bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2024‒08‒11
ten papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh
  1. Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP.
  2. Analysis types and quantification methods applied in UHPLC-MS metabolomics research: a tutorial.
  3. Liquid chromatography-mass spectrometry quantification of phytochemicals in Withania somnifera using data-dependent acquisition, multiple-reaction-monitoring, and parallel-reaction-monitoring with an inclusion list.
  4. Discrimination of Common E. coli Strains in Urine by Liquid Chromatography-Ion Mobility-Tandem Mass Spectrometry and Machine Learning.
  5. Regulation of cancer cell lipid metabolism and oxidative phosphorylation by microenvironmental acidosis.
  6. Editorial: Mass spectrometry-based proteomics in drug discovery and development.
  7. Quantitative Comparison of Deparaffinization, Rehydration, and Extraction Methods for FFPE Tissue Proteomics and Phosphoproteomics.
  8. Emerging roles of the chromatin remodeler MORC2 in cancer metabolism.
  9. Proteomic Analysis of Secreted Vesicle Proteins from the Plant Cells.
  10. Characterising the urinary acylcarnitine and amino acid profiles of HIV/TB co-infection, using LC-MS metabolomics.
  1. Nat Protoc. 2024 Aug 08.
    Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP.
    Andrew Leduc, Luke Khoury, Joshua Cantlon, Saad Khan, Nikolai Slavov.
      Single-cell proteomics by mass spectrometry (MS) allows the quantification of proteins with high specificity and sensitivity. To increase its throughput, we developed nano-proteomic sample preparation (nPOP), a method for parallel preparation of thousands of single cells in nanoliter-volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation using the plexDIA MS multiplexing method, which uses non-isobaric mass tags to barcode peptides from different samples for data-independent acquisition, demonstrates accurate quantification of ~3,000-3,700 proteins per human cell. A separate implementation with isobaric mass tags and prioritized data acquisition demonstrates analysis of 1,827 single cells at a rate of >1,000 single cells per day at a depth of 800-1,200 proteins per human cell. The protocol is implemented by using a cell-dispensing and liquid-handling robot-the CellenONE instrument-and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 d to prepare >3,000 single cells. We provide metrics and software (the QuantQC R package) for quality control and data exploration. QuantQC supports the robust scaling of nPOP to higher plex reagents for achieving reliable and scalable single-cell proteomics.
    DOI:  https://doi.org/10.1038/s41596-024-01033-8
  2. Metabolomics. 2024 Aug 07. 20(5): 95
    Analysis types and quantification methods applied in UHPLC-MS metabolomics research: a tutorial.
    Richard D Beger, Royston Goodacre, Christina M Jones, Katrice A Lippa, Oleg A Mayboroda, Donna O'Neill, Lukas Najdekr, Ioanna Ntai, Ian D Wilson, Warwick B Dunn.
      BACKGROUND: Different types of analytical methods, with different characteristics, are applied in metabolomics and lipidomics research and include untargeted, targeted and semi-targeted methods. Ultra High Performance Liquid Chromatography-Mass Spectrometry is one of the most frequently applied measurement instruments in metabolomics because of its ability to detect a large number of water-soluble and lipid metabolites over a wide range of concentrations in short analysis times. Methods applied for the detection and quantification of metabolites differ and can either report a (normalised) peak area or an absolute concentration.AIM OF REVIEW: In this tutorial we aim to (1) define similarities and differences between different analytical approaches applied in metabolomics and (2) define how amounts or absolute concentrations of endogenous metabolites can be determined together with the advantages and limitations of each approach in relation to the accuracy and precision when concentrations are reported.
