bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021‒08‒29
twenty-nine papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization.
  2. Global Mass Spectrometry-Based Analysis of Protein Ubiquitination Using K-ε-GG Remnant Antibody Enrichment.
  3. Expanding Urinary Metabolite Annotation through Integrated Mass Spectral Similarity Networking.
  4. Comprehensive polar metabolomics and lipidomics profiling discriminates the transformed from the non-transformed state in colon tissue and cell lines.
  5. Investigating Global Lipidome Alterations with the Lipid Network Explorer.
  6. A Liquid Chromatography-Mass Spectrometry Workflow for In-Depth Quantitation of Fatty Acid Double Bond Location Isomers.
  7. A Single LC-MS/MS Analysis to Quantify CoA Biosynthetic Intermediates and Short-Chain Acyl CoAs.
  8. Dysregulated cholesterol homeostasis results in resistance to ferroptosis increasing tumorigenicity and metastasis in cancer.
  9. Metabolomic and lipidomic signatures associated with activation of human cDC1 (BDCA3+ /CD141+ ) dendritic cells.
  10. Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.
  11. Comprehensive Large-Scale Integrative Analysis of Omics Data To Accelerate Specialized Metabolite Discovery.
  12. Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows.
  13. Fatty acid and oxylipin concentration differ markedly between different fetal bovine serums: A cautionary note.
  14. Global Proteome Profiling to Assess Changes in Protein Abundance Using Isobaric Labeling and Liquid Chromatography-Tandem Mass Spectrometry.
  15. SCD1, autophagy and cancer: implications for therapy.
  16. An Integrated Metabolomic Study of Osteoporosis: Discovery and Quantification of Hyocholic Acids as Candidate Markers.
  17. Lipid metabolism and mitochondria: Cross talk in cancer.
  18. High Throughput Procedure for Comparative Analysis of In Vivo Cardiac Glucose or Amino Acids Use in Cardiovascular Pathologies and Pharmacological Treatments.
  19. Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research.
  20. Extracellular Vesicles in Cancer Metabolism: Implications for Cancer Diagnosis and Treatment.
  21. Protein networks linking Warburg and reverse Warburg effects to cancer cell metabolism.
  22. Isomer-Resolved Imaging of Prostate Cancer Tissues Reveals Specific Lipid Unsaturation Profiles Associated With Lymphocytes and Abnormal Prostate Epithelia.
  23. Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE.
  24. A rapid and reliable liquid chromatography/mass spectrometry method for SARS-CoV-2 analysis from gargle solutions and saliva.
  25. The role of 5-HT metabolism in cancer.
  26. Loss of tyrosine catabolic enzyme HPD promotes glutamine anaplerosis through mTOR signaling in liver cancer.
  27. Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques.
  28. A cancer ubiquitome landscape identifies metabolic reprogramming as target of Parkin tumor suppression.
  29. Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches.
  1. Metabolites. 2021 Jul 29. pii: 492. [Epub ahead of print]11(8):
    MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization.
    Luca Nicolotti, Jeremy Hack, Markus Herderich, Natoiya Lloyd.
      Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing options are available, however, both commercial and open-source solutions for data processing have limitations, such as vendor platform exclusivity and/or requiring familiarity with diverse programming languages. Data processing of untargeted metabolite data is a particular problem for laboratories that specialize in non-routine mass spectrometry analysis of diverse sample types across humans, animals, plants, fungi, and microorganisms. Here, we present MStractor, an R workflow package developed to streamline and enhance pre-processing of metabolomics mass spectrometry data and visualization. MStractor combines functions for molecular feature extraction with user-friendly dedicated GUIs for chromatographic and mass spectromerty (MS) parameter input, graphical quality-control outputs, and descriptive statistics. MStractor performance was evaluated through a detailed comparison with XCMS Online. The MStractor package is freely available on GitHub at the MetabolomicsSA repository.
    Keywords:  LC/MS; R programming language; data analysis; metabolomics; pre-processing
    DOI:  https://doi.org/10.3390/metabo11080492
  2. Methods Mol Biol. 2021 ;2365 203-216
    Global Mass Spectrometry-Based Analysis of Protein Ubiquitination Using K-ε-GG Remnant Antibody Enrichment.
    Alissa J Nelson, Yiying Zhu, Jian Min Ren, Matthew P Stokes.
      Ubiquitination is a post-translational modification that affects protein degradation as well as a variety of cellular processes. Methods that globally profile ubiquitination are powerful tools to better understand these processes. Here we describe an updated method for identification and quantification of thousands of sites of ubiquitination from cells, tissues, or other biological materials. The method involves cell lysis and digestion to peptides, immunoaffinity enrichment with an antibody recognizing di-glycine remnants left behind at ubiquitinated lysines, and liquid chromatography-tandem mass spectrometry analysis of the enriched peptides.
    Keywords:  LC-MS/MS; Mass spectrometry; PTMScan; Post-translational modification; Protein degradation; Proteomics; Ubiquitin; Ubiquitination
    DOI:  https://doi.org/10.1007/978-1-0716-1665-9_11
  3. Anal Chem. 2021 Aug 26.
    Expanding Urinary Metabolite Annotation through Integrated Mass Spectral Similarity Networking.
    Fausto Carnevale Neto, Daniel Raftery.
