bims-mascan 2025-06-29 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–06–29
twenty-one papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

The Landscape of Cancer Metabolism as a Therapeutic Target.
High throughput single-cell proteomics of in vivo cells.
Accelerated Proteomic Sample Preparation for Accurate Ultrafast Mass Spectrometry-Based Quantitative Analysis of Cell and Tissue Proteomes.
Metabolic Assays for Brain Cancer Cells.
Development and Validation of a New LC-MS/MS Method for the Assay of Plasmatic Peripheral Short- and Medium-Chain Fatty Acids for Metabolomics Applications.
Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression.
Landscape of metabolic alterations and treatment strategies in breast cancer.
Optimization and validation of the Kairos amino acid Kit for plasma amino acid monitoring in inherited metabolic disorder patients.
Glutamine Metabolism: Molecular Regulation, Biological Functions, and Diseases.
Rapid Multi-Omics for Bacterial Identification Using Flow Injection-Ion Mobility-Mass Spectrometry.
Cancer cells get power boost by stealing mitochondria from nerves.
Quantitative approaches for spatial metabolomics with isomer differentiation using surface sampling capillary electrophoresis mass spectrometry.
Quantitative Proteomic Analysis Reveals JMJD6 and DNAJB11 as Endogenous Substrates of E3 Ligase RFFL.
Stable Isotope Labeling in Bacteria Enables Characterization and Quantification of Frataxin Protein in a Friedreich's Ataxia Zebrafish Model.
Histone Analysis Using Mobility- and Mass-Selected Ultraviolet Photodissociation in Tandem with Ultra-High-Resolution Mass Spectrometry.
Plasma lipidomic fingerprinting enables high-accuracy biomarker discovery for Alzheimer's disease: a targeted LC-MRM/MS approach.
Implications of Extra-column Effects for Targeted or Untargeted Microflow LC-MS.
Spatial metabolomics informs the use of clinical imaging for improved detection of cribriform prostate cancer.
An Integrated Platform for High-Throughput Extraction and Mass Spectrometry-Based Quantification of Cholesterol and Sphingosine.
Multicolumn Two-Dimensional Liquid Chromatography Screening Platform for Stereopeptidomics and Application to Antimicrobial Peptide Polyene and Lipopeptide.
A Methanolic Urea-enhanced Protein Extraction Enabling the Largest Bacterial Phosphorylation Resource.

Pathol Int. 2025 Jun 24.

The Landscape of Cancer Metabolism as a Therapeutic Target.

Kenji Ohshima.

  Cancer cells reprogram their metabolism during progression to adapt to the tumor microenvironment, which is characterized by distinct differences in nutrient availability, oxygen concentrations, and acidity. This metabolic reprogramming can simultaneously create metabolic vulnerabilities unique to cancer cells, making cancer metabolism a promising therapeutic target. Since the clinical application of folate antimetabolites in the 1940s, numerous therapeutic strategies targeting cancer metabolism have been developed. In recent years, advancements in technologies such as metabolome analysis have facilitated the development of agents that more specifically target cancer cell metabolism. However, these newly developed agents often face challenges in demonstrating efficacy as monotherapies in clinical trials. Nevertheless, combination therapies, designed based on precise mechanistic insights and incorporating agents such as immune-checkpoint and signaling-pathway inhibitors, have shown promising efficacy. This review provides an overview of the current landscape of therapeutic strategies targeting cancer metabolism, with a particular focus on approaches targeting amino acid, fatty acid, and glucose metabolism in cancer cells.

Keywords:  amino acid metabolism; cancer metabolism; cancer therapy; combination therapy; fatty acid metabolism; glucose metabolism

DOI:  https://doi.org/10.1111/pin.70034
Mol Cell Proteomics. 2025 Jun 20. pii: S1535-9476(25)00117-3. [Epub ahead of print] 101018

High throughput single-cell proteomics of in vivo cells.

Shiri Karagach, Joachim Smollich, Ofir Atrakchi, Vishnu Mohan, Tamar Geiger.

Single-cell mass spectrometry-based proteomics (SCP) can resolve cellular heterogeneity in complex biological systems and provide a system-level view of the proteome of each cell. Major advancements in SCP methodologies have been introduced in recent years, providing highly sensitive sample preparation methods and mass spectrometric technologies. However, most studies present limited throughput and mainly focus on the analysis of cultured cells. To enhance the depth, accuracy, and throughput of SCP for tumor analysis, we developed an automated, high-throughput pipeline that enables the analysis of 1,536 single cells in a single experiment. This approach integrates low-volume sample preparation, automated sample purification, and LC-MS analysis with the Slice-PASEF method. Integration of these methodologies into a streamlined pipeline led to a robust and reproducible identification of more than 3000 proteins per cell. We applied this pipeline to analyze tumor macrophages in a murine lung metastasis model. We identified over 1,700 proteins per cell, including key macrophage markers and more than 500 differentially expressed proteins between tumor and control macrophages. PCA analysis successfully separated these populations, revealing the utility of SCP in capturing biologically relevant signals in the tumor microenvironment. Our results demonstrate a robust and scalable pipeline poised to advance single-cell proteomics in cancer research.

