bims-mascan 2025-09-21 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–09–21
twenty-one papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics.
MSnLib: efficient generation of open multi-stage fragmentation mass spectral libraries.
Multiomics Analysis of Dried Plasma Spots Using Stable Isotope Internal Standards for Biomarker Discovery.
Metabolic Tracing of Methyl Donor Utilization in Histone Methylation via Relative Quantification of Isotopomer Distribution Mass Spectrometry.
Metabolic Reprogramming of Cancer Cells and Therapeutics Targeting Cancer Metabolism.
Differential carbon source utilization drives metabolic state and resuscitation in antibiotic-tolerant persister cells.
Protocol for RNA modification analysis by UHPLC-QqQ MS.
Features of sample preparation of cell culture samples for metabolomic screening by LC-MS/MS.
Quantitative profiling of lipid mediators in sperm cells through on-line dilution on-line polymer matrix-based solid-phase extraction liquid chromatography with mass spectrometric detection.
Current trends in sample preparation for liquid chromatography - mass spectrometry analysis of catecholamines and their metabolites in biological samples.
Mass spectrometry-based absolute quantitative proteomics of drug-metabolizing enzymes in human liver.
Toward standardized epitranscriptome analytics: an inter-laboratory comparison of mass spectrometric detection and quantification of modified ribonucleosides in human RNA.
Fueling Prostate Cancer: The Central Role of Glutamine/Glutamate Metabolic Reprogramming.
Crosstalk between dysregulated amino acid sensing and glucose and lipid metabolism in colorectal cancer.
TIE-UP-SIN: a novel method for enhanced identification of protein-protein interactions.
MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis.
Stable Isotope Labeling of Pyrimidines Using a Deconstruction-Reconstruction Strategy.
Quantitative Assessment for the Quality of Lipidomics Experiment Teaching.
Securing the Future of NMR Metabolomics Reproducibility: A Call for Standardized Reporting.
Deciphering protein long-chain S-acylation using mass spectrometry proteomics strategies.
PAMPA: A Software for Peptide Markers and Taxonomic Identification for ZooMS Samples in Archaeology and Paleontology.

bioRxiv. 2025 Sep 02. pii: 2022.10.31.514544. [Epub ahead of print]

Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics.

Ludwig R Sinn, Lukasz Szyrwiel, Justus Grossmann, Kate Lau, Katharina Faisst, Di Qin, Florian Mutschler, Luke Khoury, Andrew Leduc, Markus Ralser, Fabian Coscia, Matthias Selbach, Nikolai Slavov, Nagarjuna Nagaraj, Martin Steger, Vadim Demichev.

Quantitative mass spectrometry (MS)-based proteomics has become a streamlined technology with a wide range of usage. Many emerging applications, such as single-cell proteomics, spatial proteomics of tissue sections and the profiling of low-abundant posttranslational modifications, require the analysis of minimal sample amounts and are thus constrained by the sensitivity of the workflow. Here, we present Slice-PASEF, a mass spectrometry technology that leverages trapped ion mobility separation of ions to attain the theoretical maximum of tandem MS sensitivity. We implement Slice-PASEF using a new module in our DIA-NN software and show that Slice-PASEF uniquely enables precise quantitative proteomics of low sample amounts. We further demonstrate its utility towards a range of applications, including single cell proteomics and degrader drug screens via ubiquitinomics.

DOI: https://doi.org/10.1101/2022.10.31.514544
Nat Methods. 2025 Sep 15.

MSnLib: efficient generation of open multi-stage fragmentation mass spectral libraries.

Corinna Brungs, Robin Schmid, Steffen Heuckeroth, Aninda Mazumdar, Matúš Drexler, Pavel Šácha, Pieter C Dorrestein, Daniel Petras, Louis-Felix Nothias, Václav Veverka, Radim Nencka, Zdeněk Kameník, Tomáš Pluskal.

Untargeted high-resolution mass spectrometry is a key tool in clinical metabolomics, natural product discovery and exposomics, with compound identification remaining the major bottleneck. Currently, the standard workflow applies spectral library matching against tandem mass spectrometry (MS2) fragmentation data. Multi-stage fragmentation (MSn) yields more profound insights into substructures, enabling validation of fragmentation pathways; however, the community lacks open MSn reference data of diverse natural products and other chemicals. Here we describe MSnLib, a machine learning-ready open resource of >2 million spectra in MSn trees of 30,008 unique small molecules, built with a high-throughput data acquisition and processing pipeline in the open-source software mzmine.

DOI: https://doi.org/10.1038/s41592-025-02813-0
Anal Chem. 2025 Sep 17.