      The urine metabolome constitutes a rich source of functional information reflecting physiological states that are influenced by distinct conditions and biological stresses, such as responses to drug treatments or disease manifestations. Although global liquid chromatography-mass spectrometry (MS) profiling provides the most comprehensive measurement of metabolites in complex biological samples, annotation remains a challenge, and computational approaches are necessary to translate the molecular composition into biological knowledge. Here, we investigated the use of tandem MS-based enhanced molecular networks (MolNetEnhancer) to improve the metabolite annotation of urine extracts. The samples (n = 10) were analyzed by hydrophilic interaction chromatography-quadrupole time-of-flight mass spectrometry in both electrospray ionization (ESI) modes. Consistent with other common data preprocessing software, the use of Progenesis QI led to the annotation of up to 20 metabolites based on MS2 library searches, showing a high fragmentation score (cosine similarity ≥ 0.7), that is, ∼2% of mass features containing MS2 spectra. Molecular networking based on library matching resulted in the annotation of up to 62 urinary compounds. Using a combination of unsupervised substructure discovery (MS2LDA), the in silico tool network annotation propagation (NAP), and ClassyFire chemical ontology, embedded in a multilayered molecular network by MolNetEnhancer, we were able to expand the chemical characterization to ∼50% of the data set. The integrative approach led to the annotation of 275 compounds at the metabolomics standards initiative (MSI) confidence level 2, as well as 459 and 578 urinary metabolites (MSI level 3) in both negative and positive ESI modes, respectively. The exhaustive MS2-based annotation outperformed similar studies applied to larger cohorts while offering the discovery of metabolites not identified by the MS2 library search. This is the first work that effectively integrates orthogonal annotation methods and MS2-based fragmentation studies to improve metabolite annotation in urine samples.
    DOI:  https://doi.org/10.1021/acs.analchem.1c02041
  4. Sci Rep. 2021 Aug 26. 11(1): 17249
    Comprehensive polar metabolomics and lipidomics profiling discriminates the transformed from the non-transformed state in colon tissue and cell lines.
    Caroline Rombouts, Margot De Spiegeleer, Lieven Van Meulebroek, Lynn Vanhaecke, Winnok H De Vos.
      Colorectal cancer (CRC) is the fourth most lethal disease worldwide. Despite an urgent need for therapeutic advance, selective target identification in a preclinical phase is hampered by molecular and metabolic variations between cellular models. To foster optimal model selection from a translational perspective, we performed untargeted ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry-based polar metabolomics and lipidomics to non-transformed (CCD841-CON and FHC) and transformed (HCT116, HT29, Caco2, SW480 and SW948) colon cell lines as well as tissue samples from ten colorectal cancer patients. This unveiled metabolic signatures discriminating the transformed from the non-transformed state. Metabolites involved in glutaminolysis, tryptophan catabolism, pyrimidine, lipid and carnitine synthesis were elevated in transformed cells and cancerous tissue, whereas those involved in the glycerol-3-phosphate shuttle, urea cycle and redox reactions were lowered. The degree of glutaminolysis and lipid synthesis was specific to the colon cancer cell line at hand. Thus, our study exposed pathways that are specifically associated with the transformation state and revealed differences between colon cancer cell lines that should be considered when targeting cancer-associated pathways.
    DOI:  https://doi.org/10.1038/s41598-021-96252-4
  5. Metabolites. 2021 Jul 28. pii: 488. [Epub ahead of print]11(8):
    Investigating Global Lipidome Alterations with the Lipid Network Explorer.
    Nikolai Köhler, Tim Daniel Rose, Lisa Falk, Josch Konstantin Pauling.
      Lipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathway information remains challenging, leaving lipidomics behind compared to other omics disciplines. An especially uncharted territory is the integration of statistical and network-based approaches for studying global lipidome changes. Here we developed the Lipid Network Explorer (LINEX), a web-tool addressing this gap by providing a way to visualize and analyze functional lipid metabolic networks. It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. Researchers can customize the biochemical rules considered, to their tissue or organism specific analysis and easily share them. We demonstrate the benefits of combining network-based analyses with statistics using publicly available lipidomics data sets. LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container.
    Keywords:  bioinformatics; computational lipidomics; computational systems biology; lipidomics; lipids; metabolic networks; network biology
    DOI:  https://doi.org/10.3390/metabo11080488
  6. J Lipid Res. 2021 Aug 23. pii: S0022-2275(21)00092-4. [Epub ahead of print] 100110
    A Liquid Chromatography-Mass Spectrometry Workflow for In-Depth Quantitation of Fatty Acid Double Bond Location Isomers.
    Jing Zhao, Mengxuan Fang, Yu Xia.
