bims-mascan 2026-03-01 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2026–03–01
twenty-one papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Systematic Evaluation of Data-independent Acquisition Workflows for High-Throughput and Low-Input Proteomics Analysis with an Astral Mass Spectrometer.
Mass Spectrometry-Based Integrated Multiomics Platforms for Medicinal Plant Analysis.
Modeling lipid homeostasis using stable isotope tracing and flux analysis.
xTracer: Integrating chromatogram and mobiligram correlations for untargeted peptide identification in SLIM-based PAMAF data.
Pho-Tip: One-Pot Dephosphorylation for Rapid and Sensitive Analysis of DIA Phosphoproteomics Data.
Best practices for cysteine analysis.
Integrated Multi-Omics Enabled by Sequential Extraction for Comprehensive Molecular Profiling of Small Extracellular Vesicles.
High-throughput reaction screening using acoustic ejection mass spectrometry.
Large-scale proteomics across neurological disorders uncovers biomarker panel and targets in multiple sclerosis.
Unlocking the Bile Acid Universe: Advanced Workflows and a Multidimensional Library of 280 Unique Species.
Definition of Metabolite: Size as a Critical Criterion.
Label-free quantitative proteomics analysis of sea cucumber (Apostichopus japonicus) from different origins using data-independent acquisition mass spectrometry.
A Practical Roadmap for Clinical Translation of Metabolic Biomarkers: A Review.
Spatial Profiling of Glycosaminoglycans (GAGomics) from Laser Microdissected Mouse Brain.
Chemical reaction-enabled lipidomics: from sensitive structural analysis to biomedical applications.
Navigating the conjugated metabolome.
Mass spectrometry analysis of young and aged mice and human Alzheimer's disease with Lewy body pathology using on-slide tissue digestion.
Receptor-Mitochondria Crosstalk in the Kynurenine Metabolic Pathway: Integrating Metabolomics and Clinical Mass Spectrometry.
Metabolic Vulnerabilities as a Therapeutic Target in Breast Cancer.
A Validated Mass Spectrometry Platform for Oxysterol Analysis of Single Human Gastruloids and Liver Organoids.
Integrated GC-EI-HRMS and LC-ESI-HRMS workflow along with molecular networking for untargeted identification of new psychoactive substances.

J Proteome Res. 2026 Feb 25.

Systematic Evaluation of Data-independent Acquisition Workflows for High-Throughput and Low-Input Proteomics Analysis with an Astral Mass Spectrometer.

Zhichang Yang, Taylur P Ma, Meena Choi, Fengchao Yu, Ying Zhu.

  There is a growing interest in developing high-throughput and high-sensitivity mass spectrometry methods for proteomic profiling of low-input samples, such as sorted cells or spatially resolved tissue samples. Data-independent acquisition mass spectrometry (DIA-MS) coupled with short-gradient liquid chromatography (LC) is gaining significant attention for providing deep proteome coverage in low-input samples, particularly with the recent release of high-speed mass spectrometers. However, the quantification performance of existing DIA workflows for low-input samples has not been extensively evaluated, and there is no consensus on optimal informatics workflows to obtain high-quality quantitative data. As such, we systematically evaluated multiple factors in low-input DIA workflows on an Astral MS, including MS acquisition parameters, data analysis software (DIA-NN, Spectronaut, and FragPipe), LC separation gradient lengths, database searching algorithms, and protein quantification approaches. Using three-species proteome samples (human, yeast, and Escherichia coli) with total input ranging from 0.1 ng to 10 ng and predefined quantity ratios, we focused on proteome coverage, quantification accuracy, and precision, which are the most important considerations when applying these methods in biological applications. Our evaluation suggested a preferred DIA workflow for low-input samples, which involves using a FAIMS interface, DIA-NN-based library-free database search with the enabled match between runs (MBR) function, and MS1-level protein quantification with the maxLFQ algorithm.

Keywords:  FAIMS; MS1-level quantification; data-independent acquisition; high throughput; low input; quantification accuracy; sensitivity; software

DOI:  https://doi.org/10.1021/acs.jproteome.5c01028
Curr Protoc. 2026 Feb;6(2): e70334

Mass Spectrometry-Based Integrated Multiomics Platforms for Medicinal Plant Analysis.

Cemil Can Eylem, Sevilay Erdoğan Kablan, Tuba Reçber, Engin Koçak, Emirhan Nemutlu.

