bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2024‒09‒08
twelve papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh
  1. Fast and broad-coverage lipidomics enabled by ion mobility-mass spectrometry.
  2. Novel sampling and gas-phase derivatization strategy: Proof-of-concept by profiling ionic polar metabolites using gas chromatography-mass spectrometry.
  3. Optimized Automated Workflow for BioID Improves Reproducibility and Identification of Protein-Protein Interactions.
  4. Global 13C tracing and metabolic flux analysis of intact human liver tissue ex vivo.
  5. Protocol to analyze 1D and 2D mass spectrometry data from glioblastoma tissues for cancer diagnosis and immune cell identification.
  6. A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.
  7. Chloroform/Methanol Protein Extraction and In-solution Trypsin Digestion Protocol for Bottom-up Proteomics Analysis.
  8. Impact of internal standard selection on measurement results for long chain fatty acids in blood.
  9. Consolidating two-dimensional liquid chromatography-high-resolution tandem mass spectrometry (LC×LC-HRMS/MS) technique for the non-targeted analysis of poly- and perfluorinated substances: A trial on aqueous film-forming foams.
  10. Combinatorial targeting of glutamine metabolism and lysosomal-based lipid metabolism effectively suppresses glioblastoma.
  11. Cold-induced phosphatidylethanolamine synthesis in liver and brown adipose tissue of mice.
  12. Mass Spectrometry-Based Direct Sequencing of tRNAs De Novo and Quantitative Mapping of Multiple RNA Modifications.
  1. Analyst. 2024 Sep 02.
    Fast and broad-coverage lipidomics enabled by ion mobility-mass spectrometry.
    Yuping Cai, Xi Chen, Fandong Ren, Hongmiao Wang, Yandong Yin, Zheng-Jiang Zhu.
      Aberrant lipid metabolism has been widely recognized as a hallmark of various diseases. However, the comprehensive analysis of distinct lipids is challenging due to the complexity of lipid molecular structures, wide concentration ranges, and numerous isobaric and isomeric lipids. Usually, liquid chromatography-mass spectrometry (LC-MS)-based lipidomics requires a long time for chromatographic separation to achieve optimal separation and selectivity. Ion mobility (IM) adds a new separation dimension to LC-MS, significantly enhancing the coverage, sensitivity, and resolving power. We took advantage of the rapid separation provided by ion mobility and optimized a fast and broad-coverage lipidomics method using the LC-IM-MS technology. The method required only 8 minutes for separation and detected over 1000 lipid molecules in a single analysis of common biological samples. The high reproducibility and accurate quantification of this high-throughput lipidomics method were systematically characterized. We then applied the method to comprehensively measure dysregulated lipid metabolism in patients with colorectal cancer (CRC). Our results revealed 115 significantly changed lipid species between preoperative and postoperative plasma of patients with CRC and also disclosed associated differences in lipid classes such as phosphatidylcholines (PC), sphingomyelins (SM), and triglycerides (TG) regarding carbon number and double bond. Together, a fast and broad-coverage lipidomics method was developed using ion mobility-mass spectrometry. This method is feasible for large-scale clinical lipidomic studies, as it effectively balances the requirements of high-throughput and broad-coverage in clinical studies.
    DOI:  https://doi.org/10.1039/d4an00751d
  2. J Biosci Bioeng. 2024 Sep 03. pii: S1389-1723(24)00230-5. [Epub ahead of print]
    Novel sampling and gas-phase derivatization strategy: Proof-of-concept by profiling ionic polar metabolites using gas chromatography-mass spectrometry.
    Kazuhiro Kawamura, Eiichiro Fukusaki.