      Tracing compositional changes of fatty acids (FAs) is frequently used as a means of monitoring metabolic alterations in perturbed biological states. Given that more than half of FAs in the mammalian lipidome are unsaturated, quantitation of FAs at a carbon-carbon double bond (C=C) location level is necessary. In this work, we have developed a workflow for global quantitation of FAs, including C=C location isomers, via charge-tagging Paternò-Büchi (PB) derivatization and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The use of 2-acetylpiridine (2-acpy) as the charge-tagging PB reagent led to a limit of identification in the sub-nanomolar range for mono- and poly-unsaturated as well as conjugated FAs. Conjugated free FAs of low abundance such as FA 18:2 (n-7, n-9) and FA 18:2 (n-6, n-8) were quantified at concentrations of 0.61 ± 0.05 and 0.05 ± 0.01 mg per 100 g in yak milk powder, respectively. This workflow also enabled deep profiling of eight saturated and thirty-seven unsaturated total FAs across a span of four orders of magnitude in concentration, including ten groups of C=C location isomers in pooled human plasma. A pilot survey on total FAs in plasma from patients with type 2 diabetes revealed that the relative compositions of FA 16:1 (n-10) and FA 18:1 (n-10) were significantly elevated compared to that of normal controls. The developed FA analysis workflow may serve as a powerful tool for deep profiling of FAs in both fundamental and clinical studies.
    Keywords:  2-acetylpiridine; Fatty acids; Paternò–Büchi; charge-tagging; double bond location isomers; lipidomics; liquid chromatography; quantitation; tandem mass spectrometry; type 2 diabetes
    DOI:  https://doi.org/10.1016/j.jlr.2021.100110
  7. Metabolites. 2021 Jul 21. pii: 468. [Epub ahead of print]11(8):
    A Single LC-MS/MS Analysis to Quantify CoA Biosynthetic Intermediates and Short-Chain Acyl CoAs.
    Anthony E Jones, Nataly J Arias, Aracely Acevedo, Srinivasa T Reddy, Ajit S Divakaruni, David Meriwether.
      Coenzyme A (CoA) is an essential cofactor for dozens of reactions in intermediary metabolism. Dysregulation of CoA synthesis or acyl CoA metabolism can result in metabolic or neurodegenerative disease. Although several methods use liquid chromatography coupled with mass spectrometry/mass spectrometry (LC-MS/MS) to quantify acyl CoA levels in biological samples, few allow for simultaneous measurement of intermediates in the CoA biosynthetic pathway. Here we describe a simple sample preparation and LC-MS/MS method that can measure both short-chain acyl CoAs and biosynthetic precursors of CoA. The method does not require use of a solid phase extraction column during sample preparation and exhibits high sensitivity, precision, and accuracy. It reproduces expected changes from known effectors of cellular CoA homeostasis and helps clarify the mechanism by which excess concentrations of etomoxir reduce intracellular CoA levels.
    Keywords:  CoA biosynthesis; LC-MS/MS; etomoxir; mitochondria; short-chain acyl CoAs
    DOI:  https://doi.org/10.3390/metabo11080468
  8. Nat Commun. 2021 08 24. 12(1): 5103
    Dysregulated cholesterol homeostasis results in resistance to ferroptosis increasing tumorigenicity and metastasis in cancer.
    Wen Liu, Binita Chakraborty, Rachid Safi, Dmitri Kazmin, Ching-Yi Chang, Donald P McDonnell.
      Hypercholesterolemia and dyslipidemia are associated with an increased risk for many cancer types and with poor outcomes in patients with established disease. Whereas the mechanisms by which this occurs are multifactorial we determine that chronic exposure of cells to 27-hydroxycholesterol (27HC), an abundant circulating cholesterol metabolite, selects for cells that exhibit increased cellular uptake and/or lipid biosynthesis. These cells exhibit substantially increased tumorigenic and metastatic capacity. Notably, the metabolic stress imposed upon cells by the accumulated lipids requires sustained expression of GPX4, a negative regulator of ferroptotic cell death. We show that resistance to ferroptosis is a feature of metastatic cells and further demonstrate that GPX4 knockdown attenuates the enhanced tumorigenic and metastatic activity of 27HC resistant cells. These findings highlight the general importance of ferroptosis in tumor growth and metastasis and suggest that dyslipidemia/hypercholesterolemia impacts cancer pathogenesis by selecting for cells that are resistant to ferroptotic cell death.
    DOI:  https://doi.org/10.1038/s41467-021-25354-4
  9. Immunology. 2021 Aug 24.
    Metabolomic and lipidomic signatures associated with activation of human cDC1 (BDCA3+ /CD141+ ) dendritic cells.
    Farhan Basit, Tom van Oorschot, Jessie van Buggenum, Rico Je Derks, Sarantos Kostidis, Martin Giera, I Jolanda M de Vries.
      Dendritic cells (DCs) bridge the connection between innate and adaptive immunity. DCs present antigens to T cells and stimulate potent cytotoxic T cell responses. Metabolic reprogramming is critical for DC development and activation, however metabolic adaptations and regulation in DC subsets remains largely uncharacterized. Here, we mapped metabolomic and lipidomic signatures associated with the activation phenotype of human conventional DC type 1, a DC subset specialized in cross-presentation and therefore of major importance for the stimulation of CD8+ T cells. Our metabolomics and lipidomics analyses showed that Toll like receptor (TLR) stimulation altered glycerolipids and amino acids in cDC1. Poly I:C or pRNA stimulation reduced triglycerides and cholesterol esters, as well as various amino acids. Moreover, TLR stimulation reduced expression of glycolysis regulating genes and did not induce glycolysis. Conversely, cDC1 exhibited increased mitochondrial content, oxidative phosphorylation (OXPHOS) upon TLR3 or TLR7/8 stimulation. Our findings highlight the metabolic adaptations required for cDC1 maturation.
