bims-mascan 2025-05-04 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–05–04
28 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Multiplexed phosphoproteomics of low cell numbers using SPARCE.
Isotope tracing-based metabolite identification for mass spectrometry metabolomics.
SPE-CZE-MS Quantifies Zeptomole Amounts of Phosphorylated Peptides.
Accurate Determination of Circulatory Lipids Using a Combination of HILIC-MRM and RPLC-PRM.
Benchmarking SILAC Proteomics Workflows and Data Analysis Platforms.
Lipid metabolism in cancer: Exploring phospholipids as potential biomarkers.
Automated Integration and Quality Assessment of Chromatographic Peaks in LC-MS-Based Metabolomics and Lipidomics Using TARDIS.
SYMPOSIUM 10 - How can we integrate proteomics and metabolomics in Clinical Lab?
Dual LC column characterization for mass spectrometry-based small molecule profiling of human plasma and serum.
Application of metal stable isotopes labeling and elemental mass spectrometry for biomacromolecule profiling.
Mitochondrial metabolism in laryngeal cancer: Therapeutic mechanisms and prospects.
A Facile Workflow for Sebum Fatty Acids and Squalene Identification via Advanced Lipidomic Methodologies.
Integrating NMR and multi-LC-MS-based untargeted metabolomics for comprehensive analysis of blood serum samples.
Derivatization-Assisted Acoustic Ejection Mass Spectrometry for High-Throughput FAHFA Prescreening.
Exploring Sample Storage Conditions for the Mass Spectrometric Analysis of Extracted Lipids from Latent Fingerprints.
Serine metabolism in tumor progression and immunotherapy.
The current state in liquid chromatography-mass spectrometry methods for quantifying kynurenine pathway metabolites in biological samples: a systematic review.
Immunoregulatory macrophages induced by mycobacterial nonpolar lipids.
Analytical workflow for comprehensive blood metabolomics analysis by GC-MS. Application to children with ventilator associated pneumonia.
Rodin: a streamlined metabolomics data analysis and visualization tool.
Deep Characterization of Isomerization in the Human Eye Lens Proteome by Crystallin-Depleted Data-Independent Acquisition.
Fiber Type-Specific Adaptations to Exercise Training in Human Skeletal Muscle: Lessons From Proteome Analyses and Future Directions.
Large-Scale Metabolite Imaging Gallery of Mouse Organ Tissues to Study Spatial Metabolism.
SYMPOSIUM 1 - New approaches for deriving and applying biological variation data for clinical use.
Single cell spatial proteomics maps human liver zonation patterns and their vulnerability to fibrosis.
Protocol for the use of Oredsson universal replacement medium for cell banking and routine culturing of monolayer and suspension cultures.
Intracellular metabolic gradients dictate dependence on exogenous pyruvate.
Composite Mapping for Peptide-Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles.

Commun Biol. 2025 Apr 26. 8(1): 666

Multiplexed phosphoproteomics of low cell numbers using SPARCE.

Emily J Gaizley, Xiuyuan Chen, Amandeep Bhamra, Tariq Enver, Silvia Surinova.

Understanding cellular diversity and disease mechanisms requires a global analysis of proteins and their modifications. While next-generation sequencing has advanced our understanding of cellular heterogeneity, it fails to capture downstream signalling networks. Ultrasensitive mass spectrometry-based proteomics enables unbiased protein-level analysis of low cell numbers, down to single cells. However, phosphoproteomics remains limited to high-input samples due to sample losses and poor reaction efficiencies associated with processing low cell numbers. Isobaric stable isotope labelling is a promising approach for reproducible and accurate quantification of low abundant phosphopeptides. Here, we introduce SPARCE (Streamlined Phosphoproteomic Analysis of Rare CElls) for multiplexed phosphoproteomic analysis of low cell numbers. SPARCE integrates cell isolation, water-based lysis, on-tip TMT labelling, and phosphopeptide enrichment. SPARCE outperforms traditional methods by enhancing labelling efficiency and phosphoproteome coverage. To demonstrate the utility of SPARCE, we analysed four patient-derived glioblastoma stem cell lines, reliably quantifying phosphosite changes from 1000 FACS-sorted cells. This workflow expands the possibilities for signalling analysis of rare cell populations.

DOI: https://doi.org/10.1038/s42003-025-08068-x
bioRxiv. 2025 Apr 08. pii: 2025.04.07.647691. [Epub ahead of print]

Isotope tracing-based metabolite identification for mass spectrometry metabolomics.

Deniz Secilmis, Arjana Begzati, Nina Grankvist, Irena Roci, Jeramie Watrous, Amit R Majithia, Gordon I Smith, Samuel Klein, Mohit Jain, Roland Nilsson.

Modern mass spectrometry-based metabolomics is a key technology for biomedicine, enabling discovery and quantification of a wide array of biomolecules critical for human physiology. Yet, only a fraction of human metabolites have been structurally determined, and the majority of features in typical metabolomics data remain unknown. To date, metabolite identification relies largely on comparing MS 2 fragmentation patterns against known standards, related compounds or predicted spectra. Here, we propose an orthogonal approach to identification of endogenous metabolites, based on mass isotopomer distributions (MIDs) measured in an isotope-labeled reference material. We introduce a computational measure of pairwise distance between metabolite MIDs that allows identifying novel metabolites by their similarity to previously known peaks. Using cell material labeled with 20 individual 13 C tracers, this method identified 62% of all unknown peaks, including previously never seen metabolites. Importantly, MID-based identification is highly complementary to MS 2 -based methods in that MIDs reflect the biochemical origin of metabolites, and therefore also yields insight into their synthesis pathways, while MS 2 spectra mainly reflect structural features. Accordingly, our method performed best for small molecules, while MS 2 -based identification was stronger on lipids and complex natural products. Among the metabolites discovered was trimethylglycyl-lysine, a novel amino acid derivative that is altered in human muscle tissue after intensive lifestyle treatment. MID-based annotation using isotope-labeled reference materials enables identification of novel endogenous metabolites, extending the reach of mass spectrometry-based metabolomics.