Multiomics Analysis of Dried Plasma Spots Using Stable Isotope Internal Standards for Biomarker Discovery.

Wenqian Li, John R Koethe, Curtis L Gabriel, Heidi J Silver, Timothy J Garrett.

A comprehensive analytical strategy for multiomics analysis of dried blood spots (DBS) has been developed, featuring prespotted stable isotope internal standards (SIIS) for enhanced quantitation. The method combines an optimized Folch extraction protocol for dried plasma spots with high-resolution mass spectrometry analysis using a Thermo Q Exactive Orbitrap mass spectrometer coupled to a Dionex Ultimate 3000 ultrahigh performance liquid chromatography system. This internal quantitative DBS approach addresses key analytical challenges in microsampling applications through strategic incorporation of SIIS directly into the sampling matrix, enabling reliable normalization with improved extraction efficiency. The analytical workflow successfully integrates the simultaneous analysis of metabolites and lipids, demonstrating broad molecular coverage from minimal sample volumes in the microliter range. Method applicability was demonstrated using fasting plasma samples from a cohort of persons with HIV, revealing distinct molecular profiles between diabetic and nondiabetic participants, with hundreds of metabolites and thousands of lipids identified. The analytical platform leverages the inherent advantages of DBS, including simplified sample collection, enhanced stability during storage, and reduced biohazard risk during transportation. This methodology represents a significant advancement in quantitative DBS analysis, particularly valuable for large-scale clinical studies where conventional biobanking presents logistical challenges. The integration of SIIS into the microsampling device establishes a robust foundation for reliable multiomics analysis in resource-limited settings where whole blood or plasma storage is infeasible.

DOI: https://doi.org/10.1021/acs.analchem.5c01713
ACS Chem Biol. 2025 Sep 16.

Metabolic Tracing of Methyl Donor Utilization in Histone Methylation via Relative Quantification of Isotopomer Distribution Mass Spectrometry.

Hui Tang, Kangling Zhang.

Histone methylation depends on one-carbon metabolism, with methyl groups donated by methionine-, serine-, and glucose-derived intermediates. To dissect the metabolic origins of histone methylation, we developed Relative Quantitative Methyl Isotopomer Distribution Mass Spectrometry (RQMID-MS), a high-resolution mass spectrometry-based method that uses diagnostic low-mass fragment ions to quantify methyl group transfer from isotope-labeled precursors. Using this method, we mapped methylation sources to histone lysines in glioblastoma cells under nutrient and oxygen stress. Methionine was the dominant methyl donor under replete condition. Under combined serine and methionine depletion or prolonged methionine depletion alone, glucose emerged as a key compensatory source, particularly in U87 cells with elevated 3-phosphoglycerate dehydrogenase (PHGDH) expression. In contrast, U251 cells favored exogenous serine and glycine, correlating with higher levels of serine hydroxymethyltransferase 2 (SHMT2) expression. Hypoxia initially enhanced glucose-derived methylation but later suppressed it, likely due to impaired vitamin B12-dependent remethylation of homocysteine. RQMID-MS enables precise tracking of methyl donor routing to histones and offers a robust platform for studying metabolic and epigenetic crosstalk in cancer and beyond.

DOI: https://doi.org/10.1021/acschembio.5c00528
Cancer Med. 2025 Sep;14(18): e71244

Metabolic Reprogramming of Cancer Cells and Therapeutics Targeting Cancer Metabolism.

Jilsy M J Punnasseril, Abdul Auwal, Vinod Gopalan, Alfred King-Yin Lam, Farhadul Islam.

   BACKGROUND: Cancer metabolism is a field focused on the unique alterations in metabolic pathways that occur in cancer cells, distinguishing them from the metabolic processes in normal cells.
METHODS: An extensive review of the current literature on the metabolic adaptation of cancer cells was carried out in the current study.
RESULTS: The rapidly proliferating cells require high levels of molecules, such as glucose, amino acids, lipids, and nucleotides, along with increased energy demand (ATP). These requirements are met through alterations in the processes involving glucose, amino acid, lipid, and nucleotide metabolism. Modifications in glucose metabolism in cancer cells involve changes in glucose uptake, glycolysis, the pentose phosphate pathway, and the tricarboxylic acid cycle. Similarly, alterations in amino acid metabolism in cancer cells relate to upregulated amino acid transport and glutaminolysis. Cancer cells also have increased lipid intake from the extracellular microenvironment, upregulated lipogenesis, and enhanced lipid storage and mobilization from intracellular lipid droplets. These rapidly proliferating cells also achieve their increased demand for nucleotides by changing the expression of enzymes in the salvage and de novo nucleotide pathways. Consequently, these metabolic processes are targets for developing cancer therapeutics. However, it is important to note that the metabolic changes in cancer cells can also contribute to resistance against various cancer therapies.
CONCLUSION: This review will explore the various ways in which cancer cells reprogram metabolic processes to sustain rapid proliferation and survival. The information presented in this report could help in the therapeutics designed to target them, and the challenges of cancer drug resistance arising from these metabolic adaptations.

