bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒06‒21
twenty-nine papers selected by
Giovanny Rodriguez Blanco
The Beatson Institute for Cancer Research

  1. Cell. 2020 Jun 18. pii: S0092-8674(20)30686-3. [Epub ahead of print]
    Koundouros N, Karali E, Tripp A, Valle A, Inglese P, Perry NJS, Magee DJ, Anjomani Virmouni S, Elder GA, Tyson AL, Dória ML, van Weverwijk A, Soares RF, Isacke CM, Nicholson JK, Glen RC, Takats Z, Poulogiannis G.
      Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA-induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction.
    Keywords:  PIK3CA; PKCζ; arachidonic acid; cPLA2; cancer metabolism; diet; eicosanoids; fat restriction; iKnife; mTORC2
  2. Adv Drug Deliv Rev. 2020 Jun 14. pii: S0169-409X(20)30055-7. [Epub ahead of print]
    Wu Z, Bagarolo GI, Thoröe-Boveleth S, Jankowski J.
      Lipids are ubiquitous in the human organism and play essential roles as components of cell membranes and hormones, for energy storage or as mediators of cell signaling pathways. As crucial mediators of the human metabolism, lipids are also involved in metabolic diseases, cardiovascular and renal diseases, cancer and/or hepatological and neurological disorders. With rapidly growing evidence supporting the impact of lipids on both the genesis and progression of these diseases as well as patient wellbeing, the characterization of the human lipidome has gained high interest and importance in life sciences and clinical diagnostics within the last 15 years. This is mostly due to technically advanced molecular identification and quantification methods, mainly based on mass spectrometry. Mass spectrometry has become one of the most powerful tools for the identification of lipids. New lipidic mediators or biomarkers of diseases can be analysed by state-of-the art mass spectrometry techniques supported by sophisticated bioinformatics and biostatistics. The lipidomic approach has developed dramatically in the realm of life sciences and clinical diagnostics due to the available mass spectrometric methods and in particular due to the adaptation of biostatistical methods in recent years. Therefore, the current knowledge of lipid extraction methods, mass-spectrometric approaches, biostatistical data analysis, including workflows for the interpretation of lipidomic high-throughput data, are reviewed in this manuscript.
    Keywords:  Chemometric analysis; Ionization; Lipidomics; Lipids; Mass analyser; Mass spectrometry; Sample introduction
  3. Front Pharmacol. 2020 ;11 730
    Decara J, Rivera P, López-Gambero AJ, Serrano A, Pavón FJ, Baixeras E, Rodríguez de Fonseca F, Suárez J.
      The peroxisome proliferator-activated receptors (PPARs) are a group of nuclear receptor proteins that promote ligand-dependent transcription of target genes that regulate energy production, lipid metabolism, and inflammation. The PPAR superfamily comprises three subtypes, PPARα, PPARγ, and PPARβ/δ, with differential tissue distributions. In addition to their different roles in the regulation of energy balance and carbohydrate and lipid metabolism, an emerging function of PPARs includes normal homeostasis of intestinal tissue. PPARα activation represses NF-κB signaling, which decreases the inflammatory cytokine production by different cell types, while PPARγ ligands can inhibit activation of macrophages and the production of inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, and Il-1β. In this regard, the anti-inflammatory responses induced by PPAR activation might restore physiopathological imbalances associated with inflammatory bowel diseases (IBD). Thus, PPARs and their ligands have important therapeutic potential. This review briefly discusses the roles of PPARs in the physiopathology and therapies of the most important IBDs, ulcerative colitis (UC), and Crohn's disease (CD), as well some new experimental compounds with PPAR activity as promising drugs for IBD treatment.
    Keywords:  Crohn's disease; PPARα; PPARβ/δ; PPARγ; inflammatory bowel diseases; ulcerative colitis
  4. JCI Insight. 2020 Jun 19. pii: 140327. [Epub ahead of print]
    Thomas T, Stefanoni D, Reisz JA, Nemkov T, Bertolone L, Francis RO, Hudson KE, Zimring JC, Hansen KC, Hod EA, Spitalnik SL, D'Alessandro A.
      Reprogramming of host metabolism supports viral pathogenesis by fueling viral proliferation, by providing, for example, free amino acids and fatty acids as building blocks. To investigate metabolic effects of SARS-COV-2 infection, we evaluated serum metabolites of COVID-19 patients (n = 33; diagnosed by nucleic acid testing), as compared to COVID-19-negative controls (n = 16). Targeted and untargeted metabolomics analyses identified altered tryptophan metabolism into the kynurenine pathway, which regulates inflammation and immunity. Indeed, these changes in tryptophan metabolism correlated with interleukin-6 (IL-6) levels. Widespread dysregulation of nitrogen metabolism was also seen in infected patients, with altered levels of most amino acids, along with increased markers of oxidant stress (e.g., methionine sulfoxide, cystine), proteolysis, and renal dysfunction (e.g., creatine, creatinine, polyamines). Increased circulating levels of glucose and free fatty acids were also observed, consistent with altered carbon homeostasis. Interestingly, metabolite levels in these pathways correlated with clinical laboratory markers of inflammation (i.e., IL-6 and C-reactive protein) and renal function (i.e., blood urea nitrogen). In conclusion, this initial observational study identified amino acid and fatty acid metabolism as correlates of COVID-19, providing mechanistic insights, potential markers of clinical severity, and potential therapeutic targets.