  Plant-based multiomics approaches provide powerful tools for elucidating metabolic regulation, biochemical diversity, and functional responses to genetic and environmental variation. However, plant matrices pose unique analytical challenges due to their chemical complexity, high levels of secondary metabolites, and strong matrix effects that can compromise reproducibility if workflows are not carefully standardized. This article presents a comprehensive and integrated set of protocols for untargeted plant metabolomics, lipidomics, and proteomics, coupled with robust data processing, statistical analysis, and multiomics integration strategies. The protocols describe harmonized workflows for sample collection, preparation, and analysis using gas chromatography-mass spectrometry (GC-MS)-based metabolomics, liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-qTOF-MS)-based metabolomics, liquid chromatography-mass spectrometry (LC-MS)-based lipidomics, and microflow LC-MS/MS-based proteomics. Emphasis is placed on critical parameters specific to plant matrices, including complete solvent removal prior to GC-MS derivatization, optimized MS/MS acquisition strategies for high-confidence annotation, and quality control-driven experimental design. Detailed guidance is provided for instrument maintenance, QC strategies, and prevention of analytical artifacts. In addition, the article outlines best practices for data preprocessing, metabolite and lipid annotation, statistical analysis, pathway mapping, and integration of metabolomics with proteomics data to support biologically meaningful interpretation. Collectively, these protocols enable reproducible, high-quality plant multiomics studies and are suitable for both method development and large-scale comparative analyses across plant species, tissues, and experimental conditions. © 2026 Wiley Periodicals LLC. Basic Protocol 1: Plant material collection, handling, and extraction processing Support Protocol 1: Soxhlet extraction Alternate Protocol 1: Dichloromethane (DME)-based sample preparation for lipidomics Alternate Protocol 2: Methyl-tert-butyl ether (MTBE)-based sample preparation for lipidomics Basic Protocol 2: GC-MS-based metabolomics analysis Basic Protocol 3: LC-qTOF-MS-based metabolomics analysis Basic Protocol 4: LC-MS-based lipidomics analysis Basic Protocol 5: Microflow LC-MS/MS-based proteomics analysis Basic Protocol 6: Multiomics data integration and statistical analysis.

Keywords:  GC‐MS; LC‐MS; lipidomics; metabolomics; multiomics integration; plant; proteomics

DOI:  https://doi.org/10.1002/cpz1.70334
Cell Metab. 2026 Feb 20. pii: S1550-4131(26)00020-3. [Epub ahead of print]

Modeling lipid homeostasis using stable isotope tracing and flux analysis.

Karl Wessendorf-Rodriguez, Maureen L Ruchhoeft, Christopher W Murray, Yale Huang, Ethan L Ashley, Hector M Galvez, Grace H McGregor, Shrikaar Kambhampati, Reuben J Shaw, Christian M Metallo.

  Lipids enable compartmentation and coordinate membrane-localized signaling events in cells, and dysregulation of lipid metabolism is linked to many disease states. However, limited tools are available for quantifying metabolic fluxes across the lipidome. To measure fluxes encompassing lipid homeostasis in cells and tissue slices, we apply stable isotope tracing, liquid chromatography-high-resolution mass spectrometry, and network-based isotopologue modeling to non-small cell lung cancer (NSCLC) models. Lipid metabolic flux analysis (Lipid-MFA) enables quantitation of fatty acid synthesis, elongation, headgroup assembly, and salvage reactions within virtually any biological system. Using Lipid-MFA, we observed decreased fatty acid synthase and very long-chain fatty acid (VLCFA) elongation fluxes, along with increased sphingolipid recycling, in p53-deficient versus liver kinase B1 (LKB1)-deficient NSCLC tumors using precision-cut lung slice culture. We also apply Lipid-MFA to demonstrate the unique trafficking of ceramides with distinct n-acyl chain lengths, highlighting the utility of this approach in elucidating molecular mechanisms in lipid homeostasis.

Keywords:  ELOVL1; LKB1; TP53; ceramide; lipid homeostasis; metabolic flux analysis; non-small cell lung cancer; precision-cut lung slice culture; sphingolipids; very long-chain fatty acids

DOI:  https://doi.org/10.1016/j.cmet.2026.01.020
bioRxiv. 2026 Feb 13. pii: 2026.02.11.705440. [Epub ahead of print]

xTracer: Integrating chromatogram and mobiligram correlations for untargeted peptide identification in SLIM-based PAMAF data.

Jian Song, Liulin Deng, Lauren Royer, Bennett Kalafut, Daniel DeBord, Jesse G Meyer.

Parallel Accumulation with Mobility-Aligned Fragmentation (PAMAF) achieves near-complete ion utilization and high spectral specificity by fragmenting all mobility-separated precursors without quadrupole isolation. Leveraging the ultrahigh mobility resolution of SLIM, this quadrupole-free strategy maximizes ion utilization efficiency and offers a promising approach in mass spectrometry-based proteomics, particularly for low-abundance peptides or low-input samples. However, the unique data structure of PAMAF where precursor-fragment relationships are encoded along the mobility dimension renders it incompatible with existing peptide identification tools. Here, we present xTracer, the first untargeted peptide identification algorithm developed specifically for PAMAF data. xTracer integrates correlations across both chromatographic and mobility dimensions to associate precursor and fragment ions, reconstruct pseudo-spectra, and enable database searching using well-established DDA search engines. Applied to datasets with varying sample loads and acquisition throughputs, xTracer consistently achieved robust and reproducible peptide identifications, outperforming single-domain correlation strategies. Overall, xTracer provides a versatile and high-efficiency computational framework for reconstructing pseudo-spectra from quadrupole-free, mobility-aligned fragmentation data, enhancing the analytical power of high-resolution ion mobility (HRIM)-based proteomics.

DOI: https://doi.org/10.64898/2026.02.11.705440
Anal Chem. 2026 Feb 23.

Pho-Tip: One-Pot Dephosphorylation for Rapid and Sensitive Analysis of DIA Phosphoproteomics Data.