    KEY SCIENTIFIC CONCEPTS OF REVIEW: The pre-analysis knowledge of metabolites to be targeted, the requirement for (normalised) peak responses or absolute concentrations to be reported and the number of metabolites to be reported define whether an untargeted, targeted or semi-targeted method is applied. Fully untargeted methods can only provide (normalised) peak responses and fold changes which can be reported even when the structural identity of the metabolite is not known. Targeted methods, where the analytes are known prior to the analysis, can also report fold changes. Semi-targeted methods apply a mix of characteristics of both untargeted and targeted assays. For the reporting of absolute concentrations of metabolites, the analytes are not only predefined but optimized analytical methods should be developed and validated for each analyte so that the accuracy and precision of concentration data collected for biological samples can be reported as fit for purpose and be reviewed by the scientific community.
    Keywords:  Metabolomics; Quantification; Semi-targeted; Targeted; UHPLC-MS; Untargeted; Validation
    DOI:  https://doi.org/10.1007/s11306-024-02155-6
  3. Front Chem. 2024 ;12 1373535
    Liquid chromatography-mass spectrometry quantification of phytochemicals in Withania somnifera using data-dependent acquisition, multiple-reaction-monitoring, and parallel-reaction-monitoring with an inclusion list.
    Luke C Marney, Jaewoo Choi, Armando Alcazar Magana, Liping Yang, Natascha Techen, Md Nure Alam, Mikah Brandes, Amala Soumyanath, Jan F Stevens, Claudia S Maier.
      Characterization of botanical extracts by mass spectrometry-based metabolomics analysis helps in determining the phytochemical composition that underlies their bioactivity and potential health benefits, while also supporting reproducibility of effects in clinical trials. The quantification of seven withanolides in Withania somnifera using three mass-spectrometry methods was evaluated using Deming regression. Two high-resolution time-of-flight mass spectrometry methods were used, one operating in data-dependent acquisition mode and the other in parallel-reaction-monitoring mode with an inclusion list. The two high-resolution time-of-flight mass spectrometry methods were compared to a multiple-reaction-monitoring method. We evaluated in-source fragmentation of steroidal glycosides and optimized the methods accordingly. A novel software approach to integrating parallel-reaction-monitoring data acquired with an inclusion list was developed. Combining and comparing quantitative results allowed for quantitative specificity, good precision, and adjustment of instrument source conditions for optimal quantification by multiple-reaction-monitoring mass spectrometry, an analytical method that is widely accessible in analytical and phytochemical laboratories.
    Keywords:  Withania somnifera; ashwagandha; deming regression; mass spectrometry; metabolomics; method comparison; withanolides
    DOI:  https://doi.org/10.3389/fchem.2024.1373535
  4. J Am Soc Mass Spectrom. 2024 Aug 05.
    Discrimination of Common E. coli Strains in Urine by Liquid Chromatography-Ion Mobility-Tandem Mass Spectrometry and Machine Learning.
    Orobola E Olajide, Michael Zirpoli, Kimberly Y Kartowikromo, Jingyi Zheng, Ahmed M Hamid.
      Accurate identification of bacterial strains in clinical samples is essential to provide an appropriate antibiotherapy to the patient and reduce the prescription of broad-spectrum antimicrobials, leading to antibiotic resistance. In this study, we utilized the combination of a multidimensional analytical technique, liquid chromatography-ion mobility-tandem mass spectrometry (LC-IM-MS/MS), and machine learning to accurately identify and distinguish 11 Escherichia coli (E. coli) strains in artificially contaminated urine samples. Machine learning was utilized on the LC-IM-MS/MS data of the inoculated urine samples to reveal lipid, metabolite, and peptide isomeric biomarkers for the identification of the bacteria strains. Tandem MS and LC separation proved effective in discriminating diagnostic isomers in the negative ion mode, while IM separation was more effective in resolving conformational biomarkers in the positive ion mode. Using hierarchical clustering, the strains are clustered accurately according to their group highlighting the uniqueness of the discriminating biomarkers to the class of each E. coli strain. These results show the great potential of using LC-IM-MS/MS and machine learning for targeted omics applications to diagnose infectious diseases in various environmental and clinical samples accurately.