DOI: https://doi.org/10.1016/j.mcpro.2025.101018
Biochemistry (Mosc). 2025 May;90(5): 607-621

Accelerated Proteomic Sample Preparation for Accurate Ultrafast Mass Spectrometry-Based Quantitative Analysis of Cell and Tissue Proteomes.

Daria D Emekeeva, Tomiris Kusainova, Leyla A Garibova, Andrey A Shelepchikov, Alexey S Kononikhin, Alexey V Tretyakov, Olga I Lavrukhina, Evgeny N Nikolaev, Mikhail V Gorshkov, Irina A Tarasova.

  Advances in liquid chromatography/mass spectrometry (LC-MS) have enabled proteome-wide quantitation in minutes, achieving rate of 1000 analyses per day. This necessitates revisiting the rapid sample preparation approaches to match this data acquisition speed. Despite the fact that these approaches have been developed decades ago, their application in quantitative ultrafast proteomics and comprehensive comparison of their performance under different conditions have not been explored. In this study, the ultrasound, microwave irradiation, and elevated temperature-assisted approaches for accelerated protein reduction, alkylation, and trypsin digestion were compared. Validation was carried out with label-free quantitative LC-MS/MS and fragmentation-free DirectMS1 methods of shotgun proteome analyses of Saccharomyces cerevisiae, human cell lines, and winter wheat shoots. These data acquisition methods were applied in ultrafast implementations employing 5 to 16 min LC gradients. Human-yeast proteome mixtures were used as standards to evaluate quantitation accuracy of the sample preparation workflows. Our findings indicate that the reduced time of sample preparation insignificantly decreased efficiency of reduction, alkylation, and digestion, yet, preserved reproducible peptide and protein identification. We also found that the 30-min microwave-assisted and overnight trypsin digestion yielded comparable quantitation accuracy in ultrafast analyses using DirectMS1 method.

Keywords:  accelerated protein digestion; fragmentation-free mass spectrometry; microwave digestion; sample preparation; ultrafast proteomics

DOI:  https://doi.org/10.1134/S0006297925600930
Methods Mol Biol. 2025 ;2944 49-64

Metabolic Assays for Brain Cancer Cells.

Emma Martell, Harshal Senthil, Esha Kaul, Helgi Kuzmychova, Tanveer Sharif.

  Metabolism is a fundamental foundation of all living organisms. However, cancer cells can modulate their metabolic activity to maintain their enhanced bioenergetic needs associated with uncontrolled proliferation. Some hallmarks of cancer metabolism include enhanced glucose uptake capacity and aberrations in mitochondrial metabolic activity and ATP production. In this chapter, we will outline several methods for studying critical metabolic parameters in brain cancer cells.

Keywords:  ATP; Cancer; Glucose uptake; Metabolism; Oxygen consumption

DOI:  https://doi.org/10.1007/978-1-0716-4654-0_5
Metabolites. 2025 Jun 16. pii: 403. [Epub ahead of print]15(6):

Development and Validation of a New LC-MS/MS Method for the Assay of Plasmatic Peripheral Short- and Medium-Chain Fatty Acids for Metabolomics Applications.

Lenard Farczadi, Laura Barcutean, Smaranda Maier, Rodica Balasa, Silvia Imre.

  Background: Short-chain fatty acids (SCFAs) and medium-chain fatty acids (MCFAs) are human metabolites which are involved in various biochemical processes and can offer valuable insights and information on various pathological and metabolic issues of patients. Accurate, precise, high-performance bioanalytical methods are important tools in both research and diagnostics of many pathologies, with LC-MS being the most frequently used methodology in modern metabolomics studies. Methods: The current paper describes a complete LC-MS/MS methodology for the accurate quantification of total plasmatic SCFA concentrations in humans using high-resolution QTOF mass spectrometric detection, including sample cleanup, preparation, and derivatization. Results and Conclusions: The method was validated with regard to all relevant parameters (selectivity, sensitivity, accuracy, precision, linearity, recovery, carryover, and reproducibility of sample preparation) according to the current applicable guidelines and tested in an in vivo study to quantify peripheral SCFAs in human patients as biomarkers for gut-brain axis disruption.