    Keywords:  BDCA3; Dendritic cell Activation; Lipid Mediators; Metabolomics
    DOI:  https://doi.org/10.1111/imm.13409
  10. Mol Syst Biol. 2021 Aug;17(8): e10240
    Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.
    Jelena Čuklina, Chloe H Lee, Evan G Williams, Tatjana Sajic, Ben C Collins, María Rodríguez Martínez, Varun S Sharma, Fabian Wendt, Sandra Goetze, Gregory R Keele, Bernd Wollscheid, Ruedi Aebersold, Patrick G A Pedrioli.
      Advancements in mass spectrometry-based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much-needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step-by-step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.
    Keywords:  batch effects; data analysis; large-scale proteomics; normalization; quantitative proteomics
    DOI:  https://doi.org/10.15252/msb.202110240
  11. mSystems. 2021 Aug 24. e0072621
    Comprehensive Large-Scale Integrative Analysis of Omics Data To Accelerate Specialized Metabolite Discovery.
    Joris J R Louwen, Justin J J van der Hooft.
      Microbial specialized metabolites are key mediators in host-microbiome interactions. Most of the chemical space produced by the microbiome currently remains unexplored and uncharacterized. This situation calls for new and improved methods to exploit the growing publicly available genomic and metabolomic data sets and connect the outcomes to structural and functional knowledge inferred from transcriptomics and proteomics experiments. Here, we first describe currently available approaches that support the comprehensive mining of metabolomics and genomics data. Next, we provide our vision on how to move forward toward the automated linking of omics data of specialized metabolites to their structures, biosynthesis pathways, producers, and functions.
    Keywords:  computational biology; computational metabolomics; data mining; genomics; integrative omics; mass spectrometry; microbiome; natural products; specialized metabolites
    DOI:  https://doi.org/10.1128/mSystems.00726-21
  12. Biotechniques. 2021 Aug 25.
    Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows.
    David Kotol, Andreas Hober, Linnéa Strandberg, Anne-Sophie Svensson, Mathias Uhlén, Fredrik Edfors.
      Targeted proteomics is an attractive approach for the analysis of blood proteins. Here, we describe a novel analytical platform based on isotope-labeled recombinant protein standards stored in a chaotropic agent and subsequently dried down to allow storage at ambient temperature. This enables a straightforward protocol suitable for robotic workstations. Plasma samples to be analyzed are simply added to the dried pellet followed by enzymatic treatment and mass spectrometry analysis. Here, we show that this approach can be used to precisely (coefficient of variation <10%) determine the absolute concentrations in human plasma of hundred clinically relevant protein targets, spanning four orders of magnitude, using simultaneous analysis of 292 peptides. The use of this next-generation analytical platform for high-throughput clinical proteome profiling is discussed.
    Keywords:  blood plasma; internal standards; mass spectrometry; multiplex analysis; plasma profiling; room temperature storage; sample preparation; stability; stable Isotope standards; targeted proteomics
    DOI:  https://doi.org/10.2144/btn-2021-0047
  13. Lipids. 2021 Aug 25.
    Fatty acid and oxylipin concentration differ markedly between different fetal bovine serums: A cautionary note.
    Elisabeth Koch, Carolin Hopmann, Laura-Fabienne Fröhlich, Nils Helge Schebb.
      Fetal bovine serum (FBS) has been used as a universal supplement in cell culture for more than six decades. This includes the investigation of lipid and lipid mediator formation and biology. Little is known about the (polyunsaturated) fatty acid composition and their oxidation products in FBS. Therefore, we analyzed six different FBS purchased from three different companies regarding their fatty acid and oxylipin concentrations. We found pronounced differences in the fatty acid concentrations. Even two batches of "standardized" FBS batches from one company showed drastic differences (e.g., for eicosapentaenoic acid 5 ± 1 μM vs. 11 ± 1 μM). Oxylipin concentrations also markedly differ between the FBS lots. The highest differences were found for 12-lipoxygenase products (e.g., 12-hydroxyeicosatetraenoic acid free 21-87 nM and total 58-108 nM), probably due to inconsistent serum generation procedures. Our results indicate that for cell culture studies dealing with lipid metabolism, researchers should carefully characterize their used FBS to ensure reliability and reproducibility of study outcomes.
    Keywords:  arachidonic acid oxidation; docosahexaenoic acid oxidation; gas chromatography; liquid chromatography; mass spectrometry
    DOI:  https://doi.org/10.1002/lipd.12321
  14. Methods Mol Biol. 2021 ;2365 301-313
    Global Proteome Profiling to Assess Changes in Protein Abundance Using Isobaric Labeling and Liquid Chromatography-Tandem Mass Spectrometry.
    Anthony P Possemato, Kathryn Abell, Matthew P Stokes.
      Protein degradation is a critical component of all facets of cell biology, and recently methods have been developed to make use of targeted protein degradation as both an investigative tool and a potential therapeutic avenue. Mass spectrometry-based proteomic studies have allowed detailed characterization of changes in protein level and the biology underlying growth, development, and disease. Current methods and instrumentation allow identification and quantitative analysis of thousands of proteins in a single assay. The method described here involves cell lysis and digestion to peptides, labeling peptides with isobaric tagging TMT reagents, basic reversed phase fractionation, and liquid chromatography-tandem mass spectrometry analysis of the enriched peptides.