Katharina D Faisst, Kate Lau, Ludwig R Sinn, Lukasz Szyrwiel, Vadim Demichev.

Recent advances in instrumentation and data processing have transformed data-independent acquisition (DIA) proteomics into a reliable technology for quantitative profiling of post-translational modifications. However, analysis of DIA phosphoproteomics data is challenging due to the large search space, wherein all combinations of phosphosites on a peptide need to be considered. Current approaches therefore face significant hurdles in detecting low-abundant phosphorylated peptides, in particular when working with low sample amounts. Here we introduce Pho-Tip, a lossless one-pot dephosphorylation strategy. We show that Pho-Tip enables comprehensive mapping of phosphorylated peptide sequences, facilitating streamlined creation of experiment-focused in silico predicted spectral libraries and thus rapid and sensitive analysis of DIA phosphoproteomics experiments.

DOI: https://doi.org/10.1021/acs.analchem.5c07139
Ferroptosis Oxid Stress. 2026 ;pii: 202508. [Epub ahead of print]2

Best practices for cysteine analysis.

Feroza K Choudhury, Gina M DeNicola.

  Accurate measurement of cysteine and related thiol-containing metabolites is essential for understanding cellular redox regulation. However, the intrinsic reactivity and instability of cysteine present substantial analytical challenges. This review summarizes the biochemical context of cysteine and glutathione metabolism, emphasizing their dynamic redox equilibria and physiological relevance. We critically examine existing analytical approaches, including mass spectrometry-based, enzyme-coupled, and colorimetric methods, and discuss their respective strengths and limitations. Particular attention is given to sample preparation, derivatization strategies, and reagent selection, as these steps are crucial for preserving native thiol-disulfide status. Among various alkylating agents, N-ethylmaleimide is identified as the most reliable for thiol stabilization in liquid chromatography-mass spectrometry (LC-MS) workflows, while specific reagents such as monobromobimane or β-(4-hydroxyphenyl)ethyl iodoacetamide (HPE-IAM) are required for persulfide and polysulfide detection. The review also highlights the pitfalls of using indirect surrogates-such as glutathione or cystathionine levels-to infer cysteine availability, which can lead to significant misinterpretation of metabolic states. We conclude that direct LC-MS-based quantification of cysteine and glutathione, combined with careful derivatization and sample handling, remains the most reliable and accurate approach currently available for the assessment of thiol metabolism and redox homeostasis.

Keywords:  Cysteine; LC-MS; N-ethylmaleimide; derivatization; glutathione; redox homeostasis; thiol analysis

DOI:  https://doi.org/10.70401/fos.2025.0010
bioRxiv. 2026 Feb 20. pii: 2026.02.19.706688. [Epub ahead of print]

Integrated Multi-Omics Enabled by Sequential Extraction for Comprehensive Molecular Profiling of Small Extracellular Vesicles.

Andrew J Perciaccante, Holden T Rogers, Yanlong Zhu, Aditi Barnwal, David Inman, Man-Di Wang, Song Jin, Suzanne M Ponik, Ying Ge.

Small extracellular vesicles (sEVs) are membrane-bound particles whose protein, lipid, and metabolite cargo reflects the molecular state of their cells of origin, making them attractive targets for biomarker discovery and therapeutic development. However, comprehensive characterization of sEVs remains challenging due to the extremely limited material available. Here, we present an integrated mass spectrometry-based multi-omics platform for simultaneous characterization of lipids, metabolites, and proteins from a single sEV sample enabled by sequential extraction, maximizing sample utilization. To enhance molecular coverage and analytical depth, the platform combines iterative tandem mass spectrometry for improved small-molecule fragmentation and nano-flow proteomics with data-independent acquisition. We achieved deep and reproducible multi-omic characterization of proteins, lipids, and metabolites using 10 million sEVs. We further demonstrated the compatibility of our multi-omics platform with sEVs isolated from plasma by ultracentrifugation, size-exclusion chromatography with ultrafiltration, and polymer precipitation, revealing purification-dependent differences in molecular profiles associated with tradeoffs in yield and purity of sEVs. By enabling integrated multi-omics from the same sample, this strategy addresses a key challenge in low-input sEV analysis and establishes a robust analytical foundation for synergistic biomarker discovery and therapeutic applications.

DOI: https://doi.org/10.64898/2026.02.19.706688
Nat Protoc. 2026 Feb 23.

High-throughput reaction screening using acoustic ejection mass spectrometry.

Maowei Hu, Daniel J Blair.

High-throughput chemical synthesis plays a critical role in generating compound libraries and optimizing reaction conditions. Increasing adoption of robots and multiwell formats means that hundreds of reactions can be accessed with ease. However, conventional methods for quantitative detection of the product (for example, by liquid chromatography-mass spectrometry) create a bottleneck in the workflow because analyses need to be customized separately for each sample. Here we describe a tandem mass spectrometry approach where the samples are analyzed directly using acoustic ejection mass spectrometry. This approach features simple method development enabling accurate quantification for reactions where a characteristic neutral lost fragment is common to both the chemical starting material and the expected reaction products. Combining this precise fragmentation signature with acoustic ejection mass spectrometry allows whole 384-well plates of chemical reaction data to be collected at the same pace as two liquid chromatography-mass spectrometry samples, while maintaining the same levels of accuracy. To explain the principles involved in designing these experiments, we show four examples of common medicinal chemistry transformations for C-N and C-C bond formation that have been used in the synthesis of analogs of cereblon binding molecular glues, antifungals, antibiotics, and building blocks for automated small molecule synthesis. The whole procedure requires ~2 days of work to complete, including the 384-well plate reaction setup, analytical sample preparation, mass spectrometry data collection and analysis.

