J. Proteome Res. [JOURNAL]
Sun
200 papers
Proteomic Biomarker Discovery in Cerebrospinal Fluid Identifies CD74 and CD14 for Differentiating Multiple Sclerosis from Neuromyelitis Optica.
Ding M, Jiang Y, Zhang J … +13 more , Fan M, Zhao W, Chen D, Zhang Y, Wu X, Wang R, Chen X, Kong WJ, Yu B, Liu C, Cong Q, Zhang Y, Fang P
J Proteome Res · 2026 Jun · PMID 42059822 · Publisher ↗
Multiple sclerosis (MS) and neuromyelitis optica (NMO) are distinct autoimmune demyelinating diseases of the central nervous system with overlapping clinical features, complicating early diagnosis. Accurate differentiati...
Multiple sclerosis (MS) and neuromyelitis optica (NMO) are distinct autoimmune demyelinating diseases of the central nervous system with overlapping clinical features, complicating early diagnosis. Accurate differentiation is essential to avoid inappropriate treatment and improve outcomes. We conducted a comprehensive proteomic analysis of cerebrospinal fluid (CSF) from MS and NMO patients using both conventional proteomics and a nanoparticle-based low-abundance protein enrichment strategy (LAPE). Deep CSF proteome coverage yielded 3,816 proteins. Proteomic profiling revealed shared and distinct molecular features of MS and NMO. The common downregulation of neuronal adhesion pathways and the activation of immune responses highlight convergent mechanisms of neurodegeneration and inflammation, whereas MS-specific alterations in glycosylation suggest divergent molecular processes. Differential proteomic analysis delineated disease-specific signatures, with MS characterized by enhanced macrophage signaling, chemokine production, and complement activation, while NMO was distinguished by hemostasis-related pathways, Toll-like receptor 4 signaling, and neuroinflammatory responses. LAPE uncovered MS-associated changes in focal adhesion, cognition, and learning, and NMO-associated enrichment of lysosomal and phagocytic processes. Validation in an independent cohort using enzyme-linked immunosorbent assay (ELISA) confirmed CD74 as an MS-specific and CD14 as an NMO-specific biomarker with ROC analyses (AUC 0.75 for CD74; 0.72 for CD14) supporting their robust utility as discriminating biomarkers in clinical practice.
Obstructive Sleep Apnea Associated with Periodontitis: Evidence from Mendelian Randomization and Salivary Proteomics.
Yu M, Feng M, Chen X … +3 more , Ma K, Gong X, Gao X
J Proteome Res · 2026 Jun · PMID 42057688 · Full text
Clinical evidence supports a link between obstructive sleep apnea (OSA) and periodontitis. However, whether OSA exerts a causal effect on periodontitis and the underlying protein biomarkers remains unclear. This study ai...
Clinical evidence supports a link between obstructive sleep apnea (OSA) and periodontitis. However, whether OSA exerts a causal effect on periodontitis and the underlying protein biomarkers remains unclear. This study aimed to investigate their causal relationship and to identify salivary protein markers involved in the shared pathogenesis. First, a bidirectional two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) statistics was conducted to evaluate the causal relationship. Second, data-independent acquisition (DIA)-based salivary proteomics was applied to identify differentially expressed proteins in periodontally healthy patients with OSA ( = 30) and controls ( = 10). The OSA-associated upregulated proteins were screened for consistency with OSA severity and overlap with an independent periodontitis cohort. Network and hub protein analyses were performed. Genetic analysis in the MR suggested that OSA could statistically contribute to periodontitis development, but not in the reverse direction. Salivary proteomics revealed severity-dependent expression changes in OSA, with upregulated proteins enriched in the antigen processing and presentation pathway. Eight proteins detected in OSA patients showed increased expression with periodontal destruction. NAMPT, GSN, and S100A8/A9 emerged as hub proteins, validated by ELISA in independent OSA-associated periodontitis patients. The integrative genetic and proteomic investigations support a potential causal and proteome association between OSA and periodontitis, highlighting NAMPT, GSN, and S100A8/A9 as candidate mediators that may underpin the inflammatory interplay.
Bimodal Peptide Collision Cross Section Distribution Reflects Two Stable Conformations in the Gas Phase.
Restrepo J, Szoelloesi D, Kiermeyer T … +3 more , Wichmann C, Grubmüller H, Cox J
J Proteome Res · 2026 Jun · PMID 42053382 · Full text
Recent high-throughput applications to shotgun proteomics have shown great benefits of coupling ion mobility spectrometry (IMS) to mass spectrometry. IMS adds a separation dimension by differentiating biomolecules from t...
