bims-mascan 2026-01-25 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2026–01–25
sixteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Quantitative Food Compounds Enable Dietary Ontology Referencing across 500 Foods and Human Plasma.
Insect Lipidomics: Advances, Applications, and Physiological Insights.
Boosting the Speed and Accuracy of Protein Quantification Algorithms in Mass Spectrometry-Based Proteomics.
Unlocking the Next Decade of Proteomics with Standardized, Structured Metadata.
Highly Repeatable Tissue Proteomics for Kidney Transplant Pathology: Technical and Biological Validation of Protein Analysis using LC-MS/MS.
Proteomic and Lipidomic Atlas of Gut-Associated Lymph and Venous Depots in Female Piglets.
Integrated GC-MS/MS Metabolomics in Cardiovascular Disease: Targeted Nitro-Oleic Acid Quantification Meets Untargeted Profiling.
Clinical Applications of Phosphoproteomics: Illuminating Cancer Signaling and Enabling Rational Therapeutic Strategies.
An Integrated Method for Profiling Lipid-Protein Interactions Using Multifunctional Lipid Probes.
Microalgae-derived quality control material for reproducible and scalable LC-MS system suitability testing.
Protocol for identifying the BZR1 interactome under starvation in Arabidopsis by metabolic stable isotope labeling quantitative IP-MS.
Simultaneous determination of short-chain fatty acids and tryptophan metabolites by a propyl chloroformate- derivatized GC-MS approach.
Stable isotope labelling mass spectrometry analysis of isolated mouse sperm.
Preventing Proteomics Data Tombs Through Collective Responsibility and Community Engagement.
Comparison of six serum analyte workflows using routine liquid chromatography-tandem mass spectrometry methods at multiple laboratories with the Cobas i 601 analyzer, an automated mass spectrometry system.
ATGL-catalyzed biosynthesis mediates the upregulation of Fatty Acid Hydroxy Fatty Acids (FAHFA) levels in white adipose tissue with fasting.

Anal Chem. 2026 Jan 18.

Quantitative Food Compounds Enable Dietary Ontology Referencing across 500 Foods and Human Plasma.

Julius Agongo, Harsha Gouda, Aubreyana McMaugh, Celeste Allaband, Seyedeh Mehrnaz Aghili, Marta Sala-Climent, Shipei Xing, Jennifer Cao, Jasmine Zemlin, Mingxun Wang, Kathleen Dorrestein, Tiffany Holt, Rob Knight, Brigid S Boland, Monica Guma, Pieter C Dorrestein.

Accurate and reproducible dietary assessment remains a persistent challenge in the clinical and nutritional sciences. We present a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the absolute quantification of 200 literature-curated food compounds across 500 food item extracts and human plasma samples. The assay uses external matrix-matched calibration and robust quality control, including postextraction recovery, matrix effect assessment, and intra- and interday precision validation, demonstrating high linearity (R2 > 0.99), low coefficients of variation (<15%), and recovery within 100 ± 15% for >75% of analytes. Using 200 authentic food standards against 500 complex food items resulted in reproducible detection and quantification of 102 food compounds across diverse food classes. Their specificity and distribution were evaluated at multiple levels of dietary ontology. Supervised multivariate analysis (PLS-DA) identified discriminative compound panels that classified foods such as citrus, dairy, and vegetables with high accuracy. Key compounds such as hesperidin, hypaphorine, and piperine demonstrated strong source specificity and were applied to human plasma samples from an inflammatory bowel disease (IBD) cohort following a Mediterranean diet. Food compound concentrations tracked with dietary intake, confirming hypaphorine's association with hummus and piperine's correlation with black-pepper-containing meals. This study demonstrates the utility of a rigorously validated targeted metabolomics workflow for both food chemistry and translational dietary intake research. The framework enables quantitative mapping of food molecules to dietary exposures and supports the development of more objective, chemistry-based dietary assessment strategies in clinical contexts.

DOI: https://doi.org/10.1021/acs.analchem.5c06769
Adv Exp Med Biol. 2026 ;1494 261-291

Insect Lipidomics: Advances, Applications, and Physiological Insights.

