bims-mascan 2025-12-21 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–12–21
seventeen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

A Robust Strategy for High-Throughput and Deep Proteomics by Combining Narrow-Window Data-Independent Acquisition and Isobaric Mass Tagging.
Mass spectrometry protocol for tear fluid proteome profiling and biomarker discovery.
Epoxidation-Enhanced Charge-Switch Derivatization for Rapid Profiling of Monounsaturated Fatty Acid Isomers.
Data-Independent Acquisition Mass Spectrometry in Tumor Classification and Cancer Biomarker Research.
Proteostasis Modelling using Deuterated Water Metabolic Labeling and Data-Independent Acquisition Mass Spectrometry.
Blood Matrices and Sample Preparation Influence Blood Marker Discovery.
Middle-down proteomics: the pursuit for longer peptides.
An Analytical Perspective on Liquid Chromatography-Mass Spectrometry Methods for the Analysis of Bile Acids in Human Blood Samples.
In-Source Fragmentation Annotation in Sterol Mass Spectrometry Imaging.
A Taguchi Design of Experiments Approach for Untargeted Metabolomics Sample Preparation Optimization.
Subcellular proteome niche discovery using semi-supervised functional clustering.
Gut metabolism links precision nutrition, exercise, and healthspan in Drosophila melanogaster.
Rapid quantitation of NAD+/NADH and NADPH/NADP+ with mass spectrometry by using calibration constants.
An ultrasensitive spatial tissue proteomics workflow exceeding 100 proteomes per day.
mzLearn as a data-driven LC/MS signal detection algorithm that enables pre-trained generative models for untargeted metabolomics.
Development of a GC-MS/MS method to quantify 120 gut microbiota-derived metabolites.
Quantitative analysis of phylloquinone (vitamin K1) and menaquinone (vitamin K2) in serum of Russians by liquid chromatography-tandem mass spectrometry.

J Proteome Res. 2025 Dec 15.

A Robust Strategy for High-Throughput and Deep Proteomics by Combining Narrow-Window Data-Independent Acquisition and Isobaric Mass Tagging.

Chaewon Kang, Jiwon Hong, Hokeun Kim, JeongSu Jo, Jun-Hyeong Seo, Jeong-Won Lee, Sang-Won Lee.

  Data-independent acquisition (DIA) mass spectrometry systematically fragments all precursor ions within predefined isolation windows of a predefined mass-to-charge (m/z) range. Unlike data-dependent acquisition (DDA), which selects precursor ions based on intensity, DIA enhances identification and quantification opportunities for lower-intensity peptides, significantly improving proteome coverage. Nevertheless, standard DIA methodologies have limited application for isobaric-labeled peptides, primarily due to challenges in accurately quantifying reporter ions arising from coisolation interference from coeluting peptides, degrading quantitative precision and accuracy. Here, an ultra-narrow-window DIA workflow compatible with 18-plex TMTpro labeling is presented, a novel strategy overcoming a major limitation in conventional pipelines for isobaric labeling-based DIA analysis. Acquisition with an Orbitrap Astral mass spectrometer operating at 200 Hz MS/MS scan speed and 80,000 resolving power (m/z 200) enabled 0.6 Th isolation windows approaching DDA-level precursor specificity. Leveraging mPE-MMR, precursor masses were accurately assigned to multiplexed DIA spectra prior to conventional spectrum-centric database searching, permitting routine peptide-to-spectrum matching. Applied to ovarian cancer tissue digests, the method identified substantially more peptides and protein groups than did DDA analyses while sustaining reporter ion precision and accuracy. These gains translate into deeper proteomic coverage without compromising quantitative robustness for multiplexed proteomics, thereby holding significant potential for clinical and population-scale studies.

Keywords:  data-dependent acquisition (DDA); data-independent acquisition (DIA); mass spectrometry; multiplexed proteomics; quantitative proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.5c00501
STAR Protoc. 2025 Dec 15. pii: S2666-1667(25)00668-9. [Epub ahead of print]7(1): 104262

Mass spectrometry protocol for tear fluid proteome profiling and biomarker discovery.

Kirstine Juul-Elbaek, Maria Peiris-Pagès, Vyacheslav Akimov, Irene Rebollido-Pedrido, Mark Reardon, Blagoy Blagoev, Petra Hamerlik.