Keywords:  Warburg effect; cancer metabolism; drug resistance; glucose metabolism; nucleotide metabolism; therapeutics

DOI:  https://doi.org/10.1002/cam4.71244
Front Pharmacol. 2025 ;16 1634627

Differential carbon source utilization drives metabolic state and resuscitation in antibiotic-tolerant persister cells.

Yufei Sun, Sweta Roy, Qingbo Yang, Yinjie J Tang, Dacheng Ren.

   Introduction: Persistent infections remain challenging due to dormant bacterial cells that tolerate conventional antibiotics. Specifically, persister cells, phenotypic variants characterized by high antibiotic tolerance, can resume growth once antibiotic stress is alleviated. While general metabolic traits of persister cells have been documented, the metabolic shifts during persistence and resuscitation remain poorly understood.
Methods: We applied stable isotope labeling using 13C-glucose and 13C-acetate to investigate metabolism in Escherichia coli persisters induced by carbonyl cyanide m-chlorophenyl hydrazone (CCCP). Labeling incorporation into metabolic intermediates and proteinogenic amino acids was measured using LC-MS and GC-MS.
Results: The results demonstrated major differences in metabolic activities between normal and persister cells. Compared to normal cells, persister cells exhibited reduced metabolism. Peripheral pathways including parts of the central pathway, the pentose phosphate pathway, and the tricarboxylic acid (TCA) cycle, exhibited delayed labeling dynamics in persister cells. Proteinogenic amino acid profiling further demonstrated generalized but reduced labeling in persisters when using glucose as the sole carbon source, indicating a uniform slowdown in protein synthesis. Under acetate conditions, persister cells exhibited a more substantial metabolic shutdown, with markedly reduced labeling across nearly all pathway intermediates and amino acids. This reduction is likely due to substrate inhibition coupled with ATP demands required to activate acetate for central metabolism.
Discussion: These findings help improve the understanding of bacterial persistence by demonstrating that persister cell metabolism adapts to available carbon sources. These insights into persister metabolism may inform the development of targeted strategies to more effectively combat persistent bacterial infections.

Keywords:  CCCP; Escherichia coli; isotopic tracing; metabolism; persister; resuscitation

DOI:  https://doi.org/10.3389/fphar.2025.1634627
STAR Protoc. 2025 Sep 12. pii: S2666-1667(25)00491-5. [Epub ahead of print]6(4): 104085

Protocol for RNA modification analysis by UHPLC-QqQ MS.

Yueh-Lin Tsai, Nan Dai, Ivan R Corrêa.

  Over 170 RNA modifications have been reported across domains of life. Here, we present a protocol for identifying and quantifying modified nucleosides in RNA using ultra-high-performance liquid chromatography coupled with triple-quadrupole mass spectrometry (UHPLC-QqQ MS). We describe steps for preparing nucleoside standards, determining nucleoside retention time and mass transition, and building calibration curves for quantification. We next detail procedures for the digestion of RNA and sample analysis. This protocol was applied to RNA modification analysis in archaeal, bacterial, and eukaryotic cells. For complete details on the use and execution of this protocol, please refer to Tsai et al.1.

Keywords:  Biotechnology and bioengineering; Chemist; Mass Spectrometry

DOI:  https://doi.org/10.1016/j.xpro.2025.104085
J Pharm Biomed Anal. 2025 Sep 15. pii: S0731-7085(25)00487-X. [Epub ahead of print]267 117146

Features of sample preparation of cell culture samples for metabolomic screening by LC-MS/MS.

Nikita V Basov, Ekaterina A Butikova, Maria A Sotnikova, Ivan A Razumov, Yulia S Sotnikova, Yuriy V Patrushev, Artem D Rogachev, Nariman F Salakhutdinov, Andrey G Pokrovsky.

