bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒12‒18
24 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh


  1. Methods Mol Biol. 2023 ;2592 89-100
      Recent clinical trials demonstrated strong association between lipid abnormalities and progression of diabetic retinopathy (DR); however, whether circulating lipid levels or retinal lipid metabolism, or both, contributes to the pathogenesis of DR is not well understood. Limited amounts of retinal tissue available from animal models, such as mouse models of DR, have proved. Limited amount of retinal tissue was especially challenging for cholesterol and oxysterol detection as it precluded identification of individual isomers of each nonesterified sterol class. To measure cholesterol and oxysterols from limited retinal tissue samples, we developed extremely sensitive electrospray ionization liquid chromatography high-resolution/accurate mass measurements on an LTQ Orbitrap Velos mass spectrometer that are able to resolve sterols and oxysterols separated by reverse-phase HPLC using a gradient of 85-100% methanol containing 0.1% formic acid, with subsequent detection in positive ionization mode. This methodology will aid in our understanding of diabetes-induced changes in retinal cholesterol and oxysterol metabolism.
    Keywords:  Cholesterol; LC-MS; Lipid extraction; Lipidomics; Mass spectrometry; Metabolomics; Orbitrap; Oxysterol; Retina; Separation
    DOI:  https://doi.org/10.1007/978-1-0716-2807-2_6
  2. Methods Mol Biol. 2023 ;2609 251-270
      ADP-ribosylation is a posttranslational modification (PTM) that has crucial functions in a wide range of cellular processes. Although mass spectrometry (MS) in recent years has emerged as a valuable tool for profiling ADP-ribosylation on a system level, the use of conventional MS methods to profile ADP-ribosylation sites in an unbiased way remains a challenge. Here, we describe a protocol for identification of ADP-ribosylated proteins in vivo on a proteome-wide level, and localization of the amino acid side chains modified with this PTM. The method relies on the enrichment of ADP-ribosylated peptides using the Af1521 macrodomain (Karras GI, Kustatscher G, Buhecha HR, Allen MD, Pugieux C, Sait F, Bycroft M, Ladurner AG, EMBO J 24:1911-1920, 2005), followed by liquid chromatography-high-resolution tandem MS (LC-MS/MS) with electron transfer dissociation-based peptide fragmentation methods, resulting in accurate localization of ADP-ribosylation sites. This protocol explains the step-by-step enrichment and identification of ADP-ribosylated peptides from cell culture to data processing using the MaxQuant software suite.
    Keywords:  ADP-ribosylation; Af1521 macrodomain; Affinity purification; ETD; EThcD; Mass spectrometry; PARG; PARP; PTM; Proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2891-1_15
  3. Cell Rep. 2022 Dec 13. pii: S2211-1247(22)01697-7. [Epub ahead of print]41(11): 111809
      The gut microbiota influences acetylation on host histones by fermenting dietary fiber into butyrate. Although butyrate could promote histone acetylation by inhibiting histone deacetylases, it may also undergo oxidation to acetyl-coenzyme A (CoA), a necessary cofactor for histone acetyltransferases. Here, we find that epithelial cells from germ-free mice harbor a loss of histone H4 acetylation across the genome except at promoter regions. Using stable isotope tracing in vivo with 13C-labeled fiber, we demonstrate that the microbiota supplies carbon for histone acetylation. Subsequent metabolomic profiling revealed hundreds of labeled molecules and supported a microbial contribution to host fatty acid metabolism, which declined in response to colitis and correlated with reduced expression of genes involved in fatty acid oxidation. These results illuminate the flow of carbon from the diet to the host via the microbiota, disruptions to which may affect energy homeostasis in the distal gut and contribute to the development of colitis.