DOI: https://doi.org/10.1038/s41596-025-01320-y
Cell. 2026 Feb 25. pii: S0092-8674(26)00104-2. [Epub ahead of print]

Large-scale proteomics across neurological disorders uncovers biomarker panel and targets in multiple sclerosis.

Jakob Maximilian Bader, Christine Makarov, Sabrina Richter, Maximilian Thomas Strauss, Friederike Held, Maria Wahle, Michael Baggio Lorenz, Lara Pöschl, Patricia Skowronek, Marvin Thielert, Achim Berthele, Wen-Feng Zeng, Constantin Ammar, Isabell Bludau, Benjamin Schubert, Fabian J Theis, Christiane Gasperi, Bernhard Hemmer, Matthias Mann.

  Cerebrospinal fluid (CSF) is central to neurological diagnostics, yet biomarkers are lacking for many clinical needs. To enable its large-scale proteomic characterization, we developed a high-throughput mass spectrometry workflow quantifying approximately 1,500 proteins per CSF sample across 5,000 individuals, covering a spectrum of neurological disorders. This revealed proteomic alterations associated with blood-CSF barrier impairment, age, and sex, enabling deconvolution of shared and disease-specific signatures. We then focused on multiple sclerosis (MS), using an improved analytical technology that quantified 2,100 proteins per sample. From these data, we derived a 22-protein panel that distinguished MS from related inflammatory diseases and outperformed established markers in challenging cases. A targeted mass spectrometry assay using isotope-labeled standards validated this panel in an independent cohort, offering a clinically compatible format. Additionally, we highlight proteins of therapeutic interest and demonstrate proteome-based staging of individuals along the relapsing-progressive MS spectrum, which correlates with clinical outcomes.

Keywords:  biomarkers; blood CSF barrier impairment; cerebrospinal fluid; multiple sclerosis; oligoclonal bands; proteomics; targeted mass spectrometry

DOI:  https://doi.org/10.1016/j.cell.2026.01.017
bioRxiv. 2026 Feb 19. pii: 2026.02.18.706700. [Epub ahead of print]

Unlocking the Bile Acid Universe: Advanced Workflows and a Multidimensional Library of 280 Unique Species.

Guozhi Zhang, Emily C Vincent, Sadie M Disselkoen, James N Dodds, Quentin DuVal-Smith, Abubaker Patan, Ipsita Mohanty, Victoria Deleray, Jian Zhang, Paul A Thiessen, Evan E Bolton, Emma L Schymanski, Pieter C Dorrestein, Casey M Theriot, Erin S Baker.

Microbes and bile acids are tightly intertwined, especially in the gut. While the liver produces primary bile acids from cholesterol, gut bacteria transform these into diverse secondary forms which act as powerful signaling molecules, influencing host metabolism and immune function. Since bile acid changes are increasingly linked to health and disease, their accurate measurement in the gut and circulation is essential. Analytical evaluations, however, remain challenging as many bile acids co-elute in liquid chromatography (LC), share identical precursor masses in mass spectrometry (MS), and produce similar tandem mass spectrometry (MS/MS) spectra. As a result, conventional LC-MS/MS workflows struggle to differentiate bile acids, motivating the addition of orthogonal separations such as ion mobility spectrometry (IMS). Here, we assess optimal bile acid extraction parameters for stool, serum, and plasma; compare LC conditions; and assess electrospray ionization performance across polarities. Additionally, we created a multidimensional reference library containing LC retention times, IMS collision cross section values, and accurate precursor masses for 280 unique bile acids (264 endogenous and 16 deuterium-labeled species) including unconjugated, host-conjugated, and microbially conjugated bile acids. This multidimensional library empowers bile acid identification in complex samples and enables a more comprehensive exploration of their biological roles and disease associations.

DOI: https://doi.org/10.64898/2026.02.18.706700
J Proteome Res. 2026 Feb 24.

Definition of Metabolite: Size as a Critical Criterion.

Aldo Moreno-Ulloa.

  Metabolites have traditionally been defined as organic molecules smaller than 1500 daltons (Da). However, recent advances in analytical technologies and chemoinformatics have uncovered a wider chemical diversity, including biologically significant metabolites exceeding this conventional size cutoff─such as polypeptides, glycosphingolipids, and bacterial lipopolysaccharides. Detecting these larger metabolites challenges standard metabolomics approaches and necessitates optimized mass spectrometry acquisition parameters. In this perspective, the analysis of multiple databases (HMDB blood, GNPS, Plant Molecular Network [PMN], Natural Product Atlas [NPA] fungi, NPA bacteria, and MiMeDB) confirms that although most metabolites are below 1000 Da, notable populations exceed this threshold, particularly in bacterial data sets. Furthermore, reanalysis of liquid chromatography-mass spectrometry (LC-MS2) data sets from diverse biological samples, especially bacteria-rich matrices like feces and skin, reveals features (peaks with m/z and retention time) extending beyond 1500 m/z. These findings underscore that metabolites are often larger than commonly recognized in the literature. Therefore, the definition of metabolites should evolve to accommodate their size diversity, ensuring accurate knowledge dissemination to new generations of metabolomics researchers.