Keywords:  LC-MS/MS; multiple sclerosis; plasma; short-chain fatty acids

DOI:  https://doi.org/10.3390/metabo15060403
Cancer Cell. 2025 Jun 20. pii: S1535-6108(25)00253-3. [Epub ahead of print]

Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression.

Lisa Schweizer, Hilary A Kenny, Rahul Krishnan, Lucy Kelliher, Agnes J Bilecz, Janna Heide, Leonhard Donle, Aasa Shimizu, Andreas Metousis, Rachelle Mendoza, Thierry M Nordmann, Sarah Rauch, Sabrina Richter, Yan Li, Florian A Rosenberger, Maximilian T Strauss, Katherine C Kurnit, Marvin Thielert, Edwin Rodriguez, Johannes B Müller-Reif, S Diane Yamada, Fabian J Theis, Andreas Mund, Ricardo R Lastra, Matthias Mann, Ernst Lengyel.

  Epithelial serous borderline tumors (SBT) are non-invasive neoplastic ovarian lesions that may recur as chemo-resistant low-grade serous cancer (LGSC). While genetic alterations suggest a common origin, the transition from SBT to LGSC remains poorly understood. Here, we integrate cell-type resolved spatial proteomics and transcriptomics to elucidate the evolution from SBT to LGSC and its corresponding metastases in both stroma and tumor. The transition occurs within the epithelial compartment through an intermediary stage with micropapillary features, during which LGSC overexpresses c-Met and several brain-specific proteins. Within the tumor microenvironment, interconnectivity between cancer and stromal cells, along with enzymes degrading a packed extracellular matrix, suggests functional collaboration among various cell types. We functionally validated 16 drug targets identified through integrated spatial transcriptomics and proteomics. Combined treatment targeting CDK4/6 (milciclib) and FOLR1 (mirvetuximab) achieved significant tumor reduction in vivo, representing a promising therapeutic strategy for LGSC.

Keywords:  borderline tumor; deep visual proteomics; low-grade serous cancer; mass spectrometry; metastasis; ovarian cancer; pathology; proteomics; transcriptomics

DOI:  https://doi.org/10.1016/j.ccell.2025.06.004
Genes Dis. 2025 Sep;12(5): 101521

Landscape of metabolic alterations and treatment strategies in breast cancer.

Xiujuan Wu, Xuanni Tan, Yangqiu Bao, Wenting Yan, Yi Zhang.

  Breast cancer, the most prevalent cancer in women, poses a significant threat to their health. One of the prominent characteristics of malignant transformation in breast cancer cells is metabolic reprogramming, which encompasses glucose, lipid, and amino acid metabolism. Notably, breast cancer cells exhibit augmented energy metabolism and heightened glycolysis. In addition, there is an escalated demand for glutamine, which is met through intrinsic synthesis, uptake from extracellular sources via membrane transport proteins, or up-regulation of key metabolic enzymes in the glutamine metabolism pathway. Lipids not only serve as an energy source for tumor cells but also function as signaling molecules for intercellular communication. Extensive research in recent years has focused on unraveling the intricate mechanisms underlying metabolic reprogramming. Consequently, genes implicated in these processes have emerged as clinical therapeutic targets for cancer treatment. This review provides a comprehensive summary of the common metabolic alterations observed in cancer cells, discusses the factors and regulatory mechanisms influencing these changes, and explores potential therapeutic targets and strategies within the realm of cancer metabolism.

Keywords:  Amino acid metabolism; Breast cancer; Glucose metabolism; Lipid metabolism; Metabolic alterations

DOI:  https://doi.org/10.1016/j.gendis.2025.101521
Clin Biochem. 2025 Jun 21. pii: S0009-9120(25)00089-X. [Epub ahead of print] 110960

Optimization and validation of the Kairos amino acid Kit for plasma amino acid monitoring in inherited metabolic disorder patients.

Kiara Theron, Jeannette Gauthier, Marijn Van Hulle, Murray Potter.

   PURPOSE: Genetic disorders affecting amino acid metabolism are a significant subset of inherited metabolic disorders (IMDs). Plasma amino acid (PAA) analysis is used for the diagnosis and monitoring of these disorders in order to avoid development of severe symptoms. However, PAA assays are often lengthy in analysis time (>2h/sample) and some methods lack specificity and sensitivity. This project offers a novel solution through the optimization and clinical validation of the Kairos Amino Acid Kit by Waters Corp.
DESIGN AND METHODS: Using liquid chromatography with tandem mass spectrometry and 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate derivatization, amino acid quantification has been achieved for 45 amino acids in 15 min of chromatography time per sample. The method utilizes reversed-phase chromatography via a high-strength silica C18 column. The optimized column chemistry enables strong hydrophobic retention, resolving all isobaric amino acids for individual mass-spectrometer quantification. Method validation protocols include linearity, sensitivity, precision, and bias.
RESULTS: Clinical validation has been performed, indicating high reproducibility and clinical applicability. Linearity results demonstrated 42/45 amino acids with R2 > 0.975 over a linear range of at least 5-1000 µmol/L. Spiked plasma calibrators demonstrated high recovery with R2 > 0.971. Twenty-day precision testing demonstrated total coefficient of variation < 15 % and sensitivity testing confirmed all analytes have limits of detection < 5 µmol/L, indicating high analytical sensitivity and precision. Method comparison to Waters' MassTrak Kit demonstrates acceptable bias and supports a future study to update reference intervals.
CONCLUSION: The clinical validation of the Kairos Amino Acid Kit for plasma amino acid monitoring highlights the potential of this novel method to enhance amino acid quantification in clinical laboratories for IMD management.