    Keywords:  CP: Microbiology; colitis; epigenetics; fatty acid metabolism; histone acetylation; host-microbiota interactions
    DOI:  https://doi.org/10.1016/j.celrep.2022.111809
  4. Anal Chem. 2022 Dec 17.
      Large-scale proteome analysis requires rapid and high-throughput analytical methods. We recently reported a new paradigm in proteome analysis where direct infusion and ion mobility are used instead of liquid chromatography (LC) to achieve rapid and high-throughput proteome analysis. Here, we introduce an improved direct infusion shotgun proteome analysis protocol including label-free quantification (DISPA-LFQ) using CsoDIAq software. With CsoDIAq analysis of DISPA data, we can now identify up to ∼2000 proteins from the HeLa and 293T proteomes, and with DISPA-LFQ, we can quantify ∼1000 proteins from no more than 1 μg of sample within minutes. The identified proteins are involved in numerous valuable pathways including central carbon metabolism, nucleic acid replication and transport, protein synthesis, and endocytosis. Together with a high-throughput sample preparation method in a 96-well plate, we further demonstrate the utility of this technology for performing high-throughput drug analysis in human 293T cells. The total time for data collection from a whole 96-well plate is approximately 8 h. We conclude that the DISPA-LFQ strategy presents a valuable tool for fast identification and quantification of proteins in complex mixtures, which will power a high-throughput proteomic era of drug screening, biomarker discovery, and clinical analysis.
    DOI:  https://doi.org/10.1021/acs.analchem.2c02249
  5. Mol Cell Proteomics. 2022 Dec 07. pii: S1535-9476(22)00285-7. [Epub ahead of print] 100477
      Liquid chromatography coupled with bottom up mass spectrometry (LC-MS/MS)-based proteomics is increasingly used to detect changes in post-translational modifications (PTMs) in samples from different conditions. Analysis of data from such experiments faces numerous statistical challenges. These include the low abundance of modified proteoforms, the small number of observed peptides that span modification sites, and confounding between changes in the abundance of PTM and the overall changes in the protein abundance. Therefore, statistical approaches for detecting differential PTM abundance must integrate all the available information pertaining to a PTM site, and consider all the relevant sources of confounding and variation. In this manuscript we propose such a statistical framework, which is versatile, accurate, and leads to reproducible results. The framework requires an experimental design, which quantifies, for each sample, both peptides with post-translational modifications and peptides from the same proteins with no modification sites. The proposed framework supports both label-free and tandem mass tag (TMT)-based LC-MS/MS acquisitions. The statistical methodology separately summarizes the abundances of peptides with and without the modification sites, by fitting separate linear mixed effects models appropriate for the experimental design. Next, model-based inferences regarding the PTM and the protein-level abundances are combined to account for the confounding between these two sources. Evaluations on computer simulations, a spike-in experiment with known ground truth, and three biological experiments with different organisms, modification types and data acquisition types demonstrate the improved fold change estimation and detection of differential PTM abundance, as compared to currently used approaches. The proposed framework is implemented in the free and open-source R/Bioconductor package MSstatsPTM.
    DOI:  https://doi.org/10.1016/j.mcpro.2022.100477
  6. Anal Chem. 2022 Dec 15.
      Liquid chromatography (LC)-mass spectrometry (MS)/MS lipidomic normalization is generally performed by equalizing pre-extraction sample materials or via DNA or protein pre-quantitation methods, which have known measurement inaccuracies. We propose the use of the sulfo-phospho-vanillin assay (SPVA), a total lipid colorimetric analysis, as a pre-quantitation method to normalize lipids in lipidomic LC-MS/MS applications. The assay has been applied to a 300 μL well volume in a 96-well plate and tested using Avanti total lipid standards of porcine brain and E. coli. Assay parameters for lipid sample volume, sulfuric acid, vanillin/phosphoric acid, post-reaction incubation time, and wavelength are optimized for robust application to biologically sourced lipid samples. Standard test samples were prepared using three concentrations covering approximately 100 μg/mL range. The optimized assay yielded test sample errors less than 10%, indicating a precise and accurate assay performance. The test samples were then analyzed by LC-MS/MS and normalized using SPVA pre-quantitation and pseudo-mass normalization. The detected lipids showed smaller standard deviations and greater relative concentration differences compared to the pseudo-mass normalized lipids, showing promise as a normalization method.