Keywords:  mass spectrometry; metabolite; metabolomics; size; spectral library

DOI:  https://doi.org/10.1021/acs.jproteome.5c00747
Food Chem X. 2026 Feb;34 103666

Label-free quantitative proteomics analysis of sea cucumber (Apostichopus japonicus) from different origins using data-independent acquisition mass spectrometry.

Qiong Wu, Xiliang Yu, Shiwei Wan, Houde Cai, Jian Jiao, Jiaojiao Shi, Xiuping Dong.

  Sea cucumbers (Apostichopus japonicus) from Liaoning, China command premium market value due to superior collagen integrity, yet the proteomic basis of this geographical differentiation remains unclear. Current geographic proteomic studies using data-dependent acquisition (DDA) mass spectrometry face stochastic ion selection bias, poor low-abundance reproducibility and limited coverage. Here, we established a custom label-free data-independent acquisition (DIA) workflow to characterize proteomic profiles of 200 sea cucumbers (80 Liaoning, 120 non-Liaoning). Our approach identified 6278 proteins and discovered 64 differentially expressed proteins (DEPs), including arginase (A0A141R8A8) and glutamine synthetase (A0A076VCY3) as potential authentication markers. Functional annotation highlighted arginine biosynthesis (P = 0.00034) as the pivotal pathway, alongside two-component system and necroptosis, indicating nitrogen homeostasis prioritization and stress adaptation in Liaoning specimens. This study provides a novel DIA-based framework for discovering the proteomic basis of geographical differentiation, linking nitrogen metabolism to regional quality differences in marine foods and identifying potential molecular targets for future authentication efforts.

Keywords:  Data-independent acquisition; Food authentication; Geographical traceability; Proteomics; Sea cucumber

DOI:  https://doi.org/10.1016/j.fochx.2026.103666
Int J Mol Sci. 2026 Feb 21. pii: 2030. [Epub ahead of print]27(4):

A Practical Roadmap for Clinical Translation of Metabolic Biomarkers: A Review.

Kyung-Hee Kim, Maro Yoo, Min Yeong Choi, Byong Chul Yoo.

  Metabolomics and lipidomics enable comprehensive profiling of metabolic states across diverse diseases and have generated a vast number of candidate biomarkers. Despite this progress, only a small fraction of metabolite-based biomarkers have achieved durable clinical translation. While this gap is often attributed to biological complexity or limited cohort size, increasing evidence suggests that failure more commonly reflects systematic misalignment between analytical measurement, biological interpretation, and clinical decision-making requirements. In this review, we argue that metabolites are not intrinsically unreliable biomarkers but are frequently overinterpreted as disease-specific indicators despite being highly context-dependent reporters of physiological state. We synthesize recurrent failure modes across the translational pipeline-including pre-analytical instability, ionization bias and semi-quantitative measurement, structural and annotation ambiguity, statistical overfitting, loss of disease specificity under systemic stress, and cohort-dependent performance collapse. Building on these insights, we propose a structured roadmap for the clinical translation of metabolite and lipid biomarkers. Rather than emphasizing further discovery, this framework prioritizes decision-oriented eligibility criteria encompassing pre-analytical robustness, analytical validity, molecular definition, biological interpretability, validation under real-world heterogeneity, and alignment with clinical utility and regulatory expectations. By reframing metabolic biomarkers as context-sensitive measurements embedded within clinical decision systems, this review provides practical guidance for investigators, clinicians, and regulators seeking to translate metabolomics and lipidomics into reliable tools for clinical practice.

Keywords:  analytical validity; biomarker translation; clinical validation; cohort heterogeneity; lipidomics; metabolomics; multi-metabolite panels

DOI:  https://doi.org/10.3390/ijms27042030
Mol Cell Proteomics. 2026 Feb 19. pii: S1535-9476(26)00029-0. [Epub ahead of print] 101533

Spatial Profiling of Glycosaminoglycans (GAGomics) from Laser Microdissected Mouse Brain.

Elias Mernie, Joseph Zaia.