    Keywords:  Isobaric Tag; LC-MS/MS; Mass spectrometry; Proteome; Proteomics; TMT
    DOI:  https://doi.org/10.1007/978-1-0716-1665-9_16
  15. J Exp Clin Cancer Res. 2021 Aug 24. 40(1): 265
    SCD1, autophagy and cancer: implications for therapy.
    Francesca Ascenzi, Claudia De Vitis, Marcello Maugeri-Saccà, Christian Napoli, Gennaro Ciliberto, Rita Mancini.
      BACKGROUND: Autophagy is an intracellular degradation system that removes unnecessary or dysfunctional components and recycles them for other cellular functions. Over the years, a mutual regulation between lipid metabolism and autophagy has been uncovered.METHODS: This is a narrative review discussing the connection between SCD1 and the autophagic process, along with the modality through which this crosstalk can be exploited for therapeutic purposes.
    RESULTS: Fatty acids, depending on the species, can have either activating or inhibitory roles on autophagy. In turn, autophagy regulates the mobilization of fat from cellular deposits, such as lipid droplets, and removes unnecessary lipids to prevent cellular lipotoxicity. This review describes the regulation of autophagy by lipid metabolism in cancer cells, focusing on the role of stearoyl-CoA desaturase 1 (SCD1), the key enzyme involved in the synthesis of monounsaturated fatty acids. SCD1 plays an important role in cancer, promoting cell proliferation and metastasis. The role of autophagy in cancer is more complex since it can act either by protecting against the onset of cancer or by promoting tumor growth. Mounting evidence indicates that autophagy and lipid metabolism are tightly interconnected.
    CONCLUSION: Here, we discuss controversial findings of SCD1 as an autophagy inducer or inhibitor in cancer, highlighting how these activities may result in cancer promotion or inhibition depending upon the degree of cancer heterogeneity and plasticity.
    Keywords:  Autophagy; Lipid metabolism; cancer
    DOI:  https://doi.org/10.1186/s13046-021-02067-6
  16. Front Pharmacol. 2021 ;12 725341
    An Integrated Metabolomic Study of Osteoporosis: Discovery and Quantification of Hyocholic Acids as Candidate Markers.
    Dawei Deng, Chen Pan, Zeming Wu, Yujiao Sun, Chang Liu, Hong Xiang, Peiyuan Yin, Dong Shang.
      Osteoporosis is becoming a highly prevalent disease in a large proportion of the global aged population. Serum metabolite markers may be important for the treatment and early prevention of osteoporosis. Serum samples from 32 osteoporosis and 32 controls were analyzed by untargeted metabolomics and lipidomic approaches performed on an ultra-high performance liquid chromatography and high-resolution mass spectrometry (UHPLC-HRMS) system. To find systemic disturbance of osteoporosis, weighted gene correlation network analysis (WGCNA) and statistical methods were employed for data-mining. Then, an in-depth targeted method was utilized to determine potential markers from the family of key metabolites. As a result, 1,241 metabolites were identified from untargeted methods and WGCNA indicated that lipids metabolism is deregulated and glycerol phospholipids, sphingolipids, fatty acids, and bile acids (BA) are majorly affected. As key metabolites of lipids metabolism, 66 bile acids were scanned and 49 compounds were quantified by a targeted method. Interestingly, hyocholic acids (HCA) were found to play essential roles during the occurrence of osteoporosis and may be potential markers. These metabolites may be new therapeutic or diagnosis targets for the screening or treatment of osteoporosis. Quantified measurement of potential markers also enables the establishment of diagnostic models for the following translational research in the clinic.
    Keywords:  ageing; bile acids; lipids; metabolomics; osteoporosis
    DOI:  https://doi.org/10.3389/fphar.2021.725341
  17. Curr Drug Targets. 2021 Aug 24.
    Lipid metabolism and mitochondria: Cross talk in cancer.
    Anubhav Srivastava, Pransu Srivastava, Shashank Mathur, Sabiya Abbas, Neeraj Rai, Swasti Tiwari, Meenakshi Tiwari, Lokendra Sharma.
      Metabolic reprogramming is considered a major event in cancer initiation, progression and metastasis. The metabolic signature of cancer cells includes alterations in glycolysis, mitochondrial respiration, fatty acid/lipid and amino acid metabolism. Being at a junction of various metabolic pathways, mitochondria play a key role in fueling cancer growth through regulating bioenergetics, metabolism and cell death. Increasing evidence suggests that alteration in lipid metabolism is a common feature of metastatic progression, including fatty acid synthesis as well as fatty acid oxidation. However, the interplay between lipid metabolism and mitochondria in carcinogenesis remains obscure. The present review focuses on key lipid metabolic pathways associated with mitochondrial regulation that drive cancer phenotype and metastasis. We also review potential targets of lipid metabolism and mitochondria to improve the therapeutic regime in cancer patients. This review aims to improve our current understanding of the intricate relation of lipids with mitochondria and provides insights into new therapeutic approaches.
    Keywords:  Apoptosis; Bioenergetics; Cancer; Cardiolipin; Chemo-therapeutics; Drug Targets; Fatty acid oxidation; Lipid metabolism; Metastasis; Mitochondria
    DOI:  https://doi.org/10.2174/1389450122666210824144907
  18. Metabolites. 2021 Jul 30. pii: 497. [Epub ahead of print]11(8):
    High Throughput Procedure for Comparative Analysis of In Vivo Cardiac Glucose or Amino Acids Use in Cardiovascular Pathologies and Pharmacological Treatments.