  Here, we present a protocol for tear fluid proteomics using Schirmer strips and liquid chromatography-tandem mass spectrometry (LC-MS/MS). It includes tear sampling from human individuals and mice, followed by protein digestion, peptide desalting, and purification via solid-phase extraction. Supporting both data-dependent acquisition (DDA) and data-independent acquisition (DIA), this 5-h workflow maximizes protein recovery, minimizes contaminants, and enables reproducible biomarker discovery for ocular, neurodegenerative, and systemic diseases. Tear fluid's non-invasive collection and rich proteome make it ideal for clinical proteomics and personalized medicine.

Keywords:  bioinformatics; cancer; proteomics

DOI:  https://doi.org/10.1016/j.xpro.2025.104262
Anal Chem. 2025 Dec 17.

Epoxidation-Enhanced Charge-Switch Derivatization for Rapid Profiling of Monounsaturated Fatty Acid Isomers.

Sarah E Hancock, Linda Garthwaite, Laura L Y Choong, Iliya Dragutinovic, Jonathan C Morris, Nigel Turner.

Structural isomerism in monounsaturated fatty acids (MUFAs) presents a persistent challenge in lipidomics due to limited chromatographic resolution and indistinguishable mass spectral profiles. Moreover, many methods that overcome these limitations require specialized instruments or additional apparatus that are typically not available for those using standard lipidomics core facilities. We report a streamlined LC-MS/MS method that integrates N-(4-aminomethylphenyl)pyridinium (AMP)-based charge-switch derivatization with meta-chloroperoxybenzoic acid (mCPBA) epoxidation to enable rapid and sensitive profiling of MUFA double bond positional isomers. Charge-switching enables enhanced detection of fatty acids, while epoxidation improves chromatographic resolution and produces diagnostic fragmentation patterns upon collision-induced dissociation (CID), enabling precise localization of double bond positions. The optimized workflow achieves baseline separation of 16:1, 18:1, and 20:1 MUFA isomers within a 20 min gradient, with reproducible retention times and consistent epoxide yields. The method also supports partial resolution of polyunsaturated fatty acids (PUFA) and cis/trans isomers. Application to prostate cancer cell lines revealed distinct MUFA isomer profiles associated with aberrant fatty acid desaturase 2 (FADS2) activity, including elevated n-10 and n-12 isomers in tumorigenic lines. These results align with prior studies using other isomer-resolving techniques, validating the method's analytical performance. This accessible and robust strategy expands the toolkit for lipidomics research, providing a method that is compatible with conventional LC-MS/MS workflows, positioning it as a practical solution for high-resolution isomer analysis in complex biological samples.

DOI: https://doi.org/10.1021/acs.analchem.5c06149
Mass Spectrom Rev. 2025 Dec 15.

Data-Independent Acquisition Mass Spectrometry in Tumor Classification and Cancer Biomarker Research.

Jan Simonik, Petr Lapcik, Pavla Bouchalova, Pavel Bouchal.

  Cancer treatment is far from optimal also because current classification systems do not reflect the complex molecular status of the tumor and its phenotype in sufficient detail. To construct molecular tumor classifiers, omics tools provide complex molecular data reflecting many aspects from genotype to phenotype. However, the true molecular effectors in the cells are proteins which often serve as potent cancer biomarkers and therapy targets. This review summarizes the method aspects that allowed the data-independent acquisition (DIA) mass spectrometry (MS) to outperform the traditional, data-dependent acquisition (DDA) approach in recent years. DIA-MS studies have already recapitulated molecular classification of colorectal and breast cancer, provided data improving molecular classification of prostate and other cancers, and led to validated diagnostic, prognostic, predictive biomarkers and therapy targets for common solid tumors. Tissue-specific spectral libraries are important for a deep characterization of tissue proteomes. Further perspectives of current cancer proteomics lie in the fields of single-cell and spatial proteomics and their integration with clinical data. The importance of functional and clinical validation is highlighted to allow stratified and/or personalized targeted therapy.