    Keywords:  Amino acid metabolism; COVID-19; Intermediary metabolism; Metabolism
  5. Acta Virol. 2020 ;64(2): 201-215
    Polcicova K, Badurova L, Tomaskova J.
      Viral replication depends entirely on the energy and biosynthetic precursors supplied by the host cell metabolic network. Viruses actively reprogram host cell metabolism to establish optimal environment for their replication and spread. They stimulate the uptake of extracellular nutrients and predominantly modulate glucose, glutamine, and fatty acid metabolism to support anabolic metabolic pathways. Some viruses activate the process of aerobic glycolysis, divert the glycolytic carbon for biosynthetic reactions, and stimulate glutamine utilization to replenish tricarboxylic cycle intermediates. Others use glutamine carbon to promote de novo fatty acid synthesis, amino acid supply or glutathione production. The unique metabolic signature and different dependence of viral life cycle on the individual metabolic processes is therefore characteristic feature of almost each virus. Deeper understanding of how viruses alter cellular metabolic pathways or their upstream regulatory circuits may lead to development of more effective antiviral treatment strategies based on targeted metabolic inhibition. Keywords: virus infection; metabolism; glycolysis; glutamine metabolism; fatty acid synthesis; metabolic reprogramming; virus-host interaction.
  6. Molecules. 2020 Jun 11. pii: E2718. [Epub ahead of print]25(11):
    Li J, Zhu HJ.
      Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics is a powerful tool for identifying and quantifying proteins in biological samples, outperforming conventional antibody-based methods in many aspects. LC-MS/MS-based proteomics studies have revealed the protein abundances of many drug-metabolizing enzymes and transporters (DMETs) in tissues relevant to drug metabolism and disposition. Previous studies have consistently demonstrated marked interindividual variability in DMET protein expression, suggesting that varied DMET function is an important contributing factor for interindividual variability in pharmacokinetics (PK) and pharmacodynamics (PD) of medications. Moreover, differential DMET expression profiles were observed across different species and in vitro models. Therefore, caution must be exercised when extrapolating animal and in vitro DMET proteomics findings to humans. In recent years, DMET proteomics has been increasingly utilized for the development of physiologically based pharmacokinetic models, and DMET proteins have also been proposed as biomarkers for prediction of the PK and PD of the corresponding substrate drugs. In sum, despite the existence of many challenges in the analytical technology and data analysis methods of LC-MS/MS-based proteomics, DMET proteomics holds great potential to advance our understanding of PK behavior at the individual level and to optimize treatment regimens via the DMET protein biomarker-guided precision pharmacotherapy.
    Keywords:  LC-MS/MS; drug-metabolizing enzymes; proteomics; transporters
  7. Anal Chem. 2020 Jun 19.
    Mao Y, Kleinberg A, Li N.
      Peptide mapping coupled with liquid chromatography-mass spectrometry (LC-MS) has become an essential analytical technique to quantify the quality attributes (e.g., post-translational modifications [PTMs]) of monoclonal antibodies (mAbs) during drug development. However, the traditional label-free approach for relative quantitation of PTMs requires a great amount of instrument time for LC-MS data acquisition of individual digested samples, limiting the efficiency of peptide mapping when there is an increasing demand for protein characterization. Here, we developed a tandem mass tag (TMT) based approach in combination with targeted mass spectrometry for multiplexed site-specific PTM quantitation of monoclonal antibodies to overcome this limitation. This approach enables the simultaneous quantitation of quality attributes (e.g., PTMs) for multiple samples in a single LC-MS run. By adjusting higher-energy collision dissociation (HCD) normalized collisional energies (NCEs) from 35-90, different types of PTMs were quantified with comparable percentages to those obtained using the conventional approach. The TMT over-labeling on the off-target amino acid residues serine, threonine, and tyrosine was observed to pose a challenge for this targeted MS/MS based PTM quantitation. However, we inhibited this off-target over-labeling by adding a small molecule additive during the TMT labeling as a decoy reagent to deplete the excess amount of TMT reagent. The PTM quantitative performance of this approach demonstrated high sensitivity and reproducibility of PTM quantitation with levels as low as 1.0%. Finally, this approach has been utilized to quantify the PTMs for forced degradation samples, comparability samples and trisulfide standards of monoclonal antibodies.
  8. Nat Commun. 2020 Jun 18. 11(1): 3097
    Suchacki KJ, Tavares AAS, Mattiucci D, Scheller EL, Papanastasiou G, Gray C, Sinton MC, Ramage LE, McDougald WA, Lovdel A, Sulston RJ, Thomas BJ, Nicholson BM, Drake AJ, Alcaide-Corral CJ, Said D, Poloni A, Cinti S, Macpherson GJ, Dweck MR, Andrews JPM, Williams MC, Wallace RJ, van Beek EJR, MacDougald OA, Morton NM, Stimson RH, Cawthorn WP.
