bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–02–19
forty papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh
  1. Profiling Serum Intact N-Glycopeptides Using Data-Independent Acquisition Mass Spectrometry.
  2. An Optimized Data-Independent Acquisition Strategy for Comprehensive Analysis of Human Plasma Proteome.
  3. IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets.
  4. Early Cancer Biomarker Discovery Using DIA-MS Proteomic Analysis of EVs from Peripheral Blood.
  5. Comprehensive Targeted Lipidomic Profiling for Research and Clinical Applications.
  6. High-Throughput and In-Depth Proteomic Profiling of 5 μL Plasma and Serum Using TMTpro 16-Plex.
  7. Data-Driven Optimization of DIA Mass-Spectrometry by DO-MS.
  8. Protocol for Plasma Extracellular Vesicle and Particle Isolation and Mass Spectrometry-Based Proteomic Identification.
  9. In-Depth Blood Proteome Profiling by Extensive Fractionation and Multiplexed Quantitative Mass Spectrometry.
  10. Utilizing tandem mass spectrometry for metabolic flux analysis.
  11. The Small-Protein Enrichment Assay (SPEA) for Analysis of Low Abundance Peptide Hormones in Plasma.
  12. Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins.
  13. Quantification of Proteins in Blood by Absorptive Microtiter Plate-Based Affinity Purification Coupled to Liquid Chromatography-Mass Spectrometry.
  14. Proteome Analysis of Whole Blood Collected by Volumetric Absorptive Microsampling.
  15. A systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of Hela carcinoma cell under 2D and 3D cell culture conditions.
  16. An Overview: The Diversified Role of Mitochondria in Cancer Metabolism.
  17. Benchmarking bioinformatics pipelines in data-independent acquisition mass spectrometry for immunopeptidomics.
  18. High-Performance Liquid Chromatography Coupled with Tandem Mass Spectrometry Method for the Identification and Quantification of Lipids in Liposomes.
  19. AccuCor2: isotope natural abundance correction for dual-isotope tracer experiments.
  20. Analysis of Extracellular Vesicle and Contaminant Markers in Blood Derivatives Using Multiple Reaction Monitoring.
  21. TMEM164 is an acyltransferase that forms ferroptotic C20:4 ether phospholipids.
  22. The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study.
  23. Glycomics-Assisted Glycoproteomics Enables Deep and Unbiased N-Glycoproteome Profiling of Complex Biological Specimens.
  24. High-Throughput Proteome Profiling of Plasma and Native Plasma Complexes Using Native Chromatography.
  25. Integrated landscape of cardiac metabolism in end-stage human nonischemic dilated cardiomyopathy.
  26. Defining the Sarcomeric Proteoform Landscape in Ischemic Cardiomyopathy by Top-Down Proteomics.
  27. Progress in Targeted Mass Spectrometry (Parallel Accumulation-Serial Fragmentation) and Its Application in Plasma/Serum Proteomics.
  28. Comprehensive mass spectrometry lipidomics of human biofluids and ocular tissues.
  29. Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics.
  30. Lipid droplets and polyunsaturated fatty acid trafficking: Balancing life and death.
  31. In-Depth Proteomic Analysis of Blood Circulating Small Extracellular Vesicles.
  32. Semi-Automated Lectin Magnetic Bead Array (LeMBA) for Translational Serum Glycoprotein Biomarker Discovery and Validation.
  33. Mass Spectrometry-Based High-Throughput Quantification of Bioproducts in Liquid Culture.
  34. Ensuring Fact-Based Metabolite Identification in Liquid Chromatography-Mass Spectrometry-Based Metabolomics.
  35. Generation of Red Blood Cell Nanovesicles as a Delivery Tool.
  36. Correction to: Quantification of Very-Long-Chain and Branched-Chain Fatty Acids in Plasma by Liquid Chromatography-Tandem Mass Spectrometry.
  37. Offline Peptide Fractionation and Parallel Reaction Monitoring MS for the Quantitation of Low-Abundance Plasma Proteins.
  38. Rapid and Quantitative Enrichment of Peptides from Plasma for Mass Spectrometric Analysis.
  39. The proteome of hand eczema assessed by tape stripping.
  40. Immunoaffinity Mass Spectrometry Diagnostic Tests for Multi-Biomarker Assays.
  1. Methods Mol Biol. 2023 ;2628 365-391
    Profiling Serum Intact N-Glycopeptides Using Data-Independent Acquisition Mass Spectrometry.
    Yi Yang, Liang Qiao.
      Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data-independent acquisition (DIA) mass spectrometry is an emerging technology with deep proteome coverage as well as accurate quantitative capability for large-scale proteomics studies and has also been applied to the field of glycoproteomics. In this protocol, we describe how to analyze data from a DIA experiment for profiling serum intact N-glycopeptides. We present a comprehensive data analysis workflow using GproDIA, including glycopeptide spectral library building, chromatographic feature extraction from the DIA data, and feature scoring with appropriate statistical control of error rates. We anticipate that this method could provide a powerful tool to explore the serum glycoproteome.
    Keywords:  Data-independent acquisition; Glycoproteomics; GproDIA; N-glycopeptide; Serum; Spectral library; Statistical control
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_24
  2. Methods Mol Biol. 2023 ;2628 93-107
    An Optimized Data-Independent Acquisition Strategy for Comprehensive Analysis of Human Plasma Proteome.
    Haoyun Fang, David W Greening.
      Cartography of the plasma proteome remains technically challenging, primarily due to the abundance and dynamic range of plasma proteins and their concentrations, exceeding ten orders of magnitude, including low-abundant tissue-derived proteins in the pg/mL range. Data-independent acquisition mass spectrometry (DIA-MS) has seen advances in unbiased mass spectrometry-based proteomic analysis of the plasma proteome. Here, we describe a comprehensive proteomic workflow of human plasma from clinically relevant sample (10 μL) that includes anti-protein immunodepletion and highly sensitive sample preparation workflow, with optimized scheduled isolation DIA-MS and deep learning analysis. This approach results in over 960 proteins quantified from a single-shot analysis of broad dynamic range, across 8 orders of magnitude (8.2 ng/L to 0.67 g/L). We further compare data-dependent acquisition (DDA) MS to highlight the advantage in protein quantification and inter-sample variation. These developments have provided streamlined identification of the human plasma proteome, including low-abundant tissue-enriched proteins, and applications toward understanding the plasma proteome.
    Keywords:  Data-independent acquisition; Library-free; Low abundant; Mass spectrometry; Plasma; Quantitative proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_7
  3. bioRxiv. 2023 Feb 10. pii: 2023.02.09.527886. [Epub ahead of print]
    IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets.
    Sadjad Fakouri Baygi, Yashwant Kumar, Dinesh Kumar Barupal.
      Poor chemical annotation of high-resolution mass spectrometry data limit applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics â€" Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of LC/HRMS peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus data dependent acquisition (DDA) MS2 libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography. The cross-applicability of these libraries across independent studies can improve overall annotation rates in metabolomics and exposomics projects, providing access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R CRAN repository ( https://cran.r-project.org/package=IDSL.CSA . Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA .
    DOI:  https://doi.org/10.1101/2023.02.09.527886
  4. Methods Mol Biol. 2023 ;2628 127-152
    Early Cancer Biomarker Discovery Using DIA-MS Proteomic Analysis of EVs from Peripheral Blood.
    Camila Espejo, Bruce Lyons, Gregory M Woods, Richard Wilson.