DOI: https://doi.org/10.1101/2025.04.07.647691
J Proteome Res. 2025 Apr 28.

SPE-CZE-MS Quantifies Zeptomole Amounts of Phosphorylated Peptides.

Lia R Serrano, J Scott Mellors, J Will Thompson, Noah M Lancaster, Margaret Lea Robinson, Katherine A Overmyer, Scott T Quarmby, Joshua J Coon.

  Capillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultralow-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis. Some challenges of coupling CZE analysis with mass spectrometry analysis (MS) of complex mixtures include 1. sensitivity due to volume loading limitations of CZE and 2. incompatibility of MS duty cycles with electropherographic time scales. Here, we address these two challenges as applied to single-cell-equivalent phosphoproteomics experiments by interfacing a microchip-based CZE device integrated with a solid-phase-extraction (SPE) bed with the Orbitrap Astral mass spectrometer. Using 225 phosphorylated peptide standards and phosphorylated peptide-enriched mouse brain tissue, we investigate microchip-based SPE-CZE functionality, quantitative performance, and complementarity to nano-LC-MS (nLC-MS) analysis. We highlight unique SPE-CZE separation mechanisms that can empower fit-for-purpose applications in single-cell-equivalent phosphoproteomics.

Keywords:  Astral; SPE; capillary zone electrophoresis; phosphoproteomics; preconcentration

DOI:  https://doi.org/10.1021/acs.jproteome.5c00194
Anal Chem. 2025 May 02.

Accurate Determination of Circulatory Lipids Using a Combination of HILIC-MRM and RPLC-PRM.

Kyeong-Seog Kim, Jae-Seung Lee, Seung Seok Han, Joo-Youn Cho.

Circulatory lipids are important markers for characterizing disease phenotypes; however, accurately determining lipid species remains a significant challenge in lipidomic analysis. Here, we present a novel analytical workflow for accurate lipidome characterization in human plasma using mass spectrometry (MS) through the integration of hydrophilic interaction liquid chromatography (HILIC) and reversed-phase liquid chromatography (RPLC). This workflow enables rapid screening of 1,966 lipid species across 18 lipid classes using HILIC-multiple reaction monitoring (MRM), which enables facile identification of lipid species by lipid class-based separations. In the NIST Standard Reference Material for Human Plasma (SRM 1950), 489 lipid species were identified using HILIC-MRM and subsequently analyzed with RPLC-parallel reaction monitoring (PRM) to resolve potential lipid isobars within the same lipid class. Notably, RPLC-PRM identified 70 additional lipidomic features in SRM 1950 that were not detectable with HILIC-MRM. Furthermore, a high correlation (Pearson correlation coefficient = 0.81) was observed regarding the concentrations of lipid species not carrying isobaric interferences in between HILIC-MRM and RPLC-PRM, indicating that the individual lipid concentrations measured by each platform can be integrated. The workflow was further applied to a cohort of 284 human plasma samples from chronic kidney disease (CKD) patients, successfully profiling lipidomic phenotypes across CKD subtypes. These findings demonstrate that combining HILIC-MRM and RPLC-PRM as complementary platforms enhances the accuracy and comprehensiveness of lipidomic analysis.

DOI: https://doi.org/10.1021/acs.analchem.4c06409
Mol Cell Proteomics. 2025 Apr 30. pii: S1535-9476(25)00078-7. [Epub ahead of print] 100980

Benchmarking SILAC Proteomics Workflows and Data Analysis Platforms.

Ashley M Frankenfield, Kevin Yang, Wan Nur Atiqah Binti Mazli, Jamison Shih, Fengchao Yu, Edwin Lo, Alexey I Nesvizhskii, Ling Hao.

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful metabolic labeling technique with broad applications and various study designs. SILAC proteomics relies on the accurate identification and quantification of all isotopic versions of proteins and peptides during both data acquisition and analysis. However, a comprehensive comparison and evaluation of SILAC data analysis platforms is currently lacking. To address this critical gap and offer practical guidelines for SILAC proteomics data analysis, we designed a comprehensive benchmarking pipeline to evaluate various in vitro SILAC workflows and commonly used data analysis software. Ten different SILAC data analysis workflows using five software packages (MaxQuant, Proteome Discoverer, FragPipe, DIA-NN, and Spectronaut) were evaluated for static and dynamic SILAC labeling with both DDA and DIA methods. For benchmarking, we used both in-house generated and repository SILAC proteomics datasets from HeLa and neuron culture samples. We assessed twelve performance metrics for SILAC proteomics including identification, quantification, accuracy, precision, reproducibility, filtering criteria, missing values, false discovery rate, protein half-life measurement, data completeness, unique software features, and speed of data analysis. Each method/software has its strengths and weaknesses when evaluated for these performance metrics. Most software reaches a dynamic range limit of 100 folds for accurate quantification of light/heavy ratios. We do not recommend using Proteome Discoverer for SILAC DDA analysis despite its wide use in label-free proteomics. To achieve greater confidence in SILAC quantification, researchers could use more than one software packages to analyze the same dataset for cross-validation. In summary, this study offers the first systematic evaluation of various SILAC data analysis platforms, providing practical guidelines to support decision-making in SILAC proteomics study design and data analysis.

DOI: https://doi.org/10.1016/j.mcpro.2025.100980
Biomed Pharmacother. 2025 Apr 29. pii: S0753-3322(25)00289-6. [Epub ahead of print]187 118095

Lipid metabolism in cancer: Exploring phospholipids as potential biomarkers.

Dominique Delmas, Aurélie Mialhe, Alexia K Cotte, Jean-Louis Connat, Florence Bouyer, François Hermetet, Virginie Aires.