    DOI:  https://doi.org/10.1021/acs.analchem.2c03488
  7. J Proteome Res. 2022 Dec 14.
      Tandem mass spectrometry (MS/MS) spectra of intact proteins can be difficult to interpret owing to the variety of fragment ion types and abundances. This information is crucial for maximizing the information derived from top-down mass spectrometry of proteins and protein complexes. MS-TAFI (Mass Spectrometry Tool for the Analysis of Fragment Ions) is a free Python-based program which offers a streamlined approach to the data analysis and visualization of deconvoluted MS/MS data of intact proteins. The application also contains tools for native mass spectrometry experiments with the ability to search for fragment ions that retain ligands (holo ions) as well as visualize the location of charge sites obtained from 193 nm ultraviolet photodissociation data. The source code and complete application for MS-TAFI is available for download at https://github.com/kylejuetten.
    Keywords:  MS/MS analysis; protein fragmentation; proteomics software
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00594
  8. Molecules. 2022 Dec 01. pii: 8394. [Epub ahead of print]27(23):
      Folate (vitamin B9) is involved in one-carbon transfer reactions and plays a significant role in nucleic acid synthesis and control of cellular proliferation, among other key cellular processes. It is now recognized that the role of folates in different stages of carcinogenesis is complex, and more research is needed to understand how folate reactions become dysregulated in cancers and the metabolic consequences that occur as a result. ALDH1L1 (cytosolic 10-formyltetrahydrofolate dehydrogenase), an enzyme of folate metabolism expressed in many tissues, is ubiquitously downregulated in cancers and is not expressed in cancer cell lines. The RT4 cell line (derived from papillary bladder cancer) which expresses high levels of ALDH1L1 represents an exception, providing an opportunity to explore the metabolic consequences of the loss of this enzyme. We have downregulated this protein in RT4 cells (shRNA driven knockdown or CRISPR driven knockout) and compared metabolomes of ALDH1L1-expressing and -deficient cells to determine if metabolic changes linked to the loss of this enzyme might provide proliferative and/or survival advantages for cancer cells. In this study, cell extracts were analyzed using Ultra High Performance Liquid Chromatography High Resolution Mass Spectrometry (UHPLC-HR-MS). A total of 13,339 signals were identified or annotated using an in-house library and public databases. Supervised and unsupervised multivariate analysis revealed metabolic differences between RT4 cells and ALDH1L1-deficient clones. Glycine (8-fold decrease) and metabolites derived from S-adenosylmethionine utilizing pathways were significantly decreased in the ALDH1L1-deficient clones, compared with RT4 cells. Other changes linked to ALDH1L1 downregulation include decreased levels of amino acids, Krebs cycle intermediates, and ribose-5-phosphate, and increased nicotinic acid. While the ALDH1L1-catalyzed reaction is directly linked to glycine biosynthesis and methyl group flux, its overall effect on cellular metabolism extends beyond immediate metabolic pathways controlled by this enzyme.
    Keywords:  ALDH1L1; cancer; folate; metabolomics
    DOI:  https://doi.org/10.3390/molecules27238394
  9. Curr Opin Chem Biol. 2022 Dec 14. pii: S1367-5931(22)00123-5. [Epub ahead of print]72 102238
      Glycoproteomics, or characterizing glycosylation events at a proteome scale, has seen rapid advances in methods for analyzing glycopeptides by tandem mass spectrometry in recent years. These advances have enabled acquisition of far more comprehensive and large-scale datasets, precipitating an urgent need for improved informatics methods to analyze the resulting data. A new generation of glycoproteomics search methods has recently emerged, using glycan fragmentation to split the identification of a glycopeptide into peptide and glycan components and solve each component separately. In this review, we discuss these new methods and their implications for large-scale glycoproteomics, as well as several outstanding challenges in glycoproteomics data analysis, including validation of glycan assignments and quantitation. Finally, we provide an outlook on the future of glycoproteomics from an informatics perspective, noting the key challenges to achieving widespread and reproducible glycopeptide annotation and quantitation.
