bims-mascan 2025-09-07 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–09–07
28 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

QuickProt: A Bioinformatics and Visualization Tool for DIA and PRM Mass Spectrometry-Based Proteomics Datasets.
Liquid Chromatographic and Mass Spectrometric Methods for Quantitative Proteomic Analysis from Single-Cell and Nanogram-Level Samples.
Native and Endogenous SUMO Site Identification Using Mass Spectrometry (NESSI-MS).
Knowledge and data-driven two-layer networking for accurate metabolite annotation in untargeted metabolomics.
HLA Ligand Atlas DIA: extending the benign immunopeptidomics resource with increased sensitivity through data-independent acquisition mass spectrometry.
Open-Source System Suitability: Mass Spectrometry Query Language Lab (MassQLab).
Understanding Data Analysis Steps in Mass-Spectrometry-Based Proteomics Is Key to Transparent Reporting.
IsoPairFinder: A tool for biochemical pathway discovery using stable isotope tracing metabolomics.
CLAW-MRM: Comprehensive Lipidomics Automation Workflow for Multiple Reaction Monitoring Using Large Language Models.
Comparative evaluation of phenyl isothiocyanate derivatization and "dilute-and-shoot" methods for HPLC-MS/MS-based targeted metabolomics analysis of amine-containing metabolites in plasma samples.
Enrichment Workflow for Pyrophosphoproteome Analysis.
[A large-scale method for the enrichment and identification of N-glycopeptides in microscale plasma samples].
Benchmark for Quantitative Global and Redox Proteomics Analysis by Combining Protein-Aggregation Capture and Data Independent Acquisition.
MRMAssayDB: a comprehensive integrated resource for targeted proteomics assays.
A Comprehensive Mass Spectrometry-Based Proteomic Dataset of Human Spermatozoa.
SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.
In-depth structural characterization of sphingoid bases via derivatization and electron-activated dissociation tandem mass spectrometry.
Rapid CE-MS with Real-Time Eco-AI Resolves Proteomic Heterogeneity Among Single Human Neutrophils.
LC-MS/MS method for quantifying the HIV-1 broadly neutralizing antibody PGT 121.414.LS in human serum.
Capillary Electrophoresis Mass Spectrometry for Inositol (Pyro)phosphate Profiling.
Parallel reaction monitoring reveals N-terminal acetylation of plastid precursor proteins.
An automated Immunoaffinity liquid chromatography-tandem mass spectrometry assay for quantification of aldosterone in human plasma.
Quantitative decoding of coupled carbon and energy metabolism in Pseudomonas putida for lignin carbon utilization.
Exploring the amino acid-derived metabolomes of Arabidopsis and their associated natural variation using isotope labeling and mGWAS.
Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study.
Rewiring of cortical glucose metabolism fuels human brain cancer growth.
Mass spectrometry for clinical bioanalysis without chromatographic separation: bioequivalence for bupropion and its metabolites.
Proteome-wide analysis of the oxidation state of initiator methionines.

Proteomics. 2025 Sep 04. e70038

QuickProt: A Bioinformatics and Visualization Tool for DIA and PRM Mass Spectrometry-Based Proteomics Datasets.

Omar Arias-Gaguancela, Carmen Palii, Mehar Un Nissa, Marjorie Brand, Jeffrey Ranish.

  Mass spectrometry (MS)-based proteomics focuses on identifying and quantifying peptides and proteins in biological samples. Processing of MS-derived raw data, including deconvolution, alignment, and peptide-protein prediction, has been achieved through various software platforms. However, the downstream analysis, including quality control, visualizations, and interpretation of proteomics results, remains cumbersome due to the lack of integrated tools to facilitate the analyses. To address this challenge, we developed QuickProt, a series of Python-based Google Colab notebooks for analyzing data-independent acquisition (DIA) and parallel reaction monitoring (PRM) proteomics datasets. These pipelines are designed so that users with no coding expertise can utilize the tool. Furthermore, as open-source code, QuickProt notebooks can be customized and incorporated into existing workflows. As proof of concept, we applied QuickProt to analyze in-house DIA and stable isotope dilution (SID)-PRM MS proteomics datasets from a time-course study of human erythropoiesis. The analysis resulted in annotated tables and publication-ready figures revealing a dynamic rearrangement of the proteome during erythroid differentiation, with the abundance of proteins linked to gene regulation, metabolic, and chromatin remodeling pathways increasing early in erythropoiesis. Altogether, these tools aim to automate and streamline DIA and PRM-MS proteomics data analysis, making it more efficient and less time-consuming.

Keywords:  QuickProt; data mining and visualization; data‐independent acquisition; erythropoiesis; liquid chromatography‐tandem mass spectrometry; mass spectrometry; parallel reaction monitoring; proteomics; stable isotope dilution

DOI:  https://doi.org/10.1002/pmic.70038
Anal Chem. 2025 Sep 02. 97(34): 18415-18422

Liquid Chromatographic and Mass Spectrometric Methods for Quantitative Proteomic Analysis from Single-Cell and Nanogram-Level Samples.

Yuefan Wang, Jongmin Woo, Zhenyu Sun, Diego Assis, Zachary Kirsch, Matthew Willetts, Matthew Albano, Hongyi Liu, Kenneth J Pienta, Sarah R Amend, Hui Zhang.

Liquid chromatography (LC) and mass spectrometry (MS) are two critical components in proteomics. Advances in methods for both LC and MS have significantly enhanced protein identification and quantifications of limited amounts of proteins, particularly at the picogram-to-nanogram level of proteins. In this study, we explored various LC conditions and MS platforms to optimize protein identification and quantification using data-independent acquisition (DIA). Our investigation focused on evaluating the sensitivity for protein identification, reproducibility of quantification, and robustness across multiple models, specifically focused on analyzing proteins at pico- to nanogram levels, with an emphasis on single-cell proteomics. We further applied our approach for the proteomic analysis of HeLa single cells. Overall, we identified and quantified over 6300 proteins at the single-cell level amount of peptides with a coefficient of variation (CV) of less than 20%, and detected up to 5000 proteins from isolated single HeLa cell samples. Finally, we analyzed docetaxel-treated and nontreated PC3 cells to reveal proteome changes at the single-cell level. This study provides a comprehensive technical evaluation for LC-MS methods in protein identification and quantification for analytical applications involving single-cell proteomics from the picogram to nanogram level of proteins.