Laura Palanker Musselman, Doga Cedden, Gözde Güney, Umut Toprak.

  Lipidomics, a specialized branch of metabolomics, investigates the diversity and functionality of lipids in biological systems. Lipids serve crucial roles in energy storage, membrane composition, and environmental acclimation in insects, underpinning processes such as development and stress responses. Advances in analytical technologies, such as liquid chromatography-mass spectrometry (LC-MS), have enabled precise identification and quantification of lipid species, providing unprecedented insights into lipid metabolism and dynamics. Key lipid classes, including triacylglycerols and phospholipids, exhibit structural and functional versatility, adapting to environmental pressures through mechanisms like homeoviscous adaptation. These dynamic lipid responses are essential for maintaining cellular and cuticular integrity and functionality under stress. By exploring lipid diversity and adaptations, lipidomics offers valuable perspectives on insect physiology, survival strategies, and evolutionary ecology. This chapter summarizes methods used to study insect lipidomes and highlights comparative lipidomic studies that have advanced our understanding of insect biology.

Keywords:  Cuticular hydrocarbons; Diapause; Ecdysteroids; Insect lipidomics; Mass spectrometry

DOI:  https://doi.org/10.1007/978-3-032-04842-4_878
J Proteome Res. 2026 Jan 20.

Boosting the Speed and Accuracy of Protein Quantification Algorithms in Mass Spectrometry-Based Proteomics.

Thang V Pham, Chau T M Tran, Alex A Henneman, Long H C Pham, Duc G Le, An H Can, Phuc H L Bui, Sander R Piersma, Connie R Jimenez.

  Protein quantification is a crucial data processing step that combines quantitative values at the peptide or fragment level into protein levels in mass spectrometry-based proteomics. However, many of the current algorithms, including the state-of-the-art method MaxLFQ, do not scale well with the increasing number of samples, because of the limited system memory and algorithmic complexities. Here we introduce the iq format, a novel data structure designed to support very large data sets. We optimize existing quantification methods for both speed and memory usage. In particular, the new algorithms maxlfq-bit and rlm-cd significantly improve the base methods, MaxLFQ and the robust linear model, respectively, achieving orders of magnitude speed improvements for a large number of samples. The experimental result shows that the MaxLFQ algorithm achieves the highest accuracy, despite its comparatively higher computational cost. We also introduce a generic algorithm to boost the quantification accuracy of all methods by reducing the effect of noisy ion intensity traces. The experimental results show that the weighting approach improves the performance of all tested methods on a spike-in data set and a mixed species data set. The software implementation is publicly available in the R package iq from version 2.

Keywords:  iq format; large-scale data processing; maxlfq-bit; protein quantification; rlm-cd; robust quantification

DOI:  https://doi.org/10.1021/acs.jproteome.5c01038
J Proteome Res. 2026 Jan 21.

Unlocking the Next Decade of Proteomics with Standardized, Structured Metadata.

Tim Van Den Bossche, Ananth Prakash, Tine Claeys, Juan Antonio Vizcaíno, Lennart Martens.

  The proteomics community has fully embraced data sharing, yet data set metadata provision remains limited, especially at the level of the biological samples and experimental design. This hampers large-scale data reuse, as comprehensive and structured sample context and study design information are often essential for confident, automatic reuse, and (re)interpretation. Although standards such as Sample and Data Relationship Format for Proteomics (SDRF-Proteomics) and supporting tools are already available, their adoption remains limited. Many researchers lack incentives, and enforcement by journals and repositories remains challenging in practice. Still, metadata defines a data set's long-term value. We propose a coordinated plan to dramatically improve metadata annotation of publicly disseminated proteomics data. Funders can drive progress by investing in a sustainable, scalable metadata infrastructure. HUPO-PSI plays a central role in setting community standards and enabling validation. ProteomeXchange repositories are key to implementing and supporting metadata adoption. Data producers must treat metadata as a part of their scientific output. Instrument vendors can contribute by enabling the automatic capture of technical metadata. Software developers should embed SDRF-Proteomics metadata into analysis workflows. Finally, journals and reviewers are well positioned to shape expectations and enforce compliance. By aligning efforts across these stakeholders, we can build the road to large-scale, context-aware reuse and unlock the full value of public proteomics data sets.