    Keywords:  Database Search; False Discovery Rate; Glycopeptide Identification; Glycoproteomics; Software
    DOI:  https://doi.org/10.1016/j.cbpa.2022.102238
  10. Cells. 2022 Nov 30. pii: 3863. [Epub ahead of print]11(23):
      Targeting cancer metabolism has become one of the strategies for a rational anti-tumor therapy. However, cellular plasticity, driven by a major regulator of cellular growth and metabolism, mTORC1, often leads toward treatment resistance. Sestrin2, a stress-inducible protein, has been described as an mTORC1 inhibitor upon various types of stress signals. Immune assays and online measurements of cellular bioenergetics were employed to investigate the nature of Sestrin2 regulation, and finally, by silencing the SESN2 gene, to identify the role of induced Sestrin2 upon a single amino acid deprivation in cancer cells of various origins. Our data suggest that a complex interplay of either oxidative, energetic, nutritional stress, or in combination, play a role in Sestrin2 regulation upon single amino acid deprivation. Therefore, cellular metabolic background and sequential metabolic response dictate Sestrin2 expression in the absence of an amino acid. While deprivations of essential amino acids uniformly induce Sestrin2 levels, non-essential amino acids regulate Sestrin2 differently, drawing a characteristic Sestrin2 expression fingerprint, which could serve as a first indication of the underlying cellular vulnerability. Finally, we show that canonical GCN2-ATF4-mediated Sestrin2 induction leads to mTORC1 inhibition only in amino acid auxotroph cells, where the amino acid cannot be replenished by metabolic reprogramming.
    Keywords:  Sestrin2; amino acid deprivation; mTORC1; metabolic adaptation; nutritional stress
    DOI:  https://doi.org/10.3390/cells11233863
  11. Front Oncol. 2022 ;12 1018642
      Glutamine is a non-essential amino acid that can be synthesized by cells. It plays a vital role in the growth and proliferation of mammalian cells cultured in vitro. In the process of tumor cell proliferation, glutamine not only contributes to protein synthesis but also serves as the primary nitrogen donor for purine and pyrimidine synthesis. Studies have shown that glutamine-addicted tumor cells depend on glutamine for survival and reprogram glutamine utilization through the Krebs cycle. Potential therapeutic approaches for ovarian cancer including blocking the entry of glutamine into the tricarboxylic acid cycle in highly aggressive ovarian cancer cells or inhibiting glutamine synthesis in less aggressive ovarian cancer cells. Glutamine metabolism is associated with poor prognosis of ovarian cancer. Combining platinum-based chemotherapy with inhibition of glutamine metabolic pathways may be a new strategy for treating ovarian cancer, especially drug-resistant ovarian cancer. This article reviews the role of glutamine metabolism in the biological behaviors of ovarian cancer cells, such as proliferation, invasion, and drug resistance. Its potential use as a new target or biomarker for ovarian cancer diagnosis, treatment, and the prognosis is investigated.
    Keywords:  glutamine (Gln); mechanism; metabolism; ovarian cancer; resistance
    DOI:  https://doi.org/10.3389/fonc.2022.1018642
  12. Methods Mol Biol. 2023 ;2557 417-430
      The Golgi is the central organelle in the secretory pathway, essential for post-translational modifications, sorting and trafficking of secretory and membrane proteins and lipids in all eukaryotic cells. During mitosis, the mammalian Golgi membranes undergo continuous disassembly and reassembly processes which are critical for Golgi biogenesis during the cell division. To better understand the underlying molecular mechanism of this highly dynamic process, we analyzed the proteins that are in or associated with interphase and mitotic Golgi membranes using an in vitro Golgi assembly assay and quantitative proteomics. In this study, by combining an isobaric mass tag labeling strategy with OFFGEL peptide fractionation, LC-MS/MS analyses identified and quantified a total of 1193 Golgi-resident or -associated proteins. These proteins included Golgi structural proteins, Golgi-resident enzymes, Rab GTPases, and SNARE proteins. This systematic quantitative proteomic study revealed the comprehensive molecular machinery of the Golgi and the dynamic protein changes in its disassembly and reassembly processes. Here we describe the detailed procedures and protocols for this analysis.