DOI: https://doi.org/10.1021/acs.analchem.5c02808
Methods Mol Biol. 2025 ;2957 31-56

Native and Endogenous SUMO Site Identification Using Mass Spectrometry (NESSI-MS).

Caroline L E Lennartsson, Ivo A Hendriks.

  Small Ubiquitin-like Modifiers (SUMOs) are an important class of post-translational modification (PTM), modifying target proteins and thereby regulating virtually all nuclear processes. Various proteomics methods exist for profiling SUMO target proteins or SUMOylated lysine residues in a systemic manner, typically based on purification of SUMO followed by mass spectrometry (MS), with most approaches relying on ectopically expressed or mutant SUMO. However, to properly understand the role of SUMO in the context of health and disease, it is necessary to study native and endogenous SUMOylation, rather than relying on genetically engineered systems. Here, we present Native and Endogenous SUMOylation Site Identification using Mass Spectrometry (NESSI-MS), an MS-based proteomics strategy, which entails antibody-based purification of peptides bearing endogenous SUMO2/3 and allows exact mapping of the SUMOylated lysine residues using mass spectrometry.

Keywords:  Data-dependent acquisition; Endogenous; Label-free quantification; Mass spectrometry; PTM; Proteomics; SUMO; SUMOylated lysine mapping; SUMOylation

DOI:  https://doi.org/10.1007/978-1-0716-4710-3_3
Nat Commun. 2025 Aug 30. 16(1): 8118

Knowledge and data-driven two-layer networking for accurate metabolite annotation in untargeted metabolomics.

Haosong Zhang, Xinhao Zeng, Yandong Yin, Zheng-Jiang Zhu.

Metabolite annotation in untargeted metabolomics remains challenging due to the vast structural diversity of metabolites. Network-based approaches have emerged as powerful strategies, particularly for annotating metabolites lacking chemical standards. Here, we develop a two-layer interactive networking topology that integrates data-driven and knowledge-driven networks to enhance metabolite annotation. A comprehensive metabolic reaction network is curated using graph neural network-based prediction of reaction relationships, enhancing both coverage and network connectivity. Experimental data are pre-mapped onto this network via sequential MS1 matching, reaction relationship mapping, and MS2 similarity constraints. The generated networking topology enables interactive annotation propagation with over 10-fold improved computational efficiency. In common biological samples, it annotates over 1600 seed metabolites with chemical standards and >12,000 putatively annotated metabolites through network-based propagation. Notably, two previously uncharacterized endogenous metabolites absent from human metabolome databases have been discovered. Overall, this strategy significantly improves the coverage, accuracy, and efficiency of metabolite annotation and is freely available as MetDNA3.

DOI: https://doi.org/10.1038/s41467-025-63536-6
J Immunother Cancer. 2025 Aug 31. pii: e012083. [Epub ahead of print]13(8):

HLA Ligand Atlas DIA: extending the benign immunopeptidomics resource with increased sensitivity through data-independent acquisition mass spectrometry.

Leon Bichmann, Ana Marcu, Daniel Johannes Kowalewski, Lena Katharina Freudenmann, Linus Backert, Lena Mühlenbruch, Maren Lübke, Philipp Wagner, Tobias Engler, Sabine Matovina, Mathias Hauri-Hohl, Roland Martin, Holger Moch, Luca Regli, Michael Weller, Markus W Löffler, Juliane S Walz, Oliver Kohlbacher, Hannes Röst, Hans-Georg Rammensee, Marian C Neidert.

  The human leukocyte antigen (HLA)-presented peptide repertoire, termed immunopeptidome, plays a crucial role for T-cell mediated immune reactions. Previously, the human immunopeptidome of non-malignant tissues has been mapped in a large-scale study, the HLA Ligand Atlas, via high-resolution data-dependent acquisition (DDA) mass spectrometry. This publicly available and user-friendly web interface (https://hla-ligand-atlas.org) is frequently used as a benign tissue reference in antigen discovery, especially for immunotherapy of cancer. Here, we extend the HLA Ligand Atlas resource with paired data-independent acquisition (DIA) runs for all tissue-subject combinations. This novel dataset comprises 946 DIA HLA class I and II immunopeptidomic runs from 242 non-malignant human samples across 18 subjects and 29 distinct tissues. Together with the published DDA runs, this extends the range and depth of analyses performed on the HLA Ligand Atlas dataset. In a concise analysis, we showcase advantages of DIA over DDA concerning spectral sampling and sensitivity. These findings are attributed to the increased dynamic range in DIA, enabling the identification of peptide transitions with low signal intensities. Moreover, we demonstrate the superior sensitivity by applying an HLA-A*02:01 allotype-specific spectral library search to identify and quantify HLA-presented peptides. We encourage reanalysis of the provided DDA and DIA data in combination as a reference for future research concerning human immunology.

Keywords:  Autoimmune; Human leukocyte antigen - HLA; Immunotherapy; Infection; Major histocompatibility complex - MHC

DOI:  https://doi.org/10.1136/jitc-2025-012083
Rapid Commun Mass Spectrom. 2025 Dec 15. 39(23): e10132

Open-Source System Suitability: Mass Spectrometry Query Language Lab (MassQLab).

Heather L Winter, Dylan Johnson, Alan K Jarmusch.

   RATIONALE: Reproducible analytical instrumentation system performance is critical for mass spectrometry, particularly metabolomics, aptly named system suitability testing. We identified a need based on literature reports that stated only 2% of papers performed system suitability testing.
METHODS: We report MassQLab, built upon open-source, vendor-agnostic software called the mass spectrometry query language (MassQL). MassQL, implemented in MassQLab, provides freedom for researchers to choose their analyte/s, mass spectrometry system (including liquid chromatography-mass spectrometry), and metrics of performance.
RESULTS: In this report, we describe the use of MassQLab, demonstrate the construction of the required MassQL query, common metrics of performance (i.e., extracted ion chromatograms), uncommon metrics (i.e., MS/MS product ion spectra), and discuss insights gained about performance-including issues requiring correction prior to sample analysis.
CONCLUSIONS: MassQLab is a flexible solution for system suitability testing for mass spectrometry-based analytical measurements. Deficits in analytical performance, while unavoidable and rare, were noted prior to data collection and corrected. The open-source and adaptable nature of MassQLab will empower researchers and lead to improved implementation of system suitability testing.

