average inter/intra-day error, <10%), precise (inter/intra-day imprecision, <10%), and fast (10 min run time). In addition, time-consuming sample preparation was avoided applying dilute and shoot procedure, meeting the needs for potential large-scale population studies. The analysis of real samples demonstrated a pharmacokinetics of cannabinoids, their precursors and their metabolites dependent from quantity of carboxylated and decarboxylated compounds in pharmaceutical preparations.
    Keywords:  Biological fluids; Cannabinoids; Carboxylated and decarboxylated compounds; Medical cannabis; UHPLC-MS/MS
  23. Methods Mol Biol. 2020 ;2088 299-313
      The metabolic activity of a mammalian cell changes dynamically over time and is tied to the changing metabolic demands of cellular processes such as cell differentiation and proliferation. While experimental tools like time-course metabolomics and flux tracing can measure the dynamics of a few pathways, they are unable to infer fluxes at the whole network level. To address this limitation, we have developed the Dynamic Flux Activity (DFA) algorithm, a genome-scale modeling approach that uses time-course metabolomics to predict dynamic flux rewiring during transitions between metabolic states. This chapter provides a protocol for applying DFA to characterize the dynamic metabolic activity of various cancer cell lines.
    Keywords:  Cancer metabolism; Constraint-based modeling; Dynamic flux activity; Flux balance analysis; Genome-scale metabolic models; Time-course metabolomics
  24. Methods Mol Biol. 2020 ;2088 1-16
      The accurate and precise analysis of isotopologue and tandem mass isotopologue ratios in heavy stable isotope labeling experiments is a critical part of assessing absolute intracellular metabolic fluxes. Resulting from feeding the organism of interest with a specifically isotope-labeled substrate, the principal characteristics of these labeling experiments are the metabolites' non-naturally distributed isotopologue patterns. For the purpose of inferring metabolic rates by maximizing the fit between a priori simulated and experimentally obtained labeling patterns, 13C is the preferred stable isotope of use.The analysis of the obtained labeling patterns can be approached by different mass spectrometric approaches. Gas chromatography (GC) features broad metabolite coverage and excellent separation efficiency of biologically relevant isomers. These advantages compensate for laborious derivatization steps and the resulting need for interference correction for natural abundant isotopes.Here, we describe a workflow based on GC-high resolution mass spectrometry with chemical ionization for the analysis of carbon-isotopologue distributions and some positional labeling information of primary metabolites. To study the associated measurement uncertainty of the resulting 13C labeling patterns, guidance to uncertainty estimation according to the EURACHEM guidelines with Monte-Carlo simulation is provided.
    Keywords:  13C based metabolic flux analysis; Chemical ionization; Gas chromatography; Isotopologue distribution; Measurement uncertainty; Primary carbon metabolism; Tandem mass isotopologue distribution
  25. J Lipid Res. 2020 Jan 03. pii: jlr.RA119000198. [Epub ahead of print]
      Diets high in calories can be used to model metabolic diseases including obesity and its associated comorbidities, in animals.  Drosophila melanogaster fed high-sugar diets exhibit complications of human obesity including hyperglycemia, hyperlipidemia, insulin resistance, cardiomyopathy, increased susceptibility to infection, and reduced longevity. We hypothesize that lipid storage in the high sugar-fed fly's fat body reaches a maximum capacity, resulting in the accumulation of toxic lipids in other tissues, or lipotoxicity.  We took two approaches to characterize tissue-specific lipotoxicity. Ultra-high-performance liquid chromatography- tandem mass spectrometry (UHPLC-MS/MS) and matrix-assisted laser desorption/ionization - mass spectrometry imaging (MALDI-MSI) enabled spatial and temporal localization of lipid species in the fat body, heart, and hemolymph. Substituent chain length was diet-dependent, with fewer odd-chain esterified fatty acids on high sugar diets in all sample types. By contrast, dietary effects on double-bond content differed among organs, consistent with a model where some substituent pools are shared, and others are spatially restricted. Both di- and tri-glycerides increased on high sugar diets in all sample types, similar to observations in obese humans. Interestingly, there were dramatic effects of sugar feeding on lipid ethers, which have not been previously associated with lipotoxicity. Taken together, we have identified candidate endocrine mechanisms and molecular targets that may be involved in metabolic disease and lipotoxicity.