      One of the cornerstones of effective cancer treatment is early diagnosis. In this context, the identification of proteins that can serve as cancer biomarkers in bodily fluids ("liquid biopsies") has gained attention over the last decade. Plasma and serum fractions of blood are the most commonly investigated sources of potential cancer liquid biopsy biomarkers. However, the high complexity and dynamic range typical of these fluids hinders the sensitivity of protein detection by the most commonly used mass spectrometry technology (data-dependent acquisition mass spectrometry (DDA-MS)). Recently, data-independent acquisition mass spectrometry (DIA-MS) techniques have overcome the limitations of DDA-MS, increasing sensitivity and proteome coverage. In addition to DIA-MS, isolating extracellular vesicles (EVs) can help to increase the depth of serum/plasma proteome coverage by improving the identification of low-abundance proteins which are a potential treasure trove of diagnostic molecules. EVs, the nano-sized membrane-enclosed vesicles present in most bodily fluids, contain proteins which may serve as potential biomarkers for various cancers. Here, we describe a detailed protocol that combines DIA-MS and EV methodologies for discovering and validating early cancer biomarkers using blood serum. The pipeline includes size exclusion chromatography methods to isolate serum-derived extracellular vesicles and subsequent EV sample preparation for liquid chromatography and mass spectrometry analysis. Procedures for spectral library generation by DDA-MS incorporate methods for off-line peptide separation by microflow HPLC with automated fraction concatenation. Analysis of the samples by DIA-MS includes recommended protocols for data processing and statistical methods. This pipeline will provide a guide to discovering and validating EV-associated proteins that can serve as sensitive and specific biomarkers for early cancer detection and other diseases.
    Keywords:  Biomarker; Blood; Cancer early diagnostic; Data-independent acquisition; Extracellular vesicles; Proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_9
  5. Methods Mol Biol. 2023 ;2628 489-504
    Comprehensive Targeted Lipidomic Profiling for Research and Clinical Applications.
    Kevin Huynh, Thy Duong, Natalie A Mellett, Michelle Cinel, Corey Giles, Peter J Meikle.
      Mass spectrometry remains one of the gold standard approaches in examining the lipidome in biological samples. Recently, advancements in chromatography and mass spectrometry approaches have enabled broad coverage of the lipidome. However, many limitations still exist, and lipidomic analysis often requires a fine balance between coverage of the lipidome, structural detail, and sample throughput. For biomedical and clinical research using human samples, the diversity and natural variation between different individuals necessitate larger sample numbers to identify significant associations with clinical outcomes and account for potential confounding factors. Here we describe a targeted lipidomics workflow that enables reproducible profiling of thousands of plasma samples in a systematic manner, while maintaining good structural detail and high coverage of the lipidome.
    Keywords:  Cohort studies; Lipidomics; Mass spectrometry; Plasma; Targeted lipidomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_29
  6. Methods Mol Biol. 2023 ;2628 81-92
    High-Throughput and In-Depth Proteomic Profiling of 5 μL Plasma and Serum Using TMTpro 16-Plex.
    Yan Zhou, Rui Sun, Sainan Li, Xiao Liang, Liujia Qian, Liang Yue, Tiannan Guo.
      High-throughput and in-depth proteomic analysis of plasma and serum samples remains challenging due to the presence of multiple high-abundance proteins. Here, we provide a detailed protocol for proteomic analysis of serum and plasma specimens using a high-abundance protein depletion kit and TMTpro 16-plex reagents. This method requires only 5 μL serum or plasma, identifying and quantifying about 1000 proteins. A batch of 16 samples can be processed in 36 h. On average, each sample consumes about 1.5 h of mass spectrometer instrument time. Overall, our method can identify proteins across six orders of magnitude with high reproducibility (CV < 20%) using a shorter instrument time and less sample volume compared to existing methods. Thus, the method is suitable to be applied to large-scale proteomic studies.
    Keywords:  High-abundance protein depletion; Mass spectrometry; Peptide labeling; Plasma; Serum; TMTpro; Tandem mass tags
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_6
  7. bioRxiv. 2023 Feb 03. pii: 2023.02.02.526809. [Epub ahead of print]
    Data-Driven Optimization of DIA Mass-Spectrometry by DO-MS.
    Georg Wallmann, Andrew Leduc, Nikolai Slavov.
      Mass-spectrometry (MS) enables specific and accurate quantification of proteins with ever increasing throughput and sensitivity. Maximizing this potential of MS requires optimizing data acquisition parameters and performing efficient quality control for large datasets. To facilitate these objectives, we extended the DO-MS app ( do-ms.slavovlab.net ) to optimize and evaluate results from data independent acquisition (DIA) MS. The extension works with both label free and multiplexed DIA (plexDIA) and supports optimizations particularly relevant for single-cell proteomics. We demonstrate multiple use cases, including optimization of duty cycle methods, peptide separation, number of survey scans per duty cycle, and quality control of single-cell plexDIA data. DO-MS allows for interactive data display and generation of extensive reports, including publication quality figures, that can be easily shared. The source code is available at: github.com/SlavovLab/DO-MS .
    Abstract Figure:
    DOI:  https://doi.org/10.1101/2023.02.02.526809
  8. Methods Mol Biol. 2023 ;2628 291-300
    Protocol for Plasma Extracellular Vesicle and Particle Isolation and Mass Spectrometry-Based Proteomic Identification.
    Amirmohammad Nasiri Kenari, Linda Bojmar, Søren Heissel, Henrik Molina, David Lyden, Ayuko Hoshino.
      Plasma extracellular vesicles and particles (EVPs) are enriched in biomolecules that reflect individuals' physiological and pathological states. Several studies have demonstrated the potential of human plasma EVPs as a novel liquid biopsy. Here we describe a protocol for human plasma EVPs isolation and proteomic characterization. We isolated human plasma EVPs by the classical ultracentrifugation method and performed mass spectrometry-based proteomic profiling. Using this protocol, researchers can reveal the plasma EVPs proteome and explore the clinical application of plasma EVPs proteins for developing disease biomarkers.
    Keywords:  Extracellular vesicles and particles; Mass spectrometry; Plasma
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_19
  9. Methods Mol Biol. 2023 ;2628 109-125
    In-Depth Blood Proteome Profiling by Extensive Fractionation and Multiplexed Quantitative Mass Spectrometry.
    Xue Zhang, Huan Sun, Zhen Wang, Suiping Zhou, Yingxue Fu, High A Anthony, Junmin Peng.
      Blood in the circulatory system carries information of physiological and pathological status of the human body, so blood proteins are often used as biomarkers for diagnosis, prognosis, and therapy. Human blood proteome can be explored by the latest technologies in mass spectrometry (MS), creating an opportunity of discovering new disease biomarkers. The extreme dynamic range of protein concentrations in blood, however, poses a challenge to detect proteins of low abundance, namely, tissue leakage proteins. Here, we describe a strategy to directly analyze undepleted blood samples by extensive liquid chromatography (LC) fractionation and 18-plex tandem-mass-tag (TMT) mass spectrometry. The proteins in blood specimens (e.g., plasma or serum) are isolated by acetone precipitation and digested into peptides. The resulting peptides are TMT-labeled, separated by basic pH reverse-phase (RP) LC into at least 40 fractions, and analyzed by acidic pH RPLC and high-resolution MS/MS, leading to the quantification of ~3000 unique proteins. Further increase of basic pH RPLC fractions and adjustment of the fraction concatenation strategy can enhance the proteomic coverage (up to ~5000 proteins). Finally, the combination of multiple batches of TMT experiments allows the profiling of hundreds of blood samples. This TMT-MS-based method provides a powerful platform for deep proteome profiling of human blood samples.