Keywords:  HUPO-PSI; SDRF-Proteomics; funders; metadata; repositories; software; standards; vendors

DOI:  https://doi.org/10.1021/acs.jproteome.5c00958
Lab Invest. 2026 Jan 16. pii: S0023-6837(26)00003-6. [Epub ahead of print] 106073

Highly Repeatable Tissue Proteomics for Kidney Transplant Pathology: Technical and Biological Validation of Protein Analysis using LC-MS/MS.

Rianne Hofstraat-Boersma, Kristina Marx, Renata Blatnik, Nike Claessen, Aleksandra Chojnacka, Hessel Peters-Sengers, Sandrine Florquin, Jesper Kers, Garry Corthals.

  Accurate pathological assessment of tissue samples is key for diagnosis and optimal treatment decisions. Traditional pathology techniques suffer from subjectivity resulting in inter-observer variability, and limitations in identifying subtle molecular changes. Omics approaches provide both molecular evidence and unbiased classification, which increases the quality and reliability of final tissue assessment. Here, we focus on mass spectrometry (MS)-based proteomics as a method to reveal biopsy tissue differences. For MS data to be useful, molecular information collected from formalin fixed paraffin embedded (FFPE) biopsy tissues needs to be consistent and quantitatively accurate and contain sufficient clinically relevant molecular information. Therefore, we developed an MS-based workflow and assessed the analytical repeatability on 36 kidney biopsies, ultimately analysing molecular differences and similarities of over 5000 proteins per biopsy. Additional 301 transplant biopsies were analysed to understand other physical parameters including effects of tissue size, standing time in autosampler, and the effect on clinical validation. MS data were acquired using Data-Independent Acquisition (DIA) which provides gigabytes of data per sample in the form of high proteome representation, at exquisitely high quantitative accuracy. The FFPE-based method optimised here provides a coefficient of variation below 20%, analysing more than 5000 proteins per sample in parallel. We also observed that tissue thickness does affect the outcome of the data quality: 5 μm sections show more variation in the same sample than 10 μm sections. Notably, our data reveals an excellent agreement for the relative abundance of known protein biomarkers with kidney transplantation lesion scores used in clinical pathological diagnostics. The findings presented here demonstrate the ease, speed, and robustness of the MS-based method, where a wealth of molecular data from minute tissue sections can be used to assist and expand pathology, and possibly reduce the inter-observer variability.

Keywords:  DIA; FFPE; Kidney; Kidney Transplantation; Mass Spectrometry; Proteomics; Tissue

DOI:  https://doi.org/10.1016/j.labinv.2026.106073
Arterioscler Thromb Vasc Biol. 2026 Jan 22.

Proteomic and Lipidomic Atlas of Gut-Associated Lymph and Venous Depots in Female Piglets.

Benton J Anderson, Corinne E Moss, Daniel D Lee, Rafael S Czepielewski, Beth A Helmink, Emily J Onufer, Deanna L Davis, Michael R Strickland, Kento Kurashima, Ajay K Jain, Joshua J Coon, Gwendalyn J Randolph, Katherine A Overmyer.

   BACKGROUND: The venous and lymphatic outflows from organs may contain molecular signatures related to tissue function, but deep biomolecular analyses that compare outflow composition are lacking. Here, using blood and lymph samples from a piglet model system and mass spectrometry analysis, we compare protein and lipid cargo from 9 venous and 3 lymph depots centered on intestinal outflow.
METHODS: We obtained venous blood and plasma from piglets using new methods for dissection and sample collection. We applied mass spectrometry-based proteomics and lipidomics, using both a low-volume method and an additional proteomics sample preparation method, the Seer Proteograph XT high coverage method for the proteomics.
RESULTS: We detected 622 proteins and 1315 lipids across lymph and plasma. With the additional Seer proteomics method, we detected a further 7771 proteins across a subset of samples. We observed both expected and novel enrichments of proteins, including CCL21 and IGFBP (insulin-like growth factor-binding protein) 7 as proteins strongly enriched in lymph. When comparing lymph depots, we found that thoracic duct lymph is distinct from lymph draining the proximal and distal small intestine, especially in their lipidomic profiles, reflecting differences in dietary lipid uptake. By performing integrative multiomics of proteomics and lipidomics, we show that apos (apolipoproteins), such as the related apoA1 and apoA2 proteins, correlate with different lipid profiles and may associate with distinct functions across the plasma depots.
CONCLUSIONS: These data identify molecules and biomarkers selectively enriched in adjacent lymph and venous drainage depots from the gastrointestinal tract. The analyses and figures present in this work are expanded upon in an interactive companion Web application at gutveinlymphomics.com, facilitating access to our integrated multiomics and advancing understanding of biomolecular trends across the intestinal tract.