    Keywords:  E. coli strain differentiation; biomarkers; ion mobility; omics; tandem mass spectrometry
    DOI:  https://doi.org/10.1021/jasms.4c00189
  5. Am J Physiol Cell Physiol. 2024 Aug 05.
    Regulation of cancer cell lipid metabolism and oxidative phosphorylation by microenvironmental acidosis.
    Michala G Rolver, Marc Severin, Stine F Pedersen.
      The expansion of cancer cell mass in solid tumors generates a harsh environment characterized by dynamically varying levels of acidosis, hypoxia and nutrient deprivation. Because acidosis inhibits glycolytic metabolism and hypoxia inhibits oxidative phosphorylation, cancer cells that survive and grow in these environments must rewire their metabolism and develop a high degree of metabolic plasticity to meet their energetic and biosynthetic demands. Cancer cells frequently upregulate pathways enabling the uptake and utilization of lipids and other nutrients derived from dead or recruited stromal cells, and in particular lipid uptake is strongly enhanced in acidic microenvironments. The resulting lipid accumulation and increased reliance on β-oxidation and mitochondrial metabolism increases susceptibility to oxidative stress, lipotoxicity and ferroptosis, in turn driving changes that may mitigate such risks. The spatially and temporally heterogeneous tumor microenvironment thus selects for invasive, metabolically flexible, and resilient cancer cells capable of exploiting their local conditions as well as of seeking out more favorable surroundings. This phenotype relies on the interplay between metabolism, acidosis and oncogenic mutations, driving metabolic signaling pathways such as peroxisome proliferator-activated receptors (PPARs). Understanding the particular vulnerabilities of such cells may uncover novel therapeutic liabilities of the most aggressive cancer cells.
    Keywords:  ferroptosis; lipid metabolism; mitochondria; oxidative phosphorylation; peroxisomes
    DOI:  https://doi.org/10.1152/ajpcell.00429.2024
  6. Front Med (Lausanne). 2024 ;11 1448152
    Editorial: Mass spectrometry-based proteomics in drug discovery and development.
    Martin Pejchinovski, Pedro Magalhães, Jochen Metzger.
      
    Keywords:  biomarker; clinical application; drug development; mass spectrometry; proteomics
    DOI:  https://doi.org/10.3389/fmed.2024.1448152
  7. Anal Chem. 2024 Aug 05.
    Quantitative Comparison of Deparaffinization, Rehydration, and Extraction Methods for FFPE Tissue Proteomics and Phosphoproteomics.
    Erin M Humphries, Clare Loudon, George E Craft, Peter G Hains, Phillip J Robinson.
      Formalin-fixed paraffin-embedded (FFPE) tissues are suitable for proteomic and phosphoproteomic biomarker studies by data-independent acquisition mass spectrometry. The choice of the sample preparation method influences the number, intensity, and reproducibility of identifications. By comparing four deparaffinization and rehydration methods, including heptane, histolene, SubX, and xylene, we found that heptane and methanol produced the lowest coefficients of variation (CVs). Using this, five extraction methods from the literature were modified and evaluated for their performance using kidney, leg muscle, lung, and testicular rat organs. All methods performed well, except for SP3 due to insufficient tissue lysis. Heat n' Beat was the fastest and most reproducible method with the highest digestion efficiency and lowest CVs. S-Trap produced the highest peptide yield, while TFE produced the best phosphopeptide enrichment efficiency. The quantitation of FFPE-derived peptides remains an ongoing challenge with bias in UV and fluorescence assays across methods, most notably in SPEED. Functional enrichment analysis demonstrated that each method favored extracting some gene ontology cellular components over others including chromosome, cytoplasmic, cytoskeleton, endoplasmic reticulum, membrane, mitochondrion, and nucleoplasm protein groups. The outcome is a set of recommendations for choosing the most appropriate method for different settings.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04479
  8. Med Oncol. 2024 Aug 08. 41(9): 221
    Emerging roles of the chromatin remodeler MORC2 in cancer metabolism.