    Keywords:  Biomarker; Blood; LC-MS/MS; Liquid chromatography; Mass spectrometry; Plasma; Proteomics; Serum; Tandem mass tag
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_8
  10. Lab Invest. 2021 Apr;pii: S0023-6837(22)00647-X. [Epub ahead of print]101(4): 423-429
    Utilizing tandem mass spectrometry for metabolic flux analysis.
    Yujue Wang, Sheng Hui, Fredric E Wondisford, Xiaoyang Su.
      Metabolic flux analysis (MFA) aims at revealing the metabolic reaction rates in a complex biochemical network. To do so, MFA uses the input of stable isotope labeling patterns of the intracellular metabolites. Elementary metabolic unit (EMU) is the computational framework to simulate the metabolite labeling patterns in a network, which was originally designed for simulating mass isotopomer distributions (MIDs) at the MS1 level. Recently, the EMU framework is expanded to simulate tandem mass spectrometry data. Tandem mass spectrometry has emerged as a new experimental approach to provide information on the positional isotope labeling of metabolites and therefore greatly improves the precision of MFA. In this review, we will discuss the new EMU framework that can accommodate the tandem mass isotopomer distributions (TMIDs) data. We will also analyze the improvement on the MFA precision by using TMID. Our analysis shows that combining the MIDs of the parent and daughter ions and the TMID for the MFA is more powerful than using TMID alone.
    DOI:  https://doi.org/10.1038/s41374-020-00488-z
  11. Methods Mol Biol. 2023 ;2628 265-276
    The Small-Protein Enrichment Assay (SPEA) for Analysis of Low Abundance Peptide Hormones in Plasma.
    Dylan James Harney, Mark Larance.
      The analysis of low abundance peptide hormones such as insulin in blood plasma is difficult with unbiased mass spectrometry-based proteomics, as they are overshadowed by very abundant proteins such as albumin and IgG. The small-protein enrichment assay (SPEA) can greatly increase detection and discovery of these factors through specific enrichment, which enables fast and efficient analysis of many small-protein factors using a single untargeted LC-MS/MS acquisition. SPEA uses an alcohol-acid-based dissociation and precipitation step, prior to denaturing SEC to remove the large highly abundant plasma proteins leaving only a small-protein fraction. This is followed by an efficient sample preparation and cleanup before either data-dependent acquisition (DDA), or data-independent acquisition (DIA), LC-MS/MS analysis. Combining these workflows increases discovery of proteins, posttranslational modifications (PTMs), and cleavage sites using DDA, while DIA provides consistent analysis useful for large cohort analysis.
    Keywords:  DDA; DIA; Hormones; Peptides; Plasma; Size exclusion chromatography
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_17
  12. Methods Mol Biol. 2023 ;2628 439-473
    Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins.
    Yassene Mohammed, David Goodlett, Christoph H Borchers.
      Preclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K2EDTA or sodium citrate as anticoagulants.
    Keywords:  Blood plasma proteins; Longitudinal analysis; Quantitative evaluation; Targeted proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_27
  13. Methods Mol Biol. 2023 ;2628 221-233
    Quantification of Proteins in Blood by Absorptive Microtiter Plate-Based Affinity Purification Coupled to Liquid Chromatography-Mass Spectrometry.
    Frank Klont, Oladapo Olaleye, Rainer Bischoff.
      Liquid chromatography (LC) coupled to mass spectrometry (MS) is increasingly used for quantification of proteins in blood. This development is prompted by ongoing improvements in detection sensitivities of LC-MS instruments and corresponding sample preparation workflows. The combination of immunoaffinity enrichment and targeted LC-MS detection is a notable analytical platform in this regard as it allows for the quantification of low abundance proteins in biological matrices like plasma and serum. Here, we describe such hybrid methods which are based on the enrichment of proteins with antibodies or affimers coupled to adsorptive microtiter plates, the proteolytic digestion of enriched proteins to release protein-specific peptides, and the detection of these peptides by microflow LC coupled to selected reaction monitoring MS.
    Keywords:  Affimer; Affinity purification; Antibody; Biomarker; Immunoaffinity enrichment; Immunocapture; Liquid chromatography; Mass spectrometry; Quantification
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_15
  14. Methods Mol Biol. 2023 ;2628 173-179
    Proteome Analysis of Whole Blood Collected by Volumetric Absorptive Microsampling.
    Mark P Molloy, Cameron Hill, Matthew J McKay, Ben R Herbert.
      Proteomic biomarker discovery and analysis from human biofluids using liquid chromatography-mass spectrometry (LC-MS) is an area of intense biomedical research. There is a growing interest to analyze microsampled patient blood specimens as this is potentially more patient-friendly enabling at-home and bedside self-collection of small blood volumes. However, there are limited studies applying LC-MS proteomic analysis of whole blood as it is dominated by red blood cell proteins such as hemoglobin which suppresses the detection of other less abundant proteins. Volumetric absorptive microsampling (VAMS) devices overcome this issue in part by providing a trapping matrix which allows depletion of abundant blood cell proteins through washing, prior to proteolysis and LC-MS. This approach allows the analysis of proteins from erythrocytes, leukocytes, and plasma and leads to deeper proteomic coverage compared to conventional plasma proteomics, increasing the prospects to discover novel biomarker proteins.
    Keywords:  Blood; Mass spectrometry; Microsampling; Plasma; Proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_11
  15. Biotechnol J. 2023 Feb 16. e2200444
    A systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of Hela carcinoma cell under 2D and 3D cell culture conditions.
    Tong Wang, Xueting Wang, Yingping Zhuang, Guan Wang.
      Metabolic reprogramming has been coined as a hallmark of cancer, accompanied by which the alterations in metabolite levels have profound effects on gene expression, cellular differentiation and the tumor environment. Yet a systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of tumor cells is currently lacking. To achieve this, this study is aimed at establishing an unbiased and leakage-free metabolome preparation protocol for Hela carcinoma cell. We evaluated 12 combinations of quenching and extraction methods from three quenchers (liquid nitrogen, -40°C 50% methanol, 0.5°C normal saline) and four extractants (-80°C 80% methanol, 0.5°C methanol: chloroform: water (1:1:1, v/v/v), 0.5°C 50% acetonitrile, 75°C 70% ethanol) for global metabolite profiling of adherent Hela carcinoma cells. Based on the isotope dilution mass spectrometry (IDMS) method, gas/liquid chromatography in tandem with mass spectrometry was used to quantitatively determine 43 metabolites including sugar phosphates, organic acids, amino acids, adenosine nucleotides and coenzymes involved in central carbon metabolism. The results showed that the total amount of the intracellular metabolites in cell extracts obtained using different sample preparation procedures with the IDMS method ranged from 21.51 to 295.33 nmol/million cells. Among 12 combinations, cells that washed twice with phosphate buffered saline (PBS), quenched with liquid nitrogen, and then extracted with 50% acetonitrile was found to be the most optimal method to acquire intracellular metabolites with high efficiency of metabolic arrest and minimal loss during sample preparation. In addition, the same conclusion was drawn as these 12 combinations were applied to obtain quantitative metabolome data from three-dimensional (3D) tumor spheroids. Furthermore, a case study was carried out to evaluate the effect of doxorubicin (DOX) on both adherent cells and 3D tumor spheroids using quantitative metabolite profiling. Pathway enrichment analysis using targeted metabolomics data showed that DOX exposure would significantly affect amino acid metabolism-related pathways, which might be related to the mitigation of redox stress. Strikingly, our data suggested that compared to 2D cells the increased intracellular glutamine level in 3D cells benefited replenishing the tricarboxylic acid (TCA) cycle when the glycolysis was limited after dosing with DOX. Taken together, this study provides a well-established quenching and extraction protocol for quantitative metabolome profiling of Hela carcinoma cell under 2D and 3D cell culture conditions. Based on this, quantitative time-resolved metabolite data can serve to the generation of hypotheses on metabolic reprogramming to reveal its important role in tumor development and treatment. This article is protected by copyright. All rights reserved.