  Aberrant lipid metabolism is increasingly recognized as a hallmark of cancer, contributing to tumor growth, metastatic dissemination, and resistance to therapy. Cancer cells reprogram key metabolic pathways-including de novo lipogenesis, lipid uptake, and phospholipid remodeling-to sustain malignant progression and adapt to microenvironmental demands. This review summarizes current insights into the role of lipid metabolic reprogramming in oncogenesis and highlights recent advances in lipidomics that have revealed cancer type- and stage-specific lipid signatures with diagnostic and prognostic relevance. We emphasize the dual potential of lipid metabolic pathways-particularly those involving phospholipids-as sources of clinically relevant biomarkers and therapeutic targets. Enzymes and transporters involved in these pathways have emerged as promising candidates for both diagnostic applications and pharmacological intervention. We also examine persistent challenges hindering the clinical translation of lipid-based approaches, including analytical variability, insufficient biological validation, and the lack of standardized integration into clinical workflows. Furthermore, the review explores strategies to overcome these barriers, highlighting the importance of incorporating lipidomics into multi-omics frameworks, supported by advanced computational tools and AI-driven analytics, to decipher the complexity of tumor-associated metabolic networks. We discuss how such integrative approaches can facilitate the identification of actionable metabolic targets, improve the specificity and robustness of lipid-based biomarkers, and enhance patient stratification in the context of precision oncology.

Keywords:  Cancer metabolism; Lipid biomarkers; Lipidomics; Mass spectrometry; Metabolic reprogramming; Phospholipids

DOI:  https://doi.org/10.1016/j.biopha.2025.118095
Anal Chem. 2025 Apr 28.

Automated Integration and Quality Assessment of Chromatographic Peaks in LC-MS-Based Metabolomics and Lipidomics Using TARDIS.

Pablo Vangeenderhuysen, Matthijs Vynck, Beata Pomian, Kimberly De Windt, Emile Callemeyn, Ellen De Paepe, Lindsey De Commer, Jeroen Raes, Tim Nawrot, Johannes Rainer, Lieselot Y Hemeryck, Lynn Vanhaecke.

In recent years, liquid chromatography coupled to mass spectrometry (LC-MS) has emerged as the main technology to measure the whole of small molecules (the metabolome) in a diversity of matrices. Within the field of computational metabolomics, significant efforts have been made in the development of tools to (pre)process untargeted LC-MS data. However, tools that circumvent the time-consuming, manual preprocessing of targeted LC-MS data with vendor-specific software remain sparse. We therefore present TARDIS, an open-source R package for the analysis of targeted LC-MS metabolomics and lipidomics data. Both established (area under the curve, maximum intensity and points over the peak) and recently developed (custom signal-to-noise ratio and bell-curve similarity) quality metrics were included to offer increased efficiency of peak quality evaluation. The robustness of TARDIS' peak integration was demonstrated through a quantitative comparison to state-of-the-art vendor software. To this end, applicability at a large scale (n = 1786) was validated across three distinct biofluids (stool, saliva and urine) and two LC-MS instruments, using data from the FAME, ENVIRONAGE, and FGFP cohort studies. In conclusion, TARDIS offers a robust and scalable open-source solution for the targeted analysis of LC-MS metabolomics and lipidomics data. TARDIS and its source code are freely available at https://github.com/UGent-LIMET/TARDIS.

DOI: https://doi.org/10.1021/acs.analchem.5c00567
Clin Chem Lab Med. 2025 May 26. 63(s1): s86-s88

SYMPOSIUM 10 - How can we integrate proteomics and metabolomics in Clinical Lab?

DOI: https://doi.org/10.1515/cclm-2025-8032
Anal Chim Acta. 2025 Jun 22. pii: S0003-2670(25)00336-8. [Epub ahead of print]1356 343942

Dual LC column characterization for mass spectrometry-based small molecule profiling of human plasma and serum.

Žiga Tkalec, Štěpán Koudelka, Jana Klánová, Elliott J Price.

   BACKGROUND: Analyte annotation confidence in untargeted liquid chromatography mass-spectrometry (LC-MS) based chemical analysis can be enhanced by leveraging retention time information. For this, the chromatographic characteristics of the analytical system used should be well characterized. In this study, we measured 604 diverse chemical standards to characterize a dual LC setup consisting of pentabromobenzyl (PBr) and type-C silica hydride (SiH) columns operating in reversed-phase (RP) and aqueous normal-phase (ANP) mode, respectively.
RESULTS: ANP and RP separations individually retained 40 % and 64 % of standards in cLogP range from -6.60 to 8.67 and -3.34 to 12.95, respectively. Using both columns, the coverage increased to 79 % of standards with cLogP range from -6.60 to 12.95 (median cLogP = 1.63). Retention selectivity follows the number of basic nitrogen atoms in the molecule on SiH column and polarity (cLogP) on PBr column. Column repeatability and reproducibility were tested in triplicate using a chemically diverse subset of 108 standards. Repeatability of retention times, peak widths and peak areas was 0.3 %, 14 %, 4 % for SiH column and 0.2 %, 12 %, 4 % for PBr column. Similarly, reproducibility was 15 %, 34 %, 30 % for SiH column and 9 %, 18 % and 34 % for PBr column. Predictive RT models were developed based on experimental RT data, achieving R2 values of 0.92 and 0.96, with mean absolute errors of 0.29 min and 0.27 min for SiH and PBr columns, respectively.
SIGNIFICANCE: As proof of concept, 129 metabolites were annotated in pooled human serum and plasma by matching standard or predicted RT on one or both columns. The RT models and MS2 spectra of standards are openly available, facilitating uptake of this well-characterized chromatographic system to increase confidence in analyte annotation.

Keywords:  Aqueous normal-phase; Chemicals; Exposome; Metabolomics; Non-targeted; Retention time prediction

DOI:  https://doi.org/10.1016/j.aca.2025.343942
Biophys Rep. 2025 Apr 30. 11(2): 112-128

Application of metal stable isotopes labeling and elemental mass spectrometry for biomacromolecule profiling.