    Bibhukalyan Mohapatra, Suresh B Pakala.
      Cancer is characterized by metabolic reprogramming in cancer cells, which is crucial for tumorigenesis. The highly deregulated chromatin remodeler MORC2 contributes to cell proliferation, invasion, migration, DNA repair, and chemoresistance. MORC2 also plays a key role in metabolic reprogramming, including lipogenesis, glucose, and glutamine metabolism. A recent study showed that MORC2-regulated glucose metabolism affects the expression of E-cadherin, a crucial protein in the epithelial-to-mesenchymal transition. This review discusses recent developments in MORC2 regulated cancer cell metabolism and its role in cancer progression.
    Keywords:  Glucose metabolism; Glutamine metabolism; Lipogenesis; MORC2
    DOI:  https://doi.org/10.1007/s12032-024-02464-9
  9. Methods Mol Biol. 2024 ;2841 67-73
    Proteomic Analysis of Secreted Vesicle Proteins from the Plant Cells.
    Haidi Yin, Jianying Wang, Zhong-Ping Yao.
      A working pipeline for proteomic analysis of secreted vesicle proteins from the plant cells has been developed using urea and mass spectrometry-compatible detergent RapiGest SF, where vesicles could be efficiently lysed and membrane-bound proteins could be efficiently dissolved and digested. The vesicle lysis and the protein digestion procedures are performed within one tube to minimize the protein loss. The protein digest is analyzed using LC-MS/MS after desalting with an SPE spin column.
    Keywords:  LC-MS/MS; Plant cells; Proteomic analysis; Vesicle proteins
    DOI:  https://doi.org/10.1007/978-1-0716-4059-3_5
  10. Metabolomics. 2024 Aug 03. 20(5): 92
    Characterising the urinary acylcarnitine and amino acid profiles of HIV/TB co-infection, using LC-MS metabolomics.
    Charles Pretorius, Laneke Luies.
      INTRODUCTION: The human immunodeficiency virus (HIV) and tuberculosis (TB) co-infection presents significant challenges due to the complex interplay between these diseases, leading to exacerbated metabolic disturbances. Understanding these metabolic profiles is crucial for improving diagnostic and therapeutic approaches.OBJECTIVE: This study aimed to characterise the urinary acylcarnitine and amino acid profiles, including 5-hydroxyindoleacetic acid (5-HIAA), in patients co-infected with HIV and TB using targeted liquid chromatography mass spectrometry (LC-MS) metabolomics.
    METHODS: Urine samples, categorised into HIV, TB, HIV/TB co-infected, and healthy controls, were analysed using HPLC-MS/MS. Statistical analyses included one-way ANOVA and a Kruskal-Wallis test to determine significant differences in the acylcarnitine and amino acid profiles between groups.
    RESULTS: The study revealed significant metabolic alterations, especially in TB and co-infected groups. Elevated levels of medium-chain acylcarnitines indicated increased fatty acid oxidation, commonly associated with cachexia in TB. Altered amino acid profiles suggested disruptions in protein and glucose metabolism, indicating a shift towards diabetes-like metabolic states. Notably, TB was identified as a primary driver of these changes, affecting protein turnover, and impacting energy metabolism in co-infected patients.
    CONCLUSION: The metabolic profiling of HIV/TB co-infection highlights the profound impact of TB on metabolic pathways, which may exacerbate the clinical complexities of co-infection. Understanding these metabolic disruptions can guide the development of targeted treatments and improve management strategies, ultimately enhancing the clinical outcomes for these patients. Further research is required to validate these findings and explore their implications in larger, diverse populations.
    Keywords:  5-HIAA; Acylcarnitines; Amino acids; HIV/TB co-infection; LC–MS; Metabolomics
    DOI:  https://doi.org/10.1007/s11306-024-02161-8
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