    Keywords:  Golgi; Isobaric tags; LC-MS/MS; Mitosis; Peptide OFFGEL fractionation; Quantitative proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2639-9_25
  13. Int J Mol Sci. 2022 Nov 25. pii: 14744. [Epub ahead of print]23(23):
      Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.
    Keywords:  biomarkers; enzyme replacement therapy; inborn errors of metabolism; lysosomal disorders; proteomics
    DOI:  https://doi.org/10.3390/ijms232314744
  14. Int J Mol Sci. 2022 Dec 03. pii: 15263. [Epub ahead of print]23(23):
      Ovarian cancer is one of the most lethal gynecological cancers worldwide. The poor prognosis of this malignancy is substantially attributed to the inadequate symptomatic biomarkers for early diagnosis and effective remedies to cure the disease against chemoresistance and metastasis. Ovarian cancer metastasis is often relatively passive, and the single clusters of ovarian cancer cells detached from the primary ovarian tumor are transcoelomic spread by the peritoneal fluid throughout the peritoneum cavity and omentum. Our earlier studies revealed that lipid-enriched ascitic/omental microenvironment enforced metastatic ovarian cancer cells to undertake metabolic reprogramming and utilize free fatty acids as the main energy source for tumor progression and aggression. Intriguingly, cell susceptibility to ferroptosis has been tightly correlated with the dysregulated fatty acid metabolism (FAM), and enhanced iron uptake as the prominent features of ferroptosis are attributed to the strengthened lipid peroxidation and aberrant iron accumulation, suggesting that ferroptosis induction is a targetable vulnerability to prevent cancer metastasis. Therefore, the standpoints about tackling altered FAM in combination with ferroptosis initiation as a dual-targeted therapy against advanced ovarian cancer were highlighted herein. Furthermore, a discussion on the prospect and challenge of inducing ferroptosis as an innovative therapeutic approach for reversing remedial resistance in cancer interventions was included. It is hoped this proof-of-concept review will indicate appropriate directions for speeding up the translational application of ferroptosis-inducing compounds (FINs) to improve the efficacy of ovarian cancer treatment.
    Keywords:  ascites; chemoresistance; fatty acid metabolism (FAM); ferroptosis; omentum; ovarian cancer; peritoneal metastasis; tumor microenvironment (TME)
    DOI:  https://doi.org/10.3390/ijms232315263
  15. J Chromatogr A. 2022 Dec 07. pii: S0021-9673(22)00898-6. [Epub ahead of print]1687 463707
      Comprehensive characterization of the lipidome remains a challenge requiring development of new analytical approaches to expand lipid coverage in complex samples. In this work, offline two-dimensional liquid chromatography-mass spectrometry was investigated for lipidomics from human plasma. Hydrophilic interaction liquid chromatography was implemented in the first dimension to fractionate lipid classes. Nine fractions were collected and subjected to a second-dimension separation utilizing 50 cm capillary columns packed with 1.7 µm C18 particles operated on custom-built instrumentation at 35 kpsi. Online coupling with time-of-flight mass spectrometry allowed putative lipid identification from precursor-mass based library searching. The method had good orthogonality (fractional coverage of ∼40%), achieved a peak capacity of approximately 1900 in 600 min, and detected over 1000 lipids from a 5 µL injection of a human plasma extract while consuming less than 3 mL of solvent. The results demonstrate the expected gains in peak capacity when employing long columns and two-dimensional separations and illustrate practical approaches for improving lipidome coverage from complex biological samples.