    Keywords:  Drosophila; Lipidomics; Lipotoxicity; Mass spectrometry; Nutrition; Obesity; lipid metabolism; mass spectrometry imaging; metabolomics
  26. J Biomol Tech. 2019 Dec;30(Suppl): S2-S3
      The mission of the ABRF Proteomics Standards Research Group (sPRG) is to identify and implement technical standards that reflect the ABRF's commitment to accuracy, clarity, and consistency in the field of proteomics. There is broad interest in quantifying protein phosphorylation alterations in cellular signaling pathways under different conditions. The transient nature and low abundance of many phosphorylation sites makes this analysis challenging. Here we report on the follow up of the two-year sPRG study designed to target various issues encountered in phosphopeptide experiments. We have constructed a pool of heavy-labeled phosphopeptides that will enable core facilities to rapidly develop assays. Our pool contains over 150 phosphopeptides that have been previously observed in mass spectrometry data sets. The specific peptides have been chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling pathways: AMPK, death and apoptosis, ErbB, insulin/IGF-1, mTOR, PI3K/AKT, and stress (p38/SAPK/JNK). We feel this pool will enable researchers to test the effectiveness of their enrichment workflows and to provide a benchmark for a cross lab study. This standard should be helpful in number of ways, including providing a complete workflow solution for phosphopeptide enrichment, as an internal enrichment and chromatography calibrant, and as a pre-built biological assay for a wide variety of signaling pathways. Previously, we mixed the standard into an activated HeLa tryptic digest and distributed the mixture to over 60 ABRF member and nonmember laboratories around the world. We asked participants to enrich phosphopeptides out of the HeLa background and report ratios of the heavy phosphopeptides to the endogenous levels. In the current study, we continue validation of the standard within various RG group/ABRF members' laboratories. The aim of this follow up study is to provide reagents, an optimized phosphopeptide enrichment protocol, instrument acquisition method parameters, and data analysis templates.
  27. Adv Exp Med Biol. 2019 ;1210 185-237
      Cancers must alter their metabolism to satisfy the increased demand for energy and to produce building blocks that are required to create a rapidly growing tumor. Further, for cancer cells to thrive, they must also adapt to an often changing tumor microenvironment, which can present new metabolic challenges (ex. hypoxia) that are unfavorable for most other cells. As such, altered metabolism is now considered an emerging hallmark of cancer. Like many other malignancies, the metabolism of prostate cancer is considerably different compared to matched benign tissue. However, prostate cancers exhibit distinct metabolic characteristics that set them apart from many other tumor types. In this chapter, we will describe the known alterations in prostate cancer metabolism that occur during initial tumorigenesis and throughout disease progression. In addition, we will highlight upstream regulators that control these metabolic changes. Finally, we will discuss how this new knowledge is being leveraged to improve patient care through the development of novel biomarkers and metabolically targeted therapies.
    Keywords:  AR; Imaging; Metabolism; Prostate cancer
  28. Cell Mol Life Sci. 2020 Jan 01.
      In tumors, cancer cells coexist and communicate with macrophages that can promote tumorigenesis via pro-inflammatory signals. Lipid mediators (LMs), produced mainly by cyclooxygenases (COXs) or lipoxygenases (LOs), display a variety of biological functions with advantageous or deleterious consequences for tumors. Here, we investigated how the communication between human monocyte-derived M2-like macrophages (MDM) and cancer cells affects LM biosynthesis using LM metabololipidomics. Coculture of human MDM with human A549 epithelial lung carcinoma cells, separated by a semipermeable membrane, increased LM formation by MDM upon subsequent activation. Strongest effects were observed on 5-LO-derived LM. While expression of the 5-LO pathway was not altered, p38 MAPK and the downstream MAPKAPK-2 that phosphorylates and stimulates 5-LO were more susceptible for activation in MDM upon precedent coculture with A549 cells as compared to monocultures. Accordingly, the p38 MAPK inhibitor Skepinone-L selectively prevented this increase in 5-LO product formation. Also, 5-LO-/15-LO-derived LM including lipoxin A4, resolvin D2 and D5 were elevated after coculture with A549 cells, correlating to increased 15-LO-1 protein levels. In contrast to cancer cells, coincubation with non-transformed human umbilical vein endothelial cells (HUVEC) did not affect LM production in MDM. Vice versa, MDM increased COX-2 protein expression and COX-mediated prostanoid formation in cancer cells. Conclusively, our data reveal that the communication between MDM and cancer cells can strikingly modulate the biosynthetic capacities to produce bioactive LM with potential relevance for tumor biology.