Keywords:  apolipoproteins; lipid metabolism; lipidomics; lymph; mass spectrometry; multiomics; plasma

DOI:  https://doi.org/10.1161/ATVBAHA.125.323883
Anal Chem. 2026 Jan 22.

Integrated GC-MS/MS Metabolomics in Cardiovascular Disease: Targeted Nitro-Oleic Acid Quantification Meets Untargeted Profiling.

Yasmin Elshoura, Magy Herz, Mohamed Z Gad, Rasha Hanafi.

In recent decades, interest in nitrated fatty acids (NO2-FAs) has grown due to their role as endogenous signaling molecules involved in health and disease. As a result, their metabolic profiling has gained increasing attention. For metabolite analysis, GC-MS/MS offers greater sensitivity and robustness than LC-MS/MS, with more reliable annotation libraries. This study investigates metabolic dysregulation in cardiovascular disease (CVD) patients by using advanced metabolomics. A novel GC-MS/MS method for profiling NO2-FAs was developed, showing improved precision using 17-BrHDA as an internal standard compared to previous HDA-based methods. It is also the first report of alkylation and silylation derivatization of 17-BrHDA, demonstrating superior GC-MS sensitivity for pentafluorobenzyl-alkylated fatty acids over their silylated counterparts in positive ion mode. Untargeted metabolomics was applied to plasma samples from acute myocardial infarction (AMI) patients and healthy controls using both derivatization techniques. Multivariate analysis (PCA and PLS-DA) revealed distinct metabolic profiles. Key metabolites, identified based on VIP scores, were annotated via the Human Metabolome Database and literature. Findings highlight the complementary nature of both derivatization approaches for comprehensive plasma metabolome analysis. Notably, NO2-OA levels were significantly elevated (p < 0.01) in AMI patients, indicating its possibility to be utilized as a cardiovascular biomarker. This study represents the first use of alkylation derivatization in untargeted metabolomics for AMI and introduces a highly sensitive GC-MS/MS method with an innovative internal standard and optimized derivatization for cardiovascular biomarker discovery. The method demonstrates the potential to discriminate between groups of patients and healthy subjects.

DOI: https://doi.org/10.1021/acs.analchem.5c05647
Cancer Sci. 2026 Jan 22.

Clinical Applications of Phosphoproteomics: Illuminating Cancer Signaling and Enabling Rational Therapeutic Strategies.

Hirokazu Shoji, Narikazu Boku, Jun Adachi.

  Protein phosphorylation is a central post-translational modification regulating cellular signaling, frequently dysregulated in cancer. Mass spectrometry (MS)-based phosphoproteomics has emerged as a powerful approach to systematically profile phosphorylation events, thereby revealing aberrant kinase activity and therapeutic vulnerabilities that are not captured by genomic or transcriptomic analyses. Recent advances across the workflow-including optimized sample preparation and phosphopeptide enrichment, isotope- or label-free quantitative strategies, high-resolution mass spectrometry platforms, specialized algorithms for site identification and quantification, and integrative informatics analyses-have enabled the detection of tens of thousands of phosphorylation sites even from small clinical specimens. These developments have facilitated the characterization of signaling pathways across diverse cancer types, leading to the identification of targetable kinases and informing therapeutic strategies. In this review, we highlight studies that employed phosphoproteomic analyses of clinical specimens or patient-derived cancer cells to delineate signaling characteristics and to propose and validate therapeutic targets. Collectively, MS-based phosphoproteomics is poised to become a cornerstone of precision oncology. By enabling comprehensive and quantitative mapping of phosphorylation events, this technology allows mechanistic dissection of cancer signaling pathways and uncovers therapeutic vulnerabilities that may be exploited with targeted agents.

