SEARCH · PubMed Health

Results for “Proteomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4Linked to original sources

PubMed2026

2-Mercaptoethanol/DMSO Workflow Enables Highly Reproducible Quantitative Proteomics.

Proteomics provides a systematic and high-throughput approach to comprehensively characterize protein networks, enabling insights into cellular functions and disease mechanisms. Carbamidomethylation using iodoacetamide (IAA), a common method for cysteine alkylation, is known to cause nonspecific modifications that increase spectral complexity in mass spectrometry and reduce quantitative accuracy. Here, we established a reproducibility-focused 2-mercaptoethanol (2-ME)/dimethyl sulfoxide (DMSO) workflow and systematically evaluated its quantitative performance at the proteome-wide level. Mouse liver proteomes were processed using either 2-ME/DMSO or conventional IAA treatment, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The optimized 2-ME treatment increased the number of cysteine-modified peptides by 1.6- to 1.9-fold. Although total protein identifications were comparable, 77% of proteins exhibited improved sequence coverage with the optimized 2-ME treatment. Quantitative reproducibility was also enhanced, with the peptide quantified CV ≤ 20% increasing from 61.4% with IAA treatment to 86.1% with 2-ME treatment, and protein quantified CV ≤ 20% increasing from 80.6% with IAA treatment to 93.5% with 2-ME treatment. Application of this new workflow to ovarian clear cell carcinoma reliably detected cisplatin-induced alterations. The 2-ME/DMSO workflow offers a simple and highly reproducible proteomics strategy for accurate quantitative proteomics.

Animals↗

PubMed2026

Proteins as Regulators of Metabolic Changes in Sepsis: Alterations in Body Fluids, Immune Cells, and Organs through the Eyes of Proteomics.

Sepsis is a life-threatening syndrome characterized by a dysregulated host response to infection and profound metabolic alterations that contribute to immune dysfunction and organ failure. This Review synthesizes proteomic evidence on sepsis-associated alterations in proteins involved in metabolic pathways across circulating biofluids, immune cells, and organs. Across plasma and urine, proteomic studies identify disturbances in lipoprotein-associated pathways, redox homeostasis, mitochondrial function, and substrate metabolism, indicating that protein signatures of metabolic dysregulation are systemic and detectable across biofluids. In immune cells, monocytes and neutrophils, proteomic analyses reveal a shift toward glycolysis with concurrent impairment of mitochondrial pathways alongside phenotype-dependent differences in lipid and redox-related programs. Organ-level studies further show that metabolic responses are heterogeneous, with distinct trajectories in the kidney, heart, liver, lung, skeletal muscle, and brain. These observations support the concept that sepsis involves compartment-specific remodeling of metabolism-associated protein networks rather than a single convergent metabolic state. Proteomics also highlights potential translational opportunities by identifying metabolism-associated proteins linked to disease severity, clinical phenotypes, and biologically distinct patient subgroups, although the current evidence remains largely exploratory and context-dependent. Overall, proteomics provides a complementary framework for understanding the molecular regulation of sepsis-associated metabolic dysfunction and may refine biological stratification and therapeutic targeting, particularly when integrated with longitudinal sampling and multiomic data.

Humans↗

PubMed2026

Photocatalytic Golgi Proteomics Reveals Palmitoylation-Regulated Golgiphagy.