      Metabolomic research involves the comprehensive analysis of metabolites in biological samples and has many applications. Gas chromatography-mass spectrometry (GC-MS) is an established and widely used approach for metabolic profiling. However, sample preparation and metabolite derivatization are time-consuming, and derivatization options are limited. We propose gas-solid phase derivatization (GSPD) as a novel sampling and derivatization method that uses a silica monolith substrate and gaseous derivatization reagents for metabolomics using GC-MS. We developed a method to measure the organic acids and sugar phosphates responsible for glycolysis and the tricarboxylic acid (TCA) cycle. GSPD simplifies the sample preparation and can be applied to derivatization reactions that are difficult to perform in solution owing to solvent limitations. The developed method was applied to human plasma and tomato pulp and was shown to have a higher detection performance than the conventional method. This study provides a strategy to simplify sample preparation and expand derivatization options for GC-MS-based metabolomics.
    Keywords:  Derivatization; Gas chromatography/mass spectrometry; Metabolomics; Organic acid; Silica monolith; Sugar phosphate
    DOI:  https://doi.org/10.1016/j.jbiosc.2024.07.019
  3. J Proteome Res. 2024 Sep 04.
    Optimized Automated Workflow for BioID Improves Reproducibility and Identification of Protein-Protein Interactions.
    Emilio Cirri, Hannah Knaudt, Domenico Di Fraia, Nadine Pömpner, Norman Rahnis, Ivonne Heinze, Alessandro Ori, Therese Dau.
      Proximity-dependent biotinylation is an important method to study protein-protein interactions in cells, for which an expanding number of applications has been proposed. The laborious and time-consuming sample processing has limited project sizes so far. Here, we introduce an automated workflow on a liquid handler to process up to 96 samples at a time. The automation not only allows higher sample numbers to be processed in parallel but also improves reproducibility and lowers the minimal sample input. Furthermore, we combined automated sample processing with shorter liquid chromatography gradients and data-independent acquisition to increase the analysis throughput and enable reproducible protein quantitation across a large number of samples. We successfully applied this workflow to optimize the detection of proteasome substrates by proximity-dependent labeling.
    Keywords:  BioID; automation; high throughput; mass spectrometry; proximity labeling
    DOI:  https://doi.org/10.1021/acs.jproteome.4c00308
  4. Nat Metab. 2024 Aug 29.
    Global 13C tracing and metabolic flux analysis of intact human liver tissue ex vivo.
    Nina Grankvist, Cecilia Jönsson, Karin Hedin, Nicolas Sundqvist, Per Sandström, Bergthor Björnsson, Arjana Begzati, Evgeniya Mickols, Per Artursson, Mohit Jain, Gunnar Cedersund, Roland Nilsson.
      Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we perform in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Isotope tracing allowed qualitative assessment of a wide range of metabolic pathways within a single experiment, confirming well-known features of liver metabolism but also revealing unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Glucose production ex vivo correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes, and could be suppressed by postprandial levels of nutrients and insulin, and also by pharmacological inhibition of glycogen utilization. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.
    DOI:  https://doi.org/10.1038/s42255-024-01119-3
  5. STAR Protoc. 2024 Sep 04. pii: S2666-1667(24)00450-7. [Epub ahead of print]5(3): 103285
    Protocol to analyze 1D and 2D mass spectrometry data from glioblastoma tissues for cancer diagnosis and immune cell identification.
    Yanis Zirem, Léa Ledoux, Michel Salzet, Isabelle Fournier.
      In context of cancer diagnosis-based mass spectrometry (MS), the classification model created is crucial. Moreover, exploration of immune cell infiltration in tissues can offer insights within the tumor microenvironment. Here, we present a protocol to analyze 1D and 2D MS data from glioblastoma tissues for cancer diagnosis and immune cells identification. We describe steps for training the most optimal model and cross-validating it, for discovering robust biomarkers and obtaining their corresponding boxplots as well as creating an immunoscore based on MS-imaging data. For complete details on the use and execution of this protocol, please refer to Zirem et al.1.
    Keywords:  Cancer; Computer sciences; Immunology; Mass Spectrometry
    DOI:  https://doi.org/10.1016/j.xpro.2024.103285
  6. Proteomics. 2024 Sep 05. e2400129
    A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.
    Jennifer Guergues, Jessica Wohlfahrt, John M Koomen, Jonathan R Krieger, Sameer Varma, Stanley M Stevens.
      Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.