Keywords:  computational mass spectrometry; data science; lipidomics; metabolomics; quality assessment; quality control

DOI:  https://doi.org/10.1002/rcm.10132
J Proteome Res. 2025 Sep 03.

Understanding Data Analysis Steps in Mass-Spectrometry-Based Proteomics Is Key to Transparent Reporting.

Nadezhda T Doncheva, Veit Schwämmle, Marie Locard-Paulet.

  Mass spectrometry (MS)-based proteomics data analysis is composed of many stages from quality control, data cleaning, and normalization to statistical and functional analysis, without forgetting multiple visualization steps. All of these need to be reported next to published results to make them fully understandable and reusable for the community. Although this seems straightforward, exhaustively reporting all aspects of an analysis workflow can be tedious and error prone. This letter reports good practices when describing data analysis of MS-based proteomics data and discusses why and how the community should put efforts into more transparently reporting data analysis workflows.

Keywords:  data analysis; mass-spectrometry; proteomics; reporting; reproducibility; statistics; transparency

DOI:  https://doi.org/10.1021/acs.jproteome.5c00287
bioRxiv. 2025 Aug 22. pii: 2025.08.18.670916. [Epub ahead of print]

IsoPairFinder: A tool for biochemical pathway discovery using stable isotope tracing metabolomics.

Zhiwei Zhou, Yuanyuan Liu, Mingxun Wang, Dylan Dodd.

The functional annotation of microbial genes lags far behind genome sequencing, leaving critical gaps in our knowledge of metabolic pathways. While integrating genetic manipulation with stable isotope tracing (SIT) metabolomics holds promise for pathway discovery, existing tools lack specialized capabilities for gene perturbation experiments. To address this need, we developed IsoPairFinder, a computational tool that identifies pathway intermediates by analyzing paired unlabeled (12C) and isotope-labeled (13C) metabolomics data from gene-edited microbes. By prioritizing substrate-specific feature pairs, IsoPairFinder efficiently prioritizes biologically relevant intermediates. Implemented as an open-source R package and integrated into the GNPS2 ecosystem, IsoPairFinder provides an accessible platform for the research community to accelerate novel pathway discovery and validation.

DOI: https://doi.org/10.1101/2025.08.18.670916
Anal Chem. 2025 Sep 02.

CLAW-MRM: Comprehensive Lipidomics Automation Workflow for Multiple Reaction Monitoring Using Large Language Models.

Connor Beveridge, Sanjay Iyer, Caitlin E Randolph, Matthew Muhoberac, Palak Manchanda, Katherine A Walker, Shane Tichy, Gaurav Chopra.

Lipidomic profiling generates vast datasets, making manual annotation and trend interpretation complex and time-intensive. The structural and chemical diversity of the lipidome further complicates the analysis. While existing tools support targeted lipid identification, they often lack automated workflows and seamless integration with statistical and bioinformatics tools. Here, we introduce the comprehensive lipidomics automated workflow for multiple reaction monitoring (CLAW-MRM), a platform designed to automate lipid annotation, statistical analysis, and data parsing using custom multiple reaction monitoring (MRM) precursor product ion transitions. CLAW-MRM employs trimmed mean of m-value (TMM) normalization to account for lipid load differences, enabling robust cross-sample comparisons. To evaluate CLAW-MRM's performance, we analyzed lipid profiles in liver tissues of Alzheimer's disease (AD) mice and age-matched wild-type controls under conditions of constant and variable tissue mass, assessing the impact of normalization strategies on TMM-normalized lipidomic outcomes. Additionally, we isolated and profiled lipid droplets from individual brain regions of 18- to 24-month-old AD male mice and controls, leveraging nearly 1,500 MRM transitions across 11 lipid classes. Enhancing biological relevance, CLAW-MRM integrates LIGER (lipidome gene enrichment reactions), linking lipid expression with gene activation and suppression patterns. Through CLAW-MRM-based LIGER, we identified metabolic pathways enriched in differentially expressed lipids, offering insights into altered lipid metabolism in AD. To improve usability, CLAW-MRM incorporates a natural language interface powered by large language models, enabling artificial intelligence (AI)-driven user interaction for statistical and bioinformatics analyses. By automating lipid structural identification and integrating AI-assisted bioinformatics, CLAW-MRM provides an end-to-end workflow from data acquisition to interpretation, streamlining high-throughput lipidomics.

DOI: https://doi.org/10.1021/acs.analchem.4c05039
Anal Bioanal Chem. 2025 Aug 30.

Comparative evaluation of phenyl isothiocyanate derivatization and "dilute-and-shoot" methods for HPLC-MS/MS-based targeted metabolomics analysis of amine-containing metabolites in plasma samples.

Kangkang Xu, Markus Aigensberger, Franz Berthiller, Heidi E Schwartz-Zimmermann.

  Metabolomics, the study of small molecule metabolites in biological systems, is essential for disease diagnosis and biomarker discovery. A key consideration in developing targeted metabolomics methods using HPLC-MS/MS for human or animal plasma is whether to employ derivatization of amino acids, amino acid-related compounds, and biogenic amines. Derivatization with phenyl isothiocyanate (PITC) enhances ionization and LC-separation, but complicates sample preparation and introduces potential errors. This study focuses on (1) the validation of a PITC derivatization method employing reversed-phase (RP) HPLC-MS/MS analysis and (2) a comparison of two analytical approaches for targeted metabolomics analysis of animal and human plasma: the PITC derivatization-based RP-LC-MS/MS method and a "dilute-and-shoot" approach using hydrophilic interaction chromatography (HILIC)-MS/MS and RP-LC-MS/MS analysis. The derivatization method was validated for porcine plasma, assessing limits of detection, lower limits of quantification (LLOQs), linearity, repeatability, recovery, and trueness. Derivatization reduced LLOQs for derivatized compounds in pure solvent solutions but, due to higher dilution factors, resulted in similar LLOQs for derivatized compounds and higher LLOQs for non-derivatized compounds in plasma compared to the "dilute-and-shoot" method. Derivatization improved chromatographic separation of isomers and reduced carryover but introduced challenges such as matrix effects, coelution with impurities, and calibration issues. The "dilute-and-shoot" method performed better for non-derivatized compounds and was less error-prone. Both methods were applied to plasma from various species, demonstrating comparable concentrations for most metabolites. The results also emphasize the importance of using different approaches for cross-validation. Above all, this study highlights the strengths and limitations of both the derivatization method and the "dilute-and-shoot" approach, providing guidance for their application in targeted metabolomics.