Keywords:  biomarker; cancer classification; data‐independent acquisition; formalin‐fixed paraffin‐embedded tissue; fresh frozen tissue; spectral library

DOI:  https://doi.org/10.1002/mas.70014
bioRxiv. 2025 Nov 28. pii: 2025.11.25.690247. [Epub ahead of print]

Proteostasis Modelling using Deuterated Water Metabolic Labeling and Data-Independent Acquisition Mass Spectrometry.

Henock M Deberneh, Daniel J Wilkinson, Hannah Crossland, Natan Basisty, Kenneth Smith, Philip J Atherton, Rovshan G Sadygov.

We present the first application of a deuterated water metabolic labeling workflow coupled with data-independent acquisition (DIA) tandem mass spectrometry (MS/MS) for quantifying label enrichment in MS/MS to study protein turnover. The approach automates the turnover rate determination from combined precursor and fragment ions. The truncation of the observed isotope distributions of fragments is overcome by implementing an approach to determining the label enrichment from two mass isotopomers. The high redundancy of fragment ions provides a confident assessment for deuterium enrichment. The DIA approach provides increased proteome coverage and depth for quantifying protein turnover rates compared to the traditional data-dependent (DDA) approach. This novel approach is validated in a murine myotube model of muscle hypertrophy and atrophy through the treatment with insulin-like growth factor 1 (IGF-1) and dexamethasone (Dex), respectively.

DOI: https://doi.org/10.1101/2025.11.25.690247
J Proteome Res. 2025 Dec 16.

Blood Matrices and Sample Preparation Influence Blood Marker Discovery.

Thomas F Gronauer, Juliane Merl-Pham, Christine von Toerne, Katharina Habler, Daniel Teupser, Stefanie M Hauck.

  While plasma and serum are widely used in high-throughput proteomics, the impact of different blood matrix types remains underexplored. Routine diagnostics most commonly use serum or Li-heparin plasma, while the proteomics community primarily focuses on advancing analytical depth in EDTA plasma. Here, we systematically investigated the LC-MS/MS proteomic profiles of pooled blood samples from three healthy, voluntary probands including serum (with/without separation gel) and plasma anticoagulated with EDTA, citrate, or Li-heparin. Sample preparation was conducted with the commercially available iST and ENRICH-iST kits, strong-anion exchange (SAX) beads, the TFA-based approach SPEED, and perchloric acid (perCA) precipitation. Mass-spectrometric measurements were performed on a Q Exactive HF-X and a timsTOF HT in data-independent acquisition mode (DIA). Protein identifications varied considerably across matrix types with EDTA plasma and serum outperforming citrate plasma. Sample preparation methods with SAX beads, ENRICH-iST, and perCA yielded the highest identification numbers but also showed increased variability. Across all samples, 181 protein groups overlapped for timsTOF HT data. Subsets of protein groups were specific for the matrix and preparation. This study shows a systematic approach to determining suitable sample preparation and matrix parameters for the robust identification of individual body fluid marker proteins by mass spectrometry.

Keywords:  ENRICH-iST; Mag-Net; SPEED; biomarkers; iST; mpwR; perCA; plasma; proteomics; serum

DOI:  https://doi.org/10.1021/acs.jproteome.5c00836
Expert Rev Proteomics. 2025 Dec 15.

Middle-down proteomics: the pursuit for longer peptides.

Owen F J Hovey, Gilles A Lajoie, Tyler T Cooper.

   INTRODUCTION: Middle-down proteomics (MDP) bridges bottom-up and top-down proteomics, analyzing 3-10 kDa peptides to enhance sequence coverage and post-translational modification (PTM) localization. This approach is crucial for decoding complex proteoforms and PTM networks, advancing insights into biological and disease processes. However, its application to complex samples like cell lysates or biofluids remains largely underexplored.
AREAS COVERED: This review examines MDP's potential in complex biological samples, focusing on sample preparation, chromatography, mass spectrometry, and bioinformatics. We explore sample lysis, protein precipitation, and alternative proteases (GluC, thermolysin), supported by in silico analyses revealing peptide length and charge distribution as key limitations for current enzymes. Advanced chromatographic techniques, ion mobility (FAIMS, TIMS), and fragmentation methods (ETD, EThcD) are discussed. Experimental challenges include peptide solubility, ionization efficiency, and bioinformatic complexity from missed cleavages and promiscuous protease specificity.
EXPERT OPINION: MDP offers significant potential to uncover the 'dark' proteome, including PTM-rich regions and proteoforms undetectable by traditional workflows. However, a focused effort on improving high-throughput workflows will require optimizations to enzyme selection, LC-MS parameters, peptide ionization, ion mobility, ion fragmentation, and tailored algorithms are essential to drive MDP's adoption. Only then will deeper proteomic insights and breakthroughs in biological research be obtained.

