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PubMed2026

Spatial proteomic mapping of the human and mouse retina using IBEX.

We generated a comparative spatial proteomic atlas of the human and mouse retina using a highly multiplexed immunohistochemistry technique called iterative bleaching extends multiplexity (IBEX). We refined the IBEX workflow by integrating an antibody dissociation option alongside chemical bleaching. This dual strategy enabled removal of the entire antibody complex, permitting the flexible use of antibodies from the same host species across iterative cycles. We coupled this workflow with super-resolution imaging via deconvolution and applied it to the retina of healthy humans and WT mice and the Crb1rd8 mouse model. We successfully imaged over 25 protein markers on human and mouse tissue sections, generating spatial atlases of the major retinal cell populations. Cross-species protein expression was compared to scRNA-seq datasets to identify protein and transcript disparities. Super-resolution IBEX delineated the ultrastructural features of the outer limiting membrane (OLM), identifying CD44 as a core structural component tightly colocalized with a highly organized F-actin belt within Müller glial endfeet. Using the Crb1rd8 mouse model, disruption of this complex was spatially associated with rosette formation and OLM structural failure. In summary, spatial proteomic atlases of the human and mouse retina were used to reveal insights into the arrangement of major retinal cell populations and OLM structure.

Animals↗
PubMed2026

Nuclear Proteome Map of Mouse Heart Chambers.

Heart specialization involves nuclear programs; however, chamber-specific regulation of the nuclear proteome landscape remains unknown. In this study, we isolated the nucleus from four major anatomical regions of healthy mouse heart (fresh) and employed quantitative mass spectrometry-based proteomics to construct a comprehensive nuclear proteome landscape of left ventricle (LV, 2403 proteins), right ventricle (RV, 2242 proteins), left atrium (LA, 2368 proteins), and right atrium (RA, 1816 proteins). This led to the discovery of nuclear regional proteome signatures (ventricular signature, 297 proteins; atrial signature, 183 proteins) associated with oxidative metabolism and redox regulation, ferroptosis, extracellular-matrix remodeling, SUMO- and stress-responsive control and transcriptional regulation. Chamber-level analyses further identify distinct nuclear features in LV (120 proteins), LA (188 proteins), and RA (72 proteins). In addition, we defined conserved core nuclear proteome (230 proteins) shared across all anatomical regions, enriched for transcription-regulator complexes, nucleolar/ribosome-associated, RNA-processing, and chromatin-organization components. Within this core network, we report 78 transcription factors/co-factors and select nuclear, chromatin and RNA export-associated proteins, including 29 specific factors (e.g., Alpk3, Rbm14, Arglu1, Hmgb1, Myef2, Sf1) associated with the heart. Regionally, we verified spatial localization in heart of H2ac21 and Sun2 in LA and Ptbp2 in LV by immunofluorescence. This study provides insights into the chamber-resolved view of the nuclear proteome in the heart, establishes a framework for linking nuclear proteomic signatures to atrial and ventricular biology, unique features of the heart nuclear proteome landscape relative to other organs, and a baseline for studying nuclear remodeling in cardiac pathophysiology.

Animals↗
PubMed2025

A proteomic map of thromboinflammatory signatures in antiphospholipid syndrome: results from antiphospholipid syndrome alliance for clinical trials and international networking (APS ACTION) registry.

INTRODUCTION: Antiphospholipid syndrome (APS) is an autoimmune disease with thromboembolic and obstetric morbidity arising via a model of immunothrombosis. Individuals with APS may present with thrombotic (TAPS), obstetric (OAPS), or microvascular (MAPS) disease, while many have circulating antiphospholipid antibodies (aPL) without APS classification (NoAPS). Multiple pathophysiologic mechanisms have been proposed in APS, including activation by aPL of platelets, endothelial and immune cells, as well as complement and coagulation pathways; however, the pathophysiology of APS, particularly transition of clinical APS from aPL remains unclear. METHODS: Seeking to define the inflammatory signature of APS, we carried out an unbiased proteomic screen of persistently aPL-positive patients with different clinical phenotypes from the international APS Alliance for Clinical Trials and International Networking (ACTION) Registry and compared them to 10 healthy controls. 6398 unique proteins were estimated using an DNA aptamer-based assay. Subsequently, we validated our findings in 34 additional patients. RESULTS: Our data show that the mere presence of aPL confers a distinct thromboinflammatory signature characterized by the activation of coagulation, complement, innate and adaptive immune response pathways shared by all APS subtypes. Pathway enrichment analysis revealed increasing enrichment with rising statistical significance of thrombosis, complement, neutrophil and other innate and adaptive immune activation, as well as extracellular matrix (ECM) organization with increasing clinical severity, suggesting a model of progressive thromboinflammation in evolution of APS from NoAPS to TAPS and MAPS. CONCLUSIONS: Our findings provide novel insights into the pathogenesis of APS and identify potential novel targets for diagnostic and therapeutic intervention in APS across its entire spectrum.