Keywords:  Amino acid monitoring; Clinical validation; Derivatization; IMD; LC-MS/MS; Optimization

DOI:  https://doi.org/10.1016/j.clinbiochem.2025.110960
MedComm (2020). 2025 Jul;6(7): e70120

Glutamine Metabolism: Molecular Regulation, Biological Functions, and Diseases.

Mudasir A Kumar, Sana Khurshid Baba, Inamu Rashid Khan, Mohd Shahnawaz Khan, Fohad Mabood Husain, Saheem Ahmad, Mohammad Haris, Mayank Singh, Ammira S Al-Shabeeb Akil, Muzafar A Macha, Ajaz A Bhat.

  Glutaminolysis, the metabolic process of converting glutamine into key intermediates, plays an essential role in cellular energy production, signaling, biosynthesis, and redox balance. Deregulation of glutamine metabolism significantly influences various pathological conditions, including cancers and metabolic and neurological diseases. Emerging evidence shows that long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and oncogenic alterations in glutamine transporters and enzymes enhance glutamine's role as an alternative energy source, supporting cell survival and proliferation under nutrient and oxygen deprivation conditions. To combat the pathogenic effects of altered glutamine metabolism, researchers are developing targeted inhibitors of key enzymes and transporters involved in glutaminolysis. By interfering with the mechanisms that support the growth of cancer cells, these inhibitors may be able to stop the growth of tumors and treat metabolic and neurological conditions. This review provides a comprehensive overview of existing inhibitors and ongoing clinical trials targeting glutamine metabolism, focusing on its potential as a cancer therapeutic strategy. Additionally, the role of lncRNAs and circRNAs in regulating glutamine metabolism is explored, revealing novel avenues for therapeutic intervention in cancer and other diseases.

Keywords:  cancer; circular RNAs; glutamine metabolism; glutaminolysis; long noncoding RNAs; therapeutic targeting

DOI:  https://doi.org/10.1002/mco2.70120
Anal Chem. 2025 Jun 24.

Rapid Multi-Omics for Bacterial Identification Using Flow Injection-Ion Mobility-Mass Spectrometry.

Hannah M Hynds, Jana M Carpenter, Kelly M Hines.

The implementation of mass spectrometry (MS) in clinical microbiology has made a significant improvement in the turnaround time from positive culture to identification, but current protein-based approaches can struggle with species-level identification because of the high degree of homology within a genus. However, other MS-based strategies for bacterial identification that are based on lipids and small molecules have shown promise toward species-level identification and detection of specific phenotypes, including those related to antibiotic resistance. We are leveraging rapid gas-phase ion mobility (IM) separations coupled to MS to simultaneously detect the lipids and metabolites in bacterial pathogens. Using flow-injection (FI) rather than liquid chromatography (LC), we instead rely more directly on the structural separation of the IM dimension to resolve features from different biochemical classes and aid in identification. A head-to-head comparison demonstrates that the FI-IM-MS multiomic strategy performs similarly to LC-IM-MS in its ability to distinguish 24 strains of the high-concern ESKAPE pathogens, while shortening overall analysis time from 17 to 2 min per injection. We demonstrate that the IM dimension has excellent stability and reproducibility, which enables extracted IM peak areas to be used in lieu of chromatographic peak areas. Furthermore, the same features that are important for the discrimination of bacterial species and strains are found within both the FI-IM-MS and HILIC-IM-MS data sets. These results showcase the capabilities of mobility-enabled rapid multiomics and open the possibility to detect subtle strain-level differences and resistance phenotypes in bacterial pathogens by including additional classes of biomolecules.

DOI: https://doi.org/10.1021/acs.analchem.5c00417
Nature. 2025 Jun 25.

Cancer cells get power boost by stealing mitochondria from nerves.

Traci Watson.