  Glycosaminoglycans (GAGs) are linear, negatively charged polysaccharides composed of repeating disaccharide units. Heparan sulfate (HS) and chondroitin sulfate (CS) are highly sulfated GAG classes, ubiquitously expressed in mammalian tissues, that play critical roles in cellular signaling, tissue homeostasis, and disease progression. Aside from their biological importance, the structural analysis of HS and CS remains limited to bulk tissue analysis due to their extensive heterogeneity, structural complexity, and the presence of isomers and epimers. In this work, we developed an integrated workflow combining laser microdissection (LMD), hydrophilic interaction liquid chromatography (HILIC), and cyclic ion mobility mass spectrometry (cIM-MS) for the identification and quantification of HS and CS disaccharides from small-scale and spatially resolved mouse brain tissue sections. Through sequential enzymatic digestion of HS and CS chains from the same sample, we profiled not only the common disaccharides that serve as structural signatures for HS and CS, but also rarely detected HS disaccharides containing saturated uronic acid (UA) residues, as well as lyase-resistant 3-O-sulfated HS tetrasaccharides. HILIC enabled the separation of HS and CS disaccharides based on their composition and hydrophilicity, while cIM-MS further enhanced the resolution of positional isomers. Quantitative analysis using linear calibration curves revealed disaccharide abundances in small-scale tissue sections collected by LMD. Overall, our finding highlighted the merit of the LMD-HILIC-cIM-MS workflow for HS and CS analysis in spatial GAGomics and its potential for biomarker discovery and therapeutic application studies.

Keywords:  Chondroitin sulfate (CS); Cyclic ion mobility mass spectrometry (cIM-MS); Heparan sulfate (HS); Laser microdissection (LMD)

DOI:  https://doi.org/10.1016/j.mcpro.2026.101533
Analyst. 2026 Feb 27.

Chemical reaction-enabled lipidomics: from sensitive structural analysis to biomedical applications.

Qirui Yu, Xiaoxiao Ma.

Lipidomics has emerged as a vital discipline for understanding cellular metabolism and disease pathology. However, the immense structural diversity, wide dynamic range, and varying ionization efficiencies of lipids present significant analytical challenges. The MS analysis workflow often falls short in detecting low-abundance species and resolving complex structural isomers. To address these limitations, chemical derivatization has been widely adopted to manipulate the chemical properties of lipids prior to analysis. This review summarizes the significant progress in chemical derivatization-enabled lipidomics over the past decades, highlighting its pivotal role in bridging the gap between analytical capability and biological complexity. We critically discuss three core dimensions of improvement: (1) enhancement of detection sensitivity through derivatization strategies that increase the ionization efficiency of lipids; (2) refinement of structural elucidation, specifically using selective reactions to pinpoint carbon-carbon double bond locations and differentiate isomers; and (3) advancement of spectrometric specificity and quantification via mass-shift profiling, which enables precise quantification or high-throughput multiplex analysis. Finally, we discuss how these chemical tools are facilitating the discovery of novel lipid biomarkers and providing deeper insights into lipid metabolism in biomedical research.

DOI: https://doi.org/10.1039/d5an01334h
bioRxiv. 2026 Feb 09. pii: 2026.02.06.704496. [Epub ahead of print]

Navigating the conjugated metabolome.

Shipei Xing, Abubaker Patan, Julius Agongo, Harsha Gouda, Vincent Charron-Lamoureux, Yasin El Abiead, Zhewen Hu, Haoqi Nina Zhao, Ipsita Mohanty, Jasmine Zemlin, Wilhan Donizete Gonçalves Nunes, Lindsey A Burnett, Mingxun Wang, Dionicio Siegel, Pieter C Dorrestein.

Life's chemical diversity far exceeds current biochemical maps. While metabolomics has catalogued tens of thousands of small molecules, conjugated metabolites, formed when two or more molecular entities are covalently fused through amidation, esterification, or related chemistries, remain underexplored. These molecules can act as microbial signals, detoxification intermediates, or endogenous regulators. Here, we mined 1.32 billion MS/MS spectra across public metabolomics repositories using reverse spectral searching coupled with delta-mass inference to map conjugation events. We generated structural hypotheses for 24,227,439 MS/MS clusters. From these, we inferred 217,291 substructure pairs with dual spectral support and 3,412,720 candidate conjugates with single-match support. Predictions span host-microbe co-metabolites, diet-derived conjugates, and drug-derived species, including drug-ethanolamine and creatinine conjugates with altered bioactivities. We also uncover a family of steroid-phosphoethanolamine conjugates. Fifty-five conjugates were matched by MS/MS of synthetic standards for this work, with 27 additionally supported by retention time matching in biological samples. Guidance on how to leverage this resource is also provided. Together, these results deliver a pan-repository map of potential conjugation chemistry, establish a resource for structural discovery and MS/MS annotation, and offer a scalable framework to explore the scope and diversity of the conjugated metabolome.

DOI: https://doi.org/10.64898/2026.02.06.704496
Anal Bioanal Chem. 2026 Feb 28.

Mass spectrometry analysis of young and aged mice and human Alzheimer's disease with Lewy body pathology using on-slide tissue digestion.

Joseph T Nigro, Sayantani Chatterjee, Shira Freilich, Margaret Downs, Alec Candib, Erika Berron, Thor D Stein, Joseph Zaia, Manveen K Sethi.