      Bone marrow adipose tissue (BMAT) comprises >10% of total adipose mass, yet unlike white or brown adipose tissues (WAT or BAT) its metabolic functions remain unclear. Herein, we address this critical gap in knowledge. Our transcriptomic analyses revealed that BMAT is distinct from WAT and BAT, with altered glucose metabolism and decreased insulin responsiveness. We therefore tested these functions in mice and humans using positron emission tomography-computed tomography (PET/CT) with 18F-fluorodeoxyglucose. This revealed that BMAT resists insulin- and cold-stimulated glucose uptake, while further in vivo studies showed that, compared to WAT, BMAT resists insulin-stimulated Akt phosphorylation. Thus, BMAT is functionally distinct from WAT and BAT. However, in humans basal glucose uptake in BMAT is greater than in axial bones or subcutaneous WAT and can be greater than that in skeletal muscle, underscoring the potential of BMAT to influence systemic glucose homeostasis. These PET/CT studies characterise BMAT function in vivo, establish new methods for BMAT analysis, and identify BMAT as a distinct, major adipose tissue subtype.
  9. Metabolites. 2020 Jun 17. pii: E252. [Epub ahead of print]10(6):
    Upadhyay M, Rajagopal M, Gill K, Li Y, Bansal S, Sridharan V, Tyburski JB, Boerma M, Cheema AK.
      Long-term exposures to low dose space radiation may have adverse effects on human health during missions in deep space. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as biomarkers of organ- and tissue-specific radiation injury, particularly of injuries that appear weeks or months after radiation exposure. To assess the feasibility of using plasma metabolic and lipidomic profiles as biomarkers of injury from space radiation, we used a mouse model of exposure to low doses of oxygen ions (16O) and protons (1H). Plasma profiles were compared with those of mice exposed to γ-rays as a reference set. Our results demonstrate major changes in glycerophospholipid metabolism, amino acid metabolism, as well as fatty acid metabolism. We also observed dyslipidemia and lipid peroxidation, suggesting an inflammatory phenotype with possible long-term consequences to overall health upon exposure to low doses of high linear energy transfer (LET) radiation.
    Keywords:  ionizing radiation; lipidomics; mass spectrometry; oxygen radiation; plasma metabolomics; untargeted profiling
  10. Cell Metab. 2020 Jun 09. pii: S1550-4131(20)30303-X. [Epub ahead of print]
    Cheng X, Geng F, Pan M, Wu X, Zhong Y, Wang C, Tian Z, Cheng C, Zhang R, Puduvalli V, Horbinski C, Mo X, Han X, Chakravarti A, Guo D.
      Glioblastoma (GBM), a mostly lethal brain tumor, acquires large amounts of free fatty acids (FAs) to promote cell growth. But how the cancer avoids lipotoxicity is unknown. Here, we identify that GBM upregulates diacylglycerol-acyltransferase 1 (DGAT1) to store excess FAs into triglycerides and lipid droplets. Inhibiting DGAT1 disrupted lipid homeostasis and resulted in excessive FAs moving into mitochondria for oxidation, leading to the generation of high levels of reactive oxygen species (ROS), mitochondrial damage, cytochrome c release, and apoptosis. Adding N-acetyl-cysteine or inhibiting FA shuttling into mitochondria decreased ROS and cell death induced by DGAT1 inhibition. We show in xenograft models that targeting DGAT1 blocked lipid droplet formation, induced tumor cell apoptosis, and markedly suppressed GBM growth. Together, our study demonstrates that DGAT1 upregulation protects GBM from oxidative damage and maintains lipid homeostasis by facilitating storage of excess FAs. Targeting DGAT1 could be a promising therapeutic approach for GBM.
    Keywords:  DGAT1; ROS; acylcarnitine; fatty acids; glioblastoma; lipid droplets; lipotoxicity; mitochondria; oxidative stress; triglycerides
  11. Nat Biotechnol. 2020 Jun 15.
    Tsugawa H, Ikeda K, Takahashi M, Satoh A, Mori Y, Uchino H, Okahashi N, Yamada Y, Tada I, Bonini P, Higashi Y, Okazaki Y, Zhou Z, Zhu ZJ, Koelmel J, Cajka T, Fiehn O, Saito K, Arita M, Arita M.
      We present Mass Spectrometry-Data Independent Analysis software version 4 (MS-DIAL 4), a comprehensive lipidome atlas with retention time, collision cross-section and tandem mass spectrometry information. We formulated mass spectral fragmentations of lipids across 117 lipid subclasses and included ion mobility tandem mass spectrometry. Using human, murine, algal and plant biological samples, we annotated and semiquantified 8,051 lipids using MS-DIAL 4 with a 1-2% estimated false discovery rate. MS-DIAL 4 helps standardize lipidomics data and discover lipid pathways.