Keywords:  Cancer; Cell biology; Metabolism; Neuroscience

DOI:  https://doi.org/10.1038/d41586-025-01941-z
Talanta. 2025 Jun 18. pii: S0039-9140(25)00972-5. [Epub ahead of print]296 128482

Quantitative approaches for spatial metabolomics with isomer differentiation using surface sampling capillary electrophoresis mass spectrometry.

Anastasia Golubova, Ingela Lanekoff.

  The importance of metabolites and their isomeric structures in biological function and dysfunction is increasingly recognized. However, achieving quantitative mapping of metabolites within tissue regions, particularly with isomeric specificity, remains an analytical challenge. This work presents the development of a quantitative surface sampling capillary electrophoresis method for spatial metabolomics with isomeric resolution. Five quantitation strategies were evaluated, with the optimal approach identified as sequential injection of metabolites directly from tissue alongside standards. This methodology was applied to a rat brain tissue section in a proof-of-principle study, enabling quantitative spatial analysis of metabolites, neurotransmitters, and isomeric species. Among the findings, the aromatic amino acids tyrosine, phenylalanine, and tryptophan exhibited the most dynamic distributions across four brain regions, while leucine and isoleucine demonstrated distinct spatial profiles, with leucine consistently being the more abundant isomer. This method offers a promising tool for advancing the understanding of spatially resolved biochemical processes underlying biological function and dysfunction.

Keywords:  Brain tissue section analysis; Capillary electrophoresis-mass spectrometry; Quantitative metabolomics; Spatial metabolomics

DOI:  https://doi.org/10.1016/j.talanta.2025.128482
J Proteome Res. 2025 Jun 26.

Quantitative Proteomic Analysis Reveals JMJD6 and DNAJB11 as Endogenous Substrates of E3 Ligase RFFL.

Nikhil Dev Narendradev, Soumitra Marathe, Sabyasachi Baboo, Daniel B McClatchy, Jolene K Diedrich, Parul Jain, Rahul Purwar, John R Yates, Srinivasa Murty Srinivasula.

  The ubiquitin-proteasome system contributes to protein quality control, involving E3 ligases that ubiquitinate proteins and leading to their degradation. The dysregulation of protein degradation results in the abnormal accumulation of proteins and is implicated in the pathology of diverse diseases, making targeted protein degradation a promising therapeutic strategy. Here, we focus on RFFL, an endosome-associated RING E3 ligase involved in mitochondrial homeostasis and the clearance of misfolded cystic fibrosis transmembrane conductance regulator proteins. Using label-free quantitative mass spectrometry based proteomics for interactome and differential expression analyses, we systematically investigated and identified putative substrates of RFFL. For more confident identification, we performed these analyses on three cell lines that we generated: an RFFL knockout cell line generated using CRISPR/Cas9, another cell line rescuing RFFL expression when complemented with KO cells with stably expressing RFFL cDNA, and wild-type cells. We validated JMJD6 and DNAJB11 as substrates of endogenous RFFL, providing orthogonal validation and confidence in our screening approach. We demonstrated that RFFL ubiquitinates and degrades JMJD6 and DNAJB11 via the proteasomal pathway using in vivo assays. Interestingly, we also discovered a hitherto unknown role of RFFL in lipid metabolism. Collectively, this study provides the first comprehensive and unbiased analysis of RFFL substrates employing multiple complementary approaches.

Keywords:  E3 ligase; RFFL; interactome; proteomics; substrates

DOI:  https://doi.org/10.1021/acs.jproteome.5c00086
Anal Chem. 2025 Jun 24.

Stable Isotope Labeling in Bacteria Enables Characterization and Quantification of Frataxin Protein in a Friedreich's Ataxia Zebrafish Model.

Teerapat Rojsajjakul, Wonwook Do, Robert B Wilson, Ian A Blair.

Friedreich's ataxia (FRDA) is a neurodegenerative and cardiodegenerative genetic disorder caused primarily by homozygous mutations in the FXN gene, resulting in decreased expression of human mature frataxin (hFXN-M) protein. To test potential new drugs, we developed mutant zebrafish with a deficiency in zebrafish FXN-M (zFXN-M) production by introducing targeted mutations in the z-fxn gene. To validate this model, it was necessary to characterize and quantify zFXN-M protein, but zFXN-M protein could not be detected by Western blot in zebrafish lysates. We developed an alternative strategy involving the use of a stable isotope-labeled internal standard coupled with analysis by high-sensitivity ultrahigh-performance liquid chromatography-multiple reaction monitoring-mass spectrometry (UHPLC-MRM/MS). The endogenous zFXN-M in an internal standard prepared using stable isotope labeling by amino acids in cell culture (SILAC) would have obscured low levels of zFXN-M. In contrast, stable isotope labeling in bacteria (SILIB) provided fully labeled [13C,15N]-zFXN-M with almost undetectable amounts of endogenous protein contamination. This facilitated characterization of amol levels of zFXN-M in zebrafish embryos (120.9 ± 20.1 amol/embryo) and its quantification in intact wild-type fish with levels of 2.26 ± 0.44 ng/mg protein or 145.2 ± 24.5 pg/mg tissue. Recovery of zFXN-M was <10% when the SILIB internal standard was added after isolation, when compared with before isolation. UHPLC-MRM/MS with a SILIB internal standard was the only way to validate zebrafish heterozygous for a knockout mutation in zFXN as a model for FRDA, illustrating its utility for the characterization and quantification of very low abundance tissue proteins.