    Marta Tomczyk, Mariola Olkowicz, Ewa M Slominska, Ryszard T Smolenski.
      The heart is characterized by the prominent flexibility of its energy metabolism and is able to use diverse carbon substrates, including carbohydrates and amino acids. Cardiac substrate preference could have a major impact on the progress of cardiac pathologies. However, the majority of methods to investigate changes in substrates' use in cardiac metabolism in vivo are complex and not suitable for high throughput testing necessary to understand and reverse these pathologies. Thus, this study aimed to develop a simple method that would allow for the analysis of cardiac metabolic substrate use. The developed methods involved the subcutaneous injection of stable 13C isotopomers of glucose, valine, or leucine with mass spectrometric analysis for the investigation of its entry into cardiac metabolic pathways that were deducted from 13C alanine and glutamate enrichments in heart extracts. The procedures were validated by confirming the known effects of treatments that modify glucose, free fatty acids, and amino acid metabolism. Furthermore, we studied changes in the energy metabolism of CD73 knock-out mice to demonstrate the potential of our methods in experimental research. The methods created allowed for fast estimation of cardiac glucose and amino acid use in mice and had the potential for high-throughput analysis of changes in pathology and after pharmacological treatments.
    Keywords:  catabolism; heart; mass spectrometry
    DOI:  https://doi.org/10.3390/metabo11080497
  19. RSC Chem Biol. 2021 Aug;4 1050-1072
    Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research.
    Hannah N Miles, Daniel G Delafield, Lingjun Li.
      Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.
    Keywords:  Quantitative proteomics; biomarker discovery; cancer research; isotopic labeling; mass spectrometry; systems biology
    DOI:  https://doi.org/10.1039/d1cb00039j
  20. Technol Cancer Res Treat. 2021 Jan-Dec;20:20 15330338211037821
    Extracellular Vesicles in Cancer Metabolism: Implications for Cancer Diagnosis and Treatment.
    Qian Zhang, Xiangling Yang, Huanliang Liu.
      Metabolic reprogramming is one of the most common characteristics of cancer cells. The metabolic alterations of glucose, amino acids and lipids can support the aggressive phenotype of cancer cells. Exosomes, a kind of extracellular vesicles, participate in the intercellular communication through transferring bioactive molecules. Increasing evidence has demonstrated that enzymes, metabolites and non-coding RNAs in exosomes are responsible for the metabolic alteration of cancer cells. In this review, we summarize the past and recent findings of exosomes in altering cancer metabolism and elaborate on the role of the specific enzymes, metabolites and non-coding RNAs transferred by exosomes. Moreover, we give evidence of the role of exosomes in cancer diagnosis and treatment. Finally, we discuss the existing problems in the study and application of exosomes in cancer diagnosis and treatment.
    Keywords:  amino acids; biomarkers; cancer cells; exosomes; glucose; lipids; metabolic reprogramming
    DOI:  https://doi.org/10.1177/15330338211037821
  21. Biofactors. 2021 Aug 28.
    Protein networks linking Warburg and reverse Warburg effects to cancer cell metabolism.
    Dina Johar, Ahmed O Elmehrath, Rania M Khalil, Mostafa H Elberry, Samy Zaky, Samy A Shalabi, Larry H Bernstein.
      It was 80 years after the Otto Warburg discovery of aerobic glycolysis, a major hallmark in the understanding of cancer. The Warburg effect is the preference of cancer cell for glycolysis that produces lactate even when sufficient oxygen is provided. "reverse Warburg effect" refers to the interstitial tissue communications with adjacent epithelium, that in the process of carcinogenesis, is needed to be explored. Among these cell-cell communications, the contact between epithelial cells; between epithelial cells and matrix; and between fibroblasts and inflammatory cells in the underlying matrix. Cancer involves dysregulation of Warburg and reverse Warburg cellular metabolic pathways. How these gene and protein-based regulatory mechanisms have functioned has been the basis for this review. The importance of the Warburg in oxidative phosphorylation suppression, with increased glycolysis in cancer growth and proliferation is emphasized. Studies that are directed at pathways that would be expected to shift cell metabolism to an increased oxidation and to a decrease in glycolysis are emphasized. Key enzymes required for oxidative phosphorylation, and affect the inhibition of fatty acid metabolism and glutamine dependence are conferred. The findings are of special interest to cancer pharmacotherapy. Studies described in this review are concerned with the effects of therapeutic modalities that are intimately related to the Warburg effect. These interactions described may be helpful as adjuvant therapy in controlling the process of proliferation and metastasis.
    Keywords:  Warburg; aerobic; anaerobic; cancer; glycolysis; metastasis; proliferation; tumorigenesis
    DOI:  https://doi.org/10.1002/biof.1768
  22. Front Endocrinol (Lausanne). 2021 ;12 689600
    Isomer-Resolved Imaging of Prostate Cancer Tissues Reveals Specific Lipid Unsaturation Profiles Associated With Lymphocytes and Abnormal Prostate Epithelia.