  12. Mass Spectrom (Tokyo). 2020 ;9(1): A0080
    Nakatani K, Izumi Y, Hata K, Bamba T.
      The rapid development of next-generation sequencing techniques has enabled single-cell genomic and transcriptomic analyses, which have revealed the importance of heterogeneity in biological systems. However, analytical methods to accurately identify and quantify comprehensive metabolites from single mammalian cells with a typical diameter of 10-20 μm are still in the process of development. The aim of this study was to develop a single-cell metabolomic analytical system based on highly sensitive nano-liquid chromatography tandem mass spectrometry (nano-LC-MS/MS) with multiple reaction monitoring. A packed nano-LC column (3-μm particle-size pentafluorophenylpropyl Discovery HSF5 of dimensions 100 μm i.d.×180 mm) was prepared using a slurry technique. The optimized nano-LC-MS/MS method showed 3-132-fold (average value, 26-fold) greater sensitivity than semimicro-LC-MS/MS, and the detection limits for several hydrophilic metabolites, including amino acids and nucleic acid related metabolites were in the sub-fmol range. By combining live single-cell sampling and nano-LC-MS/MS, we successfully detected 18 relatively abundant hydrophilic metabolites (16 amino acids and 2 nucleic acid related metabolites) from single HeLa cells (n=22). Based on single-cell metabolic profiles, the 22 HeLa cells were classified into three distinct subclasses, suggesting differences in metabolic function in cultured HeLa cell populations. Our single-cell metabolomic analytical system represents a potentially useful tool for in-depth studies focused on cell metabolism and heterogeneity.
    Keywords:  hydrophilic metabolites; metabolome; multiple reaction monitoring; nano-LC-MS/MS; single-cell analysis
  13. Nat Commun. 2020 Jun 19. 11(1): 3128
    Tayri-Wilk T, Slavin M, Zamel J, Blass A, Cohen S, Motzik A, Sun X, Shalev DE, Ram O, Kalisman N.
      Whole-cell cross-linking coupled to mass spectrometry is one of the few tools that can probe protein-protein interactions in intact cells. A very attractive reagent for this purpose is formaldehyde, a small molecule which is known to rapidly penetrate into all cellular compartments and to preserve the protein structure. In light of these benefits, it is surprising that identification of formaldehyde cross-links by mass spectrometry has so far been unsuccessful. Here we report mass spectrometry data that reveal formaldehyde cross-links to be the dimerization product of two formaldehyde-induced amino acid modifications. By integrating the revised mechanism into a customized search algorithm, we identify hundreds of cross-links from in situ formaldehyde fixation of human cells. Interestingly, many of the cross-links could not be mapped onto known atomic structures, and thus provide new structural insights. These findings enhance the use of formaldehyde cross-linking and mass spectrometry for structural studies.
  14. Metabolomics. 2020 Jun 17. 16(7): 74
    Markin PA, Brito A, Moskaleva N, Lartsova EV, Shpot YV, Lerner YV, Mikhajlov VY, Potoldykova NV, Enikeev DV, La Frano MR, Appolonova SA.
      INTRODUCTION: The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling.OBJECTIVE: To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa).
    METHODS: Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined.
    RESULTS: The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal-Wallis test with Dunn's post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = - 0.60, p < 0.05; r = - 0.54, p < 0.01) and uridine (r = - 0.58, p < 0.05; r = - 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25-P75) = 883.0 (619.8-956.4) versus 570.8 (505.6-651.8), respectively (p < 0.01)].
    CONCLUSIONS: This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.
    Keywords:  Gas chromatography/mass spectrometry; Metabolome; Metabolomics; Prostate cancer; Ultra performance liquid chromatography-triple quadrupole/mass spectrometry
  15. Nutrients. 2020 Jun 17. pii: E1792. [Epub ahead of print]12(6):
    AlGhamdi AA, Mohammed MRS, Zamzami MA, Al-Malki AL, Qari MH, Khan MI, Choudhry H.
      Thymoquinone (TQ), a naturally occurring anticancer compound extracted from Nigella sativa oil, has been extensively reported to possess potent anti-cancer properties. Experimental studies showed the anti-proliferative, pro-apoptotic, and anti-metastatic effects of TQ on different cancer cells. One of the possible mechanisms underlying these effects includes alteration in key metabolic pathways that are critical for cancer cell survival. However, an extensive landscape of the metabolites altered by TQ in cancer cells remains elusive. Here, we performed an untargeted metabolomics study using leukemic cancer cell lines during treatment with TQ and found alteration in approximately 335 metabolites. Pathway analysis showed alteration in key metabolic pathways like TCA cycle, amino acid metabolism, sphingolipid metabolism and nucleotide metabolism, which are critical for leukemic cell survival and death. We found a dramatic increase in metabolites like thymine glycol in TQ-treated cancer cells, a metabolite known to induce DNA damage and apoptosis. Similarly, we observed a sharp decline in cellular guanine levels, important for leukemic cancer cell survival. Overall, we provided an extensive metabolic landscape of leukemic cancer cells and identified the key metabolites and pathways altered, which could be critical and responsible for the anti-proliferative function of TQ.