Keywords:  Amino acids; Biogenic amines; Derivatization; High-performance liquid chromatography; Mass spectrometry; Method comparison

DOI:  https://doi.org/10.1007/s00216-025-06079-5
Methods Mol Biol. 2025 ;2972 135-152

Enrichment Workflow for Pyrophosphoproteome Analysis.

Sarah Lampe, Dorothea Fiedler.

  The proteome-wide detection of different posttranslational modifications (PTMs) still poses a notable analytical challenge. Nevertheless, the identification of protein pyrophosphorylation sites using mass spectrometry (MS) was reported recently. The implementation of an enrichment workflow proved to be key to characterize this substoichiometric modification within complex cell lysate samples. Analysis of the enriched samples using data-dependent neutral-loss triggered electron transfer/higher-energy collision dissociation (DDNL EThcD) MS enabled the detection of endogenous protein pyrophosphorylation. In this chapter, the bottom-up pyrophosphoproteomics analysis, including an enrichment workflow, to identify protein pyrophosphorylation sites is described.

Keywords:  Bottom-up proteomics; EThcD; Enrichment; Fractionation; Lambda protein phosphatase; Mass spectrometry sample preparation; Posttranslational modification; Pyrophosphorylation; SIMAC

DOI:  https://doi.org/10.1007/978-1-0716-4799-8_11
Se Pu. 2025 Sep;43(9): 996-1004

[A large-scale method for the enrichment and identification of N-glycopeptides in microscale plasma samples].

Xin-Yi Yang, Wei-Jie Qin.

  Blood， which forms part of the systemic circulatory system， contains proteins from various tissues and organs. Hence， blood samples are ideal vehicles for studying diseases and physiological states. Plasma is an important component of blood and is essential for clinical proteomics research. Plasma contains rich physiological and pathological information； consequently， it is an ideal medium for discovering disease-related biomarkers. Protein N-glycosylation is a key post-translational modification route. This route is widely involved in biological processes such as intercellular communication， immune regulation， and signal transduction. Changes resulting from aberrant N-glycosylation are closely associated with various pathological conditions， including autoimmune and neurodegenerative diseases and tumors. Hence， N-glycosylation proteomics is highly valuable during biomarker and drug-target development. However， efficiently enriching N-glycopeptides in biological samples before detection by mass spectrometry （MS） is difficult. This is because the highly abundant unmodified peptides result in signal suppression. Consequently， achieving deep N-glycoproteomic coverage is a key challenge， particularly for trace plasma samples， for which in-depth studies are currently lacking. In this study， we developed a strategy for comprehensively profiling trace N-glycopeptides in plasma. This includes an efficient enrichment method in combination with highly sensitive MS. The developed approach integrates glycopeptide enrichment using advanced hydrophilic interaction liquid chromatography （HILIC） with state-of-the-art MS platforms. This significantly enhances detection depth and sensitivity during N-glycosylation analysis using minimal plasma volumes. Selectivity and efficiency during N-glycopeptide enrichment were maximized by systematically optimizing key HILIC-packed stationary-phase parameters. These parameters include chemical composition， pore size， and surface modification. Additionally， the elution gradient was fine-tuned to improve glycopeptide recovery. This optimization process delivered high N-glycopeptide specificity， even in complex plasma matrices. To overcome the limitations of single-platform MS， we implemented a complementary dual-platform strategy. This strategy combines the high-speed， high-resolution capabilities of the Tims TOF Pro 2 instrument with the ultra-high mass accuracy and resolution of the Orbitrap Lumos spectrometer. The former instrument facilitates the rapid and sensitive identification of glycopeptides， particularly for low-abundance species. It exploits the trapped ion mobility spectrometry （TIMS） and parallel accumulated sequential fragmentation （PASEF） technology. The Orbitrap Lumos provides exceptional mass accuracy and high-resolution MS/MS spectra that enable confident glycopeptide structural characterization. This synergistic approach significantly expands the N-glycopeptide identification depth and ensures comprehensive glycosylation-site and glycan-composition coverage. The developed optimized workflow successfully identified 2 962 intact N-glycopeptides using only 20 μg of plasma peptides （equivalent to 0.5 μL of whole plasma）. This set a new benchmark for sensitivity in the micro-volume plasma glycoproteome field. This achievement addresses a critical gap， where conventional methods typically require much larger sample volumes. This limits their applicability to clinical and precision medicine settings where sample availability is restricted. The developed platform provides a robust and reliable analytical framework for plasma N-glycoproteomics with significant implications for precision medicine. This method facilitates large-scale clinical studies by enabling highly sensitive glycopeptide profiling from very small plasma volumes. This included the longitudinal monitoring of disease progression and therapeutic responses. Furthermore， it offers a powerful tool for discovering novel N-glycosylation-based biomarkers for use in early disease diagnosis， prognosis， and personalized treatment strategies. In summary， this study advances the technical capabilities of plasma N-glycoproteomics. Additionally， it facilitates the broader use of plasma N-glycoproteomics in biomedical research and clinical diagnostics.

Keywords:  N-glycopeptide; enrichment; hydrophilic interaction chromatography （HILIC）; mass spectrometry （MS）; plasma; proteome

DOI:  https://doi.org/10.3724/SP.J.1123.2025.04004
Anal Chem. 2025 Sep 03.

Benchmark for Quantitative Global and Redox Proteomics Analysis by Combining Protein-Aggregation Capture and Data Independent Acquisition.

Ana Martinez-Val, Samuel Lozano-Juárez, Jorge Lumbreras Burgueño, Irene Rodríguez, Marinela Couselo-Seijas, Ana Simón-Chica, Carlos Galán-Arriola, Rodrigo Fernández-Jiménez, Estefanía Núñez, Inmaculada Jorge, David Filgueiras-Rama, Borja Ibáñez, Jesús Vázquez.