Keywords:  cancer signaling; kinases; mass spectrometry; phosphoproteomics; therapeutic targets

DOI:  https://doi.org/10.1111/cas.70323
bioRxiv. 2026 Jan 17. pii: 2026.01.17.700062. [Epub ahead of print]

An Integrated Method for Profiling Lipid-Protein Interactions Using Multifunctional Lipid Probes.

Scotland E Farley, Gaelen Guzman, Berit Blume, Frank Stein, Carsten Schultz, Fikadu G Tafesse.

Cellular lipids shape health and disease through specific protein interactions, yet lipid-protein networks remain poorly defined. Despite rapid advances in functional lipid probes, the field still lacks a practical, dedicated protocol for conducting lipid-protein interaction studies. We describe detailed methods for determining lipid interactomes from cells using multifunctionalized lipid derivatives. We provide protocols that detail 1) how to treat cells with lipid derivatives and perform photochemistry to obtain lipid-protein conjugates; 2) how to perform click chemistry with a fluorophore and observe lipid-protein conjugates by in-gel fluorescence; 3) how to perform click chemistry with azide beads and prepare lipid-protein conjugates for proteomic analysis. We provide context on important parameters for each step and include guidelines for controls, as well as suggestions for troubleshooting based on common problems encountered during the preparation of this protocol. This protocol enables mapping lipid interactomes across diverse biological systems. The entire workflow from cell treatment to complete proteomic sample preparation requires ∼15 hours over four days, depending on the type of experimental readout (in-gel fluorescence or proteomics), and the usage of pause points. Practitioners are expected to be familiar with standard biochemical techniques, such as sterile sample handling and tissue culture and gel electrophoresis. Additional skills are needed for mass spectrometric analysis, and collaboration with a proteomics core facility is recommended. The described procedures uniquely enable the identification of the protein interactors (the interactome) of select lipid species, providing for a major shift in the characterization of the biological roles of lipids in cellular systems.

DOI: https://doi.org/10.64898/2026.01.17.700062
Anal Methods. 2026 Jan 22.

Microalgae-derived quality control material for reproducible and scalable LC-MS system suitability testing.

Wonseok Bang, Hyejeong Jung, Yejin Jeon, Minjung Ju, Seong-Joo Hong, Jong-Moon Park, Hookeun Lee.

Ensuring the accuracy and reliability of liquid chromatography-mass spectrometry (LC-MS/MS)-based proteomic analysis requires robust quality control (QC) strategies. However, widely used cell line-based QC materials present challenges in reproducibility, scalability, and ethical compliance. In this study, we developed a microalgae-derived QC material based on Synechocystis sp. PCC6803 and evaluated its suitability for LC-MS/MS system performance monitoring. The Synechocystis-based QC samples demonstrated high identification reproducibility, with 76% of the protein groups being consistently detected across five replicates and maintaining a median coefficient of variation (CV) of 6.7% in quantitative precision. Furthermore, QC peptides exhibited excellent linearity (R2 ≥ 0.98) and reproducibility (CV ≤ 12.06%) across varying injection amounts. These results indicate that Synechocystis-derived QC materials provide a reproducible and scalable approach that complements conventional QC workflows. They are particularly well suited for routine LC-MS/MS system performance monitoring in proteomics workflows involving non-human or mixed biological samples.

DOI: https://doi.org/10.1039/d5ay01931a
STAR Protoc. 2026 Jan 20. pii: S2666-1667(25)00749-X. [Epub ahead of print]7(1): 104343

Protocol for identifying the BZR1 interactome under starvation in Arabidopsis by metabolic stable isotope labeling quantitative IP-MS.

Zhenzhen Zhang, Zhi-Yong Wang.