Recent high-throughput applications to shotgun proteomics have shown great benefits of coupling ion mobility spectrometry (IMS) to mass spectrometry. IMS adds a separation dimension by differentiating biomolecules from their size and shape. We (and others) find that the distribution of the peptide collision cross section (CCS) is often bimodal, which limits the utility of current machine learning predictions for peptide identification. Molecular dynamics simulations indicate that the peptides in the drift tube can adopt multiple stable conformations and that the two modes correspond to predominantly extended (mostly helical) and more compact (globular and less ordered) conformations. Most peptides have a charge-dependent strong preference for one of the two conformations, while some can adapt to both, as evidenced by a simple geometric model of the CCS data. We suggest a novel two-valued CCS predictor that allows for multiple peptide conformations. Its integration into data-independent acquisition proteomics increases identification rates of peptides compared with single-value predictors.
A Selective History of Protein Sequencing and the Impact of Donald F. Hunt on Protein Sequencing by Tandem Mass Spectrometry.
Yates JR
J Proteome Res · 2026 Jun · PMID 42048638 · Full text
This review is a selective history of protein sequencing through the year 2000, intended to illuminate just how challenging it was to establish the methods that enabled protein analysis, especially protein analysis by ma...
This review is a selective history of protein sequencing through the year 2000, intended to illuminate just how challenging it was to establish the methods that enabled protein analysis, especially protein analysis by mass spectrometry. My goal is to provide context to the development and impact of mass spectrometry-based methods on protein sequencing over the last 75 years and to highlight the significant research critical to the development of protein sequencing methods. Because the chemistry of proteins is so diverse, an easy "one size fits all" protein sequencing method (such as the methods available for sequencing DNA) was not feasible. The original protein sequencing methods pursued by Sanger, Du Vigneaud, and Edman relied on chemical methods to decipher amino acid sequences, but in 1959 Klaus Biemann used mass spectrometry to analyze di- and tripeptides, thus introducing the use of mass spectrometry to the protein sequencing field. Donald F. Hunt of the University of Virginia was the first to develop tandem mass spectrometry-based methods for sequencing peptides and proteins, and many of his methods are in use to this day. Hunt made landmark contributions in mass spectrometry technology development and applied his tandem mass spectrometry methods widely across biology, particularly in the field of immunology. The aim of this review is to provide a historical context for Hunt's contributions (as well as other mass spectrometrists!) to protein sequencing and proteomics and to honor Dr. Hunt's contributions upon his retirement.
Mitochondrial Proteomics Uncovers that Myeloid S100A9 Deficiency Promotes Liver Injury and Fibrosis Regression via Mitochondrial Metabolic Reprogramming of Macrophages.
Liu J, Liu R, Shi Y … +8 more , Sun Y, Zhang Z, Mao M, Chang L, Zhang T, Han C, Wu J, Xu P
J Proteome Res · 2026 Jun · PMID 42048253 · Publisher ↗
Macrophage-mediated inflammation has been implicated in the pathogenesis of liver fibrosis. Metabolic reprogramming involves the transition of macrophages from a proinflammatory M1 phenotype toward an anti-inflammatory M...
Macrophage-mediated inflammation has been implicated in the pathogenesis of liver fibrosis. Metabolic reprogramming involves the transition of macrophages from a proinflammatory M1 phenotype toward an anti-inflammatory M2 phenotype. S100A9 is highly expressed in activated macrophages and promotes M1 polarization; however, it is unknown whether S100A9 alters the polarization state of macrophages by regulating metabolism. This study revealed enhanced oxidative phosphorylation (OXPHOS) in -deficient bone marrow-derived macrophages (BMDMs) based on mitochondrial proteomics, characterized by increased mitochondrial fusion and elevated ATP production. Further phenotypic analysis showed that -deficient peritoneal macrophages and BMDMs exhibited an M2-like phenotype at the basal state and enhanced M2 polarization with IL-4/IL-13 stimulation, reflected by higher CD206 expression. Using the OXPHOS inhibitor oligomycin, we demonstrated that suppressing OXPHOS completely rescued the M2 polarization bias of the -deficient macrophages. Finally, we found that genetic deletion of S100A9 in myeloid cells protected against liver injury and fibrogenesis through increasing the proportion of hepatic CD206-positive M2-like anti-inflammatory macrophages in a mouse model. Our study uncovers a novel role of S100A9 in macrophage mitochondrial metabolism and phenotype reprogramming during liver fibrosis, and targeting macrophage S100A9 may be considered as a potential therapeutic strategy against liver fibrosis.
OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data.
Degnan DJ, Richardson RE, Claborne DM … +5 more , Strauch CW, Glasscock EC, Webb-Robertson BM, Stratton KG, Bramer LM
J Proteome Res · 2026 Jun · PMID 42047576 · Publisher ↗
Expression-based omics technologies (e.g., proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions...
Expression-based omics technologies (e.g., proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application OmicsMLMentor was designed to lower the barrier to ML modeling for omics data. OmicsMLMentor supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics data sets, such as proteomics, metabolomics, lipidomics, and transcriptomics. OmicsMLMentor offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user's data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, OmicsMLMentor addresses critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, OmicsMLMentor is applied to data from a lignin exposure study to highlight example workflows for fitting both supervised and unsupervised models to data.
Human Coronavirus 229E Infection Alters Histone Proteoforms.
Ives AN, Thibert S, Berger MR … +7 more , Gaffrey MJ, Mitchell HD, Williams SM, Zhou M, Waters KM, Sims AC, Zhang T
J Proteome Res · 2026 Jun · PMID 42047537 · Publisher ↗
Viruses rely on host machinery to replicate, and growing evidence demonstrates that they utilize host epigenetic regulation, including histone modification, to modulate host gene expression for their benefit. Herein, we...
Viruses rely on host machinery to replicate, and growing evidence demonstrates that they utilize host epigenetic regulation, including histone modification, to modulate host gene expression for their benefit. Herein, we employed top-down proteomics to quantify histone proteoforms in lung fibroblast (MRC-5) cells following human coronavirus 229E (HCoV-229E) infection and compared them to mock-infected controls. A total of 572 proteoforms were identified, including 461 histone proteoforms that were assigned to histone 2A (H2A), H2B, H3, or H4. 200 histone proteoforms were quantifiable. Differential abundance analysis revealed several changes in both reversible post-translational modifications (e.g., phosphorylation, acetylation) and the truncation states of core histones. Notably, we found a decreased abundance of truncated histones in HCoV-229E-infected samples, specifically C-terminally truncated histone H2A and N-terminally truncated histone H3. These findings underscore the power of top-down proteomics to resolve unique truncation states of proteoforms and support the hypothesis that viruses alter the histone length to influence host gene expression.
H NMR-Based Plasma Metabolomics and Machine Learning Reveal Distinct Metabolic Signatures of Breast Cancer in Nigerian Women.
Onyia AF, Olasehinde OE, Shagaya U … +21 more , Nwachukwu E, Oyekan A, Fatiregun O, Olatunji T, Lawal A, Alabi A, Aje EA, Sowunmi A, Ogunniyi OB, Ogo CN, Nkom ES, De Campos OC, Rotimi OA, Oyelade J, Ajibola TOP, Anake TA, Elebo N, Nweke EE, Zerbini LF, Cacciatore S, Rotimi SO
J Proteome Res · 2026 Jun · PMID 42045116 · Publisher ↗
Untargeted H NMR metabolomics offers a noninvasive means to identify biomarkers in breast cancer (BC) patients; however, metabolic signatures specific to Nigerian women remain poorly understood. This study aimed to ident...
Untargeted H NMR metabolomics offers a noninvasive means to identify biomarkers in breast cancer (BC) patients; however, metabolic signatures specific to Nigerian women remain poorly understood. This study aimed to identify plasma metabolomic and lipidomic biomarkers associated with BC in Nigerian patients, evaluate their diagnostic performance using machine learning (ML), and identify dysregulated metabolic pathways. This case-control study recruited 100 BC patients and 100 healthy controls from 4 Nigerian teaching hospitals. Plasma metabolites and lipids were profiled using H NMR spectroscopy and the Liposcale test. Multivariate and ML analyses revealed a clear distinction between BC and controls (PLS-DA accuracy: 92.4-94.4%). Twenty-four metabolites were significantly altered (FDR < 0.05), with decreased glycine and glutamine, and increased GlycA, GlycB, glucose, and ketone bodies. Lipoprotein profiling showed reduced small HDL, LDL, and large VLDL particles, alongside with increased HDL diameter. The random forest model achieved the best classification performance (AUC = 0.985) and identified 23 key biomarkers. Pathway analysis revealed 29 enriched metabolic pathways, including glyoxylate and dicarboxylate metabolism. Overall, these findings highlight distinct metabolic alterations in Nigerian BC patients and demonstrate the potential of combining NMR-based metabolomics with ML for population-specific, noninvasive BC diagnostics.