Oxidative damage plays a critical role in various diseases including cardiovascular and neurological disorders. Thiol redox reactions, acting as oxidative stress sensors, influence protein structure and function. Redox proteomics, based on the differential alkylation of cysteine sites followed by mass spectrometry, enables the comprehensive analysis of thiol redox status in cells and tissues. However, these approaches require extensive sample manipulation and are not compatible with data-independent acquisition techniques. Here, we introduce PACREDOX, an innovative strategy based on protein aggregation capture (PAC), and demonstrate its compatibility with library-free DIA. Compared with traditional methods such as FASILOX, PACREDOX reduces preparation time and costs while maintaining thiol and proteome coverage. To enable library-free DIA, we corrected in silico spectral libraries in DIA-NN using experimental retention time data from methylthiolated-Cys peptides. PACREDOX with DIA was benchmarked against FASILOX in a myocardial infarction model, yielding the same biological insights, while enhancing peptide and protein coverage. Our results underscore the potential and efficiency of this methodology for studying oxidative damage. Overall, PACREDOX offers an automatable, high-throughput, and cost-effective strategy for redox proteomics.

DOI: https://doi.org/10.1021/acs.analchem.5c03294
Expert Rev Proteomics. 2025 Sep 03.

MRMAssayDB: a comprehensive integrated resource for targeted proteomics assays.

Yassene Mohammed, Pallab Bhowmick, Christoph H Borchers.

   INTRODUCTION: Targeted quantitative proteomics is vital for accurate protein measurement in biological samples. Techniques like Multiple Reaction Monitoring (MRM or SRM) and Parallel Reaction Monitoring (PRM), often used with isotopically-labeled internal standards, provide absolute quantification and represent the current gold standard. However, developing and validating assays for individual proteins remains labor-intensive. Several repositories, such as CPTAC, SRMAtlas, PanoramaWeb, and PeptideTracker host targeted assay data with varying levels of detail. MRMAssayDB is an integrated platform that hosts and annotates the curated targeted proteomics assays from these resources.
AREAS COVERED: First launched in 2018 and updated in 2021, the latest release of MRMAssayDB includes over 1.1 million assays for 939,000 peptides, enabling quantification of 61,000 proteins from 146 organisms. The database also maps proteins to 19,000 Gene Ontology terms and 4,000 biological pathways. A newly integrated visualization module projects peptide assays onto Alphafold-predicted 3D protein structures, allowing users to examine peptide locations, post-translational modifications, and disease mutations, while also supporting mapping to structures in the Protein Data Bank (PDB).
EXPERT OPINION: MRMAssayDB significantly improves access to validated proteotypic peptides and transition data, facilitating efficient assay selection and quantitative panel building for researchers in targeted proteomics. Availability: http://mrmassaydb2.proteomicscentre.com.

Keywords:  Absolute quantitation; FDA assays; Knowledgebase; Multiplexing; assay design; data repository; proteotypic peptide suitability; targeted assays

DOI:  https://doi.org/10.1080/14789450.2025.2557023
Sci Data. 2025 Aug 28. 12(1): 1509

A Comprehensive Mass Spectrometry-Based Proteomic Dataset of Human Spermatozoa.

Ran Kong, Kaixian Yan, Defeng Liu, Wenying Wu.

Male infertility is fundamentally rooted in developmental defects of germ cells and associated molecular dysregulation, yet the underlying mechanisms remain poorly understood. Data-independent acquisition (DIA) has emerged as a powerful tool in discovery proteomics, enabling the identification of disease biomarkers, therapeutic targets, and molecular pathways with high precision and reproducibility. To analyse the aberrant regulatory events in human sperm proteins associated with male reproductive disorders in a high-throughput, reproducible, and reliable manner, we employed the Orbitrap Astral mass spectrometer, which independently operates Orbitrap Full Scan and Astral MS/MS to generate high-resolution full-scan spectra and high-quality secondary maps. Leveraging the principles of DIA technology, we constructed the most comprehensive human sperm proteomic expression profile reported to date, encompassing 9,309 proteins, 198,153 unique precursors, 154,062 modified peptides, and 145,355 peptides. Moreover, this data is derived from two types of sperm samples to facilitate the exploration of disease-specific proteins. Our data serve as a valuable resource for analysing spermatozoa protein content, facilitating deeper insights into male reproduction.

DOI: https://doi.org/10.1038/s41597-025-05824-w
Proteomics. 2025 Sep 04. e70037

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Lakmini Senavirathna, Cheng Ma, Van-An Duong, Hong-Yuan Tsai, Ru Chen, Sheng Pan.

  Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Keywords:  cancer cell heterogeneity; epithelial‐mesenchymal transition (EMT); mass spectrometry; proteomics; single‐cell proteomics; spectral library‐based multiplex segmented selected ion monitoring (SLB‐msSIM)

DOI:  https://doi.org/10.1002/pmic.70037
Analyst. 2025 Sep 02.

In-depth structural characterization of sphingoid bases via derivatization and electron-activated dissociation tandem mass spectrometry.

Xiaohui Zhang, Xue Zhao.

Sphingoid bases (SPHs) serve as the core structural backbone of all sphingolipid classes, with their diversity arising from intrachain modifications such as carbon-carbon double bonds (CC), hydroxyl groups, and methyl branching. Traditional tandem mass spectrometry (MS/MS) relying on collision-induced dissociation (CID) often fails to yield diagnostic fragmentation patterns for precise localization of these modifications, underscoring the need for advanced dissociation techniques. In this work, we present a novel analytical strategy combining carnitine derivatization of sphingoid amines with electron-activated dissociation (EAD) in MS2 to enable in-depth structural characterization. This technique uniquely suppresses intrachain fragmentation while generating diagnostic ions at modification sites, resulting in simplified mass spectra that facilitate unambiguous identification of subtle structural variations. This method was integrated into a reversed-phase liquid chromatography-mass spectrometry workflow and further applied for in-depth profiling of total SPHs in Astragalus and Escherichia coli (E. coli). Our analysis uncovered two pairs of regioisomeric SPHs: CC positional isomers of SPH d18:1 in Astragalus and hydroxylation positional isomers of SPH t18:1 in E. coli, demonstrating the method's utility in resolving structurally complex sphingolipid bases.

DOI: https://doi.org/10.1039/d5an00637f
bioRxiv. 2025 Aug 20. pii: 2025.08.14.670204. [Epub ahead of print]

Rapid CE-MS with Real-Time Eco-AI Resolves Proteomic Heterogeneity Among Single Human Neutrophils.

Bowen Shen, Fei Zhou, Isabelle Luz, Laura G Rodriguez, Steven J Prior, Wagner Fontes, Peter Nemes.