Ping Zhang, Ying Han, Yue Xu, Liang Gao.

  Biomacromolecules including proteins and nucleic acids are widely recognized for their pivotal and irreplaceable role in maintaining the normal functions of biological systems. By combining metal stable isotope labeling with elemental mass spectrometry, researchers can quantify the amount and track the spatial distribution of specific biomacromolecules in complex biological systems. In this review, the probes classification and metal stable isotope labeling strategies are initially summarized. Secondly, the technical characteristics and working principle of the elemental mass spectrometry techniques including inductively coupled plasma mass spectrometry and secondary ion mass spectrometry are introduced to achieve highly sensitive detection of multiple biomacromolecules at molecular, cellular and tissue levels. Lastly, we underline the advantages and limitations of elemental mass spectrometry combined with metal stable isotope labeling strategies, and propose the perspectives for future developments.

Keywords:  Biomacromolecule; Mass spectrometry analysis; Metal stable isotope labeling

DOI:  https://doi.org/10.52601/bpr.2024.240039
Biochim Biophys Acta Rev Cancer. 2025 Apr 29. pii: S0304-419X(25)00077-0. [Epub ahead of print] 189335

Mitochondrial metabolism in laryngeal cancer: Therapeutic mechanisms and prospects.

Yun-Jing Hou, Xin-Xin Yang, Hong-Xue Meng.

  Tumours reprogram pathways that regulate nutrient uptake and metabolism to meet the biosynthetic, bioenergetic, and redox requirements of cancer cells. This phenomenon is known as metabolic reprogramming and is edited by the deletion of oncogenes and the activation of proto-oncogenes. This article highlights the pathological mechanisms associated with metabolic reprogramming in laryngeal cancer (LC), including enhanced glycolysis, tricarboxylic acid cycle, nucleotide synthesis, lipid synthesis and metabolism, and amino acid metabolism, with a special emphasis on glutamine, tryptophan, and arginine metabolism. All these changes are regulated by HPV infection, hypoxia, and metabolic mediators in the tumour microenvironment. We analyzed the function of metabolic reprogramming in the development of drug resistance during standard LC treatment, which is challenging. In addition, we revealed recent advances in targeting metabolic strategies, assessing the strengths and weaknesses of clinical trials and treatment programs to attack resistance. This review summarises some currently important biomarkers and lays the foundation for therapeutic pathways in LC.

Keywords:  Laryngeal cancer (LC); Metabolic reprogramming; Mitochondria; Pathological mechanisms; Tumour microenvironment

DOI:  https://doi.org/10.1016/j.bbcan.2025.189335
Anal Chem. 2025 May 02.

A Facile Workflow for Sebum Fatty Acids and Squalene Identification via Advanced Lipidomic Methodologies.

Lerong Qi, Xiangzi Li, Yachen Ren, Tingxiang Yang, Yang Guan, Dong Hao Wang, Zhen Wang.

Sebum fatty acids and squalene are major components of skin secretions and play a critical role in the pathogenesis of dermatological conditions through their compositional alterations. Human sebum fatty acids are uniquely diverse in their chain length, double bond positions, and chain branching; squalene is a rare component of skin secretions with six double bonds. We introduce a facile workflow for the analysis of sebum fatty acids and squalene for elucidating their contribution to the state of skin health or disease using advanced mass spectrometric methods for qualitative and quantitative analyses. Sebum from dermatologically healthy individuals was extracted, and covalent adduct chemical ionization (CACI), electron ionization (EI), and Paternò-Büchi (PB) tandem mass spectrometry (MS/MS) techniques were employed for the identification of fatty acids with varying methyl branch and/or carbon-carbon double bond positions. A method for the full structural characterization of squalene via CACI tandem mass spectrometry was also developed. In sebum, we report for the first time unusual straight-chain polyunsaturated fatty acid isomers (n18:2n-7, n18:2n-3, n20:2n-12, and n20:2n-7), a series of previously unreported branched-chain saturated fatty acids with C19-C26, and a novel branched-chain monounsaturated fatty acid i15:1n-9. A total of 64 fatty acids were identified, exceeding the previous reports. Our study established a comprehensive qualitative and quantitative workflow for the analysis of sebum fatty acids and squalene, with the potential to advance dermatological research and clinical diagnostics.

DOI: https://doi.org/10.1021/acs.analchem.4c06010
Anal Chim Acta. 2025 Jun 22. pii: S0003-2670(25)00373-3. [Epub ahead of print]1356 343979

Integrating NMR and multi-LC-MS-based untargeted metabolomics for comprehensive analysis of blood serum samples.

Tereza Kacerova, Elisabete Pires, John Walsby-Tickle, Fay Probert, James S O McCullagh.

   BACKGROUND: Mass spectrometry (MS) and nuclear magnetic resonance (NMR) have emerged as pivotal tools in biofluid metabolomics, facilitating investigation of disease mechanisms and biomarker discovery. Despite complementary capabilities, these techniques are rarely combined, although their integration is often beneficial. Typically, different sample preparation approaches are used, and compatibility challenges potentially arise due to the requirement for deuterated buffered solvents in NMR but not MS techniques. Additionally, MS-based approaches necessitate protein removal from samples whilst in NMR proteins can be potentially useful biomarkers. In this study, we developed a blood serum preparation protocol enabling sequential NMR and multi-LC-MS untargeted metabolomics analysis using a single serum aliquot in a research discovery setting.
RESULTS: We analysed human serum samples using various untargeted NMR and multi-LC-MS platforms to assess the impact of deuterated solvents and buffers on detected compound-features. Employing multiple LC-MS profiling approaches, we observed no evidence of deuterium incorporation into metabolites following sample preparation with deuterated solvents. Furthermore, we demonstrated that buffers used in NMR were well tolerated by LC-MS. Protein removal, involving both solvent precipitation and molecular weight cut-off (MWCO) filtration, was identified as a primary factor influencing metabolite abundance. Our findings led to the development and validation of a serum sample preparation protocol enabling a combined NMR and multi-LC-MS analysis.
SIGNIFICANCE: Using a single clinical serum aliquot for simultaneous untargeted profiling via NMR and multi-LC-MS represents a highly efficient alternative to current methods. This approach reduces sample volume requirements and substantially expands the potential for broader metabolome coverage. Our study offers comprehensive insights into the impact of sample preparation on complex metabolic biofluid profiles, highlighting the compatibility and complementarity of LC-MS and NMR in metabolomics research.