    Keywords:  Cyclooxygenase; Leukotrienes; Lipoxygenase; Prostaglandins; Specialized pro-resolving mediators
  29. Methods Mol Biol. 2020 ;2088 189-204
      Recently, the sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH) method coupled with liquid chromatography has been demonstrated for the quantification of isotopic 13C enrichment in a large number of cellular metabolites and fragments. SWATH, a data-independent acquisition (DIA) method, alleviates the need for data deconvolution and shows greater accuracy in the quantification of low abundance isotopologs of fragments thereby resulting in a lower systematic error. Here we provide a detailed protocol for the design of Q1 mass isolation windows and the post-acquisition data analysis with emphasis on the untargeted nature of SWATH.
    Keywords:  13C metabolic flux analysis; Liquid chromatography–mass spectrometry; Mass isotopolog distribution; Multiple reaction monitoring; Parallel reaction monitoring
  30. Cell. 2019 Dec 21. pii: S0092-8674(19)31331-5. [Epub ahead of print]
      Autophagy is a conserved catabolic homeostasis process central for cellular and organismal health. During autophagy, small single-membrane phagophores rapidly expand into large double-membrane autophagosomes to encapsulate diverse cargoes for degradation. It is thought that autophagic membranes are mainly derived from preformed organelle membranes. Instead, here we delineate a pathway that expands the phagophore membrane by localized phospholipid synthesis. Specifically, we find that the conserved acyl-CoA synthetase Faa1 accumulates on nucleated phagophores and locally activates fatty acids (FAs) required for phagophore elongation and autophagy. Strikingly, using isotopic FA tracing, we directly show that Faa1 channels activated FAs into the synthesis of phospholipids and promotes their assembly into autophagic membranes. Indeed, the first committed steps of de novo phospholipid synthesis at the ER, which forms stable contacts with nascent autophagosomes, are essential for autophagy. Together, our work illuminates how cells spatially tune synthesis and flux of phospholipids for autophagosome biogenesis during autophagy.
    Keywords:  Acyl-CoA synthetase; autophagosome biogenesis; autophagy; de novo phospholipid synthesis; endoplasmic reticulum; fatty acid metabolism; membrane composition; membrane contact site; phagophore expansion; phospholipids
  31. Methods Mol Biol. 2020 ;2088 223-269
      Metabolic network flux analysis uses genome-scale metabolic reconstructions to integrate transcriptomics, proteomics, and/or metabolomics data to allow for comprehensive interpretation of genotype to metabolic phenotype relationships. The compilation of many Constraint-based model analysis methods into one MATLAB package, the COBRAtoolbox, has opened the possibility of using these methods to the many biologists with some knowledge of the commonly used statistical program, MATLAB. Here we outline the steps required to take a published genome-scale metabolic reconstruction and interrogate its consistency and biological feasibility. Subsequently, we demonstrate how mRNA expression data and metabolomics data, relating to one or more cell types or biological contexts, can be applied to constrain and generate metabolic models descriptive of metabolic flux phenotypes. Finally, we describe the comparison of the resulting models and model outputs with the aim of identifying metabolic biomarkers and changes in cellular metabolism.
    Keywords:  Constraint-based metabolic models; Data integration; Flux balance analysis; Genome-scale reconstruction; Metabolomics; Systems biology; Transcriptomics