  Metabolomic analysis has become an essential tool in the life sciences, providing insights into cellular metabolism. However, preparing cell cultures for metabolomic screening remains challenging, especially with samples containing variable cell numbers. Standardized and reproducible protocols are required to ensure reliable data while maintaining compatibility with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Using melanoma cell lines SK-MEL-28 (human) and B16 (mouse) as models, we developed and optimized a convenient sample preparation protocol for metabolomic screening by HPLC-MS/MS. The study is focused on optimizing key steps, including cell lysis, metabolite extraction, and normalization strategies for accurate semiquantitative analysis. The effects of cell count on metabolomic coverage and detection sensitivity were evaluated using hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) chromatography. The protocol enables efficient detection of several metabolite classes from samples containing as few as 10,000 cells. The optimal cell count for reliable analysis was found to be 400,000 - 500,000 cells, ensuring consistent and reproducible detection within the method's analytical coverage. Our findings emphasize the importance of cell size and number in metabolomic studies, as larger cells provide improved metabolomic coverage. Moreover, metabolites exhibited varying detection limits, highlighting the need to adjust sample preparation strategies according to metabolite characteristics. The proposed protocol offers a robust and reproducible approach for the metabolomic screening of adherent melanoma cell cultures by HPLC-MS/MS and can be adapted for non-adherent and other cell types. Balancing sensitivity, reproducibility, and feasibility, this method provides a standardized solution for cell metabolomic studies in pharmacometabolomics, cancer research, and related fields.

Keywords:  Cell culture metabolomics; Cell number optimization; HILIC; HPLC-MS/MS standardization; RP LC; Targeted metabolomics

DOI:  https://doi.org/10.1016/j.jpba.2025.117146
Anal Methods. 2025 Sep 15.

Quantitative profiling of lipid mediators in sperm cells through on-line dilution on-line polymer matrix-based solid-phase extraction liquid chromatography with mass spectrometric detection.

Jörg Fabian, Matthias Lehr.

An automated on-line dilution on-line solid-phase extraction liquid chromatography-mass spectrometry method was developed for the straightforward and versatile quantitative profiling of lipid mediators such as various eicosanoids, endocannabinoids, and arachidonic acid in human sperm. The LC-MS/MS system utilized a polymer matrix-based trap column (TurboFlow Cyclone™) for sample pre-treatment, followed by chromatographic separation using an ODS 3 μm, 100 × 2 mm column, and detection via a triple-quadrupole mass spectrometer equipped with an electrospray interface. The sample preparation process employed a simple "dilute and shoot" approach, with a centrifugation step to remove proteins. This method has significantly improved sensitivity and selectivity while minimising matrix effects, with limits of quantification in the low picogram range for most analytes. Linearity, accuracy, precision, and recovery all met the required criteria for bioanalytical method validation. This LC-MS/MS approach was successfully applied to determine basal levels of selected eicosanoids, endocannabinoids, and arachidonic acid in human spermatozoa.

DOI: https://doi.org/10.1039/d5ay00250h
Talanta. 2025 Sep 07. pii: S0039-9140(25)01328-1. [Epub ahead of print]298(Pt A): 128837

Current trends in sample preparation for liquid chromatography - mass spectrometry analysis of catecholamines and their metabolites in biological samples.

Maria Khalikova, Klára Faistauerová, Miroslav Lísa.

  Catecholamines, including dopamine, norepinephrine, and epinephrine, are essential neurotransmitters and hormones that regulate a wide spectrum of physiological functions, such as stress response, mood, and cardiovascular activity. They are closely associated with various health conditions, making both them and their metabolites of great interest as potential biomarkers for diagnosing and monitoring the treatment of different human diseases. The use of catecholamines and their metabolites in research and clinical practice requires sensitive and accurate determination in various biological matrices, each of which presents unique challenges. In this review, we summarize sample preparation methods for liquid chromatography-mass spectrometry (LC-MS) determination of catecholamines and their metabolites in the most widely studied biological samples. We compare methods from the literature published between 2000 and the present for LC-MS analysis of urine, blood, brain, cerebrospinal fluid, and microdialysate samples. The methods are discussed concerning the specific properties of individual sample types, with special emphasis on method validation. Future trends in sample preparation procedures are outlined, including mainly microextraction techniques and automation of sample preparation procedures.

Keywords:  Catecholamines; Liquid chromatography; Mass spectrometry; Metabolomics; Neurotransmitters; Sample preparation

DOI:  https://doi.org/10.1016/j.talanta.2025.128837
Pharmacol Ther. 2025 Sep 12. pii: S0163-7258(25)00141-X. [Epub ahead of print]275 108929

Mass spectrometry-based absolute quantitative proteomics of drug-metabolizing enzymes in human liver.

Zachary McCalla, Xinwen Wang.