DIA-NN EasyFilter Workflow for the Fast and User-Friendly Critical Assessment and Visualization of DIA-NN Proteomics Analysis Outcome.
Moagi GM, Ferreira TF, Kristof E … +4 more , Arda AG, Arianti R, Horvatovich P, Csösz É
J Proteome Res · 2026 Jun · PMID 42044457 · Publisher ↗
Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics, particularly data-independent acquisition (DIA), has become widely adopted across One Health approaches for biological and clinical research for...
Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics, particularly data-independent acquisition (DIA), has become widely adopted across One Health approaches for biological and clinical research for quantitative protein characterization. Among the many computational tools available, DIA-NN has demonstrated superior performance; however, the primary output of the current versions is provided as a compact, compressed PARQUET file that can be difficult to interrogate without programming expertise. To address this limitation, we developed DIA-NN EasyFilter (DEF), a fast, user-friendly, KNIME-based workflow for comprehensive protein filtering and visualization. DEF integrates chromatographic peak-based filtering, curated contaminant libraries, and quantity-quality assessment along with interactive modules for qualitative and quantitative data exploration. The workflow is optimized for efficient execution within the KNIME local desktop environment and is designed to support end-users in improving accuracy and interpretability without requiring coding skills. We provide a detailed description on how to run DEF and demonstrate the utility and robustness of DEF using published large-scale proteomics data sets, showing high comparability across studies regardless of instrument platform or data set size.
What Is in Fetal Bovine Serum Used for Cell Culture? Integrated Proteomics and Peptidomics Reveal Grade-Dependent Molecular Profiles.
Wijerathna-Yapa A, Sokolenko S
J Proteome Res · 2026 Jun · PMID 42043302 · Publisher ↗
Fetal bovine serum (FBS) is a widely used but poorly defined mammalian cell culture supplement, introducing substantial batch-to-batch and grade-specific variability that compromises experimental reproducibility. We perf...
Fetal bovine serum (FBS) is a widely used but poorly defined mammalian cell culture supplement, introducing substantial batch-to-batch and grade-specific variability that compromises experimental reproducibility. We performed integrative proteomics and peptidomics profiling of three commercially available FBS grades using data-independent acquisition (DIA) mass spectrometry. A conserved core of 979 proteins shared across all grades was enriched for extracellular matrix organization, immune modulation, and growth factor regulation, explaining FBS's broad utility in standard cell culture. Differential abundance analysis revealed 88 proteins differing significantly between high-grade and low-grade products, while peptidomic profiling detected over 200 differentially abundant native peptide sequences. High-grade FBS was enriched in adhesion proteins (fibronectin, vitronectin, thrombospondin-1) and growth factor binding proteins (IGFBP2, IGFBP3), supporting robust cell attachment and proliferation, while low-grade serum exhibited elevated detoxification and oxidative stress response proteins consistent with a stress-adapted biochemical signature. Multiomics integration via DIABLO revealed coordinated proteolytic regulation distinguishing serum grades, with native peptides demonstrating greater intergrade divergence than intact proteins. These findings establish a molecular framework for rational serum selection and mass spectrometry-guided lot qualification in biotechnology and regenerative medicine, and identify functional modules structural scaffolding, carrier buffering, and bioactive peptide signaling that underpin FBS bioactivity and support the development of chemically defined culture media.
Assessing High-Affinity -Glycoforms of the Human Fcγ Receptor IIIa (CD16a) via Parallel Reaction Monitoring Mass Spectrometry.
Pavan CH, Desai J, Medina Navarro V … +1 more , Chandler KB
J Proteome Res · 2026 Jun · PMID 42026724 · Publisher ↗
The Fc γ-receptor IIIa (FcγRIIIa), or CD16a, is a receptor for the Fc region of IgG that plays an essential role in the regulation of antibody effector functions. Dysregulated CD16a activity contributes to tissue damage...