Single-cell proteomics by mass spectrometry is advancing rapidly, yet throughput and sensitivity remain limiting-particularly for small, protein-poor cell types such as neutrophils. As the most abundant circulating leukocytes in humans, neutrophils are central to immune defense and inflammation, but their proteomes comprehensive single-cell level characterization has only concurrently been reported 1 and remains limited. Here, we introduce a rapid capillary electrophoresis-mass spectrometry (CE-MS) platform, which integrates electrophoresis-correlative real-time data acquisition with sub-7-minute separations and artificial intelligence (AI)-based data processing software to achieve deep, high-throughput profiling. Using single-cell-equivalent HeLa digests, the Rapid Eco-AI platform identified ∼1,350 proteins from 300 pg and ∼835 proteins from 75 pg of input- approaching the complexity of a mammalian cell proteome. Applied to freshly isolated human neutrophils, the workflow identified 151 proteins from ∼2 pg of material, ∼3% of the total cell proteome. Analysis of 13 individual cells revealed marked functional heterogeneity across pathways of degranulation, neutrophil extracellular trap (NET) formation, chemotaxis, and innate immunity, with hierarchical clustering resolving at least four distinct proteomic subtypes. These results establish Rapid Eco-AI as a sensitive, scalable, and broadly applicable CE-MS approach for immune-cell phenotyping at single-cell and subcellular resolution, facilitating new research opportunities in systems immunology and clinical proteomics.

DOI: https://doi.org/10.1101/2025.08.14.670204
J Chromatogr B Analyt Technol Biomed Life Sci. 2025 Aug 27. pii: S1570-0232(25)00328-9. [Epub ahead of print]1266 124774

LC-MS/MS method for quantifying the HIV-1 broadly neutralizing antibody PGT 121.414.LS in human serum.

Connor E Gould, Qing Ma, Raymond Cha, Kevin J Zemaitis, Robin DiFrancesco, Gene D Morse, Troy D Wood.

  Quantitation of human immunodeficiency virus-1 (HIV-1) broadly neutralizing antibodies (bNAbs) in human serum is required for clinical trials investigating the pharmacokinetics, pharmacodynamics, and drug interactions of these treatments. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is gaining interest as an alternative to ligand binding for therapeutic antibody quantitation in serum. We report the validation of a method using nonspecific purification and targeted LC-MS/MS to quantify PGT 121.414.LS (a bNAb in development for HIV-1 prevention and treatment) in human serum. High-resolution spectra of tryptic peptides derived from the variable region were obtained on an Orbitrap for surrogate peptide selection, followed by multiple reaction monitoring using triple quadrupole mass spectrometry. Surrogate peptides were evaluated for linearity and reproducibility across the therapeutic concentration range using immunopurification or ammonium sulfate precipitation. Using ammonium sulfate precipitation, linear calibration curves were validated over 10-500 μg/mL (LLOQ at 10 μg/mL) using stable isotope labeled peptide internal standards. Method accuracy and reproducibility were evaluated using quality control samples (QCs) at four concentrations in the linear range. The average concentrations of all QCs fell within ICH M10 acceptance criteria. Matrix effects were investigated at the low and high QC concentrations across six lots of human serum. Dilutional integrity, stability, and effects of hemolysis were also assessed. The method exhibits minimal carryover and negligible crosstalk. The assay provides accurate quantification of PGT 121.414.LS in serum over the range of concentrations anticipated in specimens from treated persons living with HIV (PLWH) after initial dosing and prior to subsequent dosing of PGT 121.414.LS.

Keywords:  Antibodies; HIV-1; Immunopurification; LC-MS/MS; Proteomics; Quantitation; Surrogate peptide

DOI:  https://doi.org/10.1016/j.jchromb.2025.124774
Methods Mol Biol. 2025 ;2972 95-113

Capillary Electrophoresis Mass Spectrometry for Inositol (Pyro)phosphate Profiling.

Guizhen Liu, Henning J Jessen.

  The turnover of myo-inositol phosphates (InsPs) and myo-inositol pyrophosphates (PP-InsPs) is a dynamic process that plays an important role in many physiological processes by transmitting signals within cellular pathways and networks. Profiling the InsPs and PP-InsPs isomers and quantifying their change in abundance is a significant challenge for several reasons. First, InsPs and PP-InsPs constitute a diverse metabolite pool, characterized by the complexity as a result of the numerous possible isobaric isomers. Second, these species are usually of low abundance in biological samples. Third, they lack a chromophore, making UV or fluorescence detection unfeasible. Fourth, their high charge density and the instability of P-anhydride bonds make isolation and separation requirements particularly demanding. This chapter presents a capillary electrophoresis coupled to mass spectrometry (CE-MS) method as a powerful tool. It enables the separation of multiply charged InsPs and PP-InsPs with high resolution for profiling regioisomers with high sensitivity from biological samples.

Keywords:  Capillary electrophoresis; Inositol phosphate; Inositol pyrophosphate; Mass spectrometry; Phospho-metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4799-8_8
Methods Enzymol. 2025 ;pii: S0076-6879(25)00214-9. [Epub ahead of print]718 107-128

Parallel reaction monitoring reveals N-terminal acetylation of plastid precursor proteins.

Pia Möllenbeck, Tim R Demmig, Dominique S Stolle, Sacha Baginsky.

  The N-terminus of a protein has an important regulatory impact on its in vivo stability and half-life. Proteins destined to chloroplasts and mitochondria are synthesized as precursor proteins in the cytosol with an N-terminal peptide sequence that ensures their correct targeting. During their cytosolic passage, precursor proteins are exposed to the cytosolic protein degradation machinery, hence, their N-termini must comply with regulatory processes for proteolytic degradation in the cytosol. We present here a method to determine the identity and modification state of plastid precursor protein N-termini in the cytosol by combining protoplast protein import assays with targeted mass spectrometry by means of parallel reaction monitoring (PRM). This method requires a hypothesis on potential modifications at the protein N-terminus such as methionine removal or N-terminal acetylation, that is decoded into an inclusion mass list to guide mass spectrometric data acquisition to specific peptides. This type of approach largely eliminates the stochastic nature of MS acquisition allowing different modifications to be tested as alternative hypotheses. Using Skyline, a quantitative assessment of different N-terminal modifications can be performed. We have used this method to determine the modification state of a model precursor protein RNP29 in two different genotypic backgrounds, but our workflow is easily expandable to different precursors.