    Keywords:  PRM‐PASEF; apoptosis; discovery validation; method development automation; open script; parallel accumulation serial fragmentation (PASEF); parallel reaction monitoring (PRM); pathway‐driven analysis
    DOI:  https://doi.org/10.1002/pmic.202400129
  7. Bio Protoc. 2024 Aug 20. 14(16): e5055
    Chloroform/Methanol Protein Extraction and In-solution Trypsin Digestion Protocol for Bottom-up Proteomics Analysis.
    Tess Puopolo, Navindra P Seeram, Chang Liu.
      Bottom-up proteomics utilizes sample preparation techniques to enzymatically digest proteins, thereby generating identifiable and quantifiable peptides. Proteomics integrates with other omics methodologies, such as genomics and transcriptomics, to elucidate biomarkers associated with diseases and responses to drug or biologics treatment. The methodologies employed for preparing proteomic samples for mass spectrometry analysis exhibit variability across several factors, including the composition of lysis buffer detergents, homogenization techniques, protein extraction and precipitation methodologies, alkylation strategies, and the selection of digestion enzymes. The general workflow for bottom-up proteomics consists of sample preparation, mass spectrometric data acquisition (LC-MS/MS analysis), and subsequent downstream data analysis including protein quantification and differential expression analysis. Sample preparation poses a persistent challenge due to issues such as low reproducibility and inherent procedure complexities. Herein, we have developed a validated chloroform/methanol sample preparation protocol to obtain reproducible peptide mixtures from both rodent tissue and human cell line samples for bottom-up proteomics analysis. The protocol we established may facilitate the standardization of bottom-up proteomics workflows, thereby enhancing the acquisition of reliable biologically and/or clinically relevant proteomic data. Key features • Tissue/cell pellet sample preparation for bottom-up proteomics. • Chloroform/methanol protein extraction from murine tissue samples. • In-solution trypsin digestion proteomics workflow.
    Keywords:  Chloroform/methanol; In-solution digestion; Protein extraction; Proteomics; Sample preparation
    DOI:  https://doi.org/10.21769/BioProtoc.5055
  8. J Mass Spectrom Adv Clin Lab. 2024 Aug;33 22-30
    Impact of internal standard selection on measurement results for long chain fatty acids in blood.
    John M Goodwin, Heather C Kuiper, Barrett Brister, Hubert W Vesper.
      Introduction: Internal standards correct for measurement variation due to sample loss. Isotope labeled analytes are ideal internal standards for the measurement of fatty acids in human plasma but are not always readily available. For this reason, quantification of multiple analytes at once is most often done using only a single or few internal standards. The magnitude of the impact this has on method accuracy and precision is not well studied for gas chromatography-mass spectrometry systems.Objective: This study aims to estimate bias and changes in uncertainty associated with using alternative fatty acid isotopologue internal standards for the estimation of similar or dissimilar long chain fatty acids.
    Method: Using a previously reported method for the quantification of 27 fatty acids in human plasma using 18 internal standards we obtained estimates of bias and uncertainty at up to three levels of fatty acid concentration.
    Results: With some notable exceptions, method accuracy remained relatively stable when using an alternative internal standard (Median Relative Absolute Percent Bias: 1.76%, Median Spike-Recovery Absolute Percent Bias: 8.82%), with larger changes in method precision (Median Increase in Variance: 141%). Additionally, the degree of difference between analyte and internal standard structure was related to the magnitude of bias and uncertainty of the measurement.
    Conclusion: The data presented here show that the choice of internal standard used to estimate fatty acid concentration can affect the accuracy and reliability of measurement results and, therefore, needs to be assessed carefully when developing analytical methods for the measurement of fatty acid profiles.Disclaimer: The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry. Use of trade names is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention, the Public Health Service, and the US Department of Health and Human Services.