    Keywords:  3D tumor spheroids; Hela; extraction; isotope dilution mass spectrometry; metabolomics; quenching; sample preparation
    DOI:  https://doi.org/10.1002/biot.202200444
  16. Int J Biol Sci. 2023 ;19(3): 897-915
    An Overview: The Diversified Role of Mitochondria in Cancer Metabolism.
    Yu'e Liu, Yihong Sun, Yadong Guo, Xiaoyun Shi, Xi Chen, Wenfeng Feng, Lei-Lei Wu, Jin Zhang, Shibo Yu, Yi Wang, Yufeng Shi.
      Mitochondria are intracellular organelles involved in energy production, cell metabolism and cell signaling. They are essential not only in the process of ATP synthesis, lipid metabolism and nucleic acid metabolism, but also in tumor development and metastasis. Mutations in mtDNA are commonly found in cancer cells to promote the rewiring of bioenergetics and biosynthesis, various metabolites especially oncometabolites in mitochondria regulate tumor metabolism and progression. And mutation of enzymes in the TCA cycle leads to the unusual accumulation of certain metabolites and oncometabolites. Mitochondria have been demonstrated as the target for cancer treatment. Cancer cells rely on two main energy resources: oxidative phosphorylation (OXPHOS) and glycolysis. By manipulating OXPHOS genes or adjusting the metabolites production in mitochondria, tumor growth can be restrained. For example, enhanced complex I activity increases NAD+/NADH to prevent metastasis and progression of cancers. In this review, we discussed mitochondrial function in cancer cell metabolism and specially explored the unique role of mitochondria in cancer stem cells and the tumor microenvironment. Targeting the OXPHOS pathway and mitochondria-related metabolism emerging as a potential therapeutic strategy for various cancers.
    Keywords:  cancer; mitochondria; tumor metabolism; tumor metastasis
    DOI:  https://doi.org/10.7150/ijbs.81609
  17. Mol Cell Proteomics. 2023 Feb 14. pii: S1535-9476(23)00024-5. [Epub ahead of print] 100515
    Benchmarking bioinformatics pipelines in data-independent acquisition mass spectrometry for immunopeptidomics.
    Mohammad Shahbazy, Sri H Ramarathinam, Patricia T Illing, Emma C Jappe, Pouya Faridi, Nathan P Croft, Anthony W Purcell.
      Immunopeptidomes are the peptide repertoires bound by the molecules encoded by the major histocompatibility complex (MHC) (human leukocyte antigen (HLA) in humans). These HLA-peptide complexes are presented on the cell surface for immune T-cell recognition. Immunopeptidomics denotes the utilization of tandem mass spectrometry (MS/MS) to identify and quantify peptides bound to HLA molecules. Data-independent acquisition (DIA) has emerged as a powerful strategy for quantitative proteomics and deep proteome-wide identification; however, DIA application to immunopeptidomics analyses has so far seen limited use. Further, of the many DIA data processing tools currently available, there is no consensus in the immunopeptidomics community on the most appropriate pipeline(s) for in-depth and accurate HLA peptide identification. Herein, we benchmarked four commonly used spectral library-based DIA pipelines developed for proteomics applications (Skyline, Spectronaut, DIA-NN, and PEAKS) for their ability to perform immunopeptidome quantification. We validated and assessed the capability of each tool to identify and quantify HLA-bound peptides. Generally, DIA-NN and PEAKS provided higher immunopeptidome coverage with more reproducible results. Skyline and Spectronaut conferred more accurate peptide identification with lower experimental false-positive rates. All tools demonstrated reasonable correlations in quantifying precursors of HLA-bound peptides. Our benchmarking study suggests a combined strategy of applying at least two complementary DIA software tools to achieve the greatest degree of confidence and in-depth coverage of immunopeptidome data.
    Keywords:  DIA; HLA-bound peptides; Immunopeptidomics; Mass spectrometry; Software tools benchmark; Spectral library
    DOI:  https://doi.org/10.1016/j.mcpro.2023.100515
  18. Methods Mol Biol. 2023 ;2622 227-239
    High-Performance Liquid Chromatography Coupled with Tandem Mass Spectrometry Method for the Identification and Quantification of Lipids in Liposomes.
    Yujie Shi, Xiaona Li.
      Liposomes are spherical, closed vesicles consisting of at least one lipid bilayer with a water chamber and are widely used to encapsulate bioactive molecules. Lipid membranes, composed of different types of lipids or lipophilic components, determine whether liposomes can achieve the desired purpose and determine the overall quality of liposomes. Thus, the quantification of lipid components and encapsulated molecules is essential to characterize and control the quality of liposomes. Moreover, multicomponent simultaneous determination is the preferred method for lipid component analysis in liposomes. Therefore, the present work describes an analytical methodology for the simultaneous determination of commonly used lipids in liposome formulations, using h igh-performance liquid chromatography coupled with a tandem mass spectrometry (MS) detector (HPLC-MS/MS). HPLC-MS/MS consists of a rapid and highly efficient chromatographic separation of the liposomal components with a C18 column and the subsequent detection of the ingredients through an MS detector, along with an accurate mass fragmentation pattern. The analytical process mainly includes lipid extraction, solution preparation, the optimization of chromatographic conditions, and method validation. We hope this analytical methodology is valuable and efficient and can be applied to the analysis of multiple types of lipids in liposomes, such as raw material quality analysis, formulation study, overall quality control, etc.
    Keywords:  HPLC-MS/MS; Lipid analysis; Liposome
    DOI:  https://doi.org/10.1007/978-1-0716-2954-3_20
  19. Lab Invest. 2021 10;pii: S0023-6837(22)00403-2. [Epub ahead of print]101(10): 1403-1410
    AccuCor2: isotope natural abundance correction for dual-isotope tracer experiments.
    Yujue Wang, Lance R Parsons, Xiaoyang Su.
      Stable isotope labeling techniques have been widely applied in the field of metabolomics and proteomics. Before the measured mass spectral data can be used for quantitative analysis, it must be accurately corrected for isotope natural abundance and tracer isotopic impurity. Despite the increasing popularity of dual-isotope tracing strategy such as 13C-15N or 13C-2H, there are no accurate tools for correcting isotope natural abundance for such experiments in a resolution-dependent manner. Here, we present AccuCor2 as an R-based tool to perform the correction for 13C-15N or 13C-2H labeling experiments. Our method uses a newly designed algorithm to construct the correction matrices that link labeling pattern and measured mass fractions, then use non-negative least-squares to solve the labeling patterns. Our results show that the dual-isotope experiments often require a mass resolution that is high enough to resolve 13C and 15N or 13C and 2H. Otherwise, the labeling pattern is not solvable. However, this mass resolution may not be sufficiently high to resolve other non-tracer elements such as oxygen or sulfur from the tracer elements. Therefore, we design AccuCor2 to perform the correction based on the actual mass resolution of the measurements. Using both simulated and experimental data, we show that AccuCor2 performs accurate and resolution-dependent correction for dual-isotope tracer data. The authors developed AccuCor2 as the first resolution-dependent method for accurate isotope natural abundance correction of experimental data generated from dual-isotope tracers. They show that such correction requires a minimum resolution to resolve tracer isotopologues. AccuCor2 showed improved accuracy more than previously developed tools, which assume infinite resolution of the instrument.