Humans↗
PubMed2026

Time- and Dose-Resolved DIA-PASEF Proteomics Maps the Transition from Adaptive Stress to Apoptotic Collapse in Melittin-Treated MDA-MB-231 Cells.

Melittin, the cytolytic peptide of honeybee venom, exhibits potent anticancer activity in triple-negative breast cancer (TNBC), yet the molecular programs underlying its cytotoxic effects remain incompletely defined. To address this gap, MDA-MB-231 TNBC cells were exposed to melittin at half-maximal inhibitory concentration(half IC50) and IC50 across early(0.5, 1, and 2 h), mid(3, 4 h), and late (12, 24 h) time windows. Proteomic profiling was performed using label-free data-independent acquisition(DIA) parallel accumulation-serial fragmentation(PASEF). Approximately 5800 proteins were quantified, revealing distinct dose-dependent stress responses. An integrative exploratory framework combining time-resolved log2 fold-change trajectories, area-under-the-curve(AUC) based temporal prioritization, and independent heatmap visualization identified proteins associated with melittin-induced stress remodeling. Half IC50 exposure showed a transient stress-adaptive signature characterized by chromatin remodeling(HMGN2, H2AZ1), structural and RNA-associated buffering(LRRC7), and indirect mitochondrial quality-control signaling(CPAMD8, SPATA4), which progressively weakened over time. In contrast, IC50 treatment induced rapid chromatin remodeling dominated by histone H1 variants(H1.4, H1.2), early RNA instability(LRRC7), and late-stage cytoskeletal disassembly marked by MICAL3 induction, consistent with progression toward apoptosis. These trajectories paralleled dose-dependent apoptotic phenotypes. Overall, data suggest that melittin elicits dose- and time-dependent proteomic stress responses in TNBC cells and identify candidate trajectory-associated proteins and pathways linked to adaptive stress remodeling or progression toward cytotoxic collapse.

Melitten↗
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↗
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 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable 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 co-expression analysis.

Journal Article↗
PubMed2026

Proteomic profiling of the aqueous extract from the antennal gland of the Pacific white shrimp, Litopenaeus vannamei.

The antennal gland (AnG) of decapod crustaceans has been proposed as a potential source of bioactive molecules involved in chemical communication; however, its protein composition remains largely unexplored. Here, we present the first reference proteomic map of the aqueous extract from the antennal gland of the Pacific white shrimp Litopenaeus vannamei. Protein extracts from immature and mature females were analyzed using an integrated workflow combining one-dimensional SDS-PAGE, reverse-phase high-performance liquid chromatography (RP-HPLC), and nanoLC-tandem mass spectrometry. Electrophoretic and chromatographic analyses revealed a high degree of qualitative similarity between reproductive stages. SDS-PAGE resolved six major protein bands (∼227, 166, 77, 42, 35, and 17 kDa), most comprising multiple co-migrating proteins as revealed by LC-MS/MS. Hemocyanin was identified as the predominant protein and was detected across several electrophoretic bands. Additional proteins were associated with innate immunity, including β-1,3-glucan-binding protein and coagulable hemolymph protein; reproductive processes, including vitellogenin, spermatogonial stem-cell renewal factor, farnesoic acid O-methyltransferase, estrogen sulfotransferase, and prostaglandin reductase 1; as well as energy metabolism, protein homeostasis, cytoskeletal organization, and intracellular trafficking. Because several identified proteins are widely distributed or known hemolymph components, their detection cannot be assumed to reflect AnG-specific expression or function. Collectively, these findings establish a molecular reference for the L. vannamei AnG and reveal protein components associated with multiple physiological processes. This dataset provides a proteomic framework for future comparative and functional studies aimed at elucidating antennal gland physiology and experimentally evaluating the potential involvement of proteinaceous or peptide-based molecules in chemical communication in decapod crustaceans.