  Mass spectrometry-based absolute quantitative proteomics has emerged as a powerful method for accurately quantifying hepatic drug-metabolizing enzymes, which play a crucial role in drug disposition and therapeutic outcomes. Understanding the absolute drug-metabolizing enzyme protein concentrations and the associated interindividual variability in the liver, a primary organ for drug metabolism, is essential for developing predictive models for personalized pharmacotherapy. Over the past few decades, the rapid advancement of mass spectrometry-based proteomics has enabled the application of various techniques to study drug-metabolizing enzymes, significantly enhancing our understanding of their isoform composition in the liver. However, a focused review on mass spectrometry-based absolute protein quantification of human hepatic drug-metabolizing enzymes remains lacking. This review introduces commonly used strategies in mass spectrometry-based absolute protein quantification and summarizes the absolute quantities of Phase I and Phase II hepatic drug-metabolizing enzymes. It also updates the isoform compositions of cytochrome P450s and uridine diphosphate glucuronosyltransferases and explores factors contributing to variability in quantifications across studies. Additionally, we discuss the genetic and non-genetic regulations of hepatic enzyme protein expressions, as revealed by mass-spectrometry based-proteomics. Despite its potential for clinical applications, MS-based proteomics faces challenges, such as sensitivity limitation, significant inter-study varibility, cellular heterogeneity, and a lack of integration with other omics data. Future advancements in mass spectrometry-based quantitative proteomics, including single-cell proteomics, multi-omics integration, and artificial intelligence-driven data analysis, hold promise for better understanding of drug metabolizing enzymes, improving predictions of drug responses, and optimizing therapeutic outcomes for patients.

Keywords:  Absolute protein quantification; Drug metabolism; Drug-metabolizing enzymes; Liver; Mass spectrometry; Proteomics

DOI:  https://doi.org/10.1016/j.pharmthera.2025.108929
Nucleic Acids Res. 2025 Sep 05. pii: gkaf895. [Epub ahead of print]53(17):

Toward standardized epitranscriptome analytics: an inter-laboratory comparison of mass spectrometric detection and quantification of modified ribonucleosides in human RNA.

Martin Hengesbach, Chi-Kong Chan, Tulsi Bhandari, Alan Bruzel, Michael S DeMott, Ganna Podoprygorina, Guangxin Sun, Ellen Tabeling, Vivian G Cheung, Peter C Dedon, Mark Helm, Patrick A Limbach.

The human RNome comprises all forms of RNA and the 50 + chemical structures-the epitranscriptome-that modify them. Understanding the diverse functions of RNA modifications in regulating gene expression and cell phenotype requires technologies such as RNA sequencing-based modification mapping and mass spectrometry-based quantification of modified ribonucleosides. Liquid chromatography-coupled tandem quadrupole mass spectrometry (LC-MS/MS) is the gold standard for detecting and quantifying modified ribonucleosides with accuracy and precision. However, variations in RNA isolation, processing, and LC-MS/MS analysis have hindered reproducibility across laboratories, which is essential for accurate quantification of RNA modifications. As guidance toward harmonization, we report a multi-laboratory comparison of workflows for LC-MS/MS RNA modification analysis. We compared protocols for sample shipment, RNA hydrolysis, LC-MS/MS analysis, and data processing among three laboratories working with the same total RNA samples. We detected and quantified 17 modifications consistently across protocols and operators, with another 7 that were sensitive to experimental conditions, reagent contamination, and ribonucleoside instability, leading to poor precision among laboratories. Agreement among the three labs was strong, with coefficients of variation of 20% and 10% for relative and absolute quantification, respectively. These findings establish a robust and readily adoptable epitranscriptome analytical platform that enables reliable comparisons across laboratories.

DOI: https://doi.org/10.1093/nar/gkaf895
Asian Pac J Cancer Prev. 2025 Sep 01. pii: 91865. [Epub ahead of print]26(9): 3157-3174

Fueling Prostate Cancer: The Central Role of Glutamine/Glutamate Metabolic Reprogramming.

Ahmed S Alhallaq, Nadeen S Sultan.

  Metabolic reprogramming induced by the glutamine/glutamate (Gln/Glu) metabolic pathway is a key mechanism in ATP production, precursor biosynthesis, and redox homeostasis, promoting prostate cancer (PCa) growth and proliferation. This evolutionarily acquired hallmark of cancers enables malignant cells to adapt their bioenergetic and biosynthetic pathways in response to microenvironmental stresses. Therefore, Gln/Glu metabolism orchestrates epigenetic regulation, metastatic capacity, and oxidative homeostasis in PCa, supporting the survival of PCa tumors. Fluctuations in Glu metabolite levels and oxygen tension shape the PCa epigenome by facilitating Glu-derived α-ketoglutarate (α-KG) activation of TET and KDM enzymes, which drive histone and DNA demethylation. Furthermore, tumor progression toward metastatic castration-resistant PCa is characterized by heightened Gln/Glu dependency and increased Gln uptake. Within the tumor microenvironment (TME), a dynamic tug-of-war occurs between tumor and immune cells, competing for Gln metabolites. Gln/Glu converges on critical oncogenic signaling axes, including NF-κB/Nrf2, c-Myc/androgen receptor, MAPK/ERK, and PI3K/AKT/mTOR. Additionally, extracellular Glu release via SLC7A11 and PSMA triggers metabotropic glutamate receptor (mGluR) signaling, further potentiating oncogenic programs. Targeting this Gln/Glu metabolic network thus presents a promising therapeutic approach against PCa. In this review, we summarize the role of Gln/Glu in PCa progression based on the compartmentalization of the Gln/Glu metabolic pathway to elucidate why PCa cells manifest dependence on Gln/Glu. Eventually, we highlight potential therapeutic targets that can be exploited for PCa treatment.