    Keywords:  Fatty acids; Gas chromatography; Internal standards; Isotope dilution; Mass spectrometry
    DOI:  https://doi.org/10.1016/j.jmsacl.2024.07.002
  9. Sci Total Environ. 2024 Aug 30. pii: S0048-9697(24)06064-9. [Epub ahead of print]952 175908
    Consolidating two-dimensional liquid chromatography-high-resolution tandem mass spectrometry (LC×LC-HRMS/MS) technique for the non-targeted analysis of poly- and perfluorinated substances: A trial on aqueous film-forming foams.
    Lapo Renai, Massimo Del Bubba, Andrea F G Gargano, Saer Samanipour.
      To date, poly- and perfluoroalkyl substances (PFAS) represent a real threat for their environmental persistence, wide physicochemical variability, and their potential toxicity. Thus far a large portion of these chemicals remain structurally unknown. These chemicals, therefore, require the implementation of complex non-targeted analysis workflows using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) for their comprehensive detection and monitoring. This approach, even though comprehensive, does not always provide the much-needed analytical resolution for the analysis of complex PFAS mixtures such as fire-fighting aqueous film-forming foams (AFFFs). This study consolidates the advantages of the LC×LC technique hyphenated with high-resolution tandem mass spectrometry (HRMS/MS) for the identification of PFAS in AFFF mixtures. A total of 57 PFAS homolog series (HS) were identified in 3M and Orchidee AFFF mixtures thanks to the (i) high chromatographic peak capacity (n'2D,c ~ 300) and the (i) increased mass domain resolution provided by the "remainder of Kendrick Mass" (RKM) analysis on the HRMS data. Then, we attempted to annotate the PFAS of each HS by exploiting the available reference standards and the FluoroMatch workflow in combination with the RKM defect by different fluorine repeating units, such as CF2, CF2O, and C2F4O. This approach resulted in 12 identified PFAS HS, including compounds belonging to the HS of perfluoroalkyl carboxylic acids (PFACAs), perfluoroalkyl sulfonic acids (PFASAs), (N-pentafluoro(5)sulfide)-perfluoroalkane sulfonates (SF5-PFASAs), N-sulfopropyldimethylammoniopropyl perfluoroalkane sulfonamides (N-SPAmP-FASA), and N-carboxymethyldimethylammoniopropyl perfluoroalkane sulfonamide (N-CMAmP-FASA). The annotated categories of perfluoroalkyl aldehydes and chlorinated PFASAs represent the first record of PFAS HS in the investigated AFFF samples.
    Keywords:  Data processing; Feature detection; Mass defect analysis; Tandem mass spectrometry; Two-dimensional liquid chromatography
    DOI:  https://doi.org/10.1016/j.scitotenv.2024.175908
  10. Cell Rep Med. 2024 Aug 28. pii: S2666-3791(24)00427-0. [Epub ahead of print] 101706
    Combinatorial targeting of glutamine metabolism and lysosomal-based lipid metabolism effectively suppresses glioblastoma.
    Yaogang Zhong, Feng Geng, Logan Mazik, Xinmin Yin, Aline Paixao Becker, Shabber Mohammed, Huali Su, Enming Xing, Yongjun Kou, Cheng-Yao Chiang, Yunzhou Fan, Yongchen Guo, Qiang Wang, Pui-Kai Li, Xiaokui Mo, Etienne Lefai, Liqing He, Xiaolin Cheng, Xiang Zhang, Arnab Chakravarti, Deliang Guo.
      Antipsychotic drugs have been shown to have antitumor effects but have had limited potency in the clinic. Here, we unveil that pimozide inhibits lysosome hydrolytic function to suppress fatty acid and cholesterol release in glioblastoma (GBM), the most lethal brain tumor. Unexpectedly, GBM develops resistance to pimozide by boosting glutamine consumption and lipogenesis. These elevations are driven by SREBP-1, which we find upregulates the expression of ASCT2, a key glutamine transporter. Glutamine, in turn, intensifies SREBP-1 activation through the release of ammonia, creating a feedforward loop that amplifies both glutamine metabolism and lipid synthesis, leading to drug resistance. Disrupting this loop via pharmacological targeting of ASCT2 or glutaminase, in combination with pimozide, induces remarkable mitochondrial damage and oxidative stress, leading to GBM cell death in vitro and in vivo. Our findings underscore the promising therapeutic potential of effectively targeting GBM by combining glutamine metabolism inhibition with lysosome suppression.