The Fc γ-receptor IIIa (FcγRIIIa), or CD16a, is a receptor for the Fc region of IgG that plays an essential role in the regulation of antibody effector functions. Dysregulated CD16a activity contributes to tissue damage and chronic inflammation or, conversely, compromises the removal of immune complexes. CD16a glycoforms with high-mannose -linked glycans at site N162 demonstrate higher affinity for IgG compared to other forms. Here, we developed a targeted nanoliquid chromatography tandem mass spectrometry parallel reaction monitoring (PRM) method for the site-specific study of CD16a -glycosylation. The method was applied to assess changes in site N162 -glycosylation in a model of monocyte differentiation and in CD16a from human primary monocytes and peripheral blood mononuclear cells. Site N162 -glycosylation was similar across the surveyed cell types. An increase in the proportion of high-mannose -glycan compositions at site N162 was observed, corresponding to high-affinity glycoforms of CD16a, in a model of monocyte differentiation. Here, the feasibility of using targeted glycopeptide PRM to study CD16a glycosylation in primary cells has been demonstrated. This strategy is well-suited for adaptation to clinical studies focused on the role of CD16a glycosylation in physiology, immunotherapy, and immune disorders. Data are available via ProteomeXchange with the identifier PXD071784.
Machine Learning Analysis of Serum Metabolomics for Multi-Disease Classification and Proteome-Metabolome Pathway Insights in T2D, IBD, and CRC.
Das R, Mourouganad P, Aich P
J Proteome Res · 2026 Jun · PMID 42024141 · Publisher ↗
Type 2 diabetes (T2D), inflammatory bowel disease (IBD), and colorectal cancer (CRC) share overlapping metabolic alterations that hinder early, disease-specific diagnosis. Using publicly available serum metabolomics data...
Type 2 diabetes (T2D), inflammatory bowel disease (IBD), and colorectal cancer (CRC) share overlapping metabolic alterations that hinder early, disease-specific diagnosis. Using publicly available serum metabolomics data sets (T2D: ST003390; IBD: ST003312; CRC: ST000284), a standardized workflow combining random forest-based imputation, log transformation, Pareto scaling, and ComBat batch correction was implemented prior to supervised machine learning. Eight algorithms (logistic regression, linear and RBF SVM, random forest, XGBoost, -nearest neighbors, multilayer perceptron, and partial least-squares-discriminant analysis) were benchmarked for binary and multiclass classification using stratified 5-fold cross-validation, F1-scores, and bootstrapped ROC-AUC estimates. Binary models yielded near-perfect discrimination for T2D (AUC ≈ 1.0) and high accuracy for IBD and CRC (AUC 0.93-0.95), while multilayer perceptron and partial least-squares-discriminant analysis achieved multiclass accuracy >0.9 and macro-AUC 0.98. Mapping discriminative metabolites to KEGG pathways revealed disease-linked signatures, including glucose and lipid metabolism in T2D, amino acid and porphyrin metabolism in IBD, and nucleotide and sphingolipid metabolism in CRC, supporting proteome-metabolome network perturbations. The current comparative machine learning framework of serum metabolome demonstrates a robust, though variable, multidisease classification performance across conditions (T2D, IBD, and CRC) used in this study. This strategy has the potential to provide interpretable pathway-level markers that may inform future proteome- and metabolome-centered diagnostic strategies.
Evaluation of Data-Independent Acquisition-Based Phosphoproteomics Analysis in Mammalian and Bacterial Systems.
Liu SH, Call DH, Kitata RB … +7 more , Attah IK, Chu RK, Gritsenko MA, Boradia V, Grundner C, Day LZ, Jacobs JM
J Proteome Res · 2026 May · PMID 42013821 · Full text
Recent advancements in data-independent acquisition (DIA) workflows have greatly increased the depth and throughput of mass spectrometry-based proteomics. However, many of these advancements remain undercharacterized for...
Recent advancements in data-independent acquisition (DIA) workflows have greatly increased the depth and throughput of mass spectrometry-based proteomics. However, many of these advancements remain undercharacterized for phosphoproteomics, particularly in bacteria that have fewer protein phosphorylation events. We evaluated the impact of instrument/gradient length (Orbitrap Astral, 15 min; Orbitrap Exploris, 90 min), analysis tools (DIA-NN 1.9.2, DIA-NN 2.3, FragPipe, Spectronaut), and library search strategies (spectral-library versus library-free) on phosphoproteomic coverage and quantification in a human cell line and bacterial lysate. The 15 min Astral analysis identified similar numbers of phosphopeptides compared to a 90 min Exploris acquisition method across all analysis tools, demonstrating a substantial advantage in throughput. Within the Astral workflow, Spectronaut provided the highest phosphoproteome coverage, whereas DIA-NN 1.9.2, DIA-NN 2.3, and FragPipe exhibited less quantitative variation. We compared library-free and spectral-library search strategies using the () H37Rv strain. We observed greater phosphopeptide identifications yet different phosphopeptide profiles via library-free searches in comparison to spectral-library searches. When comparing harvested at different growth phases, phosphosite fold-changes were consistent, whereas statistical significance varied between tools. This work can be informative for workflow selection in DIA phosphoproteomics studies, especially for biological samples with low phosphorylation frequencies.