The Golgi apparatus (GA) orchestrates protein modification, trafficking, and secretion through highly dynamic remodeling, yet its proteomic complexity remains difficult to resolve in living systems. Here, we report CAT-Golgi, a genetically independent and light-controlled photocatalytic proximity labeling strategy for in situ spatiotemporal mapping of the Golgi-associated proteome. Combining a cysteine-conjugated eosin photocatalyst (GolgiCat) with an aniline probe, CAT-Golgi enables rapid and precise protein labeling within minutes under mild green light, requiring no genetic manipulation and operating efficiently in hard-to-transfect and primary cells. Leveraging our extensive efforts in organelle-targeted photocatalytic systems, we extended this chemistry to the highly dynamic and reversible Golgi apparatus. CAT-Golgi achieved quantitative and comparative proteomics in HeLa, K562, Jurkat and primary HEKa cells, revealing both conserved and cell-type-specific profiles. Under Brefeldin A-induced Golgiphagy, CAT-Golgi captured large-scale proteome remodeling and identified palmitoyl-protein thioesterase 1 (PPT1) as a potential regulatory component. PPT1 downregulation enhanced ULK1 and TRPML1 palmitoylation, disrupted redox balance, and activated Golgiphagy. CAT-Golgi provides a broadly applicable chemical platform for decoding organelle dynamics, offering both conceptual and technical foundations for extending photocatalytic proteomics to other transient organelles and illuminating molecular mechanisms of organelle plasticity and disease progression.

Golgi Apparatus↗

PubMed2026

7-day longitudinal proteomics of critically ill patients: a pilot study.

An adult's health, indicated by measurable parameters, is stable over time. With the exception of circadian rhythms, variability in these parameters typically does not exceed 20%. In this pilot study, we looked into the stability of proteome in intensive care unit (ICU) patients. This was a single-center, prospective, observational pilot study of blood plasma from adult ICU patients with statistically heterogeneous patterns of clinically observed parameters. Eight week-long batches from seven patients (one patient participated twice) were analyzed by means of bottom-up proteomics. The data were analyzed with MaxQuant software against reference proteome. The obtained intensities were further processed with in-house R and Python scripts. In total, 218 proteins were identified; however, only 68 proteins appeared in all samples from all patients. Most proteins remained stable within observation (within-patient variance was less than 30%). The random-effects model also confirmed high impact of within-patient variance on the protein levels. The effects of time on the protein level variances did not exceed 5%. Z-score-based hierarchical clustering analysis revealed that the daily data of each patient were clustered together indicating that the plasma proteome of ICU patients both bears individual traits and remains stable during short-term progression of the patients' condition. Therefore, in this pilot group of patients, the analysis over seven consecutive days fails to reveal proteome dynamics.

Humans↗

PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗

PubMed2025

Sex differences in cerebrospinal fluid proteomics of patients with restless legs syndrome.

STUDY OBJECTIVES: The pathobiology of restless legs syndrome (RLS) remains poorly understood, complicating effective treatment. This observational cross-sectional study aimed to identify a cerebrospinal fluid proteomic signature of RLS and to explore sex-specific differences in cerebrospinal fluid proteomics. METHODS: Cerebrospinal fluid samples were collected from 22 untreated RLS patients and 18 controls, matched for age, body mass index, and sex. Proteomic analysis was conducted using the SOMAscan platform, assessing over 7000 peptides. RESULTS: Eight proteins were differentially abundant between patients and controls, with CRP and JAML increased, and TAPBPL and IL1RL1 decreased. Pathway analysis highlighted significant involvement in immune response, coagulation, and cytoskeletal regulation. Analyses were then carried out using sex stratification, comparing men and women separately. Sex-specific analyses revealed more pronounced proteomic alterations in males (68 differentially abundant proteins vs. control males) than in females (17 proteins). Gene enrichment analysis revealed that men with RLS had more involvement in gene regulation and epigenetic factors than control males and women with restless legs syndrome had greater involvement in systemic inflammatory and vascular processes than control females. CONCLUSIONS: This study identified a cerebrospinal fluid proteomic signature in RLS, implicating immune and inflammatory pathways in the disease's pathophysiology. Significant sex differences in protein level suggest potential sex-specific mechanisms in RLS, warranting further investigation. These findings contribute to the current understanding of RLS and could inform future therapeutic strategies.