    Keywords:  DNA damage; LC-MS/MS; leukemia; metabolism; metabolites; thymoquinone
  16. J Proteome Res. 2020 Jun 15.
    Guan S, Taylor PP, Han Z, Moran MF, Ma B.
      Data dependent acquisition (DDA) and data independent acquisition (DIA) are traditionally separate experimental paradigms in bottom-up proteomics. In this work, we developed a strategy combining the two experimental methods into a single LC-MS/MS run. We call the novel strategy data dependent-independent acquisition proteomics, or DDIA for short. Peptides identified from DDA scans by a conventional and robust DDA identification workflow provide useful information for interrogation of DIA scans. Deep learning based LC-MS/MS property prediction tools, developed previously, can be used repeatedly to produce spectral libraries facilitating DIA scan extraction. A complete DDIA data processing pipeline, including the modules for iRT vs RT calibration curve generation, DIA extraction classifier training, and false discovery rate control, has been developed. Compared to another spectral library-free method, DIA-Umpire, the DDIA method produced a similar number of peptide identifications, but nearly twice as many protein group identifications. The primary advantage of the DDIA method is that it requires minimal information for processing its data.
    Keywords:  data-dependent acquisition; data-independent acquisition; deep learning; peptide identification; protein identification; retention time prediction; spectrum prediction
  17. J Vis Exp. 2020 May 31.
    Bogusiewicz J, Goryńska PZ, Gaca M, Chmara K, Goryński K, Jaroch K, Paczkowski D, Furtak J, Harat M, Bojko B.
      Despite the variety of tools available for cancer diagnosis and classification, methods that enable fast and simple characterization of tumors are still in need. In recent years, mass spectrometry has become a method of choice for untargeted profiling of discriminatory compound as potential biomarkers of a disease. Biofluids are generally considered as preferable matrices given their accessibility and easier sample processing while direct tissue profiling provides more selective information about a given cancer. Preparation of tissues for the analysis via traditional methods is much more complex and time-consuming, and, therefore, not suitable for fast on-site analysis. The current work presents a protocol combining sample preparation and extraction of small molecules on-site, immediately after tumor resection. The sampling device, which is of the size of an acupuncture needle, can be inserted directly into the tissue and then transported to the nearby laboratory for instrumental analysis. The results of metabolomics and lipidomics analyses demonstrate the capability of the approach for the establishment of phenotypes of tumors related to the histological origin of the tumor, malignancy, and genetic mutations, as well as for the selection of discriminating compounds or potential biomarkers. The non-destructive nature of the technique permits subsequent performance of routinely used tests e.g., histological tests, on the same samples used for SPME analysis, thus enabling attainment of more comprehensive information to support personalized diagnostics.
  18. Front Oncol. 2020 ;10 791
    Yoshida GJ.
      Cancer cells generate large amounts of lactate derived from glucose regardless of the available oxygen level. Cancer cells finely control ATP synthesis by modulating the uptake of substrates and the activity of enzymes involved in aerobic glycolysis (Warburg effect), which enables them to adapt to the tumor microenvironment. However, increasing evidence suggests that mitochondrial metabolism, including the tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), and glutaminolysis, is paradoxically activated in MYCN-amplified malignancies. Unlike non-amplified cells, MYCN-amplified cancer cells significantly promote OXPHOS-dependent ATP synthesis. Furthermore, tumor cells are differentially dependent on fatty acid β-oxidation (FAO) according to N-Myc status. Therefore, upregulation of FAO-associated enzymes is positively correlated with both N-Myc expression level and poor clinical outcome. This review explores therapeutic strategies targeting cancer stem-like cells for the treatment of tumors associated with MYCN amplification.
    Keywords:  N-Myc; TCA cycle; acyclic retinoid; amino acid transporter; cancer stem-like cells; fatty acid β-oxidation; glutaminolysis; mitochondria
  19. Metabolites. 2020 Jun 15. pii: E249. [Epub ahead of print]10(6):
    Fan TW, Higashi RM, Chernayavskaya Y, Lane AN.
      The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.
    Keywords:  3D cultures; stable isotope resolved metabolomics; tissue slices; tumor microenvironment
  20. Mol Cell. 2020 Jun 18. pii: S1097-2765(20)30355-5. [Epub ahead of print]78(6): 1019-1033
    Bader JE, Voss K, Rathmell JC.
      The growing field of immune metabolism has revealed promising indications for metabolic targets to modulate anti-cancer immunity. Combination therapies involving metabolic inhibitors with immune checkpoint blockade (ICB), chemotherapy, radiation, and/or diet now offer new approaches for cancer therapy. However, it remains uncertain how to best utilize these strategies in the context of the complex tumor microenvironment (TME). Oncogene-driven changes in tumor cell metabolism can impact the TME to limit immune responses and present barriers to cancer therapy. These changes also reveal opportunities to reshape the TME by targeting metabolic pathways to favor immunity. Here we explore current strategies that shift immune cell metabolism to pro-inflammatory states in the TME and highlight a need to better replicate physiologic conditions to select targets, clarify mechanisms, and optimize metabolic inhibitors. Unifying our understanding of these pathways and interactions within the heterogenous TME will be instrumental to advance this promising field and enhance immunotherapy.