  Identification of interacting proteins, particularly those mediating protein degradation, remains technically challenging. The transcription factor BZR1 in Arabidopsis is activated by brassinosteroid (BR) signaling to promote plant growth and is degraded under starvation conditions to restrict growth and promote survival. Here, we present a protocol for identifying BZR1 interactors in plants under sugar starvation using 15N stable isotope labeling (SIL) followed by immunoprecipitation and quantitative mass spectrometry (IP-MS) analysis. This protocol has broad potential applications in studying the protein interactome. For complete details on the use and execution of this protocol, please refer to Zhang et al.1.

Keywords:  Plant sciences; Proteomics; Signal Transduction

DOI:  https://doi.org/10.1016/j.xpro.2025.104343
J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Jan 12. pii: S1570-0232(26)00014-0. [Epub ahead of print]1271 124925

Simultaneous determination of short-chain fatty acids and tryptophan metabolites by a propyl chloroformate- derivatized GC-MS approach.

Yefeng Han, Xiaofang He, Yueling Gong, Mingxiao Li, Lili Sheng, Ningning Zheng, Jianbo Wan, Houkai Li, Yuanyuan Li.

  Short-chain fatty acids (SCFAs) and tryptophan metabolites, serve as key mediators of host-microbiota crosstalk, influencing physiological and pathological processes. Their interconnected roles necessitate simultaneous quantification to fully elucidate the potential mechanism of gut microbiota in metabolic diseases. However, they are difficult to be detected simultaneously due to differences in content or different polarity which contain specific carboxylic group, amino group or phenolic hydroxyl groups. In current study, our primary goal is to establish a rapid and sensitive quantitative measurement for SCFAs and tryptophan metabolites by using propyl chloroformate-(PCF) derivatization based on gas chromatography-triple quadrupole mass spectrometry (GC-MS/MS) analysis. Then, we applied the established method in measurement of serum samples from healthy subjects and metabolic associated fatty liver disease (MAFLD) patients. First, we optimized the reaction conditions including PCF volume, reaction time, extraction reagent ratio, and alkaline reagent concentration, enabling the simultaneous detection of acetic acid, propionic acid, isobutyric acid, butyric acid, isovaleric acid, valeric acid, 2-methylvaleric acid, hexanoic acid, indole, succinic acid, quinolinic acid, indole acetic acid, glutamine, indole butyric acid, 3-hydroxyanthranilic acid, melatonin, kynurenine, tyrosine, and tryptophan. 2-chloro-L-phenylalanine was set as the internal standard. The optimized condition showed good linearity, and the intra/inter-day precision achieved in the range from 0.81% to 14.88%. The recovery ranged from 85.68% to 114.50% and the matrix effect ranged from 85.81% to 113.42%. In addition, the influence of different storage conditions on sample stability was also acceptable. Finally, the quantitation result of serum samples indicated that isovaleric acid, quinolineic acid, indoleacetic acid, glutamine, melatonin, tyrosine, and tryptophan had significant difference between healthy subjects and MAFLD patients. The levels of isovaleric acid, indoleacetic acid, glutamine, tyrosine, and tryptophan had significant correlations with clinical indicators such as ALT, AST, Cap, Cr and TG, supporting their potential for further translational studies. In summary, this improved method is applicable for quantitative measurement of SCFAs and tryptophan metabolites, as well as those endogenous metabolites containing carboxylic, amino and phenolic hydroxyl groups.

Keywords:  Gas chromatography–mass spectrometry; Metabolic associated fatty liver disease; Propyl chloroformate derivatization; Short-chain fatty acids; Tryptophan metabolites

DOI:  https://doi.org/10.1016/j.jchromb.2026.124925
Biol Reprod. 2026 Jan 23. pii: ioag022. [Epub ahead of print]

Stable isotope labelling mass spectrometry analysis of isolated mouse sperm.

George Dobson, Melanie Balbach.