    Reuben S E Young, Britt S R Claes, Andrew P Bowman, Elizabeth D Williams, Benjamin Shepherd, Aurel Perren, Berwyck L J Poad, Shane R Ellis, Ron M A Heeren, Martin C Sadowski, Stephen J Blanksby.
      Prostate cancer is the fourth most common cancer worldwide with definitive diagnosis reliant on biopsy and human-graded histopathology. As with other pathologies, grading based on classical haematoxylin and eosin (H&E) staining of formalin fixed paraffin-embedded material can be prone to variation between pathologists, prompting investigation of biomolecular markers. Comprising around 50% of cellular mass, and with known metabolic variations in cancer, lipids provide a promising target for molecular pathology. Here we apply isomer-resolved lipidomics in combination with imaging mass spectrometry to interrogate tissue sections from radical prostatectomy specimens. Guided by the histopathological assessment of adjacent tissue sections, regions of interest are investigated for molecular signatures associated with lipid metabolism, especially desaturation and elongation pathways. Monitoring one of the most abundant cellular membrane lipids within these tissues, phosphatidylcholine (PC) 34:1, high positive correlation was observed between the n-9 isomer (site of unsaturation 9-carbons from the methyl terminus) and epithelial cells from potential pre-malignant lesions, while the n-7 isomer abundance was observed to correlate with immune cell infiltration and inflammation. The correlation of lipid isomer signatures with human disease states in tissue suggests a future role for isomer-resolved mass spectrometry imaging in assisting pathologists with prostate cancer diagnoses and patient stratification.
    Keywords:  imaging; lipid; lipid metabolism; mass spectrometry imaging; pathology
    DOI:  https://doi.org/10.3389/fendo.2021.689600
  23. Metabolites. 2021 Jul 23. pii: 477. [Epub ahead of print]11(8):
    Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE.
    Don D Nguyen, Veronika Saharuka, Vitaly Kovalev, Lachlan Stuart, Massimo Del Prete, Kinga Lubowiecka, René De Mot, Vittorio Venturi, Theodore Alexandrov.
      Metabolite annotation from imaging mass spectrometry (imaging MS) data is a difficult undertaking that is extremely resource intensive. Here, we adapted METASPACE, cloud software for imaging MS metabolite annotation and data interpretation, to quickly annotate microbial specialized metabolites from high-resolution and high-mass accuracy imaging MS data. Compared with manual ion image and MS1 annotation, METASPACE is faster and, with the appropriate database, more accurate. We applied it to data from microbial colonies grown on agar containing 10 diverse bacterial species and showed that METASPACE was able to annotate 53 ions corresponding to 32 different microbial metabolites. This demonstrates METASPACE to be a useful tool to annotate the chemistry and metabolic exchange factors found in microbial interactions, thereby elucidating the functions of these molecules.
    Keywords:  imaging mass spectrometry; microbial natural products; spatial metabolomics
    DOI:  https://doi.org/10.3390/metabo11080477
  24. Anal Bioanal Chem. 2021 Aug 24.
    A rapid and reliable liquid chromatography/mass spectrometry method for SARS-CoV-2 analysis from gargle solutions and saliva.
    Marc Kipping, Dirk Tänzler, Andrea Sinz.
      We describe a rapid liquid chromatography/tandem mass spectrometry (LC-MS/MS) method for the direct detection and quantitation of SARS-CoV-2 nucleoprotein in gargle solutions and saliva. The method is based on a multiple-reaction monitoring (MRM) mass spectrometry approach with a total cycle time of 5 min per analysis and allows the detection and accurate quantitation of SARS-CoV-2 nucleoprotein as low as 500 amol/μL. We improved the sample preparation protocol of our recent piloting SARS-CoV-2 LC-MS study regarding sensitivity, reproducibility, and compatibility with a complementary reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) analysis of the same sample. The aim of this work is to promote diagnostic tools that allow identifying and monitoring SARS-CoV-2 infections by LC-MS/MS methods in a routine clinical environment.
    Keywords:  Liquid chromatography; Mass spectrometry; Multiple-reaction monitoring; SARS-CoV-2; Triple quadrupole
    DOI:  https://doi.org/10.1007/s00216-021-03614-y
  25. Biochim Biophys Acta Rev Cancer. 2021 Aug 21. pii: S0304-419X(21)00116-5. [Epub ahead of print] 188618
    The role of 5-HT metabolism in cancer.
    Di Ye, Huanji Xu, Qiulin Tang, Hongwei Xia, Chenliang Zhang, Feng Bi.
      Serotonin (5-hydroxytryptamine, 5-HT) metabolism has long been linked to tumorigenesis and tumor progression. Numerous studies have shown the functions of 5-HT and its metabolites in the regulation of tumor biological processes like cell proliferation, invasion, metastasis, tumor angiogenesis and immunomodulatory through multi-step complex mechanisms. Reprogramming of 5-HT metabolism has been revealed in various tumors paving way for development of drugs that target enzymes, metabolites or receptors involved in 5-HT metabolic pathway. However, information on the role of 5-HT metabolism in cancer is scanty. This review briefly describes the main metabolic routes of 5-HT, the role of 5-HT metabolism in cancer and systematically summarizes the most recent advances in 5-HT metabolism-targeted cancer therapy.