Animals↗
PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗
PubMed2026

Resolving cellular signaling in space and time: From organelle proteomics to spatial phosphoproteomics.

Cellular signaling is inherently organized in space and time, requiring coordinated control of protein localization, molecular interactions, and enzymatic activity across subcellular compartments. Recent advances in chemical biology, protein engineering, and quantitative proteomics have made it possible to interrogate these dimensions in an integrated manner. Here, we highlight emerging strategies to resolve signaling organization across three interconnected dimensions: organelle-resolved proteome mapping to define spatial context, proximity labeling to capture local protein interaction networks, and spatially resolved phosphoproteomics to quantify signaling outputs. Developments in proximity labeling, including split, conditionally activated and light-gated enzymes, enable temporally controlled, context-dependent profiling of transient protein assemblies in living cells. Advances in high-throughput and low-input phosphoproteomics, together with improved computational frameworks for kinase activity inference and subcellular enrichment strategies, are enabling spatially resolved measurement of signaling activity. Together, these approaches are shifting the field from static localization maps toward dynamic models of signaling networks.

Proteomics↗
PubMed2026

Auditing bacterial dark-gene screens for superimposed open reading frame artefacts: A multi-layer analysis of Rv2438A in Mycobacterium tuberculosis.

Essentiality and knockdown-vulnerability screens can promote spurious bacterial open reading frames when those frames overlap essential genes, because such a frame inherits its neighbour's signals undiluted and therefore satisfies the screen's criteria better than a genuine small gene. We present a multi-layer audit that tests this failure mode across genome annotation, transposon mutagenesis, CRISPR interference, homology, transcript mapping, proteomics, and population variation. We apply it to Rv2438A, a 92-codon conserved hypothetical open reading frame of Mycobacterium tuberculosis ranked first by our own dark-gene target screen. Rv2438A is superimposed on the essential NAD synthetase locus nadE: 44% lies within its coding sequence on the opposite strand, and the remainder covers its promoter and transcription start site. Consequently, three of five Himar1 sites lie within nadE, no CRISPRi guide can target Rv2438A without binding nadE, and the cross-species hit maps to the same nadE start junction. Rv2438A lacks its own transcription start site and is absent from every proteomic dataset that detects nadE. A genome-wide scan identifies six short, overlapping, uncharacterised loci among 3907 annotated genes, but only Rv2438A combines overlap and essentiality with non-detection across all proteomic datasets; rare genome-wide, it ranked first among screen hits. We provide an implementable audit workflow and a codon-position control, but measure the control's sensitivity as only two of five genes with attested protein, limiting it to confirmatory use. Overlap coordinates and neighbour-specific experimental resolution should therefore be reported before bacterial dark genes are prioritised.

CRISPR interference↗
PubMed2026

Tissue-layer-resolved proteome landscape of Crohn's disease strictures highlights potential drivers of fibrosis progression.

The chronic inflammation of Crohn's disease frequently leads to fibrosis and muscular hypertrophy of the intestinal wall. This often culminates in strictures, a serious condition lacking directed therapy. Severe pathological changes occur in the submucosa and muscularis propria intestinal wall layers of strictures, yet stricture-associated proteome changes in these layers is unexplored. We perform unbiased proteomics on submucosa and muscularis propria microdissected from transmural sections of strictured and nonstrictured ileum. Proteome changes in strictured submucosa reflected a transition from homeostasis to tissue remodeling, inflammation, and smooth muscle changes. Top submucosal features included reduced vascular components and lipid metabolism proteins accompanied by increased proteins with immune-, ECM-, or stress-related functions, including CTHRC1, TNC, IL-16, MZB1, and TXNDC5. In parallel, predominant changes in strictured muscularis propria included increased ECM (POSTN) and immune (mast cell CPA3) proteins alongside decreased proteins with lipid metabolic, mitochondrial, or key muscle functions. Finally, trends of differentially expressed proteins along nonstrictured submucosa suggest progressive profibrotic tissue remodeling and muscle expansion as proximity to strictures increases. The comprehensive proteome map presented here offers tissue-layer-resolved insight into the stricture microenvironment and potential drivers of fibrotic disease, providing a valuable resource to fuel biomarker and therapeutic target research.