  Metabolism provides sperm with the energy needed to swim to and fertilize the oocyte. While mammalian sperm become motile during ejaculation and undergo maturation in the female genital tract, their energy demand increases. Investigations into the metabolism of sperm and the capacitation-induced increase in energy demand have been stymied by a lack of appropriate methodologies. Here, we present a detailed methodology to perform stable isotope labeling mass spectrometry in isolated mouse sperm, allowing to follow the fate of exogenous energy substrates through their metabolic pathways. As an example, mouse sperm are exposed to ubiquitously and positionally labelled 13C-glucose and the rate of accumulation of 13C in different metabolites is detected and analyzed. Using this assay in the presence of different exogenous energy substrates, with sperm from different species, genetically modified mouse lines, and/or pharmacological activators and/or inhibitors can provide important insight into the contribution of different metabolic enzymes and pathways to sperm energy homeostasis.

Keywords:  Mammalian sperm; capacitation; etabolism; metabolomics

DOI:  https://doi.org/10.1093/biolre/ioag022
Sci Data. 2026 Jan 22.

Preventing Proteomics Data Tombs Through Collective Responsibility and Community Engagement.

Uladzislau Vadadokhau, Mai Soliman, Leticia Castillon, Paula Pastor Muñoz, Linda Id, Swethaa Natraj Gayathri, Ankita Srivastava, Tyko Runeberg, Tamara González-Armijos, Karina Šapovalovaitė, Milda Sakalauskaite, Sadiksha Adhikari, Oluwatosin Abe, Tiialotta Tohmola, Hao Li, Srividhya Sundaresan, Hanna Vesikukka, Jannica Roininen, Ehsan Zangene, Rabah Soliymani, Sami T Tuomivaara, Veit Schwämmle, Amir A Saei, Markku Varjosalo, Mohieddin Jafari.

Public proteomics repositories now host vast amounts of mass spectrometry data, yet much of it remains difficult to reuse, risking "data tombs" that are open access but not practically re-analyzable. In spring 2025, a graduate-level course at the University of Helsinki tasked six student teams with reanalyzing six projects from the Proteomics Identification Database (label-free quantification only) using a common R-based workflow (rpx, mzR, QFeatures, DEP/MSqRob2/limma/OmicsQ packages) that was shared across all teams. The teams reproduced identification, optional quantification, normalization, imputation, and differential expression analyses, and compared the outcomes to the original studies. As expected, systemic barriers recurred across cases: (i) no sample and data relationship format for proteomics metadata in any of the cases; (ii) missing details regarding decoy sets for false discovery rate assessment; (iii) proprietary-only outputs or software (e.g., Thermo.msf, Progenesis) that impeded open reanalysis in interoperable, community-standard formats; (iv) missing data-independent acquisition spectral libraries or protein sequences database files (FASTA); (v) absent or vague normalization/imputation/statistical parameters; (vi) inconsistent file naming; and (vii) insufficient biological/technical replication in at least one project. These shortcomings yielded large discrepancies in the analysis results (e.g., 13,068 vs. 4,923 proteins; 108 vs. 11 differentially expressed proteins), and, in one instance, a highlighted protein lacked robust support in the deposited identifications. We observed that reproducibility in mass spectrometry-based proteomics hinges less on instruments than on transparent metadata, open formats, and executable analysis provenance. We propose that data creators provide a minimum re-analysis package, including raw data and open formats, community standards, basic quality control summaries, data-independent acquisition spectral libraries, and complete parameter/code sets with pinned versions or containers. Moreover, we recommend repository-level nudges toward making such packages mandatory. This educational exercise simultaneously trains the students as well as stress-tests the community data practices to prevent proteomics "data tombs".

DOI: https://doi.org/10.1038/s41597-026-06614-8
Clin Chem Lab Med. 2026 Jan 26.

Comparison of six serum analyte workflows using routine liquid chromatography-tandem mass spectrometry methods at multiple laboratories with the Cobas i 601 analyzer, an automated mass spectrometry system.

Pieter Vermeersch, Robert de Jonge, Takamaro Miyazawa, Mads Nybo, Palle Fruekilde, Barry J Toole, Philippe Metz, Eva Albrecht, Karl Slusarczyk, Michael Vogeser, Robert L Fitzgerald.