Selection of Reversed-Phase C18 Separation Media for Bottom-Up Proteomics: Multifactor Comparison of Fully Porous Sorbents Including Separation Selectivity and Carryover Characteristics.
Yeung D, Lao Y, Spicer V … +3 more , Paulo J, Zahedi RP, Krokhin OV
J Proteome Res · 2026 May · PMID 42013376 · Publisher ↗
Seven popular C18 stationary phases for peptide separation in bottom-up proteomics have been evaluated based on overall peptide retention, column backpressure, separation selectivity and efficiency, number of peptide ide...
Seven popular C18 stationary phases for peptide separation in bottom-up proteomics have been evaluated based on overall peptide retention, column backpressure, separation selectivity and efficiency, number of peptide identifications, and carryover statistics. Under standard 0.1% formic acid water-acetonitrile elution conditions, peptide retention varies within an elution range of ∼3.4% acetonitrile and increases in the following order: XSelect CSH C18 2.5 μm, 130 Å < Luna C18(2) 3 μm, 100 Å < PepMap RSLC C18 2 μm, 100 Å ≪ Reprosil-Pur ODS-3 3 μm, 120 Å < Reprosil-Pur C18 AQ 3 μm, 120 Å < Magic C18 AQ 3 μm, 200 Å < XBridge BEH C18 2.5 μm, 130 Å. While the lower retention on the XSelect was expected due to the embedded positively charged groups, the behavior of Luna C18(2) and PepMap C18 can be explained by the reduction of surface accessibility for small pore size matrices. Pore size was a major contributor to varying separation selectivity. The number of unique peptide identifications is driven by peptide separation efficiency and retentivity. These factors favor sorbents with smaller particle sizes and higher retentivity, such as XBridge BEH C18. Low peptide retentivity and average separation efficiency diminish identification output for Luna C18(2) and PepMap RSLC with 100 Å pore size.
Site Confidence Scores among All Available Structures to Help Infer Conformational Origins of Identified Cross-Links.
Keller A, Bakhtina AA, Eng JK … +1 more , Bruce JE
J Proteome Res · 2026 May · PMID 42013371 · Publisher ↗
Cross-linked peptides are indicative of protein conformations in samples due to their reactivity with multiple proximate residues. Since their cross-linked proteins often have alternative conformations, each with availab...
Cross-linked peptides are indicative of protein conformations in samples due to their reactivity with multiple proximate residues. Since their cross-linked proteins often have alternative conformations, each with available structures, large-scale cross-link data sets require advanced capabilities to readily and accurately assess the likelihood of a cross-link originating from all available structures. Traditionally, the Euclidean or solvent-accessible surface distance (SASD) separating the residues has been used to assess the possibility that a cross-linked product arises from one of many structures. However, solvent accessibility and the potential for salt bridge formation of each reactive residue can also affect the likelihood of cross-linker attachment. Here, we describe the addition to the public cross-linking database XLinkDB of a confidence score that combines SASD, solvent accessibility, and salt bridge information to better assess the likelihood of a cross-link originating from residue pair sites among possible structures. We show how this score correctly predicts the state specificity of cross-links of ADP/ATP translocase, identifying cross-links that can serve as biomarkers of particular protein conformational configurations. These efforts also reveal that 12% of cross-links on XLinkDB have no PDB structures available that yield high confidence scores and thus may have value for additional modeling to predict alternate structures.
Parkinson's Disease-Associated Remodeling of Synaptic -Glycans in the Human Prefrontal Cortex.
Adeniyi M, Fowowe M, Oluokun O … +5 more , Sahioun S, Sandilya V, Daramola O, Bennett AI, Mechref Y
J Proteome Res · 2026 Jun · PMID 42012257 · Full text
Parkinson's disease (PD) is characterized by progressive motor and cognitive dysfunction and is associated with synaptic pathology and impaired neurotransmission, including dysfunction of synaptic vesicles (SVs) and pres...