Humans↗

PubMed2026

Comparison of Proteomic Analysis of Cerebrospinal Fluid From Neurological Patients With and Without Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterised by progressive muscle weakness in both bulbar and extremity muscles, leading to a diverse clinical phenotype with motor and non-motor symptoms. Approximately 85% of ALS cases are sporadic (sALS), while the remaining 10%-15% are familial (fALS). Biological biomarkers of sporadic ALS remain poorly understood, hindering precise patient screening, delaying diagnosis and negatively affecting prognosis. This study aims to identify potential proteomic biomarkers by comparing the cerebrospinal fluid (CSF) of sALS patients with that of patients suffering from other neurological diseases. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used for proteomic profiling of CSF samples from 24 sALS patients and 26 patients with other neurological diseases. The complete protein expression profiles were compared using a two-tailed Student's t-test, with a p < 0.05 considered statistically significant with additional FDR correction at the 0.1 level. Proteomic analysis of CSF samples identified significant quantitative changes in 96 proteins with threshold p < 0.05 and 74 proteins with FDR < 0.1 between sALS and non-ALS patients, including alterations in proteins associated with neurodegenerative processes, such as amyloid precursor proteins and inflammatory markers. CSF proteomic analysis reveals altered inflammatory and neurodegenerative metabolic pathways, providing valuable insights into the proteomic landscape of sALS. Several dysregulated proteins were consistent with the disease mechanisms highlighted in previous studies. These findings represent a step forward in developing personalised approaches for diagnosing and managing the disease.

Humans↗

PubMed2025

Proteomic Characterization of the Rhesus Macaque Lens Nucleus: Similarity to Human Lens, Age Effects on Protein Solubility, and Trends in Post-Translational Modifications.

PURPOSE: Proteomes of lens nuclei from young (4 years old) and old (15-16 years old) rhesus macaques (Macaca mulatta) were analyzed to determine similarity of the proteomic profile to that of human lenses, age-related differences in protein solubility, and association of various post-translational modifications with age and protein solubility. METHODS: Lens core proteins were separated into water-soluble and water-insoluble fractions using aqueous buffer and centrifugation. The water-insoluble fraction was solubilized using sodium dodecyl sulfate (SDS). Proteins were processed using S-trap columns, and peptide digests were analyzed using high-resolution, label-free data-dependent acquisition (DDA) proteomics. Open modification searches were performed using MSFragger to identify possible post-translational modifications (PTMs). The number of modified peptide tandem mass spectra confidently assigned to samples by age or solubility were compared to find PTMs with statistically significant count differences. RESULTS: The overall proteomic profile of rhesus macaque lenses was very similar to human lenses, consisting of 80.2% crystallins, 1.1% beaded filament proteins, and 18.7% other proteins. The crystallin fraction consisted of 27% alpha crystallins, 67.6% beta/gamma crystallins, and 5.4% taxon-specific psi crystallin. Glycolytic enzymes, beta/gamma crystallins, and a few glutathione-related enzymes were found to have age-related shifts to the water-insoluble fraction. There were significant differences in deamidation, dioxidation, carbamylation, carboxymethylation, and trioxidation based on age and/or solubility of proteins. CONCLUSIONS: These data indicate a high level of conformity between rhesus macaque and human lens proteomes, and a few key differences. We identified several age-related differences in protein solubility and PTM that may contribute to lens pathology.

Animals↗

PubMed2026

Integrated analysis of gut microbiota, serum metabolomics, and proteomics reveals novel associations with clinical symptoms in patients with cerebral infarction.

BACKGROUND: Cerebral infarction (CI) is a major cause of adult disability and mortality worldwide. Mounting evidence supports the critical role of the gut-brain axis in cerebrovascular disease progression. This study aimed to characterize the alterations in gut microbiota, serum metabolome, and serum proteome in patients with CI, and to identify multi-omics signatures associated with clinical symptoms. METHODS: A total of 20 CI patients and 20 healthy controls (HC) were enrolled. Fecal microbiota was profiled using 16 S rRNA gene high-throughput sequencing. Serum metabolomics and proteomics were analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and data-independent acquisition (DIA) proteomics, respectively. Spearman correlation and multi-omics integration were applied to explore the associations among microbiota, metabolites, proteins, and clinical indicators. RESULTS: CI patients displayed significant gut microbiota dysbiosis, with a markedly lower gut microbiota health index (GMHI) and higher microbiota disorder index (MDI) compared with HC (P < 0.001). The genera g_norank_o_RF39 and Oxalobacter were significantly enriched in CI patients, whereas Clostridium_sensu_stricto_1 and Agathobacter were enriched in HC. Metabolomic analysis identified 445 differential metabolites, mainly involved in glycerophospholipid metabolism, phenylalanine metabolism, and caffeine metabolism. Proteomic analysis revealed 140 differentially expressed proteins linked to inflammatory responses, calcium signaling, and NF-κB signaling. Multi-omics integration showed that signature gut microbiota was strongly correlated (P < 0.005) with key serum metabolites and proteins implicated in CI pathogenesis. CONCLUSIONS: This integrated multi-omics study revealed distinct gut microbiota, serum metabolomic, and proteomic alterations in CI patients. The microbiota-metabolite-protein regulatory axes provide novel insights into the gut-brain axis in CI and may serve as potential diagnostic biomarkers or therapeutic targets.