   OBJECTIVES: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) offers substantial analytical advantages over traditional immunoassay methods, including greater specificity and robustness. Conventional LC-MS/MS methods are labor-intensive, requiring highly trained, dedicated laboratory staff. The Cobas® i 601 analyzer (Roche Diagnostics International Ltd., Rotkreuz, Switzerland) is an automated, random-access, mass spectrometry (MS) system designed to improve workflows and reduce turnaround times. This study evaluated turnaround times for analyses with the i 601 analyzer vs. routine LC-MS/MS using batch processing.
METHODS: We performed a workflow analysis for six sets of analytes (mycophenolic acid, antibiotics, antiepileptics, voriconazole, testosterone, and 25-hydroxyvitamin D) in seven laboratories across Europe, North America, and Asia. We recorded batch size, result turnaround times, and hands-on times (including quality control) for 93 batches analyzed on routine LC-MS/MS. These were compared to equivalent measurements generated using the i 601 analyzer in batch mode as part of a prototype pilot study at Ludwig Maximilian University, Munich.
RESULTS: Turnaround times were shorter with the i 601 analyzer vs. routine LC-MS/MS for all tested workflows, independent of batch size and analyte workflow. Median time from batch start to final result availability with the i 601 analyzer was 6.8-fold shorter vs. routine LC-MS/MS (1 h, 34 min vs. 10 h, 37 min, respectively). In addition, median total hands-on time was 19-fold shorter with the i 601 analyzer vs. routine LC-MS/MS (5 vs. 93 min).
CONCLUSIONS: Compared with routine LC-MS/MS methods, the i 601 analyzer substantially reduced turnaround and hands-on times for common analytes, regardless of batch size.

Keywords:  automation; liquid chromatography-tandem mass spectrometry; steroids; therapeutic drug monitoring; workflow

DOI:  https://doi.org/10.1515/cclm-2025-0994
J Biol Chem. 2026 Jan 20. pii: S0021-9258(26)00039-6. [Epub ahead of print] 111169

ATGL-catalyzed biosynthesis mediates the upregulation of Fatty Acid Hydroxy Fatty Acids (FAHFA) levels in white adipose tissue with fasting.

Anna Santoro, Zhenlong Chen, Andrew T Nelson, Dionicio Siegel, Barbara B Kahn.

  FAHFAs are a family of bioactive lipids. A subclass of these, Palmitic Acid Hydroxy Stearic Acids (PAHSAs) have anti-inflammatory and anti-diabetic effects. Adipose tissue PAHSA levels are upregulated with increased de novo lipogenesis and fasting, and downregulated with insulin resistance and obesity. Adipose Triglyceride Lipase (ATGL) regulates FAHFAs through two distinct mechanisms: hydrolysis of triacylglycerol (TG)-containing FAHFAs and catalyzing formation of the ester bond found in all FAHFAs through a transacylase reaction. ATGL mediates the increase of PAHSAs with fasting in white adipose tissue (WAT), but the mechanism for this has not been determined. Here, we show that multiple FAHFAs are dynamically regulated with fasting and short-term refeeding in both perigonadal (PG) and subcutaneous (SQ) WAT due to ATGL transacylase activity. Our in vivo studies with stable isotopes demonstrate that de novo FAHFA synthesis is upregulated with fasting. This observation along with the fact that FAHFA-TGs are unchanged (SQ WAT) or increased (PG WAT) with fasting and FAHFA hydrolysis is unchanged, suggests that the primary mechanism by which FAHFAs increase in WAT with fasting is de novo synthesis. Using adipose tissue-specific ATGL knock out mice, we show that ATGL is required for the fasting-induced upregulation of endogenous levels and de novo synthesis of multiple FAHFAs. Altogether, this study shows that fasting upregulates multiple FAHFAs by increasing ATGL-mediated synthesis of FAHFAs, inferring that fasting, a physiologic state that is classically known to activate the lipase activity of ATGL, also stimulates its transacylase activity.

Keywords:  ATGL-KO mice; FAHFA; Hydroxy Stearic Acids; PAHSA; TG-FAHFA; adipose tissue metabolism; adipose triglyceride lipase (ATGL); lipid metabolism; lipid synthesis; triglyceride

DOI:  https://doi.org/10.1016/j.jbc.2026.111169