Parkinson's disease (PD) is characterized by progressive motor and cognitive dysfunction and is associated with synaptic pathology and impaired neurotransmission, including dysfunction of synaptic vesicles (SVs) and presynaptic terminals. However, the role of protein -glycosylation within synaptic subcellular fractions remains understudied. Here, -glycomics analysis was performed on synaptosomes and SVs enriched from the prefrontal cortex (PFC) of post-mortem PD and control brains using high-resolution LC-MS/MS. A total of 66 -glycans were identified in synaptosomes and 68 in SVs, with PD-associated glycomics alterations showing clear fraction-specific patterns. PD synaptosomes exhibited reduced sialofucosylation alongside increased fucosylated and neutral glycans, including altered sialyl Lewis X (sLeX)-bearing structures, suggesting potential involvement in neuroinflammation and aberrant cell signaling. In contrast, PD SVs showed elevated high-mannose and neutral glycans. Isomer-resolved -glycomics revealed distinct remodeling of glycan isomers in PD, characterized by altered branching, fucosylation, and sialylation in both fractions. Notably, PD synaptosomes displayed shifts toward highly branched fucosylated and sialylated isomers, while PD SVs exhibited changes consistent with impaired glycan maturation. Together, these findings demonstrate that PD induces distinct -glycan alterations in PFC synaptic fractions, providing new insights into synaptic dysfunction associated with cognitive decline in PD.
Proximity Labeling Reveals How Lrp2 Interacts with the Endocytic Machine.
Shen TH, Beenken A, Erdjument-Bromage H … +12 more , Weisz OA, Ghotra A, Kushner JS, Sturley RE, Kahn A, Kronenberg L, Rahmani G, Nesanir K, High FA, Donahoe PK, Barasch J, Neubert TA
J Proteome Res · 2026 May · PMID 42008627 · Full text
LRP2 (Megalin or low-density lipoprotein-related receptor 2), together with Cubilin and Amnionless, is responsible for binding and internalizing a wide range of nutrients and toxins from the kidney's glomerular filtrate...
LRP2 (Megalin or low-density lipoprotein-related receptor 2), together with Cubilin and Amnionless, is responsible for binding and internalizing a wide range of nutrients and toxins from the kidney's glomerular filtrate by endocytosis. Accordingly, Lrp2 deletion or mutation results in the loss of these ligands into the urine. Yet Lrp2 is essential not only for receptor-mediated but also for fluid-phase endocytosis, implicating a broader role beyond ligand binding. To identify the linkage between Lrp2 and endocytosis, we engineered Lrp2-APEX2-expressing mice and performed biotinylation in vivo to label Lrp2's cytoplasmic partners. We demonstrated the specificity and sensitivity of this technique by mass spectrometric identification of biotinylated proteins from kidney lysate and immunostaining kidney sections. We identified critical endocytic regulators interacting with Lrp2, but also many proteins functionally associated with endocytosis that are not already known to interact with Lrp2. These data suggest that Lrp2 plays a central role in organizing apical membranes through PDZ domain proteins and engages with regulators and molecular motors during endocytosis. These interactions are abolished in the absence of Lrp2.
A Targeted LC-MS/MS Assay of a Health Surveillance Panel and Its Application to Chronic Kidney Disease.
Fu Q, Johnson CWC, Inker LA … +2 more , Van Eyk JE, CRIC Study Investigators
J Proteome Res · 2026 May · PMID 42007652 · Publisher ↗
Robust and reproducible assays capable of specific and quantitative monitoring of multiple biologically important proteins, among the thousands of human plasma proteins, can be used to represent the overall health of an...
Robust and reproducible assays capable of specific and quantitative monitoring of multiple biologically important proteins, among the thousands of human plasma proteins, can be used to represent the overall health of an individual and distinguish health versus disease. In this study, we established an LC-MS assay to monitor a Health Surveillance Panel (HSP), comprising 60 circulating plasma proteins selected based on their biological functions and/or disease associations. Plasma samples were prepared for proteomic analysis in an automated process and analyzed using an optimized, scheduled LC-MRM assay composed of 60 endogenous proteins monitored by 364 transitions from 117 proteotypic peptides, along with their stable isotopically labeled standard peptides. For each proteotypic peptide, a quantifier ion and at least two qualifier ions were selected based on consistent peak area ratios, a linear response for the quantifier ion, and a low limit of quantification. As proof of concept, we evaluated the performance of our HSP assay in a case-control study of progressive chronic kidney disease (CKD). Reduced plasma concentrations of alpha-2-antiplasmin, antithrombin-III, and immunoglobulin heavy constant alpha 1 correlated with CKD, with -values <0.05. These results demonstrate that CKD-associated differences can be detected with a multiplexed HSP assay panel.