    Keywords:  Cancer therapy; Metabolism; Serotonin
    DOI:  https://doi.org/10.1016/j.bbcan.2021.188618
  26. Cell Rep. 2021 Aug 24. pii: S2211-1247(21)01055-X. [Epub ahead of print]36(8): 109617
    Loss of tyrosine catabolic enzyme HPD promotes glutamine anaplerosis through mTOR signaling in liver cancer.
    Man Tong, Tin-Lok Wong, Hongzhi Zhao, Yuanyuan Zheng, Yu-Nong Xie, Cheuk-Hin Li, Lei Zhou, Noélia Che, Jing-Ping Yun, Kwan Man, Terence Kin-Wah Lee, Zongwei Cai, Stephanie Ma.
      The liver plays central roles in coordinating different metabolic processes, such as the catabolism of amino acids. In this study, we identify a loss of tyrosine catabolism and a concomitant increase in serum tyrosine levels during liver cancer development. Liver cells with disordered tyrosine catabolism, as exemplified by the suppression of a tyrosine catabolic enzyme 4-hydroxyphenylpyruvate dioxygenase (HPD), display augmented tumorigenic and proliferative potentials. Metabolomics profiling and isotope tracing reveal the metabolic reliance of HPD-silenced cells on glutamine, coupled with increased tricarboxylic acid cycle metabolites and their associated amino acid pools. Mechanistically, HPD silencing reduces ketone bodies, which regulate the proliferative and metabolic phenotypes via the AMPK/mTOR/p70S6 kinase pathway and mTOR-dependent glutaminase (GLS) activation. Collectively, our results demonstrate a metabolic link between tyrosine and glutamine metabolism, which could be exploited as a potentially promising anticancer therapy for liver cancer.
    Keywords:  HPD; glutamine metabolism; liver cancer; mTOR signaling; tyrosine catabolism
    DOI:  https://doi.org/10.1016/j.celrep.2021.109617
  27. Anal Bioanal Chem. 2021 Aug 26.
    Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques.
    Shuting Xu, Cheng Yang, Xiuping Yan, Huwei Liu.
      Mass spectrometry (MS) is attractive for single-cell analysis because of its high sensitivity, rich information, and large dynamic ranges, especially for the single-cell metabolome and proteome analysis. Efforts have been made to deal with the throughput and information coverage problems in typical manual single-cell MS techniques. In this review, advanced techniques to improve the automation and throughput for single-cell sampling and single-cell metabolome and proteome MS detection have been discussed. Furthermore, representative MS-based strategies that can increase the in-depth cellular information coverage and achieve the more comprehensive single-cell multiomics information during high throughput detection have been highlighted, providing an ongoing perspective of the MS performance for the single-cell research.
    Keywords:  High throughput; Mass spectrometry; Metabolomics; Multiomics; Proteomics; Single-cell analysis
    DOI:  https://doi.org/10.1007/s00216-021-03624-w
  28. Sci Adv. 2021 Aug;pii: eabg7287. [Epub ahead of print]7(35):
    A cancer ubiquitome landscape identifies metabolic reprogramming as target of Parkin tumor suppression.
    Ekta Agarwal, Aaron R Goldman, Hsin-Yao Tang, Andrew V Kossenkov, Jagadish C Ghosh, Lucia R Languino, Valentina Vaira, David W Speicher, Dario C Altieri.
      Changes in metabolism that affect mitochondrial and glycolytic networks are hallmarks of cancer, but their impact in disease is still elusive. Using global proteomics and ubiquitome screens, we now show that Parkin, an E3 ubiquitin ligase and key effector of mitophagy altered in Parkinson's disease, shuts off mitochondrial dynamics and inhibits the non-oxidative phase of the pentose phosphate pathway. This blocks tumor cell movements, creates metabolic and oxidative stress, and inhibits primary and metastatic tumor growth. Uniformly down-regulated in cancer patients, Parkin tumor suppression requires its E3 ligase function, is reversed by antioxidants, and is independent of mitophagy. These data demonstrate that cancer metabolic networks are potent oncogenes directly targeted by endogenous tumor suppression.
    DOI:  https://doi.org/10.1126/sciadv.abg7287
  29. J Proteome Res. 2021 Aug 27.
    Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches.
    Polina Kudriavtseva, Matvey Kashkinov, Attila Kertész-Farkas.
      Spectrum annotation is a challenging task due to the presence of unexpected peptide fragmentation ions as well as the inaccuracy of the detectors of the spectrometers. We present a deep convolutional neural network, called Slider, which learns an optimal feature extraction in its kernels for scoring mass spectrometry (MS)/MS spectra to increase the number of spectrum annotations with high confidence. Experimental results using publicly available data sets show that Slider can annotate slightly more spectra than the state-of-the-art methods (BoltzMatch, Res-EV, Prosit), albeit 2-10 times faster. More interestingly, Slider provides only 2-4% fewer spectrum annotations with low-resolution fragmentation information than other methods with high-resolution information. This means that Slider can exploit nearly as much information from the context of low-resolution spectrum peaks as the high-resolution fragmentation information can provide for other scoring methods. Thus, Slider can be an optimal choice for practitioners using old spectrometers with low-resolution detectors.
    Keywords:  PSM scoring; convolutional neural networks; deep learning; fast; spectrum annotation; tandem mass spectrometry
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00315
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