    DOI:  https://doi.org/10.1038/s41374-021-00631-4
  20. Methods Mol Biol. 2023 ;2628 301-320
    Analysis of Extracellular Vesicle and Contaminant Markers in Blood Derivatives Using Multiple Reaction Monitoring.
    Lauren A Newman, Zivile Useckaite, Ting Wu, Michael J Sorich, Andrew Rowland.
      Extracellular vesicles (EVs) are naturally occurring membranous particles that can be isolated from blood and other biofluids. EVs have drawn considerable attention for their potential as a minimally invasive biomarker source for a range of conditions, based on tissue-specific expression of proteins and other molecular information. To promote robust characterization of EV isolates, the International Society for Extracellular Vesicles (ISEV) has established consensus minimal requirements for the study of extracellular vesicles (MISEV) reporting guidelines. A core element of MISEV guidance is the recommendation for the analysis of protein markers in samples, including positive EV-associated markers and negative contaminant markers based on commonly co-isolated components of the sample matrix. Furthermore, there is growing interest in circulating EVs enriched for tissue-specific origin, and in this context, the degree of nontarget EV "contamination" (e.g., EVs derived from blood cells) may inform assessment of sample purity. The increasing application of EVs as a liquid biopsy for clinical applications requires a high-throughput multiplexed approach that enables analysis of protein markers from small volumes of starting material, ideally utilizing the same platform for measuring biomarkers of interest. To this end, targeted liquid chromatography mass spectrometry using multiple reaction monitoring (LC-MRM-MS) is a key platform for the quantitative assessment of target proteins within EV samples. Here we describe a protocol for the isolation of EVs from blood and parallel analytical methods targeting general EV markers and blood cell-derived EV markers, along with guidance of best practice for sample collection and processing.
    Keywords:  EV characterization; Extracellular vesicles; Liquid chromatography tandem mass spectrometry; Multiple reaction monitoring; Plasma; Protein markers; Serum
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_20
  21. Nat Chem Biol. 2023 Feb 13.
    TMEM164 is an acyltransferase that forms ferroptotic C20:4 ether phospholipids.
    Alex Reed, Timothy Ware, Haoxin Li, J Fernando Bazan, Benjamin F Cravatt.
      Ferroptosis is an iron-dependent form of cell death driven by oxidation of polyunsaturated fatty acid (PUFA) phospholipids. Large-scale genetic screens have uncovered a specialized role for PUFA ether phospholipids (ePLs) in promoting ferroptosis. Understanding of the enzymes involved in PUFA-ePL production, however, remains incomplete. Here we show, using a combination of pathway mining of genetic dependency maps, AlphaFold-guided structure predictions and targeted lipidomics, that the uncharacterized transmembrane protein TMEM164-the genetic ablation of which has been shown to protect cells from ferroptosis-is a cysteine active center enzyme that selectively transfers C20:4 acyl chains from phosphatidylcholine to lyso-ePLs to produce PUFA ePLs. Genetic deletion of TMEM164 across a set of ferroptosis-sensitive cancer cell lines caused selective reductions in C20:4 ePLs with minimal effects on C20:4 diacyl PLs, and this lipid profile produced a variable range of protection from ferroptosis, supportive of an important but contextualized role for C20:4 ePLs in this form of cell death.
    DOI:  https://doi.org/10.1038/s41589-022-01253-7
  22. bioRxiv. 2023 Feb 03. pii: 2023.02.01.526566. [Epub ahead of print]
    The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study.
    Tong Shen, Ciara Conway, Kaitlin R Rempfert, Jennifer E Kyle, Sean M Colby, David A Gaul, Hani Habra, Fanzhou Kong, Kent J Bloodsworth, Douglas Allen, Bradley S Evans, Xiuxia Du, Facundo M Fernandez, Thomas O Metz, Oliver Fiehn, Charles R Evans.
      Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.
    DOI:  https://doi.org/10.1101/2023.02.01.526566
  23. Methods Mol Biol. 2023 ;2628 235-263
    Glycomics-Assisted Glycoproteomics Enables Deep and Unbiased N-Glycoproteome Profiling of Complex Biological Specimens.
    The Huong Chau, Anastasia Chernykh, Julian Ugonotti, Benjamin L Parker, Rebeca Kawahara, Morten Thaysen-Andersen.
      Mass spectrometry-driven glycomics and glycoproteomics, the system-wide profiling of detached glycans and intact glycopeptides from biological samples, respectively, are powerful approaches to interrogate the heterogenous glycoproteome. Efforts to develop integrated workflows employing both glycomics and glycoproteomics have been invested since the concerted application of these complementary approaches enables a deeper exploration of the glycoproteome. This protocol paper outlines, step-by-step, an integrated -omics technology, the "glycomics-assisted glycoproteomics" method, that first establishes the N-glycan fine structures and their quantitative distribution pattern of protein extracts via porous graphitized carbon-LC-MS/MS. The N-glycome information is then used to augment and guide the challenging reversed-phase LC-MS/MS-based profiling of intact N-glycopeptides from the same protein samples. Experimental details and considerations relating to the sample preparation and the N-glycomics and N-glycoproteomics data collection, analysis, and integration are discussed. Benefits of the glycomics-assisted glycoproteomics method, which can be readily applied to both simple and complex biological specimens such as protein extracts from cells, tissues, and bodily fluids (e.g., serum), include quantitative information of the protein carriers and site(s) of glycosylation, site occupancy, and the site-specific glycan structures directly from biological samples. The glycomics-assisted glycoproteomics method therefore facilitates a comprehensive view of the complexity and dynamics of the heterogenous glycoproteome.
    Keywords:  Glycomics; Glycomics-assisted glycoproteomics; Glycopeptide; Glycoproteome; Glycoproteomics; Mass spectrometry; N-Glycan
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_16
  24. Methods Mol Biol. 2023 ;2628 53-79
    High-Throughput Proteome Profiling of Plasma and Native Plasma Complexes Using Native Chromatography.
    Aleksandr Gaun, Niclas Olsson, John C K Wang, Dan L Eaton, Fiona E McAllister.
      We describe a high-throughput method for co-fractionation mass spectrometry (CF-MS) profiling for native plasma protein profiling. CF-MS allows the profiling of endogenous protein complexes between samples. Proteins often interact with other proteins and form macromolecular complexes that are different in disease states as well as cell states and cell types. This protocol describes an example for the sample preparation of 954 individual size exclusion chromatography (SEC) fractions, derived from 18 plasma samples that were separated into 53 fractions. Eighteen plasma samples were chosen based on the TMTpro multiplexing, but this methodology can be adapted for fewer or larger numbers of samples as appropriate. Our automated sample preparation method allows for high-throughput native plasma profiling, and we provide detailed methods for both a label-free and an isobaric labeling approach, discuss the merits of each approach, and detail the advantages of combining these strategies for comprehensive native plasma proteome profiling.