Top-Down Proteomics of Zebrafish Brain Regions Using Capillary Zone Electrophoresis-Tandem Mass Spectrometry.
Falamarzi Askarani M, Poulos W, Rahimzadeh Dashtaki M … +3 more , Fang F, Cibelli JB, Sun L
J Proteome Res · 2026 May · PMID 41995712 · Full text
Understanding region-specific proteoform profiles in the brain is crucial for deciphering neural function and identifying therapeutic targets. Zebrafish (Danio rerio) is a valuable vertebrate model for neuroscience resea...
Understanding region-specific proteoform profiles in the brain is crucial for deciphering neural function and identifying therapeutic targets. Zebrafish (Danio rerio) is a valuable vertebrate model for neuroscience research due to its substantial conservation of brain structure and function with that of mammals. We present a label-free quantitative top-down proteomics (TDP) analysis of distinct zebrafish brain regions using microdissection and capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS). We analyzed four anatomically distinct regions─telencephalon (Tele), combined habenula-optic tectum (Tec/Hab), cerebellum (Cer), and medulla (Med)─identifying 1,050 proteoforms from 336 proteins. Only 89 proteoforms (5.1%) were shared across all regions, demonstrating substantial proteoform heterogeneity. Quantitative comparisons of proteoform intensity between any two brain regions revealed drastic proteoform abundance differences. Interestingly, proteoforms of the same genes (i.e., , and ) showed opposite expression patterns between brain regions, indicating potential proteoform-specific functions. Nearly 153 neuropeptides were identified using a recently published neuropeptide prediction algorithm with a prediction probability of over 75%, and some neuropeptide proteoforms showed brain-region-specific expression (i.e., , and ). Gene Ontology analysis of the differentially expressed proteoforms between regions revealed region-specific biological process enrichment, i.e., innate immune response and chromatin organization in Cer, actin organization in Med, microtubule-based processes in Tele, and axonogenesis in Tec/Hab. Comparing quantitative TDP and bottom-up proteomics data from the four zebrafish brain regions revealed substantial discrepancies between proteoform-specific and protein-group-specific data sets, highlighting the value of spatially resolved TDP of brains for better understanding of protein function in a proteoform-specific manner.
NetMHCIIphosPan: A Machine Learning Tool for Predicting HLA Class II Antigen Presentation of Phosphorylated Peptides.
Garcia Alvarez HM, Kaabinejadian S, Yari H … +7 more , Shepherd CM, Hildebrand WH, Sette A, Peters B, Parker R, Ternette N, Nielsen M
J Proteome Res · 2026 May · PMID 41994856 · Full text
Phosphorylated peptides presented by human leukocyte antigen (HLA) class II molecules play pivotal roles in immune regulation, yet their characterization and prediction remain challenging due to data noise and limited HL...
Phosphorylated peptides presented by human leukocyte antigen (HLA) class II molecules play pivotal roles in immune regulation, yet their characterization and prediction remain challenging due to data noise and limited HLA coverage. Here, we introduce NetMHCIIphosPan, a prediction method for HLA-II antigen presentation of phosphorylated peptides, developed using mass spectrometry (MS)-based immunopeptidomics data sets. Employing a refined peptide identification workflow, we reanalyzed earlier HLA-II phospholigand data sets and trained predictive models, achieving superior performance compared to models trained on the original data. Binding motif analysis revealed that HLA-specific preferences for phospholigands closely aligned with those of unmodified ligands. Incorporating unmodified ligands into training further enhanced predictive accuracy, particularly for HLA-DP and HLA-DQ molecules. NetMHCIIphosPan outperformed existing tools, such as NetMHCIIpan-4.3 and MixMHC2pred-1.3, for prediction of HLA antigen presentation of phosphorylated peptides, demonstrating robustness and utility. This work establishes NetMHCIIphosPan as a state-of-the-art tool for understanding the HLA-II phospholigandome, with potential applications in immunotherapy and vaccine design.
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