    Keywords:  ASCT2; GLS; SREBP-1; cholesterol; fatty acids; glioblastoma; glutamine; lipid droplets; lysosome; pimozide
    DOI:  https://doi.org/10.1016/j.xcrm.2024.101706
  11. Biochim Biophys Acta Mol Cell Biol Lipids. 2024 Aug 28. pii: S1388-1981(24)00112-4. [Epub ahead of print]1870(1): 159562
    Cold-induced phosphatidylethanolamine synthesis in liver and brown adipose tissue of mice.
    Maria Soledad Hidrobo, Marcus Höring, Sarah Brunner, Gerhard Liebisch, Sabine Schweizer, Martin Klingenspor, Renate Schreiber, Rudolf Zechner, Ralph Burkhardt, Josef Ecker.
      Increasing energy expenditure in brown adipose (BAT) tissue by cold-induced lipolysis is discussed as a potential strategy to counteract imbalanced lipid homeostasis caused through unhealthy lifestyle and cardiometabolic disease. Yet, it is largely unclear how liberated fatty acids (FA) are metabolized. We investigated the liver and BAT lipidome of mice housed for 1 week at thermoneutrality, 23 °C and 4 °C using quantitative mass spectrometry-based lipidomics. Housing at temperatures below thermoneutrality triggered the generation of phosphatidylethanolamine (PE) in both tissues. Particularly, the concentrations of PE containing polyunsaturated fatty acids (PUFA) in their acyl chains like PE 18:0_20:4 were increased at cold. Investigation of the plasma's FA profile using gas chromatography coupled to mass spectrometry revealed a negative correlation of PUFA with unsaturated PE in liver and BAT indicating a flux of FA from the circulation into these tissues. Beta-adrenergic stimulation elevated intracellular levels of PE 38:4 and PE 40:6 in beige wildtype adipocytes, but not in adipose triglyceride lipase (ATGL)-deficient cells. These results imply an induction of PE synthesis in liver, BAT and thermogenic adipocytes after activation of the beta-adrenergic signaling cascade.
    Keywords:  Cold exposure; Lipidomics; Lipolysis; Liver lipidome; PUFA; Phosphatidylethanolamine
    DOI:  https://doi.org/10.1016/j.bbalip.2024.159562
  12. J Am Chem Soc. 2024 Sep 04.
    Mass Spectrometry-Based Direct Sequencing of tRNAs De Novo and Quantitative Mapping of Multiple RNA Modifications.
    Xiaohong Yuan, Yue Su, Benjamin Johnson, Michele Kirchner, Xudong Zhang, Sihang Xu, Sophia Jiang, Jing Wu, Shundi Shi, James J Russo, Qi Chen, Shenglong Zhang.
      Despite the extensive use of next-generation sequencing (NGS) of RNA, simultaneous direct sequencing and quantitative mapping of multiple RNA nucleotide modifications remains challenging. Mass spectrometry (MS)-based sequencing can directly sequence all RNA modifications without being limited to specific ones, but it requires a perfect MS ladder that few tRNAs can provide. Here, we describe an MS ladder complementation sequencing approach (MLC-Seq) that circumvents the perfect ladder requirement, allowing de novo MS sequencing of full-length heterogeneous cellular tRNAs with multiple nucleotide modifications at single-nucleotide precision. Unlike NGS-based methods, which lose RNA modification information, MLC-Seq preserves RNA sequence diversity and modification information, revealing new detailed stoichiometric tRNA modification profiles and their changes upon treatment with the dealkylating enzyme AlkB. It can also be combined with reference sequences to provide quantitative analysis of diverse tRNAs and modifications in total tRNA samples. MLC-Seq enables systematic, quantitative, and site-specific mapping of RNA modifications, revealing the truly complete informational content of tRNA.
    DOI:  https://doi.org/10.1021/jacs.4c07280
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