  Neurodegenerative disorders such as Alzheimer's disease (AD) and Lewy body disease (LBD) are typically diagnosed after irreversible pathology has developed. Aging, the strongest risk factor, drives molecular changes that predispose the brain to synaptic dysfunction and proteinopathy. Glycosylation and extracellular matrix (ECM) remodeling represent underexplored mechanisms linking aging to neurodegeneration, opening avenues for biomarker discovery, yet mass spectrometry-based glycoproteomics and glycomics studies remain limited. Here, we optimized an on-slide tissue digestion workflow for integrated glycome and proteome profiling from 5-mm brain regions from mice and humans using liquid chromatography data-independent acquisition-tandem mass spectrometry (LC-DIA-MS/MS). This workflow was applied to whole brains from age- and sex-stratified wild-type mice (n = 12) and to human postmortem prefrontal cortex tissue from individuals (n = 14) with brainstem- (n = 8) or limbic-predominant (n = 6) LBD, with or without AD co-pathology. DIA substantially increased protein, glycosylated protein, and ECM coverage by two- to threefold relative to traditional data-dependent acquisition (DDA), while library-free DIA searches further improved detection of low-abundance or region-specific proteins. In aged mouse brains, we observed increased levels of synapse-related proteins-including SYNPR, ZNT3, and HPCA-and enrichment of glutamatergic and postsynaptic pathways, reflecting age-associated synaptic remodeling. Glycomics revealed subtle shifts in the sulfation of chondroitin sulfate (CS) disaccharides with age. In human samples, AD-LBD brainstem tissue exhibited significantly reduced unsulfated, 4-O-sulfated, and total CS levels, along with differential expression of ECM, glycosylated, and mitochondrial proteins, and enrichment of mitochondrial pathways compared with LBD brainstem and AD-LBD limbic tissues. These findings indicate that AD co-pathology exerts a region-specific influence on the proteomic and glycomic landscape of LBD. Collectively, this study establishes a robust DIA-based on-slide digestion platform for high-resolution spatial glycomics and proteomics from minimal tissue, revealing aging- and pathology-specific molecular alterations relevant to neurodegeneration and providing a framework for biomarker discovery.

Keywords:  Aging; Alzheimer’s disease; Data-independent acquisition; Formalin-fixed paraffin-embedded tissue; Fresh frozen tissue; Glycomics; Lewy body pathology; Liquid chromatography; Mass spectrometry; On-slide tissue digestion; Proteomics

DOI:  https://doi.org/10.1007/s00216-026-06385-6
Antioxidants (Basel). 2026 Feb 19. pii: 261. [Epub ahead of print]15(2):

Receptor-Mitochondria Crosstalk in the Kynurenine Metabolic Pathway: Integrating Metabolomics and Clinical Mass Spectrometry.

László Juhász, Zsolt Galla, Masaru Tanaka, László Vécsei.

  Mitochondria govern energy transfer, redox balance, and cell fate. Tryptophan catabolism generates kynurenines (KYNs) that can tune mitochondrial function, with growing evidence that G protein-coupled receptor 35 (GPR35), aryl hydrocarbon receptor (AhR), and N-methyl-D-aspartate receptors (NMDA receptors) link extracellular cues to adenosine 5 prime triphosphate (ATP) maintenance, calcium (Ca2+) handling, mitophagy, and inflammasome control. In parallel, quinolinic acid (QA)-driven de novo nicotinamide adenine dinucleotide (NAD+) synthesis connects KYN flux to tricarboxylic acid (TCA) cycle activity and sirtuin programs across tissues. Key gaps remain: receptor pharmacology is rarely integrated with NAD+ economics and respiration, and clinical workflows still lack single-run assays that quantify both kynurenine and TCA nodes. We therefore integrate receptor proximal signaling, QA-driven NAD+ supply, and unified liquid chromatography-mass spectrometry (LC-MS) measurement into one translational framework spanning kynurenic acid (KYNA), KYN, 3-hydroxykynurenine (3-HK), and QA, using mitochondrial endpoints as the common readout. We synthesize evidence for mitochondrial GPR35 signaling that preserves ATP, AhR programs that tune oxidative defenses and mitophagy, and NMDA receptor antagonism that limits excitotoxic stress. These mechanisms are linked to QA-dependent NAD+ biogenesis and alpha ketoglutarate control points, then aligned with chromatography and ionization choices suited to routine LC-MS workflows. This receptor to organelle framework couples KYN flux to respiratory control and provides a practical roadmap for standardized single-run LC-MS panels. It can strengthen target validation in ischemia, neurodegeneration, psychiatry, and oncology while improving biomarker qualification through harmonized analytics and decision-grade readouts.

Keywords:  G protein-coupled receptors; N-methyl-D-aspartate (NMDA); aryl hydrocarbon receptor (AhR); kynurenic acid (KYNA); liquid chromatography–mass spectrometry (LC-MS); metabolomics; mitochondria; mitophagy; nicotinamide adenine dinucleotide (NAD+); receptors; tricarboxylic acid (TCA) cycle

DOI:  https://doi.org/10.3390/antiox15020261
Curr Oncol. 2026 Feb 23. pii: 129. [Epub ahead of print]33(2):

Metabolic Vulnerabilities as a Therapeutic Target in Breast Cancer.

Sabrina Guo, Christina L Addison.