Humans↗
PubMed2026

Mapping the plasma proteomic architecture of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune disease, yet the molecular basis underlying this variability remains incompletely understood. We profiled the plasma proteome in 260 SLE patients and 86 healthy volunteers (HVs) using the SomaScan v4.1 platform, quantifying 7,288 analytes corresponding to 6,595 unique proteins. We identified 215 proteins that were robustly differentially abundant between SLE patients and HVs in both discovery (n = 207 SLE, n = 45 HVs) and validation sets (n = 53 SLE, n = 41 HVs). Within-cases analyses identified 421 proteins associated with disease activity. Network-based clustering delineated correlated protein modules, including an interferon-associated (IFN-associated) module and a kidney-associated module. Autoantibody-stratified analyses further uncovered distinct proteomic endotypes; positivity for antibodies targeting RNA-binding proteins (anti-Sm, anti-Ro-60, anti-RNP68, anti-RNP-A) was associated with increased IFN-stimulated protein levels (e.g., MX1, ISG15, and CXCL10), independent of disease activity. Anti-Sm, anti-RNP-A, and anti-Ro52 antibodies were associated with reduced plasma levels of their respective autoantigens. Anti-dsDNA antibodies were associated with elevated levels of CD40 ligand (CD40LG) and the neutrophil protease, proteinase-3. Moreover, we identified an association between CD40LG and disease activity specific to the anti-dsDNA-positive subgroup. Together, these data define plasma protein signatures of SLE and disease activity, highlight autoantibody-specific molecular phenotypes, and provide a basis for precision medicine.

Humans↗
PubMed2026

Mapping the covalent cysteine interactome of Ebselen reveals high-sensitivity target engagement and redox proteome remodeling.

Ebselen is a covalent organoselenium compound with broad pharmacological activity, yet its cellular cysteine targets and downstream proteomic consequences remain incompletely defined. Here, we integrated competitive gel-based activity-based protein profiling, reactivity-dependent tandem orthogonal proteolysis-activity-based protein profiling, and TMT-based quantitative proteomics to map Ebselen-induced cysteine engagement and proteome remodeling in living cancer cells. Ebselen exhibited dose-dependent cytotoxicity and markedly perturbed intracellular thiol-redox balance, as reflected by glutathione depletion and altered reactive oxygen species-associated fluorescence readouts. Competitive gel-based profiling confirmed concentration-dependent engagement of protein cysteine residues in live cells. Quantitative rdTOP-ABPP further identified hundreds of dose-responsive cysteine sites in HeLa and HepG2 cells and revealed a preference for cysteine microenvironments enriched with basic residues. Cross-cell-line comparison highlighted CDK5 Cys53, SMU1 Cys298, and RPSA2 Cys163 as conserved covalent nodes, among which CDK5 Cys53 showed high sensitivity to Ebselen treatment, a finding validated by competitive labeling and MS-based site assignment. Global TMT proteomics revealed extensive remodeling of redox-related and cell-survival-associated pathways, including compensatory upregulation of selenoproteins such as TXNRD1 and GPX family members. Together, these results define a chemical proteomic atlas of Ebselen-cysteine interactions and provide a framework for understanding and optimizing covalent organoselenium therapeutics.

Humans↗
PubMed2026

Proteome-wide Ubiquitinome Profiling Reveals Substrate-specific Dynamics Within the USP7 Network.