Keywords:  Mass spectrometry; Middle-down; Post-translational modifications; bioinformatics; chromatography; in silico Analysis; ion mobility; peptide fragmentation; protease; proteoforms; proteomics

DOI:  https://doi.org/10.1080/14789450.2025.2604157
Crit Rev Anal Chem. 2025 Dec 18. 1-17

An Analytical Perspective on Liquid Chromatography-Mass Spectrometry Methods for the Analysis of Bile Acids in Human Blood Samples.

Monika Sostaric, Hayley Abbiss, Armaghan Shafaei.

  Bile acids (BA) are traditionally recognized as detergents that facilitate lipid and glucose digestion and homeostasis. More recently, they have emerged as signaling molecules with the ability to influence metabolic processes via the gut-brain axis. BA are implicated in a wide range of diseases and conditions, including gastrointestinal, hepatobiliary, metabolic, cardiovascular, and neurological disorders. Accurate quantification of total bile acids (TBA) and individual BA species is essential for understanding their roles in health and disease. Liquid chromatography coupled with mass spectrometry (LC-MS) offers the sensitivity and selectivity required to detect these metabolites at trace levels in human blood samples. This systematic review critically examines validated LC-MS methodologies for BA analysis in human blood, focusing on studies published between January 2010 and April 2024. It highlights experimental designs, validation criteria, and methodological differences, aiming to inform the development of standardized analytical protocols. By addressing current gaps and emphasizing comprehensive analytical validation, this review seeks to enhance the reliability of BA quantification and support future biomarker discovery and clinical applications.

Keywords:  Bile acids; LC-MS; human blood; liquid chromatography; mass spectrometry

DOI:  https://doi.org/10.1080/10408347.2025.2599298
Anal Chem. 2025 Dec 17.

In-Source Fragmentation Annotation in Sterol Mass Spectrometry Imaging.

Iulia Sidorov, Nina Ogrinc, Lena Spieth, Michal Kopcil, Marieke Heijink, Hans Dalebout, Gesine Saher, Stefan A Berghoff, Gary Siuzdak, Martin Giera.

Spatial biology has emerged as a pivotal area in many life science fields, with mass spectrometry imaging (MSI) becoming a cornerstone for molecular imaging. Among recent advancements to increase sensitivity, MALDI-2 technology has significantly expanded the molecular space accessible to MSI, increasing the ion yields of neutral metabolites, such as sterols. Sterols have recently taken center stage in numerous (patho-) physiological processes, including neurodegenerative diseases that have attracted significant scientific interest. However, in-source fragmentation (ISF) poses a substantial challenge for accurate biological interpretation of mass spectrometric data. In this study, we observed and investigated the ISF of cholesterol during MSI under MALDI and MALDI-2 conditions. Using a murine intervention model, we demonstrate how ISF can compromise the accuracy of biological interpretations, potentially leading to significant misinterpretations. Our study underscores the critical need to address ISF to ensure accurate molecular annotation, particularly through tandem mass spectrometry of in-source fragments. This is especially important when using MALDI-2 techniques. Furthermore, we introduce a high-resolution (5 μm) MSI technique, enabling the precise spatial analysis of cholesterol distribution.

DOI: https://doi.org/10.1021/acs.analchem.5c05199
J Biomol Tech. 2025 Sep 30. 36(3):

A Taguchi Design of Experiments Approach for Untargeted Metabolomics Sample Preparation Optimization.

Brianna M Garcia, Goncalo J Gouveia, Amanda O Shaver, Ricardo M Borges, I Jonathan Amster, Arthur S Edison, Franklin E Leach Iii.