  Metabolic reprogramming is a defining feature of breast cancer, enabling tumor cells to sustain rapid proliferation, survive under stress, and resist therapy. Key pathways including glycolysis, glutaminolysis, lipid metabolism, and one-carbon metabolism, play central roles in meeting the energetic and biosynthetic demands of malignant cells. Enhanced glycolytic flux supports ATP generation and lactate production, while glutamine metabolism fuels the tricarboxylic acid cycle and provides nitrogen for nucleotide synthesis. Lipid metabolic pathways, particularly fatty acid synthesis, contribute to membrane biogenesis and signaling, and one-carbon metabolism driven by serine and glycine supplies methyl groups for epigenetic regulation and nucleotide production. These metabolic adaptations not only promote tumor growth but also create vulnerabilities that can be exploited therapeutically. Inhibiting these pathways has shown promise in preclinical models; however, challenges such as metabolic plasticity, tumor heterogeneity, and potential toxicity in normal tissues underscore the need for biomarker-driven strategies and rational combination therapies. Herein, we describe current knowledge of the role of these pathways in breast cancer progression, highlighting the role of key enzymes in promoting breast cancer tumor cell growth and in breast cancer prognoses.

Keywords:  TCA cycle; breast cancer; fatty acids; glutaminolysis; glycolysis; metabolism; pentose phosphate pathway; prognosis; serine biosynthesis; tumor growth

DOI:  https://doi.org/10.3390/curroncol33020129
Anal Chem. 2026 Feb 23.

A Validated Mass Spectrometry Platform for Oxysterol Analysis of Single Human Gastruloids and Liver Organoids.

Kristina Sæterdal Kømurcu, Malgorzata Elzbieta Zawadzka, Igor Meszka, Aleksandra Aizenshtadt, Helena Hrušková, Lydia Emilie Aakervik, James L Thorne, Steven Ray Wilson, Stefan Johannes Karl Krauss, Hanne Røberg-Larsen.

Oxysterols, i.e., hydroxylated cholesterol metabolites, are associated with various signaling pathways and diseases. Their low abundance and structural complexity create analytical challenges, particularly in small sample sizes. We here present an optimized and validated miniaturized sample preparation method that enables oxysterol detection and quantification in single stem cell-derived 3D cell aggregates, as exemplified in human liver organoids (stem cell-based 3D liver models) and human gastruloids (stem cell-based embryo models) using liquid chromatography-mass spectrometry (LC-MS). The method, utilizing enzyme-assisted derivatization with Girard-T reagent, allowed a 10-fold decrease in starting material compared to conventional methodology while maintaining sensitivity and precision. A validation based on Eurachem guidelines confirmed quantitative performance and reproducibility across days and operators. In addition, we introduce a tailored normalization method, allowing same-sample measurements of oxysterols and the total protein content. The miniaturized method enabled successful detection and quantification of oxysterols of expected presence (e.g., 26-hydroxycholesterol), as well as unexpected (24S-hydroxycholesterol) and unknown oxysterols. Using our updated method, we could reveal significant heterogeneity among individual organoids and gastruloids, both between and within cell sources/protocols. Overall, we provide a reliable and high-sensitivity method for analyzing oxysterols in limited biological samples, opening opportunities for further insights into their roles in, e.g., liver function and early embryogenesis.

DOI: https://doi.org/10.1021/acs.analchem.5c07140
Talanta. 2026 Feb 11. pii: S0039-9140(26)00188-8. [Epub ahead of print]304 129533

Integrated GC-EI-HRMS and LC-ESI-HRMS workflow along with molecular networking for untargeted identification of new psychoactive substances.

Romain Magny, Mathieu Le Seigle, Thomas Schiestel, Bruno Mégarbane, Laurence Labat, Pascal Houzé.

  Untargeted toxicological screening (UTS) remains challenging due to the structural diversity of xenobiotics and current limitations of analytical platforms. On one hand, LC-HRMS workflows are considered the gold standard in UTS despite the lack of comprehensive spectral databases of xenobiotics, especially with new psychoactive substances (NPS). On the other hand, GC-MS benefits from extensive and highly reproducible EI spectral libraries, but its application to untargeted workflows remains limited in complex biological matrices, as deconvolution must be performed on unit-mass data, which restricts selectivity thus impacting sensitivity. Furthermore, in both platforms, dedicated tools for MS data organization are needed to facilitate the identification step. To overcome these limitations, we implemented and assessed an integrative workflow combining GC-EI-HRMS and LC-ESI-HRMS with molecular networks (MN). As a first step, we leveraged high resolution mass measurements to increase the selectivity of deconvolution allowing to provide accurate-mass EI spectra that can be directly matched to conventional libraries. As a second step, as LC-ESI-HRMS allows access to precursor ions and MS/MS spectra under soft ionization, such an analysis allows to confirm proposed structures and enables phase I and II metabolite annotation. In addition, the annotations proposed through the UTS performed using GC-EI-HRMS may thus be regarded as anchor strategy for MN built using LC-ESI-HRMS data. We applied this combined approach to two poisoning cases involving arylcyclohexylamines and cathinones and showed that MN built from GC-HRMS data can refine ambiguous spectral matches, improve annotation consistency, and support the identification of previously unreported metabolites. In conclusion, this dual-platform strategy addresses several limitations of LC-HRMS-only workflows and highlights the value of integrating GC- and LC-based MN to achieve more confident xenobiotic identification, opening new perspectives for broad exposomic applications.

Keywords:  GC-HRMS; Molecular network; Toxicological screening; Xenobiotics

DOI:  https://doi.org/10.1016/j.talanta.2026.129533