  21. Angew Chem Int Ed Engl. 2020 Jun 14.
    Chen N, Liu Y, Li Y, Wang C.
      Protein 4 ' - phosphopantetheinylation is an essential post-translational modification (PTM) in prokaryotes and eukaryotes. So far, only five protein substrates of this specific PTM have been discovered in mammalian cells. These proteins are known to perform important functions including fatty acid biosynthesis and folate metabolism, as well as β -alanine activation. In order to explore existing and new substrates of 4 ' - phosphopantetheinylation in mammalian proteomes, we designed and synthesized a series of new pantetheine analogue probes enabling effective metabolic labelling of 4 ' - phosphopantetheinylated proteins in HepG2 cells . In combination with a quantitative chemical proteomic platform, we enriched and identified all the currently known 4 ' - phosphopantetheinylated proteins with high confidence, and unambiguously determined their exact sites of modification. More encouragingly, we discovered, via targeted proteomics , a potential 4 ' - phosphopantetheinylated site in the protein of mitochondrial dehydrogenase/reductase SDR family member 2 (DHRS2).
    Keywords:  4'-phosphopantetheinylation; DHRS2; chemical proteomics; metabolic labeling; targeted proteomics
  22. J Steroid Biochem Mol Biol. 2020 Jun 11. pii: S0960-0760(20)30234-X. [Epub ahead of print] 105709
    Gan C, Huang X, Wu Y, Zhan J, Zhang X, Liu Q, Huang Y.
      The current study aims to evaluate the antiproliferative activity of B-norcholesteryl benzimidazole compounds in human ovarian cancer cells (SKOV3). Our experimental data indicates that the tested compounds can induce apoptosis in SKOV3 cells, block S-phase growth, and decrease mitochondrial membrane potential. Western blot results showed that B-norcholesteryl benzimidazole compounds (1 and 2) induced apoptosis in SKOV3 cells via activation of the mitochondrial signaling pathway. Following SKOV3 cells treatment with compounds 1 and 2, the cell metabolism was assessed using the UHPLC-QE-MS (Ultra High Performance Liquid Chromatography-Q Exactive Orbitrap- Mass Spectrometry) non-target metabolomics analysis method. The results showed 10 metabolic pathways that mediated the effects of compound 1, including arginine and proline metabolism; alanine, aspartate, and glutamate metabolism; histidine metabolism; D-glutamine and D-glutamate metabolism; cysteine and methionine metabolism; aminoacyl-tRNA biosynthesis; purine metabolism; Glutathione metabolism; D-Arginine and D-ornithine metabolism; and Nitrogen metabolism. From the perspective of metabolomics, compound 1 inhibits intracellular metabolism, protein synthesis, and slows down energy metabolism in SKOV3 cells. These changes result in the inhibition of proliferation and signal transduction, abrogate invasive and metastatic properties, and induce apoptosis, thus, exerting anti-tumor effects. Application of compound 2 altered activation of metabolic pathways in SKOV3 cells. The main metabolic pathways involved were glycerophospholipid metabolism; arginine and proline metabolism; purine metabolism; glycine, serine, and threonine metabolism; and ether lipid metabolism. The metabolic pathway with the greatest impact and the deepest enrichment was the glycerophospholipid metabolism. In conclusion, compound 2 inhibits proliferation of SKOV3 cells by interfering with glycerate metabolism, which plays a major role in regulation of cell membrane structure and function. Additionally, compound 2 can inhibit the invasion and metastasis of SKOV3 cells and induce apoptosis via interfering with the metabolism of arginine and proline.
    Keywords:  B-norcholesteryl benzimidazole compounds; SKOV3 cells; apoptosis; untargeted metabolomics
  23. Anal Bioanal Chem. 2020 Jun 17.
    Ellisor DL, Davis WC, Pugh RS.
      Biological reference materials (RMs) are essential for quality assurance, traceability of measurement results and for method validation. When addressing new measurement questions or emerging regulatory issues, rigorous large-scale CRM production may not be time efficient or economically practical using current production methods. By amending a relatively small matrix batch with a compound(s) of interest at the homogenization step, the National Institute of Standards and Technology (NIST) can create a custom material on an "as-needed" basis and circumvent the time delay inherent in large-batch production, thereby generating a fit-for-purpose, rapid-response RM. Here, Coho salmon (Oncorhynchus kisutch) was cryohomogenized and spiked with an aquaculture antibiotic and antibiotic metabolite. The resultant material was analyzed using liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) to determine the effectiveness of the amendment technique in a fresh-frozen matrix by assessing homogeneity and accuracy to the target concentration (e.g. mass fraction). Target mass fractions were achieved for both spike components, with RSDs below 5% in replicate measurements of each compound (n = 8). The stability of the spiked compounds was assessed one year post-production and mass fractions were stable, within 1-6% of the initial measurement results, indicating minimal change to the amended analyte concentrations over time. The results support this method as a promising new technique for custom, small-batch RM generation.