Keywords:  N-terminal acetylation; PRM; Plastid precursor proteins; Protoplast import assay; Skyline data analysis

DOI:  https://doi.org/10.1016/bs.mie.2025.06.006
J Chromatogr B Analyt Technol Biomed Life Sci. 2025 Aug 23. pii: S1570-0232(25)00327-7. [Epub ahead of print]1266 124773

An automated Immunoaffinity liquid chromatography-tandem mass spectrometry assay for quantification of aldosterone in human plasma.

Liang-Xing Li, Jian-You Xue, Wan-Ying Lin, Xiao-Feng Yin, Ting-Ting Luo, Zhi-Liang Cai, Chao-Chao Wu, Qiang Gao, Xin Li, Ru-Yi Zhang.

  The diagnosis of primary aldosteronism (PA) relies on the accurate determination of aldosterone. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has long been considered the gold standard for aldosterone quantification but it is hindered by labor-intensive sample preparation. To address this, we developed an immunoaffinity-mass spectrometry (iMS) assay on a fully automated device combining anti-aldosterone antibodies with stable isotope-labeled internal standards (IS). This method completes sample preparation within 15 min for at least six parallel samples in parallel with minimal manual intervention. The key performance metrics include a lower limit of quantitation (LOQ) of 50 pg/mL, recovery rates between 105.1 and 113.9 %, and linearity in the range of 50-2000 pg/mL (R2 = 0.9993). Inter-assay coefficient of variation (CV) ranged from 2.33 % to 3.91 %. In addition, plasma aldosterone concentrations by iMS and immunoassay had a high correlation coefficient (R = 0.947). Overall, this automated high-throughput platform delivers clinical-grade sensitivity, precision, and scalability, making it suitable for routine testing and adaptable for other clinical analytes.

Keywords:  Aldosterone; Automated immunoaffinity; LC-MS/MS; Primary aldosteronism

DOI:  https://doi.org/10.1016/j.jchromb.2025.124773
Commun Biol. 2025 Aug 29. 8(1): 1310

Quantitative decoding of coupled carbon and energy metabolism in Pseudomonas putida for lignin carbon utilization.

Nanqing Zhou, Rebecca A Wilkes, Xinyu Chen, Kelly P Teitel, James A Belgrave, Gregg T Beckham, Allison Z Werner, Yanbao Yu, Ludmilla Aristilde.

Soil Pseudomonas species, which thrive on lignin derivatives, are widely explored for biotechnology applications in lignin valorization. However, how the native metabolism coordinates phenolic carbon processing with required cofactor generation remains poorly understood. Here, we achieve quantitative understanding of this metabolic balance through a detailed multi-omics investigation of Pseudomonas putida KT2440 grown on four common phenolic acid substrates: ferulate, p-coumarate, vanillate, and 4-hydroxybenzoate. Relative to succinate, proteomics reveals > 140-fold increase in transport and catabolic proteins for aromatics, but metabolomics identifies bottlenecks in initial catabolism to maintain favorable cellular energy charge, which is compromised in mutants with resolved bottlenecks. Up to 30-fold increase in pyruvate carboxylase and glyoxylate shunt proteins implies a metabolic remodeling confirmed by kinetic 13C-metabolomics. Quantitative analysis by 13C-fluxomics demonstrates coupling of this remodeling with cofactor production. Specifically, anaplerotic carbon recycling through pyruvate carboxylase promotes tricarboxylic acid cycle fluxes to generate 50-60% NADPH yield and 60-80% NADH yield, resulting in up to 6-fold greater ATP surplus than with succinate metabolism; the glyoxylate shunt sustains cataplerotic flux through malic enzyme for the remaining NADPH yield. This quantitative blueprint affords cofactor imbalance predictions in proposed engineering of key metabolic nodes in lignin valorization pathways.

DOI: https://doi.org/10.1038/s42003-025-08723-3
Plant Physiol. 2025 Sep 04. pii: kiaf381. [Epub ahead of print]

Exploring the amino acid-derived metabolomes of Arabidopsis and their associated natural variation using isotope labeling and mGWAS.

Zhi-Wei Luo, Jeffrey P Simpson, Abigail Sipes, Caden Tuinstra, Caroline Marks, Grace Charpentier, Bruce R Cooper, Fabiola Muro-Villanueva, William Delacruz, Brian Dilkes, Clint Chapple.

  In this study, we used stable isotope labeling coupled with reversed-phase HPLC-MS to annotate the origin of metabolite features in Arabidopsis (Arabidopsis thaliana) (Columbia-0) seedling rosettes and stems. Using this strategy, a total of 1,240 metabolite features were shown to be derived from 15 amino acids, and these represented 10% to 30% of the total ion counts detected by untargeted LC-MS. The amino acid-derived metabolomes (AADMs) of rosettes and stems exhibited differing patterns of accumulation. Precursor-of-origin annotations (POA) revealed that some metabolites were generated solely from individual amino acids, whereas others were derived from multiple sources. Amino acid feeding altered the abundance of their corresponding AADMs as well as the levels of features derived from other amino acids. These data suggest that the accumulation of amino acid-derived features (AADFs) is restricted by availability of their amino acid precursors and that perturbation of amino acid metabolic networks can lead to long distance changes in end-product accumulation. The alignment of annotated AADFs with features from a previous metabolic genome-wide association study (mGWAS) led to the identification of 87,820 and 61,618 metabolite feature-SNP associations (P < 10-4) in leaves and stems, respectively. Genes associated with AADF accumulation, including METHYLTHIOALKYLMALATE SYNTHASE 1 (MAM1) and D-AMINO ACID RACEMASE 1 (DAAR1), were retrieved from this analysis, demonstrating that the integration of isotope labeling and mGWAS can contribute to the identification of genes involved in plant metabolite accumulation.

Keywords:  Amino acid metabolism; Genome-Wide Association Study; untargeted metabolomics

DOI:  https://doi.org/10.1093/plphys/kiaf381
J Am Soc Mass Spectrom. 2025 Aug 28.

Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study.

Jesi Lee, Dinesh Barupal.