USP7 is a pleiotropic deubiquitylating enzyme that is involved in tumor suppression, (neuro) development, chromatin regulation and the DNA damage response. How USP7 regulates these diverse pathways is still unclear. Here, we report data-independent acquisition and label free quantitation mass spectrometry to profile the proteome-wide impact of USP7 on substrate de-ubiquitylation and overall protein abundance. First, we identified proteins associated with endogenous USP7 by immunopurification followed by data-independent acquisition and label free quantitation mass spectrometry. Integration of our new results with earlier interactomes of epitope-tagged USP7 yielded a consensus set of high-confidence protein targets. Domain mapping analysis revealed that, in addition to the TRAF domain, the ubiquitin-like domains of USP7 play a key role in substrate selection. Using specific enrichment of tryptic K-ε-GG peptides, we mapped proteome-wide changes in ubiquitinome dynamics following inhibition of USP7. Combining unbiased proteome-wide and targeted quantitative mass spectrometry revealed that deubiquitylation by USP7 can have different effects on the stability of distinct substrates, and suggests that USP7's activity profile is substrate-dependent rather than an intrinsic enzymatic property. Thus, in addition to providing a proteome-wide map of USP7 target sites, our multi-angle proteomics approach reveals that the effects of USP7-mediated deubiquitylation on its targets are remarkably variable and substrate-specific. Finally, based on these detailed molecular insights we show how USP7 connects various neurodevelopmental syndromes and tumor suppression pathways.

Ubiquitin-Specific Peptidase 7↗
PubMed2026

Hex-MASP for mapping the whole-tissue spatial proteome and the intrabrain distribution of monoclonal antibodies.

Whole-tissue level spatial proteomics provides critical insights into region-specific biological regulations but remains challenging. Previously, we introduced the micro-scaffold assisted spatial proteomics (MASP) concept for whole-tissue mapping. However, this prototype required substantial development in spatial resolution, practicality, and throughput for practical application. Here we present a next-generation MASP technique (hex-MASP) featuring i) a new design of hexagonal-micro-wells fabricated with optimized projection micro-stereolithography 3D-printing, achieving high spatial resolution, sampling robustness, and mechanical strength for reproducibly compartmentalizing even tough tissues; ii) enhanced throughput/effectiveness in sample preparation and LC-MS analysis with high quantitative quality. Applied to mouse brain, hex-MASP achieved in-depth, whole-tissue mapping for >6,000 proteins in mouse brains, with high spatial accuracy and excellent data quality. The substantially improved resolution revealed critical regional details across the entire brain, that were not previously captured, enabling precise depiction of protein distribution heterogeneity. This technique enabled the identification of many unreported regionally enriched proteins across brain structures. We further applied hex-MASP to investigate the intrabrain distribution of intracerebroventricularly dosed antibody therapeutics and related proteins, which enabled whole-tissue mapping of protein drugs revealed insights into antibody brain penetration and distribution. Hex-MASP represents a robust, scalable platform for whole-tissue spatial proteomics.

Animals↗
PubMed2025

Stage-dependent proteomic alterations in aqueous humor of diabetic retinopathy patients based on data-independent acquisition and parallel reaction monitoring.

BACKGROUND: Diabetic retinopathy (DR), a microvascular complication of diabetes mellitus (DM), represents the predominant cause of preventable vision loss in working-age populations globally. While the pathophysiological mechanisms underlying DR progression remain incompletely understood, our study employs comprehensive proteomic profiling of aqueous humor (AH) to identify stage-specific biomarkers and therapeutic targets in type 2 diabetes mellitus (T2DM) patients across DR progression. METHODS: Utilizing data-independent acquisition (DIA) mass spectrometry, we quantified AH proteomes in a discovery cohort comprising 24 subjects: 18 T2DM patients stratified by DR severity [6 non-DR, 6 non-proliferative DR (NPDR), 6 proliferative DR (PDR)] and 6 cataract controls without diabetes (non-DM). Validation cohort analysis (including 10 AH samples in each group) was performed using parallel reaction monitoring (PRM) strategy for verification of target proteins. Comprehensive bioinformatics analyses included gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network construction, receiver operating characteristic (ROC) curve analysis, and ConnectivityMap (Cmap)-based drug prediction. RESULTS: Proteomic profiling identified 739 quantifiable AH proteins (62% extracellular) with clear separation among the four clinical stages in the discovery cohort. GSEA uncovered altered expression of proteins mainly related to complement and coagulation cascades, folate metabolism, and the selenium micronutrient network in patients with DR. WGCNA-derived protein modules yielded 83 PRM-validated targets, including 5 hub proteins differentiating NPDR from non-DR and 33 hub proteins showed significant upregulation in PDR versus NPDR comparison. Clinical correlation analysis identified F2, FGG, FGB, RBP4, AMBP, VTN, C8A, CPB2, and C2 associated with clinical traits. C6, FAM3C, SPP1, and JCHAIN levels were altered post-anti-VEGF treatment. Pharmacological prediction identified potential therapeutic compounds, including perindopril, triciribine, and XAV-939 for NPDR, and topiramate, triciribine, and vecuronium for PDR. CONCLUSION: This study established a comprehensive AH proteomic signature of DR progression, offering insights into the pathogenesis of DR and highlighting potential biomarkers and novel therapeutic targets.