Keywords:  Mass spectrometry; Multi-platform metabolomics; Nuclear magnetic resonance; Sample preparation; Untargeted metabolomics

DOI:  https://doi.org/10.1016/j.aca.2025.343979
Anal Chem. 2025 Apr 30.

Derivatization-Assisted Acoustic Ejection Mass Spectrometry for High-Throughput FAHFA Prescreening.

Na An, Peng-Cheng Mei, Ao Li, Xiu-Feng Fu, Xin-Ze Wu, Han-Peng Jiang, Quan-Fei Zhu, Yu-Qi Feng.

Fatty acid esters of hydroxy fatty acids (FAHFAs) are bioactive lipids with significant structural diversity and potential health benefits, playing crucial roles in metabolic regulation, inflammation, and insulin sensitivity. However, the low abundance of FAHFAs in biological samples (0.1% to 0.001% of free fatty acids) and the wide range of molecular polarities (ClogP values from 0.26 to 18.24) across short-chain to long-chain FAHFAs pose substantial challenges for high-throughput screening. Here, we developed a novel high-throughput prescreening strategy, termed DAEMS (derivatization-assisted acoustic ejection mass spectrometry), which integrates chemical derivatization with acoustic ejection mass spectrometry (AEMS). By leveraging the ultrafast analysis speed of AEMS (1-3 samples per second) and the sensitivity enhancement of N,N-dimethylethylenediamine (DMED) derivatization, DAEMS enables the screening of over 2800 potential FAHFA species in less than 2 h─significantly faster than the conventional LC-MRM MS-based screening approaches. The DAEMS strategy achieved 83% coverage and 79% accuracy in preliminary screening compared to the LC-MRM MS. Furthermore, we also revealed novel oxidized FAHFA species in edible fungi for the first time, suggesting potential biosynthesis involving oxylipins or oxidative modifications. This study demonstrates DAEMS as a promising tool for rapid FAHFA prescreening, and the discovery of oxidized FAHFAs provides new insights into FAHFA diversity and metabolism.

DOI: https://doi.org/10.1021/acs.analchem.5c01004
Biomolecules. 2025 Mar 25. pii: 477. [Epub ahead of print]15(4):

Exploring Sample Storage Conditions for the Mass Spectrometric Analysis of Extracted Lipids from Latent Fingerprints.

Aleesa E Chua, Eden P Go, Heather Desaire.

  In large-scale studies, uncontrolled systematic variability introduced during sample preparation, processing, and storage can interfere with the detection of subtle biological signals. This study evaluates storage conditions, including two sample preparation methods and storage durations, to minimize systematic variability in the analysis of extracted lipids from latent fingerprints. In the traditional approach, samples are prepared immediately, stored as lipid extracts, and processed in multiple batches. In an alternative method, samples are stored directly on the deposition foil, and preparation is delayed until all can be processed in a single batch. Storage duration is evaluated to determine if shorter storage with analysis in multiple batches is more effective than longer storage with analysis in a single batch. Our findings demonstrate that storage of latent fingerprint samples on the deposition foil is a viable option, with minimal degradation of key features even after eight months of storage. While some differences in lipid profiles were observed across storage conditions, these differences were minor and would likely have little impact in larger studies where biological variability is greater. These insights offer practical guidance for implementing latent fingerprint sampling in large-scale studies by identifying optimal conditions that preserve sample quality and streamline workflows.

Keywords:  data analysis; lipids; mass spectrometry; sample processing; storage; variability

DOI:  https://doi.org/10.3390/biom15040477
Discov Oncol. 2025 Apr 28. 16(1): 628

Serine metabolism in tumor progression and immunotherapy.

Dong Huang, Hui Cai, HaiYu Huang.

  Serine plays a vital role in various metabolic processes including the synthesis of proteins and other amino acids, which are essential for the cell proliferation and growth. Cancer cells either absorb exogenous serine or produce it through the serine synthesis pathway, enabling the generation of intracellular glycine and one-carbon units, which are crucial for nucleotide biosynthesis. This metabolic process, referred to as serine-glycine-one-carbon (SGOC) metabolism, is essential for tumorigenesis and exhibits considerable complexity and clinical significance. Enzymes involved in the SGOC pathway are linked to tumor growth, metastasis, and resistance to therapies. The SGOC pathway is a vital metabolic network that facilitates cell survival and proliferation, especially in aggressive cancers. Understanding how this network is regulated is crucial for tackling tumor heterogeneity and recurrence. This review emphasizes recent advancements in understanding the roles and effects of the SGOC metabolic pathway in the context of cancer progression. Additionally, it outlines the complex influences of the SGOC metabolic pathway on the tumor microenvironment (TME), offering potential strategies to enhance cancer immunotherapy.

Keywords:  Immunotherapy; One-carbon metabolism; Serine; Tumor microenvironment; Tumor progression

DOI:  https://doi.org/10.1007/s12672-025-02358-w
Crit Rev Clin Lab Sci. 2025 Apr 29. 1-17

The current state in liquid chromatography-mass spectrometry methods for quantifying kynurenine pathway metabolites in biological samples: a systematic review.

Md Munnaf Hossen, Bobbi Fleiss, Rosita Zakaria.