Humans↗

PubMed2026

Preliminary Exploration on Melatonin-Mediated Protective Effects in Intracranial Aneurysms: Transcriptomic, Proteomic, and Metabolomic Profiling of Cerebral Vascular Tissues Combined with in vivo Animal Experiments.

BACKGROUND: Intracranial aneurysm (IA) is a life-threatening cerebrovascular disease with unclear molecular mechanisms and limited drug treatment. Our previous research has shown that melatonin (MLT) has potential protective effects in IA, but its mechanism remains unclear. The purpose of this study is to explore the pathological mechanism of IA and the therapeutic mechanism of MLT by integrating transcriptomic, proteomic and metabolomic analyses. METHODS: In this study, mouse models of IA were successfully established by combining elastase injection with angiotensin II infusion. C57BL/6 mice were divided into control, IA model, IA model+MLT, and IA model+nimodipine groups. The pathological conditions were evaluated by hematoxylin-eosin (HE) staining, TUNEL staining, and scanning electron microscopy. Transcriptomic (n=3 for each group), proteomic (n=3 for each group), and metabolomic (n=6 for each group) analyses were performed based on cerebral vascular tissue samples. The screening thresholds for differentially expressed genes and differentially expressed proteins were P <0.05 and fold change >1.5 and fold change <0.667. The screening criteria for differential metabolites were variable importance for the projection (VIP)> 1.0, fold change >1.2 and fold change <0.833, and P <0.05. RESULTS: MLT alleviated brain tissue damage, vascular endothelial damage, structural disruption, and apoptosis in IA mice. Transcriptomic, proteomic and metabolomic analyses identified numerous differential molecules. Functional annotation revealed that these molecules may be involved in biological pathways and processes such as immune inflammation, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress and metabolic pathways, thereby regulating the occurrence and development of IA or mediating the therapeutic effects of MLT. Furthermore, transcriptomic and proteomic analyses also suggest that there may be extensive post-transcriptional, translational and post-translational regulatory events in the progression of IA and the therapeutic effects of MLT. Integrated transcriptomic and proteomic analyses suggest that Npy may be a key molecule in regulating IA progression and mediating MLT therapeutic effects, and its potential value is further supported by our immunohistochemical validation results. CONCLUSION: Multi-omics integrative analysis preliminarily revealed that the potential mechanisms of MLT may involve the regulation of inflammatory response, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress, metabolic pathways, and post-transcriptional/translational regulation.

Animals↗

PubMed2026

Pilot study identifying distinct circulating proteomic profiles associated with longitudinal CT-defined fibrotic and inflammatory sarcoidosis.