The field of metabolomics leverages advanced analytical techniques, such as nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS), to identify and quantify metabolites that are integral to biology. The scope of untargeted metabolomics methods is highly dependent on the protocols employed prior to analysis. These include homogenization and extraction processes, which directly influence the metabolites detected and, consequently, the biological interpretations drawn. Given the substantial variability introduced by different homogenization and extraction parameters, the optimization of these protocols for non-routine or novel sample matrices is essential, particularly in core facilities where a diverse range of matrices are expected to be analyzed. In response to this need, we demonstrate the utility of a Taguchi design of experiments (DOE) method for the systematic optimization of matrix-specific sample preparation parameters using the model organism Caenorhabditis elegans. This methodology was applied to optimize four critical factors: (1) extraction solvent, (2) solvent volume, (3) extraction duration, and (4) LC reconstitution solvent, during a sequential non-polar and polar metabolite extraction for LC-MS and NMR spectroscopy. Despite its infrequent use in metabolomics, the Taguchi DOE method offers a structured and efficient pathway for optimizing multiple sample preparation variables, enhancing throughput, reproducibility, and cost-effectiveness. This approach is particularly valuable for the metabolomics community, as it provides a scalable, adaptable framework applicable across various sample types and research objectives. This work serves as a demonstration of the methodology, underscoring its potential to enhance method development and optimization across diverse metabolomics applications.

DOI: https://doi.org/10.7171/3fc1f5fe.54585830
ArXiv. 2025 Dec 08. pii: arXiv:2512.08087v1. [Epub ahead of print]

Subcellular proteome niche discovery using semi-supervised functional clustering.

Ziyue Zheng, Loay J Jabre, Matthew McIlvin, Mak A Saito, Sangwon Hyun.

Intracellular compartmentalization of proteins underpins their function and the metabolic processes they sustain. Various mass spectrometry-based proteomics methods (subcellular spatial proteomics) now allow high throughput subcellular protein localization. Yet, the curation, analysis and interpretation of these data remain challenging, particularly in non-model organisms where establishing reliable marker proteins is difficult, and in contexts where experimental replication and subcellular fractionation are constrained. Here, we develop FSPmix, a semi-supervised functional clustering method implemented as an open-source R package, which leverages partial annotations from a subset of marker proteins to predict protein subcellular localization from subcellular spatial proteomics data. This method explicitly assumes that protein signatures vary smoothly across subcellular fractions, enabling more robust inference under low signal-to-noise data regimes. We applied FSPmix to a subcellular proteomics dataset from a marine diatom, allowing us to assign probabilistic localizations to proteins and uncover potentially new protein functions. Altogether, this work lays the foundation for more robust statistical analysis and interpretation of subcellular proteomics datasets, particularly in understudied organisms.
bioRxiv. 2025 Dec 02. pii: 2025.11.29.691311. [Epub ahead of print]

Gut metabolism links precision nutrition, exercise, and healthspan in Drosophila melanogaster.

Fangchao Wei, Shiyu Liu, Yudong Sun, Juan Liu.

Longevity-promoting interventions commonly entail functional trade-offs, raising the unresolved question of whether lifespan extension necessarily compromises physiological performance. Here, utilizing a chemically defined diet (CDD) in Drosophila melanogaster , we systematically evaluated a multimodal intervention combining methionine restriction (MR), taurine supplementation (Tau), and moderate exercise. This combinatorial approach synergistically extended lifespan, preserved reproductive capacity, and improved locomotor function. Integrative targeted metabolomics and stable isotope tracing revealed increased mitochondrial tricarboxylic acid (TCA) cycle flux and enhanced redox homeostasis in the gut as central metabolic features. Notably, Lactobacillus plantarum was identified as a key microbial mediator responsive to dietary and behavioral stimuli, potentially coordinating host energy metabolism and maintaining physiological integrity. Together, these observations outline a "nutrition-behavior-microbiota" framework that uncouples the traditional trade-off between lifespan and functional health, offering new perspectives for promoting healthy aging.

DOI: https://doi.org/10.64898/2025.11.29.691311
Redox Biol. 2025 Nov 29. pii: S2213-2317(25)00466-5. [Epub ahead of print]89 103953

Rapid quantitation of NAD+/NADH and NADPH/NADP+ with mass spectrometry by using calibration constants.

Qiuyuan Guo, Mike Lingjue Wang, Michaela Schwaiger-Haber, Xiangfeng Niu, Shanshan Zhang, Leah P Shriver, Gary J Patti.