Keywords:  Glutamine; Metabolic Reprogramming; Prostate Cancer; Tumor Microenvironment; glutamate

DOI:  https://doi.org/10.31557/APJCP.2025.26.9.3157
Front Oncol. 2025 ;15 1665056

Crosstalk between dysregulated amino acid sensing and glucose and lipid metabolism in colorectal cancer.

Danning Wang, Shaomin Zou, Junkang Ding, Chang Gao, Jianwei Wang, Zhe Tang.

  Cancer cells reprogram the metabolism of glucose, lipids, and proteins (amino acids) to meet their energy needs during tumor initiation and progression. Amino acid sensing pathways play rucial roles in the progression and spread of colorectal cancer (CRC), but the crosstalk between these pathways and glucose and lipid metabolism has not been systematically elucidated. We summarize the roles of key amino acids in CRC, the corresponding nutrient sensors, the associated dysregulated signaling pathways, and their subcellular localization. Furthermore, we highlight how disrupted amino acid sensing forms an integrated regulatory network that modulates glucose and lipid metabolism through multiple signaling cascades. These insights reveal both opportunities for clinical translation and unresolved challenges in the field. We believe that this comprehensive review will stimulate further research in this emerging area and draw significant attention from both the scientific community and broader audiences. This review aims to identify new diagnostic markers, therapeutic targets, and prognostic indicators by enhancing the understanding of nutrient metabolic pathway interactions.

Keywords:  amino acid sensing; colorectal cancer; glucose metabolism; lipid metabolism; mTORC1 signaling; metabolic reprogramming

DOI:  https://doi.org/10.3389/fonc.2025.1665056
Front Microbiol. 2025 ;16 1657647

TIE-UP-SIN: a novel method for enhanced identification of protein-protein interactions.

Maximilian Schedlowski, Stephan Michalik, Tilly Hoffmüller, Marco Harms, Leif Steil, Kristin Surmann, Christian Hentschker, Manuela Gesell Salazar, Uwe Völker, Alexander Reder.

  Proteins function through complex interaction networks that govern nearly all aspects of cellular physiology. Identifying protein-protein interactions (PPIs) under native conditions remains challenging due to the transient nature of many complexes and technical limitations of conventional approaches. We present TIE-UP-SIN (Targeted Interactome Experiment for Unknown Proteins by Stable Isotope Normalization), a robust and reproducible method for in vivo identification of PPIs. This approach combines metabolic labeling with 15N isotopes, reversible in vivo formaldehyde crosslinking, affinity purification, and quantitative mass spectrometry. TIE-UP-SIN is specifically designed to preserve transient or weak interactions during purification and to quantify interaction partners using internal light/heavy peptide ratios, reducing experimental variability and increasing reproducibility across biological replicates. The method employs a triple-sample design (WT/WT, Bait/WT, Bait/Bait) to distinguish specific from non-specific interactors. Peptide-level L/H ratios are normalized against sample-specific factors, aggregated at the protein level, and statistically analyzed using moderated testing. This strategy enables reliable detection of differential PPIs across physiological states, even in organisms with limited labeling options. We demonstrate the utility of TIE-UP-SIN by mapping interaction partners of the essential housekeeping sigma factor RpoD (SigA) under control and ethanol stress conditions. Known partners such as RNA polymerase subunits (RpoA, RpoB, RpoC) were robustly enriched, while potential novel candidates, including ClpX and AcpA, were detected at lower abundance. TIE-UP-SIN offers a simple, cost-effective, and modular platform for quantitative interactome analysis and can be adapted to a wide range of bacterial and non-bacterial systems. Compared to established approaches such as label-free IP-MS or proximity-based labeling methods, TIE-UP-SIN is intended as a complementary option. Its combination of specific control, robust quantification, and suitability for low-input material provides an additional tool within the broader proteomics workflow collection.