DOI: https://doi.org/10.1021/acs.analchem.4c07095
Anal Chem. 2025 Jun 24.

Histone Analysis Using Mobility- and Mass-Selected Ultraviolet Photodissociation in Tandem with Ultra-High-Resolution Mass Spectrometry.

Cassandra N Fuller, Md Shofiul Alam, Kevin Jeanne Dit Fouque, Lilian Valadares Tose, Richard M Searfoss, Francisca N de Luna Vitorino, Mariangela Kosmopoulou, Detlev Suckau, Mark E Ridgeway, Steve Van Orden, Benjamin A Garcia, Francisco Fernandez-Lima.

Ultra-high-resolution Fourier transform ion cyclotron resonance mass spectrometry (UHR FT-ICR MS) for top-down proteomics has shown the potential to resolve proteoforms and splice variants, particularly those with post-translational modifications. Here, we integrate trapped ion mobility and mass selection in tandem with ultraviolet photodissociation (UVPD) followed by FT-ICR MS measurements. The proposed method using mobility/mass-selected UVPD before FT-ICR MS allows for high protein sequence coverage and PTM localization with high mass accuracy (<1 ppm) and a better duty cycle (2×). When applied to the analysis of a bovine histone mixture, characteristic UVPD a/b/c/x/y/z ions led to the annotation of 51 proteoforms from H2B, H2A, and H4 core histones with high sequence coverages (up to 77%). Histone variants and PTM combinations, including acetylation, mono-, di-, and trimethylation, and phosphorylation, identified at the top-down level were confirmed using bottom-up analysis. This work provides the foundation for effective mobility and mass preselection of precursor ions and better annotation and spectral decongestion of UVPD fragments from protein mixtures, with general applicability for top-down proteoform analysis with minimal sample preparation.

DOI: https://doi.org/10.1021/acs.analchem.5c02166
Geroscience. 2025 Jun 27.

Plasma lipidomic fingerprinting enables high-accuracy biomarker discovery for Alzheimer's disease: a targeted LC-MRM/MS approach.

Xia Gao, Xiaoqin Cheng, Peipei Chen, Ling Lin, Xiaoyu Wang, Runbing Xu, Huali Shen, Qian Yang.

  Dysregulation of lipid metabolism is increasingly recognized as a key factor in the pathogenesis of Alzheimer's disease (AD). Unfortunately, an accurate lipidomic fingerprints in AD patients' biofluids remains challenging. A comprehensive analysis of plasma samples from 26 patients with AD and 30 healthy individuals was performed using untargeted and targeted lipidomics techniques with strict lipid annotation criteria. By monitoring characteristic fragments per precursor, we achieved precise lipid characterization and quantification for approximately 270 lipid species. Multivariate statistical analysis revealed a distinct lipid profile between AD patients and controls, with 72 lipids significantly altered (FC > 1.5 or < 0.667, VIP > 1, P < 0.05). Notably, a biomarker analysis based on the multivariate exploratory receiver operating characteristic (ROC) curve identified a comprehensive panel consisting of 10 novel lipids as potential markers for AD, achieving 98.2% accuracy with a favorable auxiliary diagnostic value (area under curve of 0.995). Additionally, the higher levels of SM(d18:1/16:0), SM(d18:1/18:1), and LPE 18:0 were strongly correlated with the clinical dementia rating (CDR) and mini-mental state examination (MMSE) scores, underscoring the therapeutic potential of lipid modulation in AD. These findings reveal the intricate relationship between lipid alterations and AD pathology and emphasize the necessity for LC-MRM/MS lipidomics with rigorous criteria in the discovery of reliable biomarkers, enriching our understanding of lipid roles in neurodegenerative processes and informing future mechanistic investigations and drug target development.

Keywords:  Alzheimer's disease; Biomarkers; Machine learning; Targeted lipidomics

DOI:  https://doi.org/10.1007/s11357-025-01777-5
ACS Meas Sci Au. 2025 Jun 18. 5(3): 332-344

Implications of Extra-column Effects for Targeted or Untargeted Microflow LC-MS.