INTRODUCTION: Pulmonary sarcoidosis exhibits heterogeneous clinical trajectories ranging from self-limited disease resolution to chronic progressive fibrosis, yet reliable biomarkers capable of distinguishing these disease patterns remain lacking. Whether longitudinal CT-defined sarcoidosis phenotypes are associated with distinct circulating molecular signatures remains unknown. METHODS: We performed high-throughput plasma proteomics (SomaScan 11K) in participants with pulmonary sarcoidosis classified into longitudinal chest CT-defined progressive fibrosis, progressive nodular inflammatory disease, or resolving disease trajectories, along with healthy controls. CT phenotypes were assigned based on predefined longitudinal changes in reticulation, traction bronchiectasis, nodular involvement, and mediastinal lymphadenopathy across serial CT scans. One plasma sample per participant was selected from the study visit corresponding to the CT time point at which criteria for the assigned longitudinal phenotype were met. Principal component analysis, hierarchical clustering, pathway enrichment, and correlation-based analyses linking protein expression to quantitative CT features were used to evaluate whether distinct longitudinal CT phenotypes were associated with divergent proteomic signatures. RESULTS: Principal component analysis and hierarchical clustering suggested partial segregation by CT-defined phenotype. Longitudinal CT phenotypes were associated with distinct pathway-level proteomic signatures, with progressive fibrosis enriched for epithelial-mesenchymal transition signaling, and progressive nodular inflammatory disease enriched for mTORC1, MYC, oxidative phosphorylation, adipogenesis, and fatty acid metabolism pathways. Correlation analyses showed coordinated protein-expression patterns associated with fibrotic CT features and mediastinal lymph node enlargement. DISCUSSION: These findings suggest that longitudinal CT-defined fibrotic and inflammatory sarcoidosis phenotypes are associated with distinct pathway-level proteomic signatures. This pilot study provides preliminary proof-of-concept evidence that integrating longitudinal CT imaging phenotypes with plasma proteomics may serve as a framework for future mechanistic studies and biomarker discovery in pulmonary sarcoidosis.

Humans↗

PubMed2026

Next-generation brain proteomics: Integrating single-cell, spatial, and multi-omics for clinical biomarker discovery.

The mammalian brain's functional complexity arises from the sophisticated architecture of neurons and glia. This network is essentially defined by its dynamic proteome, which reveals the functional execution underlying neural computation and disease. This review integrates the technological leap in neuroproteomics. It has moved beyond bulk tissue proteome cataloguing to high-sensitivity single-cell and spatial resolution. We detail how next-generation platforms, such as TIMS-PASEF and Orbitrap-Astral, have enabled deeper and faster phenotypic profiling of limited brain samples. However, the proteome coverage remains constrained by dynamic range, sample loss, ionisation bias and incomplete detection of low-abundance regulatory proteins. We further examine how such studies have revealed the proteomic remodelling that drives lineage specification and synaptic plasticity by linking temporal protein expression waves to biological function. Crucially, we delineate the clinical translational trajectory, illustrating how aberrant signatures are verified in cerebrospinal fluid (CSF) and validated in plasma to support precision medicine. Finally, we argue for the necessity of "fused" multi-omics integration and Artificial Intelligence (AI) to decode the non-linear molecular logic of brain pathology.

Humans↗

PubMed2024

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗

PubMed2026

Systemic Proteomic Alterations and Predictive Biomarkers of Paroxetine Response in Refractory Rosacea: A Secondary Analysis of a Randomized Clinical Trial.