  Kynurenine pathway (KP) metabolites are implicated in various disorders, including Alzheimer's disease, schizophrenia, and adverse pregnancy outcomes. Simultaneous measurement of multiple KP metabolites offers valuable insight into the pathway's role in health and disease, would improve this relatively undeveloped field. This systematic review aim was to summarize the state of the art for measuring the eight key KP metabolites, using liquid chromatography-mass spectrometry (LC-MS), explicitly focusing on whether methods were validated using established guidelines with superior sensitivity and selectivity. We undertook a comprehensive review of the literature using the PRISMA guidelines. Our search uncovered 66 publications, and 39 qualified the defined key criteria. We summarized each publication's method development parameters, analytical design, and method performance specifications. We found notable variability in sample preparation techniques and analytical design across biological matrices, underscoring a lack of universally established and validated methods for KP metabolite quantification. We also identified significant gaps in the basic method evaluation. Our findings highlight that no single method has been evaluated for quantifying the eight key KP metabolites across three or more biological sample types, revealing a critical gap in the field. Our review emphasizes the need for robust analytical methods to quantify KP metabolites across multiple biological matrices, facilitating a better understanding of their roles in health and disease. Given the diversity of disorders involving the KP in the clinical testing lab, developing such methods will reduce diagnostic errors and advance KP metabolite research, supporting more precise, and personalized medical care.

Keywords:  Bioanalytical methods; brain disorders; kynurenic acid; method evaluation; quinolinic acid

DOI:  https://doi.org/10.1080/10408363.2025.2495160
J Immunol. 2025 Apr 25. pii: vkae058. [Epub ahead of print]

Immunoregulatory macrophages induced by mycobacterial nonpolar lipids.

Jéssica Dias Petrilli, Paulo Estevão, Luana Evangelista De Araújo, Igor Muller, Marcos Yukio Yoshinaga, Pablo Ivan Pereira Ramos, Adriano Britto Chaves-Filho, Thainá Horta, Carlos Arterio Sorgi, Sayuri Miyamoto, Lee Riley, Sérgio Arruda, Adriano Queiroz.

  The capacity of Mycobacterium tuberculosis (Mtb) to establish long-term survival is attributed to its ability to subvert host defense mechanisms, especially macrophages. Although Mtb lipids are believed to play a role in this host-pathogen crosstalk, how mycobacterial lipids drive this complex interaction is poorly characterized. Here, we cultured macrophages with nonpolar cell wall Mtb lipids and applied high-throughput expression profiling (RNA sequencing), mass spectrometry-based targeted eicosanoid, and untargeted lipidomics analysis. This system-level analysis revealed that Mtb nonpolar lipid triggered the expression of phenotypic markers for classically and alternatively activated macrophages, a state previously referred as immunoregulatory. Specifically, under lipid stimulation, macrophages expressed high levels of proinflammatory markers, activated components of the interleukin-1 family, underwent an imbalance in lipid metabolism, and shifted the eicosanoid synthesis pathway toward the prostaglandin axis. Taken together, these results suggest an intricate mechanism of Mtb-driven macrophage immunomodulation that may favor its long-term survival.

Keywords:   Mycobacterium tuberculosis ; immunoregulatory macrophages; lipidomic; nonpolar lipids; transcriptomic

DOI:  https://doi.org/10.1093/jimmun/vkae058
J Chromatogr A. 2025 Mar 31. pii: S0021-9673(25)00272-9. [Epub ahead of print]1753 465924

Analytical workflow for comprehensive blood metabolomics analysis by GC-MS. Application to children with ventilator associated pneumonia.

M Ioannidis, T Mouskeftara, E Iosifidis, M Simitsopoulou, E Roilides, H Gika, María Fernanda Rey-Stolle, C Virgiliou.

  Metabolomics is a widely used approach for analyzing a vast array of low molecular weight compounds such as amino acids, organic acids, vitamins, biogenic amines and carbohydrates in biological samples, with the aim of investigating biomarkers in personalized medicine studies. Advancements in gas chromatography- mass spectrometry (GC-MS) instrumentation, along with the availability of commercial and public spectral libraries, have highlighted the relevance of GC-MS analysis as a valuable tool for metabolomics applications. Stability assessment in derivatisation and GC-MS analysis is a crucial yet often overlooked aspect of metabolomics studies. In this study, an untargeted GC-MS method workflow for large scale metabolomics studies is presented after assessment and optimization of whole blood sample's stability. The method consists of a common two-step derivatisation procedure including methoximation using methoxyamine hydrochloride, followed by silylation with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA). To ensure the stability of the studied metabolites, extensive stability experiments were performed. The stability of the derivatives was evaluated over 24 h in the autosampler at room temperature, as well as after storage for 24 and 48 h at -20 °C for both derivatized and dried extracts. While derivatised samples remained stable for 24-48 h in the freezer, dried extracts exhibited variability after 48 h. Findings support the storage of derivatised samples over dried extracts, ensuring greater stability. To increase condidence in metabolite identification data from the analysis of 120 standard compounds were utilized. The developed method was applied to analyze blood samples from 32 children with ventilator-associated pneumonia (VAP), collected at four different time points during ICU hospitalization. This analysis led to the identification of 43 metabolites. The results of multivariate and univariate statistical analyses demonstrated several statistically significant metabolites, including aspartic acid, alanine, and pyroglutamic acid, which showed a strong correlation with the disease's manifestation and may potentially serve as biomarkers in the diagnosis of ventilator-associated pneumonia VAP at the stage of clinical suspicion.

Keywords:  Blood; Derivatisation; GC-MS; Metabolomics; Stability; Ventilator-associated pneumonia

DOI:  https://doi.org/10.1016/j.chroma.2025.465924
Bioinform Adv. 2025 ;5(1): vbaf088

Rodin: a streamlined metabolomics data analysis and visualization tool.