  A significant number of compounds in exposome databases and chemical inventories lack mass spectral data due to the nonavailability of reference standards. To address this limitation, computational chemistry methods can be utilized to extend mass spectral libraries for a set of chemicals. In this pilot study, we employed quantum-chemistry-based software QCxMS to generate collision-induced dissociation mass spectra for 121 compounds from the Blood Exposome Database. We developed a scalable computational framework that integrates QCxMS and additional tools, utilizing a grid-based parameter selection strategy and defined coverage criteria. Our approach systematically explored protomeric isomers and applied predefined parameter combination sets sequentially based on molecular structures. This workflow produced high-quality in silico spectra for 81 compounds that achieved entropy similarity scores ≥700 and at least two matching fragment ions against the NIST23 library, yielding 71% spectral coverage. These results highlight the importance of optimizing simulation parameters and accounting for protomeric diversity to enhance the spectral quality and computational efficiency. This workflow provides a practical strategy to add mass spectral data for most compounds in the Blood Exposome Database at reasonable computational cost, supporting the spectral library expansion for improved compound annotation in exposomics.

Keywords:  Blood Exposome; Mass Spectra Simulation; Metabolomics; QCCIDMS; QCxMS; Semiempirical methods

DOI:  https://doi.org/10.1021/jasms.5c00179
Nature. 2025 Sep 03.

Rewiring of cortical glucose metabolism fuels human brain cancer growth.

Andrew J Scott, Anjali Mittal, Baharan Meghdadi, Alexandra O'Brien, Justine Bailleul, Palavalasa Sravya, Abhinav Achreja, Weihua Zhou, Jie Xu, Angelica Lin, Kari Wilder-Romans, Ningning Liang, Ayesha U Kothari, Navyateja Korimerla, Donna M Edwards, Zhe Wu, Jiane Feng, Sophia Su, Li Zhang, Peter Sajjakulnukit, Anthony C Andren, Junyoung O Park, Johanna Ten Hoeve, Vijay Tarnal, Kimberly A Redic, Nathan R Qi, Joshua L Fischer, Ethan Yang, Michael S Regan, Sylwia A Stopka, Gerard Baquer, Krithika Suresh, Jann N Sarkaria, Theodore S Lawrence, Sriram Venneti, Nathalie Y R Agar, Erina Vlashi, Costas A Lyssiotis, Wajd N Al-Holou, Deepak Nagrath, Daniel R Wahl.

The brain avidly consumes glucose to fuel neurophysiology1. Cancers of the brain, such as glioblastoma, relinquish physiological integrity and gain the ability to proliferate and invade healthy tissue2. How brain cancers rewire glucose use to drive aggressive growth remains unclear. Here we infused 13C-labelled glucose into patients and mice with brain cancer, coupled with quantitative metabolic flux analysis, to map the fates of glucose-derived carbon in tumour versus cortex. Through direct and comprehensive measurements of carbon and nitrogen labelling in both cortex and glioma tissues, we identify profound metabolic transformations. In the human cortex, glucose carbons fuel essential physiological processes, including tricarboxylic acid cycle oxidation and neurotransmitter synthesis. Conversely, gliomas downregulate these processes and scavenge alternative carbon sources such as amino acids from the environment, repurposing glucose-derived carbons to generate molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary amino acid modulation selectively alters glioblastoma metabolism, slows tumour growth and augments the efficacy of standard-of-care treatments. These findings illuminate how aggressive brain tumours exploit glucose to suppress normal physiological activity in favour of malignant expansion and offer potential therapeutic strategies to enhance treatment outcomes.

DOI: https://doi.org/10.1038/s41586-025-09460-7
Bioanalysis. 2025 Sep 05. 1-11

Mass spectrometry for clinical bioanalysis without chromatographic separation: bioequivalence for bupropion and its metabolites.

Jinhui Zhang, Patrick J Faustino.

   BACKGROUND: High-throughput solid-phase extraction coupled with tandem mass spectrometry (HT-SPE-MS/MS) is an automated sample delivery system to mass spectrometry that operates without chromatographic separation. The typical analysis time per sample using this platform is 10-30 s. While the HT-SPE-MS/MS system has demonstrated efficacy for in vitro assays, its application to the analysis of biological samples from in vivo bioavailability and bioequivalence studies presents challenges due to the complexity of the sample matrix. Three critical issues - matrix effect, specificity, and carryover - have not been thoroughly evaluated in complex biological matrices such as plasma.
RESEARCH DESIGN AND METHODS: This study assessed the feasibility of utilizing HT-SPE-MS/MS for the analysis of three metabolically related compounds (bupropion, hydroxybupropion, and threobupropion) in human plasma samples from a clinical bioequivalence study. Critical bioanalytical parameters, including matrix effect, specificity, accuracy, precision, and carryover, were systematically investigated.
RESULTS: These methods were subsequently applied to a bioequivalence study of bupropion. The HT-SPE-MS/MS approach achieved comparable accuracy, precision, linearity, and sensitivity to conventional ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) methods, while offering 20- to 30-fold higher analysis speeds.
CONCLUSION: The results of this study indicate that the HT-SPE-MS/MS system shows potential for high-throughput in vivo bioanalysis, particularly in bioavailability and bioequivalence studies.

Keywords:  Mass spectrometry; SPE-MS/MS; bioequivalence; bupropion; matrix effect

DOI:  https://doi.org/10.1080/17576180.2025.2557187
Methods Enzymol. 2025 ;pii: S0076-6879(25)00229-0. [Epub ahead of print]718 241-256

Proteome-wide analysis of the oxidation state of initiator methionines.

Ruiyue Tan, Margaret Hoare, Shane Bryan, Sina Ghaemmaghami.

  In bacteria, protein translation is initiated with formylated methionine residues. A subset of initiator methionines are retained, whereas others are removed from nascent polypeptides. Initiator methionines are prone to oxidation and are readily converted to methionine sulfoxides (MetO) by reactive oxygen species. Oxidation of initiator methionines prevents their subsequent deformylation and hydrolysis, which can negatively impact the function of some proteins. To protect against deleterious methionine oxidation, cells can enzymatically reduce MetO residues using a conserved class of enzymes known as methionine sulfoxide reductases (Msrs). Analysis of the oxidation state of initiator methionines can, therefore, provide important information regarding their propensity for downstream processing that may influence the folding and stability of newly synthesized proteins. Here, we present two protocols, Methionine Oxidation by Blocking (MObB) and Methionine Oxidation by Blocking with Alkylation (MObBa), for quantitation of oxidation levels of methionines within complex protein mixtures using mass spectrometry-based proteomics. Among other applications, these two approaches enable researchers to investigate the interplay between the oxidation and processing of initiator methionines.

Keywords:  Formylation; Mass spectrometry; Methionine; Methionine sulfoxide reductases; Oxidation; Proteomics

DOI:  https://doi.org/10.1016/bs.mie.2025.06.021