  32. Int J Oncol. 2019 Dec 20.
      Wilms' tumor is one of the most common malignant tumors of the abdomen in children. However, there is currently no recognized specific biomarker for the clinical diagnosis and prognosis of this tumor. Lipid metabolism is involved in membrane synthesis and oxidation in tumor cells. This process plays an important role in the development of tumors, but it has not yet been investigated in Wilms' tumor. The aim of the present study was to characterize the changes in lipid metabolism and to contribute to the diagnosis and prognosis of Wilms' tumor. Proteomics analysis was performed to detect lipid‑metabolizing enzymes in 9 tissue samples from Wilms' tumors and adjacent tissues, and proteomics revealed the presence of 19 differentially expressed lipid‑metabolizing enzymes. Protein interaction analysis with the Search Tool for the Retrieval of Interacting Genes/Proteins was used to identify the interacting proteins. Immunohistochemistry (IHC), immunofluorescence and western blotting were used to further confirm whether the expression of fatty acid synthase (FASN) was significantly increased in the tumor tissues. Oncomine database and reverse transcription‑PCR analyses further confirmed that the expression of FASN at the gene level was significantly increased in the tumors. Following collection of 65 pediatric cases of Wilms' tumor at the Shandong Provincial Hospital between 2007 and 2012, the association between the expression of FASN and the clinical characteristics was analyzed, and IHC analysis further demonstrated that FASN expression was significantly associated with tumor stage and size. The association between FASN and the prognosis of children with Wilms' tumor was analyzed using Kaplan‑Meier survival curves. In addition, univariate survival analysis revealed that higher expression of FASN in Wilms' tumors was associated with poorer prognosis. Our findings revealed that FASN may be used as a prognostic biomarker in patients with Wilms' tumor. Furthermore, lipid metabolism may play an important role in the occurrence and development of Wilms' tumor.
  33. Talanta. 2020 Mar 01. pii: S0039-9140(19)31226-3. [Epub ahead of print]209 120593
      The impact of preanalytical sample handling on lipid stability has been assessed in human plasma using targeted LC-MS/MS quantification of endocannabinoids, sphingolipids and LPA, complemented by non-targeted lipidomics screening with LC-QTOFMS. The study involved incubation of whole blood and plasma from healthy volunteers at room temperature or in ice water for time periods ranging from 20 min to 24 h. The impact of two different anticoagulants, K3EDTA and sodium fluoride/citrate, on lipid stability was evaluated. It was found that the concentrations determined for several endogenous lipids vary when whole blood and plasma samples are processed at room temperature, whereas the concentrations of most lipids were stable for 4 h in ice water. Surprisingly, the detected amounts of endocannabinoids 1- and 2-arachidonoyl glycerol and arachidonoyl ethanolamide increased markedly by 60, 95, and 30% in K3EDTA whole blood after storage in ice water for only 20 min. When using sodium fluoride/citrate blood collection tubes, the stability of several lipids, including that of the endocannabinoids, was improved. Accordingly, it is absolutely necessary to keep the blood sampling and plasma processing time below 1 h to avoid ex-vivo formation of endocannabinoids. It is worth mentioning that baseline lipid levels differ when using K3EDTA or sodium fluoride/citrate blood sampling tubes, which emphasizes the importance of traceability of reported plasma concentrations to the used anticoagulant.
    Keywords:  Ceramides; Endocannabinoids; Lipidomics; Lysophosphatidic acid; Mass spectrometry; Preanalytical stability
  34. Anal Chem. 2020 Jan 02.
      Identification of metabolites at trace level in complex samples is still one of major challenges in untargeted metabolomics. One formula in the metabolomic database is always corresponding for more than one candidate, which increases the difficulty and cost in the process of standard compound matching. Hydrogen-deuterium exchange combined with liquid chromatography-mass spectrometry (HDX-LC-MS) can decrease the number of candidates through reflecting the number of labile hydrogen atoms according to isotopic distribution. However, current methods of HDX-LC-MS are only suitable for the identification of metabolites with specific structures, which is insufficient for untargeted metabolomics. In this study, we developed an effective method for metabolite identification by H-D scrambling based on chemical isotope labeling coupled with LC-MS (HDS-CIL-LC-MS). HDS is sorted as the intramolecular HDX and occur with the addition of energy. After isotope labeling, the labile hydrogen atoms in analytes can produce HDS under collision-induced dissociation (CID), which expands the scope of application of HDS in metabolites. The HDS can effectively reflect the numbers of labile hydrogen atoms in analytes and thus distinguish isomers of with different functional groups. In addition, the relative intensity between isotopic peaks generated by HDS can distinguish isomers containing the same functional groups. Finally, the developed method was applied to the determination of amine metabolites in mice feces. Using HDS rules, the obtained candidates were reduced by 64% on average, which greatly reduces the cost of standard compound matching. Taken together, the developed HDS-CIL-LC-MS analysis was demonstrated to be a promising method for untargeted metabolomics.