Boris Minasenko, Dongxue Wang, Piera Cirillo, Nickilou Krigbaum, Barbara Cohn, Dean P Jones, Jeffrey M Collins, Xin Hu.

Summary: Recent advances in high-resolution mass spectrometry have revolutionized metabolomics, enabling the profiling of hundreds of thousands of metabolic features in a single experiment, with widespread applications across health sciences. To streamline analysis of metabolomics data, we developed Rodin, a Python-based application offering fast, efficient processing of large datasets via a web interface or programming library. Rodin integrates multiple stages of analysis, including feature preprocessing, statistical testing, interactive visualizations, and pathway analysis, generating outputs while tracking user-defined parameters within a single page. By enhancing the accessibility of tools for metabolomics data analysis, Rodin not only streamlines the workflow but also enhances analytic throughput by enabling a broader range of users to perform these analyses. Compared to other tools, Rodin excels in user-friendliness, ease of access, and seamless integration of multiple functionalities, enabling reproducible, efficient workflows for users of all computational skill levels.
Availability and implementation: Web interface-https://rodin-meta.com/. Python library-https://github.com/BM-Boris/rodin.

DOI: https://doi.org/10.1093/bioadv/vbaf088
Aging Cell. 2025 May 01. e70028

Deep Characterization of Isomerization in the Human Eye Lens Proteome by Crystallin-Depleted Data-Independent Acquisition.

Evan E Hubbard, Thomas A Shoff, Manhoi Hur, Tyler R Lambeth, Chengwei Chen, Ethan Kung, Bruce D Pan, Matthew K Lui, Javian R Linares, Lee S Cantrell, Kevin L Schey, Ryan R Julian.

  The eye lens is a unique tissue optimized for light transmission and refraction, necessitating dissolution of all organelles in mature fiber cells. This absence of organelles prevents protein turnover and leads to the accumulation of many spontaneous modifications over time. One modification that is oft overlooked is isomerization, despite its known impact on protein structure, interference with enzymatic activity, and association with disease. Prior analysis of isomerization in the lens has been limited to a small number of targets, consisting primarily of the highly abundant crystallin proteins. Proteomic coverage can be greatly increased by first depleting the crystallins and then employing state-of-the-art data-independent acquisition (DIA) mass spectrometry (MS). However, this approach has not been combined with data analysis methods capable of identifying isomers. By so doing, we identified hundreds of previously unreported, noncrystallin Asp isomer sites. To a lesser extent, isomerization was also detected at serine and glutamic acid, consistent with previous reports of relative isomerization propensities. Interestingly, we also identify histidine isomerization sites in a select number of peptides associated with metal adduction. We further analyzed our results according to primary sequence and secondary structure to explore factors potentially influencing isomerization. Finally, we found that while isomerization percents for individual proteins are modestly accurate predictor of age, inclusion of multiple isomerized sites affords a more accurate prediction of age, which may be useful for applications in forensics.

Keywords:  data‐independent acquisition; eye lens; human aging; isomerization; proteomics

DOI:  https://doi.org/10.1111/acel.70028
Scand J Med Sci Sports. 2025 May;35(5): e70059

Fiber Type-Specific Adaptations to Exercise Training in Human Skeletal Muscle: Lessons From Proteome Analyses and Future Directions.

Morten Hostrup, Atul S Deshmukh.

  Skeletal muscle is a key determinant of sports performance. It is a highly specialized, yet complex and heterogeneous tissue, comprising multiple cell types. Muscle fibers are the main functional cell type responsible for converting energy into mechanical work. They exhibit a remarkable ability to adapt in response to stressors, such as exercise training. But while it is recognized that human skeletal muscle fibers have distinct contractile and metabolic features, classified as slow/oxidative (type 1) or fast/glycolytic (type 2a/x), less attention has been directed to the adaptability of the different fiber types. Methodological advancements in mass spectrometry-based proteomics allow researchers to quantify thousands of proteins with only a small amount of muscle tissue-even in a single muscle fiber. By exploiting this technology, studies are emerging highlighting that muscle fiber subpopulations adapt differently to exercise training. This review provides a contemporary perspective on the fiber type-specific adaptability to exercise training in humans. A key aim of our review is to facilitate further advancements within exercise physiology by harnessing mass spectrometry proteomics.

Keywords:  athletes; exercise; muscle adaptations; physical activity; proteomics; training

DOI:  https://doi.org/10.1111/sms.70059
J Proteome Res. 2025 Apr 28.

Large-Scale Metabolite Imaging Gallery of Mouse Organ Tissues to Study Spatial Metabolism.

Karl W Smith, Antonia Fecke, Siva Swapna Kasarla, Prasad Phapale.

  Mass spectrometry imaging (MSI) has revolutionized the study of tissue metabolism by enabling the visualization of small molecule metabolites (SMMs) with high spatial resolution. However, comprehensive SMM imaging databases for different organ tissues are lacking, hindering our understanding of spatial organ metabolism. To address this resource gap, we present a large-scale SMM imaging gallery for mouse brain, kidney, and liver, capturing SMMs spanning eight chemical super classes and encompassing over 40 metabolic pathways. Manual curation and display of these imaging data sets unveil spatial patterns of metabolites that are less documented in the reported organs. Specifically, we identify 65 SMMs in brain coronal sections and 71 in sagittal tissue sections, including spatial patterns for neurotransmitters. Furthermore, we map 98 SMMs in kidneys and 66 SMMs in liver, providing insights into their amino acid and glutathione metabolism. Our insightful SMM imaging gallery serves as a critical resource for the spatial metabolism research community, filling a significant resource gap. This resource is freely available for download and can be accessed through the BioImage Archive and METASPACE repositories, providing high-quality annotated images for potential future computational models and advancing our understanding of tissue metabolism at the spatial level.