    Keywords:  Isobaric labeling; Native separation; Plasma; Protein complexome; Protein-protein interactions; TMT/tandem mass tag
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_5
  25. Nat Cardiovasc Res. 2022 Sep;1(9): 817-829
    Integrated landscape of cardiac metabolism in end-stage human nonischemic dilated cardiomyopathy.
    Emily Flam, Cholsoon Jang, Danielle Murashige, Yifan Yang, Michael P Morley, Sunhee Jung, Daniel S Kantner, Hannah Pepper, Kenneth C Bedi, Jeff Brandimarto, Benjamin L Prosser, Thomas Cappola, Nathaniel W Snyder, Joshua D Rabinowitz, Kenneth B Margulies, Zolt Arany.
      Heart failure (HF) is a leading cause of mortality. Failing hearts undergo profound metabolic changes, but a comprehensive evaluation in humans is lacking. We integrate plasma and cardiac tissue metabolomics of 678 metabolites, genome-wide RNA-sequencing, and proteomic studies to examine metabolic status in 87 explanted human hearts from 39 patients with end-stage HF compared with 48 nonfailing donors. We confirm bioenergetic defects in human HF and reveal selective depletion of adenylate purines required for maintaining ATP levels. We observe substantial reductions in fatty acids and acylcarnitines in failing tissue, despite plasma elevations, suggesting defective import of fatty acids into cardiomyocytes. Glucose levels, in contrast, are elevated. Pyruvate dehydrogenase, which gates carbohydrate oxidation, is de-repressed, allowing increased lactate and pyruvate burning. Tricarboxylic acid cycle intermediates are significantly reduced. Finally, bioactive lipids are profoundly reprogrammed, with marked reductions in ceramides and elevations in lysoglycerophospholipids. These data unveil profound metabolic abnormalities in human failing hearts.
    DOI:  https://doi.org/10.1038/s44161-022-00117-6
  26. J Proteome Res. 2023 Feb 17.
    Defining the Sarcomeric Proteoform Landscape in Ischemic Cardiomyopathy by Top-Down Proteomics.
    Emily A Chapman, Timothy J Aballo, Jake A Melby, Tianhua Zhou, Scott J Price, Kalina J Rossler, Ienglam Lei, Paul C Tang, Ying Ge.
      Ischemic cardiomyopathy (ICM) is a prominent form of heart failure, but the molecular mechanisms underlying ICM remain relatively understudied due to marked phenotypic heterogeneity. Alterations in post-translational modifications (PTMs) and isoform switches in sarcomeric proteins play important roles in cardiac pathophysiology. Thus, it is essential to define sarcomeric proteoform landscape to better understand ICM. Herein, we have implemented a top-down liquid chromatography (LC)-mass spectrometry (MS)-based proteomics method for the identification and quantification of sarcomeric proteoforms in the myocardia of donors without heart diseases (n = 16) compared to end-stage ICM patients (n = 16). Importantly, quantification of post-translational modifications (PTMs) and expression reveal significant changes in various sarcomeric proteins extracted from ICM tissues. Changes include altered phosphorylation and expression of cardiac troponin I (cTnI) and enigma homologue 2 (ENH2) as well as an increase in muscle LIM protein (MLP) and calsarcin-1 (Cal-1) phosphorylation in ICM hearts. Our results imply that the contractile apparatus of the sarcomere is severely dysregulated during ICM. Thus, this is the first study to uncover significant molecular changes to multiple sarcomeric proteins in the LV myocardia of the end-stage ICM patients using liquid chromatography-mass spectrometry (LC-MS)-based top-down proteomics. Raw data are available via the PRIDE repository with identifier PXD038066.
    Keywords:  Z-disk proteins; human heart proteomics; ischemic cardiomyopathy; myofilament proteins; quantitative proteomics; sarcomere; top-down proteomics
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00729
  27. Methods Mol Biol. 2023 ;2628 339-352
    Progress in Targeted Mass Spectrometry (Parallel Accumulation-Serial Fragmentation) and Its Application in Plasma/Serum Proteomics.
    Anqi Hu, Jiayi Zhang, Huali Shen.
      Targeted mass spectrometry using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) has been commonly used for protein biomarker validation in plasma, serum, or other clinically relevant specimens due to its high specificity, selectivity, and multiplexing capability compared with immunoassays. As the emerging mode termed parallel accumulation-serial fragmentation (prmPASEF) significantly improved analyte throughput (100-1000), sensitivity (attomole level), and acquisition speed, it promises to broaden the application of targeted mass spectrometry to simultaneous biomarker discovery and validation with high accuracy. Here, we summarize the general approach of the MRM and PRM techniques used for serum/plasma proteomics and describe a detailed step-by-step procedure for the development of MRM/PRM assays for secreted proteins.
    Keywords:  Biomarker validation; Multiple reaction monitoring; Parallel reaction monitoring; Secreted proteins; Simultaneous discovery and validation; Targeted mass spectrometry
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_22
  28. J Lipid Res. 2023 Feb 09. pii: S0022-2275(23)00016-0. [Epub ahead of print] 100343
    Comprehensive mass spectrometry lipidomics of human biofluids and ocular tissues.
    Glenda Vasku, Caroline Peltier, Zhiguo He, Gilles Thuret, Philippe Gain, Pierre-Henry Gabrielle, Niyazi Acar, Olivier Berdeaux.
      Evaluating lipid profiles in human tissues and biofluids is critical in identifying lipid metabolites in dysregulated metabolic pathways. Due to various chemical characteristics, single-run lipid analysis has not yet been documented. Such approach is essential for analysing pathology-related lipid metabolites. Age-Related Macular Degeneration (AMD), the leading cause of vision loss in western countries, is emblematic of this limitation. Several studies have identified alterations in individual lipids, but the majority are based on targeted approaches. In this study, we analyzed and identified approximately 500 lipid species in human biofluids (plasma and erythrocytes) and ocular tissues (retina and retinal pigment epithelium) using the complementarity of hydrophilic interaction liquid chromatography (HILIC) and reversed-phase chromatography (RPC), coupled to high-resolution mass spectrometry (HRMS). For that, lipids were extracted from human eyeglobes and blood from 10 subjects and lipidomic analysis was carried out through analysis in HILIC and RPC, alternately. Furthermore, we illustrate the advantages and disadvantages of both techniques for lipid characterization. RPC showed greater sensitivity in hydrophobicity-based lipid separation, detecting diglycerides (DAG), triglycerides (TAG), cholesterol (Chol), and cholesterol esters (CEs), whereas no signal of these molecules was obtained in HILIC. However, due to coelution, RPC was less effective in separating polar lipids like phospholipids, which were separated effectively in HILIC in both ionization modes. The complementary nature of these analytical approaches was essential for the detection and identification of lipid classes/subclasses, which can then provide distinct insights into lipid metabolism, a determinant of the pathophysiology of several diseases involving lipids, notably AMD.
    Keywords:  RPE/Choroid; age-related macular degeneration; erythrocytes; eye/retina; glycolipids; lipidomic analysis; mass spectrometry; phospholipids; plasma
    DOI:  https://doi.org/10.1016/j.jlr.2023.100343
  29. Methods Mol Biol. 2023 ;2628 557-577
    Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics.
    Yassene Mohammed, David Goodlett, Christoph H Borchers.
      In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.
    Keywords:  Bioinformatics; Knowledgebases; Plasma proteins; Quantitative targeted proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_32
  30. Front Cell Dev Biol. 2023 ;11 1104725
    Lipid droplets and polyunsaturated fatty acid trafficking: Balancing life and death.