    Keywords:  Capillary liquid chromatography; Lipidomics; Nanoscale liquid chromatography; Two-dimensional chromatography; Ultra-high pressure liquid chromatography
    DOI:  https://doi.org/10.1016/j.chroma.2022.463707
  16. Nat Protoc. 2022 Dec 16.
      Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to a perturbation, protein structure may be altered by various molecular events, such as post-translational modifications, protein-protein interactions, aggregation, allostery or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of biological processes and pathways. Here, we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale. In LiP-MS, proteins undergo a brief proteolysis in native conditions followed by complete digestion in denaturing conditions, to generate structurally informative proteolytic fragments that are analyzed by mass spectrometry. We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition-based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. We introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. The experimental procedures take 3 d, mass spectrometric measurement time and data processing depend on sample number and statistical analysis typically requires ~1 d. These improvements expand the adaptability of LiP-MS and enable wide use in functional proteomics and translational applications.
    DOI:  https://doi.org/10.1038/s41596-022-00771-x
  17. Cancers (Basel). 2022 Nov 29. pii: 5896. [Epub ahead of print]14(23):
      The long-chain fatty acyl CoA synthetase (ACSLs) family of enzymes contributes significantly to lipid metabolism and produces acyl-coenzyme A by catalyzing fatty acid oxidation. The dysregulation of ACSL3 and ACSL4, which belong to the five isoforms of ACSLs, plays a key role in cancer initiation, development, metastasis, and tumor immunity and may provide several possible therapeutic strategies. Moreover, ACSL3 and ACSL4 are crucial for ferroptosis, a non-apoptotic cell death triggered by the accumulation of membrane lipid peroxides due to iron overload. Here, we present a summary of the current knowledge on ACSL3 and ACSL4 and their functions in various cancers. Research on the molecular mechanisms involved in the regulation of ferroptosis is critical to developing targeted therapies for cancer.
    Keywords:  ACSL3; ACSL4; cancer; ferroptosis
    DOI:  https://doi.org/10.3390/cancers14235896
  18. Mass Spectrom Rev. 2022 Dec 16. e21826
      Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body.
    Keywords:  cancer diagnosis; mass spectrometry; metabolomics; newborn screening
    DOI:  https://doi.org/10.1002/mas.21826
  19. Methods Mol Biol. 2023 ;2557 785-810
      Cancer cells utilize secretory pathways for paracrine signaling and extracellular matrix remodeling to facilitate directional cell migration, invasion, and metastasis. The Golgi apparatus is a central secretory signaling hub that is often deregulated in cancer. Here we described technologies that utilize microscopic, biochemical, and proteomic approaches to analyze Golgi secretory functions in genetically heterogeneous cancer cell lines.
    Keywords:  Cancer; Confocal microscopy; Golgi apparatus; Live-cell imaging; Proteomics; Quantitative image analysis; Secretion; Subcellular fractionation; Vesicle trafficking
    DOI:  https://doi.org/10.1007/978-1-0716-2639-9_47
  20. FEBS J. 2022 Dec 14.
      Advances in cancer biology over the past decades have revealed that metabolic adaptation of cancer cells is an essential aspect of tumorigenesis. However, recent insights into tumor metabolism in vivo have revealed dissimilarities with results obtained in vitro. This is partly due to the reductionism of in vitro cancer models that struggle to reproduce the complexity of tumor tissues. This review describes some of the discrepancies in cancer cell metabolism between in vitro and in vivo conditions, and presents current methodological approaches and tools used to bridge the gap with the clinically relevant microenvironment. As such, these approaches should generate new knowledge that could be more effectively translated into therapeutic opportunities.