Keywords:  affinity purification-mass spectrometry; formaldehyde crosslinking; heavy nitrogen metabolic labeling; in vivo crosslinking; mass spectrometry; protein–protein interactions

DOI:  https://doi.org/10.3389/fmicb.2025.1657647
Anal Chem. 2025 Sep 18.

MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis.

Amoon Jamzad, Jade Warren, Ayesha Syeda, Martin Kaufmann, Natasha Iaboni, Christopher J B Nicol, John F Rudan, Kevin Y M Ren, David Hurlbut, Sonal Varma, Gabor Fichtinger, Parvin Mousavi.

Mass spectrometry imaging (MSI) combines spatial and spectral data to reveal detailed molecular compositions within biological samples. Despite their immense potential, MSI workflows are hindered by the complexity and high dimensionality of the data, making their analysis computationally intensive and often requiring expertise in coding. Existing tools frequently lack the integration needed for seamless, scalable, and end-to-end workflows, forcing researchers to rely on local solutions or multiple platforms, which hinders efficiency and accessibility. We introduce MassVision, a comprehensive software platform for MSI analysis. Built on the 3D Slicer ecosystem, MassVision integrates MSI-specific functionalities while addressing general user requirements for accessibility and usability. Its intuitive interface lowers barriers for researchers with varying levels of computational expertise, while its scalability supports high-throughput studies and multislide data sets. Key functionalities include visualization, segmentation, colocalization, data set curation, data set merging, spectral and spatial preprocessing, statistical analysis, AI model training, and AI deployment on full MSI data. We detail the workflow and functionalities of MassVision and demonstrate its effectiveness through different experimental use cases such as exploratory data analysis, ion identification, and tissue-type classification on in-house and publicly available data from different MSI modalities. These use cases underscore MassVision's ability to seamlessly integrate MSI data handling steps into a single platform and highlight its potential to reveal new insights and structures when examining biological samples. By combining cutting-edge functionality with user-centric design, MassVision addresses longstanding challenges in MSI data analysis and provides a robust tool for advancing the user's ability to achieve biologically meaningful insights from MSI data. MassVision is freely available via 3D Slicer (documentation: https://SlicerMassVision.readthedocs.io/). The in-house MSI data have been made publicly available in MetaboLights with the identifier MTBLS12868.

DOI: https://doi.org/10.1021/acs.analchem.5c04018
J Am Chem Soc. 2025 Sep 17.

Stable Isotope Labeling of Pyrimidines Using a Deconstruction-Reconstruction Strategy.

Benjamin J H Uhlenbruck, Andrew McNally.

Incorporating stable isotopes into bioactive molecules is crucial in pharmaceutical development, particularly for metabolic studies where higher mass isotopologs of candidate compounds are required. Here we present an isotope exchange method for synthesizing isotopically enriched pyrimidines. By deconstructing pyrimidines into vinamidinium salts and reconstructing them with deuterium, 13C, and 15N-enriched amidines, we achieve high isotopic enrichment across various substitution patterns, including complex drug-like pyrimidine derivatives. The process involves a Tf2O-mediated ring-opening and ring-closing sequence to form a pyrimidinium ion, followed by cleavage to the vinamidinium salt with pyrrolidine. Cyclization with labeled amidines under basic conditions then forms the labeled pyrimidine. Additionally, we deuterated the 5-position of pyrimidines using this approach to offer further versatility in generating higher mass isotopologs.

DOI: https://doi.org/10.1021/jacs.5c09719
Biochem Mol Biol Educ. 2025 Sep 17.

Quantitative Assessment for the Quality of Lipidomics Experiment Teaching.

Jinglin Zhou, Jian Pan, Wei Li.

  Sample preparation is a key step in most biological experiments, including in the subject of lipidomics. Lipidomics focuses on the study of lipids produced in specific organisms, so samples required in lipidomics experiments are usually solutions of biological lipids. To make sure that the scientific experiments are reliable, lipid samples in a set of controlled experiments must be standardized, that is, have almost the same quality. Preparing standardized samples is therefore an important taught component in most undergraduate as well as postgraduate programs in lipidomics. Previously, the standardization of lipid samples has only been assessed qualitatively. How to evaluate the effectiveness of students' standard operation training is crucial. In this paper, we propose a quantitative assessment metric and process for preparing standardized lipid samples, which is further evaluated in our teaching practice. We find out that the proposed method is effective, with the help of which we can identify gaps in our teaching.

Keywords:  assessment; lipidomics; sample preparation; standardization; teaching practice

DOI:  https://doi.org/10.1002/bmb.70013
Anal Chem. 2025 Sep 15.

Securing the Future of NMR Metabolomics Reproducibility: A Call for Standardized Reporting.