IMPORTANCE: Rosacea is a chronic inflammatory cutaneous disorder characterized by persistent erythema and vascular dysregulation. While paroxetine has shown clinical efficacy in reducing these symptoms, the systemic molecular mechanisms underlying its therapeutic response remain poorly characterized. OBJECTIVE: To investigate systemic proteomic alterations and identify potential predictive biomarkers in patients with refractory erythematous rosacea following paroxetine treatment. DESIGN, SETTING, AND PARTICIPANTS: This prospective plasma proteomic analysis was nested within a multicenter, randomized, double-blind, placebo-controlled clinical trial (Prospective Rosacea Refractory Erythema Randomized Clinical Trial [PRRERCT]). Participants included patients aged 18 to 65 years with refractory rosacea (Clinician's Erythema Assessment [CEA] score ≥3). Plasma samples were collected at baseline and after 12 weeks of treatment. The data for this study were analyzed between September 2025 and November 2025. INTERVENTIONS: Participants received oral paroxetine, 25 mg per day, for a 12-week treatment period. MAIN OUTCOMES AND MEASURES: Systemic protein expression profiles were analyzed using data-independent acquisition liquid chromatography-tandem mass spectrometry. Clinical response was evaluated using CEA and the Flushing Assessment Tool. Correlations between proteomic changes and clinical improvements were assessed, and predictive biomarkers were identified using receiver operating characteristic curve analysis. RESULTS: Among 24 participants (mean [SD] age, 35 [11] years; 24 [100%] female), paroxetine treatment significantly reduced mean (SD) CEA scores from 3.1 (0.3) to 2.3 (0.7) and Flushing Assessment Tool scores from 3.1 (0.6) to 2.0 (0.9) (P < .001). Exploratory proteomic analysis revealed 497 candidate differentially expressed proteins after treatment. Downregulated proteins showed preliminary enrichment in pathways related to immune response activation, insulin receptor signaling, and neuronal remodeling. A subset of 98 reversed-response proteins was observed, primarily linked to synaptic vesicle cycles and vascular smooth muscle contraction. Proteomic alterations were associated with clinical improvement (65 proteins for erythema; 73 for flushing). Candidate biomarkers, notably OLFML3 (area under the receiver operating characteristic curve [AUC], 0.87 [95% CI, 0.70-1.00]) and IGFBP2 (AUC, 0.80 [95% CI 0.55-1.00]), demonstrated high predictive value for clinical response. CONCLUSIONS AND RELEVANCE: In this secondary analysis of a randomized clinical trial, paroxetine treatment was associated with modulation of systemic neuro-vascular-immune networks in patients with rosacea. These exploratory findings provide preliminary mechanistic clues regarding the possible disease-modifying potential of paroxetine and point to circulating protein signatures that may facilitate personalized therapeutic strategies for rosacea management. TRIAL REGISTRATION: Chinese Clinical Trial Registry Identifier: ChiCTR2000031479.

Humans↗

PubMed2025

Proteomic Profiling of the Large-Vessel Vasculitis Spectrum Identifying Shared Signatures of Innate Immune Activation and Stromal Remodeling.

OBJECTIVE: Takayasu arteritis (TAK) and giant cell arteritis (GCA), the most common forms of large-vessel vasculitis (LVV), can result in serious morbidity. Understanding the molecular basis of LVV should aid in developing better biomarkers and treatments. METHODS: Plasma proteomic profiling of 184 proteins was performed in two cohorts. Cohort 1 included patients with established TAK (n = 96) and large-vessel GCA (LV-GCA) (n = 35) in addition to healthy control participants (HCs) (n = 35). Cohort 2 comprised patients presenting acutely with possible cranial GCA (C-GCA) in whom the diagnosis was subsequently confirmed (C-GCA, n = 150) or excluded (Not C-GCA, n = 89). Proteomic findings were compared to published transcriptomic data from LVV-affected arteries. RESULTS: In cohort 1, comparison to HCs revealed 52 differentially abundant proteins (DAPs) in TAK and 72 DAPs in LV-GCA. Within-case analyses identified 16 and 18 disease activity-associated proteins in TAK and LV-GCA, respectively. In cohort 2, comparing C-GCA versus not C-GCA revealed 31 DAPs. Analysis within C-GCA cases suggested the presence of distinct endotypes, with more pronounced proteomic changes in the biopsy-proven subgroup. Cross-comparison of TAK, LV-GCA, and biopsy-proven C-GCA revealed highly similar plasma proteomic profiles, with 26 shared DAPs including interleukin 6 (IL-6), monocyte/macrophage-related proteins (CCL7, CSF1), tissue remodeling proteins (TIMP1, TNC), and novel associations (TNFSF14, IL-7R). Plasma proteomic findings reflected LVV arterial phenotype; for 42% of DAPs, the corresponding gene was differentially expressed in tissue. CONCLUSION: These findings suggest shared pathobiology across the LVV spectrum involving innate immunity, lymphocyte homeostasis, and tissue remodeling. Network-based analyses highlighted immune-stromal cross-talk and identified novel therapeutic targets (eg, TNFSF14).