    Mauro Danielli, Leja Perne, Eva Jarc Jovičić, Toni Petan.
      Lipid droplets are fat storage organelles ubiquitously distributed across the eukaryotic kingdom. They have a central role in regulating lipid metabolism and undergo a dynamic turnover of biogenesis and breakdown to meet cellular requirements for fatty acids, including polyunsaturated fatty acids. Polyunsaturated fatty acids esterified in membrane phospholipids define membrane fluidity and can be released by the activity of phospholipases A2 to act as ligands for nuclear receptors or to be metabolized into a wide spectrum of lipid signaling mediators. Polyunsaturated fatty acids in membrane phospholipids are also highly susceptible to lipid peroxidation, which if left uncontrolled leads to ferroptotic cell death. On the one hand, lipid droplets act as antioxidant organelles that control polyunsaturated fatty acid storage in triglycerides in order to reduce membrane lipid peroxidation, preserve organelle function and prevent cell death, including ferroptosis. On the other hand, lipid droplet breakdown fine-tunes the delivery of polyunsaturated fatty acids into metabolic and signaling pathways, but unrestricted lipid droplet breakdown may also lead to the release of lethal levels of polyunsaturated fatty acids. Precise regulation of lipid droplet turnover is thus essential for polyunsaturated fatty acid distribution and cellular homeostasis. In this review, we focus on emerging aspects of lipid droplet-mediated regulation of polyunsaturated fatty acid trafficking, including the management of membrane lipid peroxidation, ferroptosis and lipid mediator signaling.
    Keywords:  fatty acid; ferroptosis; lipid droplet; lipid oxidation; lipolysis; membrane remodeling; phospholipase
    DOI:  https://doi.org/10.3389/fcell.2023.1104725
  31. Methods Mol Biol. 2023 ;2628 279-289
    In-Depth Proteomic Analysis of Blood Circulating Small Extracellular Vesicles.
    Veronica De Giorgis, Elettra Barberis, Marco Falasca, Marcello Manfredi.
      Circulating small extracellular vesicles (sEVs), also called exosomes, are key players in the investigation of cell-cell communication mechanisms and in the identification of new potential biomarkers. These particles can carry proteins, DNA, mRNA, miRNA, lipids and metabolites that are transported all over the human body, potentially reaching all the cells. In particular, proteins, which are well-known biological actors in cell signalling, will be discussed in this context. In this article, we present a mass spectrometry approach for the in-depth characterization of the sEVs proteome. The protocols include strategies for the isolation and purification of sEVs, for the extraction of proteins and the purification of sEVs proteins by the immunodepletion of the most abundant plasmatic proteins. Finally, bioinformatic analysis for the extraction of the most important biological features associated with the proteomic content of sEVs is reported.
    Keywords:  Bioinformatics; Mass spectrometry; Proteomics; Qualitative analysis; Small extracellular vesicles
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_18
  32. Methods Mol Biol. 2023 ;2628 395-411
    Semi-Automated Lectin Magnetic Bead Array (LeMBA) for Translational Serum Glycoprotein Biomarker Discovery and Validation.
    Mriga Dutt, Marisa N Duong, Scott Bringans, Renée S Richards, Richard Lipscombe, Michelle M Hill.
      Aberrant protein glycosylation is a characteristic of diverse diseases which has been explored as biomarkers. To support translational serum glycoprotein biomarker discovery and validation, we developed a semi-automated workflow using individual lectin-coupled magnetic beads to conduct lectin pulldowns in a high-throughput format. Lectins are naturally occurring glycoprotein binding proteins widely used in glycobiology. While lectin-affinity isolation has been coupled to mass spectrometry-based proteomics, the lectin magnetic bead array (LeMBA) platform allows technically robust screening and measurement of clinical cohorts. This chapter describes detailed lectin-magnetic bead coupling, serum denaturation, lectin magnetic bead pulldown, and on-bead trypsin digest. The resulting tryptic peptides are analyzed by untargeted or targeted liquid chromatography-mass spectrometry (LC-MS), for biomarker discovery, or qualification/validation, respectively. LeMBA-MS generates quantitative data for glycoforms based on lectin affinity of the glycoprotein coupled with MS measurement of one or more prototypic peptides and has successfully been used to discover and validate novel serum cancer glycoprotein biomarkers. This chapter includes detailed protocols for two different liquid handlers, along with recommendations on quality control measures for clinical biomarker studies.
    Keywords:  Glycoproteomics; Glycosylation; Lectin; Liquid handler; Serum biomarkers
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_25
  33. Anal Chem. 2023 Feb 15.
    Mass Spectrometry-Based High-Throughput Quantification of Bioproducts in Liquid Culture.
    Shuaizhen Zhou, Zia Fatma, Pu Xue, Shekhar Mishra, Mingfeng Cao, Huimin Zhao, Jonathan V Sweedler.
      To meet the ever-increasing need for high-throughput screening in metabolic engineering, information-rich, fast screening methods are needed. Mass spectrometry (MS) provides an efficient and general approach for metabolite screening and offers the capability of characterizing a broad range of analytes in a label-free manner, but often requires a range of sample clean-up and extraction steps. Liquid extraction surface analysis (LESA) coupled MS is an image-guided MS surface analysis approach that directly samples and introduces metabolites from a surface to MS. Here, we combined the advantages of LESA-MS and an acoustic liquid handler with stable isotope-labeled internal standards. This approach provides absolute quantitation of target chemicals from liquid culture-dried droplets and enables high-throughput quantitative screening for microbial metabolites. In this study, LESA-MS was successfully applied to quantify several different metabolites (itaconic acid, triacetic acid lactone, and palmitic acid) from different yeast strains in different mediums, demonstrating its versatility, accuracy, and efficiency across a range of microbial engineering applications.
    DOI:  https://doi.org/10.1021/acs.analchem.2c04845
  34. Anal Chem. 2023 Feb 15.
    Ensuring Fact-Based Metabolite Identification in Liquid Chromatography-Mass Spectrometry-Based Metabolomics.
    Georgios Theodoridis, Helen Gika, Daniel Raftery, Royston Goodacre, Robert S Plumb, Ian D Wilson.
      Metabolite identification represents a major bottleneck in contemporary metabolomics research and a step where critical errors may occur and pass unnoticed. This is especially the case for studies employing liquid chromatography-mass spectrometry technology, where there is increased concern on the validity of the proposed identities. In the present perspective article, we describe the issue and categorize the errors into two types: identities that show poor biological plausibility and identities that do not comply with chromatographic data and thus to physicochemical properties (usually hydrophobicity/hydrophilicity) of the proposed molecule. We discuss the problem, present characteristic examples, and propose measures to improve the situation.
    DOI:  https://doi.org/10.1021/acs.analchem.2c05192
  35. Methods Mol Biol. 2023 ;2628 321-336
    Generation of Red Blood Cell Nanovesicles as a Delivery Tool.
    Auriane Drack, Alin Rai, David W Greening.
      Extracellular vesicles (EVs) are natural membranous vesicles with immense potential as drug delivery tools. However, their large-scale production remains a huge technical challenge, is time consuming, and expensive. Thus, EV mimetics (nanovesicles) generated from easily sourced red blood cells (RBCs) have gained vested interest as an effective and scalable drug delivery system. Their surface proteins (e.g., CD47) inherited from parental RBCs also improve their biocompatibility and bioavailability. Here, we outline a step-by-step guide for large-scale production of RBC nanovesicles using one-step extrusion method coupled to rapid density-cushion centrifugation. We also outline protocol for their extensive biophysical characterization (size and morphology using single particle analysis and cryogenic electron microscopy), and in-depth mass spectrometry-based proteome characterization. Finally, we outline two strategies (active loading during extrusion vs. passive loading via diffusion) to incorporate pharmacological compound(s) into nanovesicles and detect their loading using spectrophotometry.