  NAD+/NADH and NADPH/NADP+ are important indicators of cellular redox status, but they cannot be reliably calculated from the relative intensities of mass spectrometry signals alone. Establishing accurate redox ratios by mass spectrometry has historically required converting relative signal intensities into absolute concentrations, which is a time-consuming process that limits rapid analysis. Here, we describe a simpler strategy to determine NAD+/NADH and NADPH/NADP+ by using mass spectrometry. While ionization is strongly influenced by factors such as instrument drift and sample type, we discovered that the relative signal intensities of oxidized and reduced cofactors change at the same rate across experiments performed on the same mass spectrometer. That rate can be experimentally determined and expressed as a calibration constant. Using calibration constants, relative intensities of mass spectrometry signals can be rapidly transformed into accurate redox ratios without the use of authentic standards or isotopically labeled internal standards. We present a metabolomics workflow to measure NAD+/NADH and NADPH/NADP+ by using calibration constants and compare the results to other methods, including commercial colorimetric assays. Although colorimetric assays are the most widely used, we demonstrate that mass spectrometry quantitation with calibration constants provides more accurate results.

Keywords:  Calibration constants; LC/MS; Metabolomics; NAD(+)/NADH; NADPH/NADP(+); Nicotinamide adenine dinucleotide; Nicotinamide adenine dinucleotide phosphate

DOI:  https://doi.org/10.1016/j.redox.2025.103953
Mol Cell Proteomics. 2025 Dec 17. pii: S1535-9476(25)00588-2. [Epub ahead of print] 101489

An ultrasensitive spatial tissue proteomics workflow exceeding 100 proteomes per day.

Melissa Klingeberg, Christoph Krisp, Sonja Fritzsche, Simon Schallenberg, Daniel Hornburg, Fabian Coscia.

Achieving high-resolution spatial tissue proteomes requires careful balancing and integration of optimized sample processing, chromatography, and MS acquisition. Here, we present an advanced cellenONE protocol for loss-reduced tissue processing and compare all Evosep ONE Whisper Zoom gradients (20, 40, 80, and 120 samples per day), along with three common DIA acquisition schemes on a timsUltra AIP mass spectrometer. We found that tissue type was as important as gradient length and sample amount in determining proteome coverage. Moreover, the benefit of increased tissue sampling was gradient- and dynamic range-dependent. Analyzing mouse liver, a high dynamic range tissue, over tenfold more tissue sampling led to only ∼30% gain in protein identification for short gradients (120 SPD and 80 SPD). However, even the lowest tested tissue amount (0.04 nL) yielded 3,200 reproducibly quantified proteins for the 120 SPD method. Longer gradients (40 SPD and 20 SPD) instead significantly benefited from more tissue sampling, quantifying over 7,500 proteins from 0.5 nL of tonsil T-cell niches. Finally, we applied our workflow to a rare squamous cell carcinoma of the oral cavity, uncovering disease-associated pathways and region-specific protein level changes. Our study demonstrates that more than 100 high-quality spatial tissue proteomes can be prepared and acquired daily, laying a strong foundation for cohort-size spatial tissue proteomics in translational research.

DOI: https://doi.org/10.1016/j.mcpro.2025.101489
Commun Chem. 2025 Dec 18. 8(1): 398

mzLearn as a data-driven LC/MS signal detection algorithm that enables pre-trained generative models for untargeted metabolomics.

Leila Pirhaji, Jonah Eaton, Adarsh K Jeewajee, Min Zhang, Matthew Morris, Maria Karasarides.

Metabolite alterations are linked to diseases, yet large-scale untargeted metabolomics remains constrained by challenges in signal detection and integration of diverse datasets for developing pre-trained generative models. Here, we introduce mzLearn, a data-driven MS¹ signal-detection and alignment method that runs from mzML files without user-set parameters. Across 15 public datasets, mzLearn detects 11,442 signals on average vs 7,100 (XCMS) and 4,655 (ASARI), with higher TP (89.0% vs 77.4% vs 49.6%) and lower FP (12.5% vs 17.3% vs 18.8%), while correcting instrument drifts across large cohorts without experimental QC samples. mzLearn detected 2,736 robust metabolite signals from 22 public studies (20,548 blood samples), enabling the development of pre-trained variational autoencoder for untargeted metabolomics. Learned metabolite representations reflected demographic data and when fine-tuned on unseen renal cell carcinoma data, improved risk stratification and overall survival predictions, while feature-importance analysis (SHAP) highlighted biologically plausible lipid and carnitine signals. By producing a consistent, high-quality MS¹ feature matrix at scale, mzLearn paves the way for developing pre-trained foundation models for untargeted metabolomics.