    Keywords:  Bioanalytical methods; Biological samples; Reference materials
  24. Methods. 2020 Jun 13. pii: S1046-2023(20)30080-3. [Epub ahead of print]
    Ying Y, Li H.
      Deamidation is a nonenzymatic and spontaneous posttranslational modification (PTM) that introduces changes in both structure and charge of proteins, strongly associated with aging proteome instability and degenerative diseases. Deamidation is also a common PTM occurring in biopharmaceutical proteins, representing a major cause of degradation. Therefore, characterization of deamidation alongside its inter-related modifications, isomerization and racemization, is critically important to understand their roles in protein stability and diseases. Mass spectrometry (MS) has become an indispensable tool in site-specific identification of PTMs for proteomics and structural studies. In this review, we focus on the recent advances of MS analysis in protein deamidation. In particular, we provide an update on sample preparation, chromatographic separation, and MS technologies at multi-levels, for accurate and reliable characterization of protein deamidation in both simple and complex biological samples, yielding important new insight on how deamidation together with isomerization and racemization occurs. These technological progresses will lead to a better understanding of how deamidation contributes to the pathology of aging and other degenerative diseases and the development of biopharmaceutical drugs.
  25. J Chromatogr A. 2020 Aug 02. pii: S0021-9673(20)30469-6. [Epub ahead of print]1624 461206
    Cebo M, Fu X, Gawaz M, Chatterjee M, Lämmerhofer M.
      Oxylipins, the oxidation products of polyunsaturated fatty acids, are important signaling molecules in living organisms. Some of them have pro-inflammatory properties, while others act as pro-resolving agents. Oxylipins also play a major role in platelet biology and the progression of thrombo-inflammation. Depending on their structure, they may be pro-thrombotic or anti-thrombotic. For an unbiased biological interpretation, a detailed analysis of a broad spectrum of oxylipins including their stereoisomers is necessary. In our work, we developed for the first time an enantioselective UHPLC-ESI-MS/MS assay which allows quantifying individual oxylipin enantiomers. The assay made use of a sub-2µm particle-based amylose-(3,5-dimethylphenylcarbamate) chiral stationary phase (Chiralpak IA-U) under MS-compatible reversed-phase conditions. It covered 19 enantiomeric pairs of oxylipins and one diasteromeric pair of a lipid mediator: 2 pairs of hydroxyoctadecadienoic acids (HODE), 6 pairs of hydroxyeicosatetraenoic acids (HETE), 5 pairs of hydroxyeicosapentaenoic acids (HEPE), 3 pairs of hydroxydocosahexaenoic acids (HDoHE) and one pair of each: resolvins D1, hydroxyeicosatrienoic acid (HETrE), hydroxyoctadecatrienoic acid (HOTrE) and dihydroxyeicosatetraenoic acid (DiHETE). The new method is fast and showed outstanding peak resolution for most of the isomeric pairs. Excellent method sensitivity (average LOD was equal to 2.7 pg on column) was obtained by using a triple quadrupole instrument as a detector in a targeted, selected reaction monitoring (SRM) mode. The applicability of the method was verified by preliminary validation. It was then applied to analyze oxylipins produced by autoxidation of polyunsaturated fatty acids (PUFA) in air. Multiple oxylipins were found in each of the samples as racemic mixtures and served as reference substances for identification. Finally, the new enantioselective UHPLC method was applied to analyze releasates from platelets in resting state, and following activation with thrombin. The highest abundant oxylipin in the platelet releasate was 12(S)-HETE, but many other oxylipins were found in the thrombin activated samples, usually as single enantiomers (e.g. 12(S)-HEPE, 11(R)-HETE, 9(R)-HODE, 13-(S)-HODE, 14(S)-HDoHE). The latter was detected at about similar concentration in resting platelet releasates as well. 15-HETE showed elevated levels for both R-and S-enantiomers in releasates of thrombin-activated platelets. 12-HETrE was found presumably as both enantiomers, however, retention time inconsistencies indicate that the R-enantiomer is actually a different compound, maybe another constitutional isomer with different double-bond configuration.
    Keywords:  Autoxidation; Chiral separation; Chiral stationary phase; Oxylipin enantiomer; Polyunsaturated fatty acid; Targeted lipidomics
  26. Metabolites. 2020 Jun 13. pii: E243. [Epub ahead of print]10(6):
    Liebal UW, Phan ANT, Sudhakar M, Raman K, Blank LM.