Humans↗

PubMed2025

Proximity Proteomics to Profile Ebola Virus Protein Interactome in Its Functional Context.

Proximity labeling-based proteomics (proximity proteomics) has emerged as a popular and versatile approach to illuminate the molecular interactions between viruses and their hosts. In this approach, a proximity labeling enzyme tag is fused to a bait protein and labels neighboring proteins with a chemical handle such as biotin, allowing for downstream affinity purification. Compared to another widely used technique, affinity purification coupled mass spectrometry, proximity proteomics enables the detection of low affinity or transient interactors that might have important functions in the viral life cycle. Further, proximity proteomics can identify interactors of a labile bait protein, of which affinity purification is technically challenging. Here, we describe a proximity proteomic protocol to identify cellular interactors of the Ebola virus polymerase. A similar strategy is readily applicable to elucidate the virus-host interactions for Marburg virus.

Ebolavirus↗

PubMed2026

Proteomic profile of the dentine pellicle modified with plant polyphenols and fluoride.

OBJECTIVES: Despite its protective role, the dentine pellicle has rarely been studied, therefore we aimed to map out the proteomic profile of in vitro dentine pellicles before and after modification. MATERIALS AND METHODS: A total of 135 human dentine specimens were prepared. After initial pellicle formation with 150 µl pooled human saliva (37 °C, 30 min), the dentine specimens were immersed in one of 9 pellicle modification solutions (2 ml/specimen): deionized water (non-modified pellicle), SnCl2/NaF/AmF (commercial solution containing 800 ppm Sn2+ and 500 ppm F-), NaF solution (500 ppm F- ), and six polyphenol solutions (2 mg / ml) with or without 500 ppm F-: blueberry extract (BBE and BBE + F-), green tea extract (GTE and GTE + F-) and grape seed extract (GSE and GSE + F-). After another aliquot of saliva (150 µl, 37 °C, 60 min), the pellicles were harvested with sodium dodecyl sulphate by rubbing with cotton balls, and taken to proteomic analyses by Liquid Chromatography-Tandem Mass Spectrometry after tryptic digestion. RESULTS: A total of 382 proteins were identified in all the proteomic analyses for all groups. Pellicle modification with fluoride, either NaF or SnCl2/NaF/AmF, led to the presence of 12 or 14 exclusive proteins, respectively, whereas modification with the solutions containing polyphenols presented less exclusive proteins (4-6 proteins). The number of exclusive proteins was even lower for when polyphenols and fluoride (GTE + F- and GSE + F-) were used, with lower abundance of proteases. CONCLUSIONS: We conclude that NaF and SnCl2/NaF/AmF significantly modify the proteome of the dentine pellicle. The combination of fluoride with polyphenols further lowers the abundance of proteins and proteases, which explains the positive effect of these solutions on the dentine pellicles. CLINICAL RELEVANCE: Plant extract solutions with fluoride can significantly modify the proteomic structure of the dentine pellicle, which clarifies the mechanism of action of polyphenols on the protection of dentine demineralization.

Humans↗

PubMed2024

Chemical proteomics to study metabolism, a reductionist approach applied at the systems level.

Cellular metabolism encompasses a complex array of interconnected biochemical pathways that are required for cellular homeostasis. When dysregulated, metabolism underlies multiple human pathologies. At the heart of metabolic networks are enzymes that have been historically studied through a reductionist lens, and more recently, using high throughput approaches including genomics and proteomics. Merging these two divergent viewpoints are chemical proteomic technologies, including activity-based protein profiling, which combines chemical probes specific to distinct enzyme families or amino acid residues with proteomic analysis. This enables the study of metabolism at the network level with the precision of powerful biochemical approaches. Herein, we provide a primer on how chemical proteomic technologies custom-built for studying metabolism have unearthed fundamental principles in metabolic control. In parallel, these technologies have leap-frogged drug discovery through identification of novel targets and drug specificity. Collectively, chemical proteomics technologies appear to do the impossible: uniting systematic analysis with a reductionist approach.

Humans↗