    Keywords:  Drug delivery; Erythrocyte-derived nanovesicles (edNVs); Mass spectrometry; Proteomics; Red blood cell
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_21
  36. Methods Mol Biol. 2022 ;2546 C1
    Correction to: Quantification of Very-Long-Chain and Branched-Chain Fatty Acids in Plasma by Liquid Chromatography-Tandem Mass Spectrometry.
    Irene De Biase, Marzia Pasquali.
      
    DOI:  https://doi.org/10.1007/978-1-0716-2565-1_49
  37. Methods Mol Biol. 2023 ;2628 353-364
    Offline Peptide Fractionation and Parallel Reaction Monitoring MS for the Quantitation of Low-Abundance Plasma Proteins.
    Claudia Gaither, Robert Popp, Vincent R Richard, René P Zahedi, Christoph H Borchers.
      Mass spectrometry (MS)-based protein quantitation is an attractive means for research and diagnostics due to its high specificity, precision, sensitivity, versatility, and the ability to develop multiplexed assays for the "absolute" quantitation of virtually any protein target. However, due to the large dynamic range of protein concentrations in blood, high abundance proteins in blood plasma hinder the detectability and quantification of lower-abundance proteins which are often relevant in the context of different diseases. Here we outline a streamlined method involving offline high-pH reversed-phase fractionation of human plasma samples followed by the quantitative analysis of specific fractions using nanoLC-parallel reaction monitoring (PRM) on a Q Exactive Plus mass spectrometer for peptide detection and quantitation with increased sensitivity. Because we use a set of synthetic peptide standards, we can more efficiently determine the precise retention times of the target peptides in the first-dimensional separation and specifically collect eluting fractions of interest for the subsequent targeted MS quantitation, making the analysis faster and easier. An eight-point standard curve was generated by serial dilution of a mixture of previously validated unlabeled ("light") synthetic peptides of interest at known concentrations. The corresponding heavy stable-isotope-labeled standard (SIS) analogues were used as normalizers to account for losses during sample processing and analysis. Using this method, we were able to improve the sensitivity of plasma protein quantitation by up to 50-fold compared to using nanoLC-PRM alone.
    Keywords:  2D LC-PRM-MS; High-pH fractionation; Mass spectrometry; Parallel reaction monitoring; Plasma proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_23
  38. Methods Mol Biol. 2023 ;2628 477-488
    Rapid and Quantitative Enrichment of Peptides from Plasma for Mass Spectrometric Analysis.
    Amy L George, Rachel E Foreman, Mariwan H Sayda, Frank Reimann, Fiona M Gribble, Richard G Kay.
      Mass spectrometric analysis of peptides enables the assignment of their exact mass and confirmation of all or a significant portion of the peptide's amino acid sequence. LC-MS/MS analysis has proven invaluable in peptidomics research and can identify new biomarkers and assign their circulatory concentrations to aid research into disease processes. However, due to the high background plasma protein content, which masks the presence of the naturally low abundance circulatory peptidome, extraction of peptides from plasma prior to mass spectrometric analysis is therefore crucial. Organic solvents efficiently precipitate these high molecular weight plasma proteins while leaving small molecular weight peptides in solution, providing a rapid and effective technique for separating peptides from the contaminating plasma proteins. A secondary cleanup step involving solid phase extraction is required to remove lipids and highly hydrophobic contaminants before LC-MS/MS analysis. The method described within this chapter is effective at enriching circulatory plasma peptides prior to LC-MS/MS analysis and has been used in multiple peptidomic studies to improve peptide detection and quantification. Peptides studied using this methodology include insulin, C-peptide, glucagon, PYY, GIP, and a number of other challenging gut peptide hormones. Quantitative analyses of peptides using the described method showed good correlation with existing immunoassays.
    Keywords:  Mass spectrometry; Organic solvent precipitation; Peptide quantitation; Plasma peptidomics; Solid phase extraction
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_28
  39. J Invest Dermatol. 2023 Feb 09. pii: S0022-202X(23)00071-4. [Epub ahead of print]
    The proteome of hand eczema assessed by tape stripping.
    Julie B K Sølberg, Anna S Quaade, Lylia Drici, Karolina Sulek, Nina H Ulrich, Marianne B Løvendorf, Jacob P Thyssen, Matthias Mann, Beatrice Dyring-Andersen, Jeanne D Johansen.
      Hand eczema (HE) is a prevalent skin disease. However, classification of HE into different subtypes remains challenging. Limited number of prior studies have employed invasive biopsy-based strategies; yet, studies of the HE proteome using non-invasive tape stripping methodology have not been reported. In this study, we wanted to assess whether global proteomic analysis of skin tape strip samples can be used for sub-classification of HE patients. Tape strips were collected from patients with HE and healthy skin. Liquid chromatography-mass spectrometry (LC/MS) proteomics was performed, and the global protein expression was analyzed. We identified 2,919 proteins in stratum corneum-derived skin cells from tape strip samples. Compared to healthy skin, the lesional samples from HE patients exhibited increased expression of immune-related markers and a decreased expression of structural barrier proteins. The difference between HE subtypes was restricted to the lesional skin areas, and included an increased expression of skin barrier-related proteins independently of the concurrent AD. In conclusion we found, that the non-invasive tape strip method used in combination with LC/MS proteomics can be used for analysis of skin protein expression in HE patients. Thus, the method shows potential for assessing the proteomic differences between subtypes of HE, and biomarker discovery.
    Keywords:  AD; Atopic dermatitis; DEP; DIA; Data-independent acquisition; Differentially expressed protein; EASI; Eczema Area and Severity Index; HE(+AD); HE(-AD); HECSI; HPLC; Hand eczema severity index; Hand eczema with atopic dermatitis; Hand eczema without atopic dermatitis; High-performance liquid chromatography; LC-MS; Liquid chromatography–mass spectrometry; MS; Mass spectrometry; Nano-scale liquid chromatographic; PCA; Principal component analysis; nLC
    DOI:  https://doi.org/10.1016/j.jid.2022.12.024
  40. Methods Mol Biol. 2023 ;2628 195-206
    Immunoaffinity Mass Spectrometry Diagnostic Tests for Multi-Biomarker Assays.
    Scott Bringans, Tammy Casey, Jun Ito, Tasha Lumbantobing, Ronan O'Neill, Richard Lipscombe.
      Immunoaffinity mass spectrometry as an approach for diagnostic biomarker assays combines the advantages of antibody selectivity with the multiplexing and analytical performance of mass spectrometry. A method has been developed to detect and quantify three protein biomarkers for a diabetic kidney disease prognostic assay, PromarkerD. The methodology reflects an immunoaffinity approach compatible with higher throughput and robust clinical application. After preparation and purification of antibody-bead conjugates for the three target proteins, an immunoaffinity capture step provides a solution for reduction, alkylation, and digestion on-bead. Targeted mass spectrometry provides a quantitative measure of each biomarker in a rapid 8 min run using a microflow LCMS workflow.
    Keywords:  Assay development; Biomarkers; Diabetic kidney disease; Immunoaffinity; Targeted mass spectrometry
    DOI:  https://doi.org/10.1007/978-1-0716-2978-9_13
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