      The metabolome of an organism depends on environmental factors and intracellular regulation and provides information about the physiological conditions. Metabolomics helps to understand disease progression in clinical settings or estimate metabolite overproduction for metabolic engineering. The most popular analytical metabolomics platform is mass spectrometry (MS). However, MS metabolome data analysis is complicated, since metabolites interact nonlinearly, and the data structures themselves are complex. Machine learning methods have become immensely popular for statistical analysis due to the inherent nonlinear data representation and the ability to process large and heterogeneous data rapidly. In this review, we address recent developments in using machine learning for processing MS spectra and show how machine learning generates new biological insights. In particular, supervised machine learning has great potential in metabolomics research because of the ability to supply quantitative predictions. We review here commonly used tools, such as random forest, support vector machines, artificial neural networks, and genetic algorithms. During processing steps, the supervised machine learning methods help peak picking, normalization, and missing data imputation. For knowledge-driven analysis, machine learning contributes to biomarker detection, classification and regression, biochemical pathway identification, and carbon flux determination. Of important relevance is the combination of different omics data to identify the contributions of the various regulatory levels. Our overview of the recent publications also highlights that data quality determines analysis quality, but also adds to the challenge of choosing the right model for the data. Machine learning methods applied to MS-based metabolomics ease data analysis and can support clinical decisions, guide metabolic engineering, and stimulate fundamental biological discoveries.
    Keywords:  MS-based metabolomics; machine learning; metabolic engineering; metabolic flux analysis; multi-omics; synthetic biology
  27. Sci Rep. 2020 Jun 17. 10(1): 9804
    Carlisle SM, Trainor PJ, Hong KU, Doll MA, Hein DW.
      Human arylamine N-acetyltransferase 1 (NAT1), present in all tissues, is classically described as a phase-II xenobiotic metabolizing enzyme but can also catalyze the hydrolysis of acetyl-Coenzyme A (acetyl-CoA) in the absence of an arylamine substrate using folate as a cofactor. NAT1 activity varies inter-individually and has been shown to be overexpressed in estrogen receptor-positive (ER+) breast cancers. NAT1 has also been implicated in breast cancer progression however the exact role of NAT1 remains unknown. The objective of this study was to evaluate the effect of varying levels of NAT1 N-acetylation activity in MDA-MB-231 breast cancer cells on global cellular metabolism and to probe for unknown endogenous NAT1 substrates. Global, untargeted metabolomics was conducted via ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) on MDA-MB-231 breast cancer cell lines constructed with siRNA and CRISPR/Cas9 technologies to vary only in NAT1 N-acetylation activity. Many metabolites were differentially abundant in NAT1-modified cell lines compared to the Scrambled parental cell line. N-acetylasparagine and N-acetylputrescine abundances were strongly positively correlated (r = 0.986 and r = 0.944, respectively) with NAT1 N-acetylation activity whereas saccharopine abundance was strongly inversely correlated (r = -0.876). Two of the most striking observations were a reduction in de novo pyrimidine biosynthesis and defective β-oxidation of fatty acids in the absence of NAT1. We have shown that NAT1 expression differentially affects cellular metabolism dependent on the level of expression. Our results support the hypothesis that NAT1 is not just a xenobiotic metabolizing enzyme and may have a role in endogenous cellular metabolism.
  28. Cancer Metab. 2020 ;8 6
    Kang YP, Falzone A, Liu M, González-Sánchez P, Choi BH, Coloff JL, Saller JJ, Karreth FA, DeNicola GM.
      Background: d-3-phosphoglycerate dehydrogenase (PHGDH), which encodes the first enzyme in serine biosynthesis, is overexpressed in human cancers and has been proposed as a drug target. However, whether PHGDH is critical for the proliferation or homeostasis of tissues following the postnatal period is unknown.Methods: To study PHGDH inhibition in adult animals, we developed a knock-in mouse model harboring a PHGDH shRNA under the control of a doxycycline-inducible promoter. With this model, PHGDH depletion can be globally induced in adult animals, while sparing the brain due to poor doxycycline delivery.
    Results: We found that PHGDH depletion is well tolerated, and no overt phenotypes were observed in multiple highly proliferative cell compartments. Further, despite detectable knockdown and impaired serine synthesis, liver and pancreatic functions were normal. Interestingly, diminished PHGDH expression reduced liver serine and ceramide levels without increasing the levels of deoxysphingolipids. Further, liver triacylglycerol profiles were altered, with an accumulation of longer chain, polyunsaturated tails upon PHGDH knockdown.
    Conclusions: These results suggest that dietary serine is adequate to support the function of healthy, adult murine tissues, but PHGDH-derived serine supports liver ceramide synthesis and sustains general lipid homeostasis.
    Keywords:  Ceramide; Mouse model; PHGDH; Serine; Triacylglycerol
  29. Nature. 2020 Jun 17.
    Müller JB, Geyer PE, Colaço AR, Treit PV, Strauss MT, Oroshi M, Doll S, Virreira Winter S, Bader JM, Köhler N, Theis F, Santos A, Mann M.
      Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported1, advances in mass-spectrometry-based proteomics2 have enabled increasingly comprehensive identification and quantification of the human proteome3-6. However, there have been few comparisons across species7,8, in stark contrast with genomics initiatives9. Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides from Bacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at