Troy T Handlovic, Umang Dhaubhadel, Ondřej Horáček, Martin Novák, Lucie Nováková, Daniel W Armstrong.

  Mass spectrometry (MS) has changed our understanding of health, disease, and the environment through untargeted analyses where entire molecular classes are investigated. These techniques generate huge amounts of data which when processed by statistical tools can identify important molecular features or biomarkers. The complexities of these samples are not compatible with direct introduction to the MS system and require a high-resolution separation step, typically low flow liquid chromatography (LC), prior to MS. LC columns that can produce adequate linear velocities at these low flow rates are small in volume making their results susceptible to resolution loss in extra-column volumes. Here, we investigate the implications of the extra-column effects in five LC-MS systems with triple quadrupole and orbitrap mass analyzers. The extra-column volume of these systems in their standard configuration ranged from 26.4 to 78.1 μL which we reduced to 9.57 to 18.7 μL by optimizing the fluidics. The effects of this volume reduction were assessed by studying a hydrolyzed protein sample in a proteomics environment where the intensity of the largest MS peak was improved by 1.8-3.8×. Additionally, the number of molecular features detected in the protein sample improved by up to 7.5×. The relationship between extra-column volumetric variance and flow rate shows that broadening will become much larger for MS detectors at higher flow rates, unlike a traditional small volume UV detector. The methods, applications, and theoretical insights in this work can be used to improve the mass spectrometric results of any LC-MS system.

Keywords:  LC-MS; band broadening; extra-column effects; instrumentation; liquid chromatography; omics; proteomics

DOI:  https://doi.org/10.1021/acsmeasuresciau.5c00015
Proc Natl Acad Sci U S A. 2025 Jul;122(26): e2502423122

Spatial metabolomics informs the use of clinical imaging for improved detection of cribriform prostate cancer.

Nikita Sushentsev, Gregory Hamm, Roido Manavaki, Mary A McLean, Jonathan Birchall, Dmitry Soloviev, David Y Lewis, Luigi Aloj, Lucy Flint, Aleksandr Zakirov, Ian G Mills, Vincent J Gnanapragasam, Anne Y Warren, Simon T Barry, Richard J A Goodwin, Ferdia A Gallagher, Tristan Barrett.

  Cribriform prostate cancer (crPCa) is associated with poor clinical outcomes, yet its accurate detection remains challenging due to the poor sensitivity of standard-of-care diagnostic tools. Here, we use untargeted spatial metabolomics to identify fatty acid biosynthesis as a key metabolic pathway enriched in crPCa epithelium. We also show that imaging tumor lipid metabolism using [1-11C]acetate PET/CT and proton magnetic resonance spectroscopy differentiates cribriform from noncribriform intermediate-risk prostate cancers in two prospective patient cohorts. These findings support the feasibility of using clinical metabolic imaging techniques as adjunctive tools for improving crPCa detection in clinical practice, with prospective studies in larger cohorts warranted to obtain definitive results.

Keywords:  MRI; cancer metabolism; nuclear medicine; prostate cancer; spectroscopy

DOI:  https://doi.org/10.1073/pnas.2502423122
Anal Chem. 2025 Jun 24.

An Integrated Platform for High-Throughput Extraction and Mass Spectrometry-Based Quantification of Cholesterol and Sphingosine.

Yi-Han Lin, Yuhong Fang, Maya L Gosztyla, Edward Zhu, Abhijeet Kapoor, Andrés E Dulcey, Daniel C Talley, Shu Yang, Miao Xu, Xin Hu, Wei Zheng, Anton Simeonov, Juan J Marugan, Mark J Henderson, Christopher A LeClair, Bolormaa Baljinnyam, Dingyin Tao.

Quantification of cellular lipids in a reproducible and high-throughput manner is a key step in the development of therapeutics for lipid storage diseases. Niemann-Pick Disease Type C (NPC) is a genetic disorder characterized by the accumulation of unesterified cholesterol in late endosomes/lysosomes, which is usually measured by the filipin fluorescence assay. However, the nonspecific binding of filipin to other sterol derivatives, multiple assay steps, and difficulty in quantitation present limitations for high-throughput screening and accurate cellular cholesterol quantification. We report the development of an integrated and semiautomated protocol to extract and quantify cellular cholesterol in 384-well plates by utilizing a liquid handling platform in conjunction with a high-throughput mass spectrometry (MS) system. The 384-well plate format enables seamless lipid extraction and subsequent MS analysis in less than 2 h from a cell culture plate to final MS data. Cholesterol was extracted from neural stem cells differentiated from NPC induced pluripotent stem cells using methyl tert-butyl ether (MTBE), with 13C-cholesterol serving as an internal standard for quantification and normalization of native cholesterol. This integrated platform showed excellent quantification linearity and reproducibility (intraday and interday, R2 > 0.99) with a recovery rate between 83 and 107%. We employed this integrated platform to screen a collection of 241 investigational compounds at seven concentrations each, benchmarking the method as an efficient, label-free cellular cholesterol quantification assay for high-throughput applications. Furthermore, we demonstrated the capability to multiplex extraction and quantification of sphingosine/cholesterol in a single MS run, extending the applicability of this integrated workflow to other lipid storage diseases.