Humans↗
PubMed2026

Proteomic insights into Helicobacter pylori infection in stomach cells, revealing host response and host-targeted therapeutics repurposing.

BACKGROUND: Helicobacter pylori (H. pylori) is a globally prevalent gastric pathogen strongly associated with chronic gastritis, peptic ulcers, and gastric cancer. While bacterial factors have been extensively studied, host proteomic responses and their therapeutic potential remain largely underexplored. RESEARCH DESIGN AND METHODS: Current analyses employed a systematic proteomics-based data integration and harmonization approach (retrospective qualitative cohort study) to identify important differentially regulated host proteins. Proteomic datasets were curated from in vitro studies and analyzed for functional enrichment, protein-protein interaction networks, and hub protein identification. To explore therapeutic repurposing, drug repositioning was performed using the DrugBank database. RESULTS: Data summation describing protein differential regulation in human gastric cells as a result of the infection revealed 1672 perturbed host proteins. Bioinformatics analysis revealed 11 proteins including CSK, MET, RELA, MARK2, GRB2, FTO, PLCG1, CRKL, RPS5, RPS9, and RPS27A to be ideal host targets for therapeutic repurposing. Clinically approved drugs such as Dasatinib (targeting CSK) and Crizotinib (targeting MET) emerged as promising candidates due to favorable pharmacokinetics and known bioactivity. CONCLUSIONS: Host-directed therapeutics could offer alternative strategies to conventional antibiotic therapy, addressing challenges such as resistance and infection recurrence, providing a foundation for future experimental validation and development of host-targeted interventions for infection control.

Humans↗
PubMed2026

Integrative multi-omics analysis of metabolite-protein interaction networks across different stages of coronary heart disease.

To elucidate the molecular characteristics of synergistic interactions across the clinical stages of coronary heart disease (CHD)-specifically stable angina pectoris (SAP), unstable angina pectoris (UAP), and acute myocardial infarction (AMI)-through integrated metabolomic and proteomic analyses. Based on a cohort including SAP, UAP, AMI, and healthy controls, metabolomic and proteomic analyses were performed to identify differentially expressed molecules, followed by KEGG pathway enrichment analysis. Pathways co-enriched across both omics platforms were selected to construct metabolite-protein interaction networks. The number of pathways co-enriched in both metabolomic and proteomic analyses increased markedly with disease stage. Only two pathways (histidine metabolism and arginine and proline metabolism) were identified in the SAP stage; this number increased to five in the UAP stage (including ferroptosis and efferocytosis) and expanded to 25 in the AMI stage, encompassing three major functional modules: immune inflammation, metabolic reprogramming, and cell signaling. The core network exhibited a stepwise increase in connectivity, shifting from a sparse structure in the SAP stage to a highly interconnected architecture in the AMI stage, with L-glutamate and KNG1 identified as the central hubs in this cross-sectional network. In addition, CNDP1 exhibited a stage-dependent functional transition, shifting from downregulation in SAP to upregulation in AMI. In this cross-sectional analysis, metabolic dysregulation and immune activation exhibited stepwise increases in interconnectivity across the SAP, UAP, and AMI groups, with the most extensive crosstalk observed in the AMI stage-a network configuration consistent with a tightly coupled "molecular storm". These findings provide novel insights into stage-associated molecular signatures of CHD and identify candidate hub molecules for stage-oriented therapeutic investigation.

Humans↗