Erik R Andersson, Amanda L Bayless, Robert B Brua, Fabio Casu, Leo L Cheng, Munki Choo, Arthur S Edison, Hamid R Eghbalnia, Candace C Fleischer, Goncalo J Gouveia, Jeffrey C Hoch, Gagandeep Kaur, Da-Wei Li, Wimal Pathmasiri, István Pelczer, Fay Probert, Daniel Raftery, David Rovnyak, Michael Secreto, Tracey B Schock, Panteleimon G Takis, Mario Uchimiya, David S Wishart, Ali Yılmaz, Lloyd W Sumner, Robert Powers, Valérie Copié, Teklab Gebregiworgis.

Metabolomics is a rapidly growing multidisciplinary field with ever increasing demand and usability, which is attracting a surge of new researchers. While their varied skill sets, scientific questions, and approaches enrich the field with fresh perspectives and innovation, individual investigators also bring wide-ranging levels of metabolomics-specific experience and diverse areas of interest. These factors introduce considerable variability and inconsistency in both the methodology and reporting. A recent comparative literature review of nuclear magnetic resonance (NMR) metabolomics from studies published in 2010 and 2020 revealed significant shortcomings in the reporting of experimental details necessary for evaluating both the scientific rigor and the reproducibility of NMR-based metabolomics experiments. Each stage of metabolomics research contains multiple methodological choices and various optimization parameters, all of which can introduce experimental bias and alter the study results. This emphasizes the need for proper reporting to enhance reproducibility, data reusability, and study comparability. To address these concerns, the NMR Special Interest Group within the Metabolomics Association of North America presents reporting recommendations focused on fundamental aspects of NMR metabolomics research identified from the detailed literature review report. These include specifics with respect to study design, sample preparation, data acquisition, data processing and analysis, data accessibility, and comparability to previous studies. Also presented is a complementary list of seminal papers in the field to guide the study design and implementation of NMR metabolomics experiments. This initiative seeks to enhance the long-term impact of NMR metabolomics by supporting high-quality, reproducible, and impactful data collected from well-executed and thoroughly reported studies.

DOI: https://doi.org/10.1021/acs.analchem.5c03274
RSC Chem Biol. 2025 Sep 08.

Deciphering protein long-chain S-acylation using mass spectrometry proteomics strategies.

Anneroos E Nederstigt, Samiksha Sardana, Marc P Baggelaar.

Protein long-chain S-acylation, the reversible attachment of fatty acids such as palmitate to cysteine residues via thioester bonds, is a widespread post-translational modification that plays a crucial role in regulating protein localization, trafficking, and stability. Despite its prevalence and biological relevance, the study of long-chain S-acylation has long lagged behind that of other dynamic PTMs due to the hydrophobic nature and lability of the lipid modification, which complicate conventional proteomic workflows. Recent advances in mass spectrometry-based strategies have significantly expanded the toolbox for studying long-chain S-acylation, with improved workflows enabling more sensitive, site-specific, and quantitative analysis. This review summarizes key developments from the past decade across both direct and indirect mass spectrometry-based strategies, including acyl-biotin exchange, lipid metabolic labeling, and novel enrichment and fragmentation methods. We also highlight emerging challenges in distinguishing lipid-specific modifications, achieving robust quantification, and mitigating artifacts from in vitro systems, while outlining future directions to advance functional and therapeutic exploration of the S-acyl-(prote)ome.

DOI: https://doi.org/10.1039/d5cb00146c
J Proteome Res. 2025 Sep 15.

PAMPA: A Software for Peptide Markers and Taxonomic Identification for ZooMS Samples in Archaeology and Paleontology.

Fabrice Bray, Hélène Touzet.

  ZooMS (Zooarcheology by Mass Spectrometry) is a rapid and cost-effective method for species identification of animal remains through peptide mass fingerprinting. After mass spectrum generation, a common way to perform taxonomic identification is to compare the mass fingerprints to a reference database of diagnostic peptide markers to determine the species of origin. This analytical stage, however, is tedious and error-prone, often necessitating a manual examination of spectra. In this article, we present a comprehensive approach to automate and standardize the usage of peptide markers and the classification of ZooMS spectra. We have developed software called PAMPA (protein analysis by mass spectrometry for ancient species), for which we demonstrate the effectiveness using a variety of spectral data from bone samples generated by MALDI-TOF and MALDI-FTICR. PAMPA is open source and comes with a database of peptide markers and a collection of curated COL1A1 and COL1A2 sequences. We believe it will be a valuable resource for the scientific community.

Keywords:  MALDI FTICR MS; MALDI-TOF MS; Palaeoproteomics; Zooarcheology by mass spectrometry; bioinformatics; taxonomy

DOI:  https://doi.org/10.1021/acs.jproteome.5c00389