DOI: https://doi.org/10.1021/acs.analchem.4c06628
Anal Chem. 2025 Jun 24.

Multicolumn Two-Dimensional Liquid Chromatography Screening Platform for Stereopeptidomics and Application to Antimicrobial Peptide Polyene and Lipopeptide.

Cornelius Knappe, Simon J Jaag, Taulant Dema, Ruslan Jaufmann, Stephan Buckenmaier, Harald Gross, Stephanie Grond, Michael Lämmerhofer.

Therapeutic peptides are a rapidly growing field in research and drug development. While the majority of natural and synthetic therapeutic peptides have l-amino acids as building blocks, d-amino acid-containing peptides are found frequently in nonribosomal peptides or can be formed during peptide synthesis by epimerization. Thus, analytical methods are needed for the quality control of stereointegrity and the determination of absolute configurations. Enantioselective amino acid analysis following complete hydrolysis is indispensable in the field but leads to the loss of sequence information, i.e., the position of d-amino acids can no longer be unambiguously assigned. Here, we propose a multicolumn two-dimensional liquid chromatography-tandem high-resolution mass spectrometry (2D LC-HRMS) platform with multiple reversed-phase type columns (C18, charged surface hybrid C18, mixed-mode C18 AX) in the first dimension (1D) and multiple chiral columns in the second dimension (2D) (teicoplanin, teicoplanin aglycone, crown ether, and zwitterionic quinine and quinidine carbamate-based chiral stationary phases). It allows the combination of distinct 1D columns (for peptide epimer/diastereomer separations) and 2D columns (for peptide enantiomer separations), enabling the full resolution of complex peptide stereoisomer mixtures. The utility of this 2D-LC platform for peptide analyses was demonstrated for a tetrapeptide amide from an antimicrobial peptide polyene natural product and a lipopeptide, digested into dipeptides for middle-down/middle-up stereoselective peptide analysis. Multiple heart-cutting and selective comprehensive 2D-LC, respectively, with active solvent modulation and sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) enabled the full separation of all stereoisomers and the clarification of the configurations of all sample peptides. Such a 2D-LC-HRMS screening platform can be valuable as an efficient and fast generic approach for streamlining method development in the pharmaceutical industry.

DOI: https://doi.org/10.1021/acs.analchem.5c02658
Mol Cell Proteomics. 2025 Jun 24. pii: S1535-9476(25)00118-5. [Epub ahead of print] 101019

A Methanolic Urea-enhanced Protein Extraction Enabling the Largest Bacterial Phosphorylation Resource.

Pei-Shan Wu, Ting-An Chen, Bo-Yu Chen, Yasushi Ishihama, Miao-Hsia Lin.

Mass spectrometry (MS)-based phosphoproteomics analysis is a powerful approach for elucidating the regulatory roles of protein phosphorylation across all domain of life. However, bacterial phosphoproteomics still faces significant technical challenges due to the extremely low substoichiometry of phosphorylation evens and the structural complexity of bacterial cell envelopes, which impede efficient cell lysis, protein recovery and purity. To address these obstacles, we developed Methanolic Urea-enhanced Protein Extraction (MUPE), a streamlined, detergent-free, solvent-based method that leverages the amphiphilic nature of methanol and the chaotropic properties of urea to enhance protein yield and lysis efficiency. Furthermore, MUPE seamlessly integrates with liquid-liquid extraction, enabling efficient protein purification without requiring sample transfer and complex manipulations. This workflow significantly improves phosphoproteome coverage and quantitative accuracy across Gram-positive and Gram-negative bacteria, while minimizing sample input requirements. Our datasets substantially expand the known landscape of bacterial O-phosphorylation, revealing distinct phosphorylation preferences within bacterial signaling networks. Application of MUPE to Listeria monocytogenes under bile insult revealed extensive phosphorylation changes independent of protein expression, highlighting phosphorylation as a rapid and dynamic regulatory mechanism. Collectively, MUPE provides a robust and scalable platform for bacterial phosphoproteomic studies, advancing our understanding of phosphosignaling in the context of bacterial physiology and pathogenesis.

DOI: https://doi.org/10.1016/j.mcpro.2025.101019