Keywords:  MALDI-MSI; imaging database; mass spectrometry imaging; metabolite imaging; organ metabolism; small molecules; spatial metabolomics; tissue metabolism

DOI:  https://doi.org/10.1021/acs.jproteome.4c00594
Clin Chem Lab Med. 2025 May 26. 63(s1): s23-s26

SYMPOSIUM 1 - New approaches for deriving and applying biological variation data for clinical use.

DOI: https://doi.org/10.1515/cclm-2025-8013
bioRxiv. 2025 Apr 13. pii: 2025.04.13.648568. [Epub ahead of print]

Single cell spatial proteomics maps human liver zonation patterns and their vulnerability to fibrosis.

Caroline A M Weiss, Lauryn A Brown, Lucas Miranda, Paolo Pellizzoni, Shani Ben-Moshe, Sophia Steigerwald, Kirsten Remmert, Jonathan Hernandez, Karsten Borgwardt, Florian A Rosenberger, Natalie Porat-Shliom, Matthias Mann.

Understanding protein distribution patterns across tissue architecture is crucial for deciphering organ function in health and disease. Here, we applied single-cell Deep Visual Proteomics to perform spatially-resolved proteome analysis of individual cells in native tissue. We combined this with a novel strategic cell selection pipeline and a continuous protein gradient mapping framework to investigate larger clinical cohorts. We generated a comprehensive spatial map of the human hepatic proteome by analyzing hundreds of individual hepatocytes from 18 individuals. Among more than 2,500 proteins per cell about half exhibited zonated expression patterns. Cross-species comparison with mouse data revealed conserved metabolic functions and human-specific features of liver zonation. Analysis of fibrotic samples demonstrated widespread disruption of protein zonation, with pericentral proteins being particularly susceptible. Our study provides a comprehensive resource of human liver organization while establishing a broadly applicable framework for spatial proteomics analyses along tissue gradients.

DOI: https://doi.org/10.1101/2025.04.13.648568
STAR Protoc. 2025 Apr 29. pii: S2666-1667(25)00187-X. [Epub ahead of print]6(2): 103781

Protocol for the use of Oredsson universal replacement medium for cell banking and routine culturing of monolayer and suspension cultures.

Stina Oredsson, Atena Malakpour-Permlid, Johan Zhu, Tilo Weber.

  The Oredsson universal replacement (OUR) medium is the formulation of a universal xeno-free medium designed for the cultivation of human normal and cancer cells in 2D and 3D cultures. Here, we present a protocol for the use of OUR medium for routine culturing, cell banking, and medium modification for suspension culture. We describe steps for thawing, sub-culturing, and freezing cells. We then detail procedures for using these techniques for VERO, A549, THP-1, and Jurkat cells.

Keywords:  Cancer; Cell culture; Cell-based assays

DOI:  https://doi.org/10.1016/j.xpro.2025.103781
Nat Metab. 2025 Apr 28.

Intracellular metabolic gradients dictate dependence on exogenous pyruvate.

Benjamin T Jackson, Angela M Montero, Sangita Chakraborty, Julia S Brunner, Paige K Arnold, Anna E Bridgeman, Pavlina K Todorova, Katrina I Paras, Lydia W S Finley.

During developmental transitions, cells frequently remodel metabolic networks, including changing reliance on metabolites such as glucose and glutamine to fuel intracellular metabolic pathways. Here we used embryonic stem (ES) cells as a model system to understand how changes in intracellular metabolic networks that characterize cell state transitions affect reliance on exogenous nutrients. We find that ES cells in the naive ground state of pluripotency increase uptake and reliance on exogenous pyruvate through the monocarboxylate transporter MCT1. Naive ES cells, but not their more committed counterparts, rely on exogenous pyruvate even when other sources of pyruvate (glucose, lactate) are abundant. Pyruvate dependence in naive ES cells is a consequence of their elevated mitochondrial pyruvate consumption at the expense of cytosolic NAD+ regeneration. Indeed, across a range of cell types, increased mitochondrial pyruvate consumption is sufficient to drive demand for extracellular pyruvate. Accordingly, restoring cytosolic NAD+ regeneration allows naive ES cells to tolerate pyruvate depletion in diverse nutrient microenvironments. Together, these data demonstrate that intracellular metabolic gradients dictate uptake and reliance on exogenous pyruvate and highlight mitochondrial pyruvate metabolism as a metabolic vulnerability of naive ES cells.

DOI: https://doi.org/10.1038/s42255-025-01289-8
Adv Sci (Weinh). 2025 Apr 26. e2503790

Composite Mapping for Peptide-Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles.

Anxun Zhang, Longjie Wang, Xiaowei Zhai, Yao Xiao, Yanchan Wu, Yongxi Zhao, Kai Liu, Ji-Shen Zheng, Dong Chen.

  Peptides are natural information-bearing mediums and are promising for high-density data storage. However, conventional mapping of one amino acid (AA) to one binary code has limited the improvement of coding density by increasing the total number of different AAs. Here, a novel composite mapping strategy is developed, where each position in the peptide sequence is a composite letter consisting of several different AAs, and thousands of composite letters are available for mapping, thus breaking the limit of conventional mapping. When 20 different AAs are used, the coding density of six-AAs composite mapping achieves 15 bits/letter, while conventional mapping only reaches 4 bits/AA. The whole process of encoding data into composite letter sequences, synthesizing composite letter sequences via solid-phase peptide synthesis, sequencing composite letter sequences by mass spectrometry, and decoding data from composite letter sequences is successfully demonstrated for the first time. Composite mapping also demonstrates several distinct advantages, including high coding density, few synthesis cycles, high reliability against errors, low probability of homopolymers, and good compatibility with other encoding algorithms. The developed composite mapping strategy provides a novel way for peptide-based data storage to increase the coding density and reduce the synthesis cycles, showing great potential for large-scale data storage.

Keywords:  composite mapping; data storage; mass spectrometry sequencing; solid‐phase peptide synthesis; statistical analysis

DOI:  https://doi.org/10.1002/advs.202503790