DOI: https://doi.org/10.1038/s42004-025-01791-w
Anal Bioanal Chem. 2025 Dec 15.

Development of a GC-MS/MS method to quantify 120 gut microbiota-derived metabolites.

Nikita Denisov, Fabian Springer, Amber Brauer-Nikonow, George Maftei, Georg Zeller, Denise Medeiros Selegato, Michael Zimmermann.

  The gut microbiota produces metabolites that are important for host physiology and have critical roles in the development of diseases, such as metabolic disorders, cardiovascular diseases, and cancer. Here, we developed a gas chromatography-coupled tandem mass spectrometry (GC-MS/MS) method for the quantification of 120 volatile and semi-volatile compounds produced by gut bacteria, including short-chain fatty acids, indols, nucleotides, organic acids, and amino acid derivatives. The method is based on multiple-reaction-monitoring (MRM) of each analyte and their respective isotopically labeled internal standard, enabling absolute metabolite quantification between 0.45 pmol and 1 nmol. Applying the method to different tissue samples from germfree and conventionally colonized mice, we illustrate the ability to quantify microbiota-produced metabolites in different sample matrices-plasma, liver, feces, and intestinal content-and at different concentrations. Lastly, we demonstrate that this protocol is capable of quantifying microbiota-derived metabolites in stool samples stored in DNA stabilization buffers that are typically used in sequencing-based microbiome studies. Altogether, the developed GC-MS/MS method adds a valuable analytical tool to quantify microbiota-host metabolic interactions.

Keywords:  Bacterial metabolites; DNA stabilization buffers; GC-MS/MS; Gut microbiota

DOI:  https://doi.org/10.1007/s00216-025-06256-6
Clin Chem Lab Med. 2025 Dec 16.

Quantitative analysis of phylloquinone (vitamin K1) and menaquinone (vitamin K2) in serum of Russians by liquid chromatography-tandem mass spectrometry.

Mikhail Vokuev, Anastasia Frolova, Stepan Makarkin, Daria Prosuntsova, Timur Baygildiev, Lidia Nefedova, Oleg Klychnikov, Igor Rodin.

   OBJECTIVES: Vitamin K homologues are essential to human health, and their concentrations in biological samples serve as valuable diagnostic biomarkers. This study was aimed to develop a method for determining vitamins K1 (phylloquinone, VK1) and K2 (menaquinone, MK-4) in human serum. The proposed method was validated and applied to the serum of a cohort of 20 Russian individuals.
METHODS: High-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) was used to analyse the content of VK1 and MK-4 in serum. Atmospheric pressure chemical ionisation (APCI) in negative mode was applied to ionise VK1 and MK-4. Protein precipitation and solid-phase extraction (SPE) on polystyrene-divinylbenzene resin were combined to isolate and preconcentrate the analytes from serum.
RESULTS: The HPLC-MSMS method was developed and validated for the determination of vitamins VK1 and MK-4 in human serum. The method demonstrated a lower limit of quantification (LLOQ) of 0.05 μg/L, with more than 71 % recoveries and precision within 17 %. To demonstrate the applicability of the method to real samples, serum from 20 healthy adults was analyzed. VK1 was detected in four individuals (0.094-0.96 μg/L), whereas MK-4 concentrations were below 0.22 μg/L in all cases.
CONCLUSIONS: The validated HPLC-MS/MS workflow provides a reliable and sensitive approach for the quantification of VK1 and MK-4 in minimal serum volumes. The method demonstrates robustness, reproducibility, and suitability for large-scale analytical applications. The proposed LC-MS/MS protocol successfully applied to native human serum samples, illustrating its applicability for future clinical and biochemical studies involving vitamin K.

Keywords:  liquid chromatography; menaquinone; phylloquinone; serum levels; tandem mass spectrometry; vitamins

DOI:  https://doi.org/10.1515/cclm-2025-0719