    Keywords:  3D models; metabolic heterogeneity; metabolic sensors; tissue culture media; tumor cell metabolism
    DOI:  https://doi.org/10.1111/febs.16704
  21. Mol Metab. 2022 Dec 10. pii: S2212-8778(22)00222-8. [Epub ahead of print] 101653
      BACKGROUND: Key cellular metabolites reflecting the immediate activity of metabolic enzymes as well as the functional metabolic state of intracellular organelles can act as powerful signal regulators to ensure the activation of homeostatic responses. The citrate/acetyl-CoA pathway, initially recognized for its role in intermediate metabolism, has emerged as a fundamental branch of this nutrient-sensing homeostatic response. Emerging studies indicate that fluctuations in acetyl-CoA availability within different cellular organelles and compartments provides substrate-level regulation of many biological functions. A fundamental aspect of these regulatory functions involves Nε-lysine acetylation.SCOPE OF REVIEW: Here, we will examine the emerging regulatory functions of the citrate/acetyl-CoA pathway and the specific role of the endoplasmic reticulum (ER) acetylation machinery in the maintenance of intracellular crosstalk and homeostasis. These functions will be analyzed in the context of associated human diseases and specific mouse models of dysfunctional ER acetylation and citrate/acetyl-CoA flux. A primary objective of this review is to highlight the complex yet integrated response of compartment- and organelle-specific Nε-lysine acetylation to the intracellular availability and flux of acetyl-CoA, linking this important post-translational modification to cellular metabolism.
    MAJOR CONCLUSIONS: The ER acetylation machinery regulates the proteostatic functions of the organelle as well as metabolic crosstalk between different intracellular organelles and compartments. This crosstalk enables the cell to impart adaptive responses within the ER and the secretory pathway. However, it also enables the ER to impart adaptive responses within different cellular organelles and compartments. Defects in the homeostatic balance of acetyl-CoA flux and ER acetylation reflect different but converging disease states in humans as well as converging phenotypes in relevant mouse models. In conclusion, citrate and acetyl-CoA should not only be seen as metabolic substrates of intermediate metabolism but also as signaling molecules that direct functional adaptation of the cell to both intracellular and extracellular messages. Future discoveries in CoA biology and acetylation are likely to yield novel therapeutic approaches.
    Keywords:  Acetyl-CoA; Acetylation; Citrate; CoA; Endoplasmic Reticulum
    DOI:  https://doi.org/10.1016/j.molmet.2022.101653
  22. Front Mol Biosci. 2022 ;9 1021889
      Imaging mass spectrometry (MS) is becoming increasingly applied for single-cell analyses. Multiple methods for imaging MS-based single-cell metabolomics were proposed, including our recent method SpaceM. An important step in imaging MS-based single-cell metabolomics is the assignment of MS intensities from individual pixels to single cells. In this process, referred to as pixel-cell deconvolution, the MS intensities of regions sampled by the imaging MS laser are assigned to the segmented single cells. The complexity of the contributions from multiple cells and the background, as well as lack of full understanding of how input from molecularly-heterogeneous areas translates into mass spectrometry intensities make the cell-pixel deconvolution a challenging problem. Here, we propose a novel approach to evaluate pixel-cell deconvolution methods by using a molecule detectable both by mass spectrometry and fluorescent microscopy, namely fluorescein diacetate (FDA). FDA is a cell-permeable small molecule that becomes fluorescent after internalisation in the cell and subsequent cleavage of the acetate groups. Intracellular fluorescein can be easily imaged using fluorescence microscopy. Additionally, it is detectable by matrix-assisted laser desorption/ionisation (MALDI) imaging MS. The key idea of our approach is to use the fluorescent levels of fluorescein as the ground truth to evaluate the impact of using various pixel-cell deconvolution methods onto single-cell fluorescein intensities obtained by the SpaceM method. Following this approach, we evaluated multiple pixel-cell deconvolution methods, the 'weighted average' method originally proposed in the SpaceM method as well as the novel 'linear inverse modelling' method. Despite the potential of the latter method in resolving contributions from individual cells, this method was outperformed by the weighted average approach. Using the ground truth approach, we demonstrate the extent of the ion suppression effect which considerably worsens the pixel-cell deconvolution quality. For compensating the ion suppression individually for each analyte, we propose a novel data-driven approach. We show that compensating the ion suppression effect in a single-cell metabolomics dataset of co-cultured HeLa and NIH3T3 cells considerably improved the separation between both cell types. Finally, using the same ground truth, we evaluate the impact of drop-outs in the measurements and discuss the optimal filtering parameters of SpaceM processing steps before pixel-cell deconvolution.
    Keywords:  SpaceM; fluorescein diacetate (FDA); imaging mass spectrometry (imaging MS); ion suppression; pixel-cell deconvolution; spatial single-cell metabolomics
    DOI:  https://doi.org/10.3389/fmolb.2022.1021889
  23. Int J Mol Sci. 2022 Nov 23. pii: 14620. [Epub ahead of print]23(23):
      Metabolic stable isotope labeling followed by liquid chromatography coupled with mass spectrometry (LC-MS) is a powerful tool for in vivo protein turnover studies of individual proteins on a large scale and with high throughput. Turnover rates of thousands of proteins from dozens of time course experiments are determined by data processing tools, which are essential components of the workflows for automated extraction of turnover rates. The development of sophisticated algorithms for estimating protein turnover has been emphasized. However, the visualization and annotation of the time series data are no less important. The visualization tools help to validate the quality of the model fits, their goodness-of-fit characteristics, mass spectral features of peptides, and consistency of peptide identifications, among others. Here, we describe a graphical user interface (GUI) to visualize the results from the protein turnover analysis tool, d2ome, which determines protein turnover rates from metabolic D2O labeling followed by LC-MS. We emphasize the specific features of the time series data and their visualization in the GUI. The time series data visualized by the GUI can be saved in JPEG format for storage and further dissemination.
    Keywords:  graphical user interface for mass spectral data; heavy water metabolic labeling; in vivo protein turnover; isotope distribution; time series of isotope labeling
    DOI:  https://doi.org/10.3390/ijms232314620
  24. Int J Mol Sci. 2022 Nov 26. pii: 14808. [Epub ahead of print]23(23):
      Metabolic alterations that support the supply of biosynthetic molecules necessary for rapid and sustained proliferation are characteristic of cancer. Some cancer cells rely on glutamine to maintain their energy requirements for growth. Glutamine is an important metabolite in cells because it not only links to the tricarboxylic acid cycle by producing α-ketoglutarate by glutaminase and glutamate dehydrogenase but also supplies other non-essential amino acids, fatty acids, and components of nucleotide synthesis. Altered glutamine metabolism is associated with cancer cell survival, proliferation, metastasis, and aggression. Furthermore, altered glutamine metabolism is known to be involved in therapeutic resistance. In recent studies, lncRNAs were shown to act on amino acid transporters and glutamine-metabolic enzymes, resulting in the regulation of glutamine metabolism. The lncRNAs involved in the expression of the transporters include the abhydrolase domain containing 11 antisense RNA 1, LINC00857, plasmacytoma variant translocation 1, Myc-induced long non-coding RNA, and opa interacting protein 5 antisense RNA 1, all of which play oncogenic roles. When it comes to the regulation of glutamine-metabolic enzymes, several lncRNAs, including nuclear paraspeckle assembly transcript 1, XLOC_006390, urothelial cancer associated 1, and thymopoietin antisense RNA 1, show oncogenic activities, and others such as antisense lncRNA of glutaminase, lincRNA-p21, and ataxin 8 opposite strand serve as tumor suppressors. In addition, glutamine-dependent cancer cells with lncRNA dysregulation promote cell survival, proliferation, and metastasis by increasing chemo- and radio-resistance. Therefore, understanding the roles of lncRNAs in glutamine metabolism will be helpful for the establishment of therapeutic strategies for glutamine-dependent cancer patients.
    Keywords:  glutamine anaplerosis; glutamine metabolism; long non-coding RNA; therapeutic resistance
    DOI:  https://doi.org/10.3390/ijms232314808