Journal of Proteomics

Mass spectrometry-based proteomics requires downstream analysis of processed protein abundance data, including data inspection, filtering, statistical testing, functional enrichment, protein set comparison, network analysis, and visualization. MiraProt was developed as a modular, metadata-aware R Shiny platform that integrates these steps in a single interactive workflow for processed protein-level proteomics data. Its metadata-aware design enables identifiers, sample information, experimental conditions, transformations, and derived data columns to be defined during data preparation and reused consistently across downstream analyses. To demonstrate its use, we reanalyzed a previously published label-free proteomic dataset of primary retinal Mueller cells from healthy horses and horses with equine recurrent uveitis (ERU). ERU is a naturally occurring autoimmune eye disease of horses characterized by recurrent intraocular inflammation triggered by autoreactive T-cells. Mueller cells are specialized retinal macroglia with various functions such as maintaining retinal ion homeostasis and supporting retinal neuron metabolism. Of 193 proteins with an adjusted p-value [≤] 0.05, 187 also showed at least a twofold abundance difference between ERU-derived and control Mueller cells. Functional enrichment highlighted nuclear RNA processing, chromatin-associated structures, DNA and RNA binding, interferon responses, and cell-cycle-associated programs. Gene set enrichment analysis identified positive enrichment of Interferon Alpha Response, Interferon Gamma Response, and MYC-, E2F-, and G2M-associated gene sets. Network analysis of shared proteins further linked this signature to DNA replication, mitotic checkpoint control, and RNA processing. ERU-derived Mueller cells also showed increased abundance of MHC class II-associated proteins. Together, these findings identified an interferon-responsive, cell-cycle-associated, and MHC class II-associated Mueller cell protein signature in ERU and generated experimentally testable hypotheses for further mechanistic studies. MiraProt provides an accessible, metadata-aware framework for reproducible downstream exploration of processed proteomic datasets and prioritization of candidate proteins and pathways for experimental follow-up.

The axolotl salamander can fully regenerate amputated limbs, yet the systemic consequences underlying this process remain largely understudied. Cerebrospinal fluid is an emerging signaling medium capable of communicating with both the central and peripheral nervous systems, but its composition and potential role in salamander limb regeneration have not yet been examined using modern multi-omics techniques. Here, we developed a protocol for extracting mixed perilymph-cerebrospinal fluid (P-CSF) from axolotl and provided the first proteomic and metabolomic characterization of this biological fluid. We identified 2,626 unique proteins and 173 high-confidence metabolites and quantified them across four time points of early limb regeneration. We demonstrated that limb amputation drives progressive shifts in P-CSF proteins, including an elevation of sarcomeric muscle proteins, regeneration-associated factors, and protease/extracellular matrix proteins. We observed shifts in metabolites involved in oxidative stress, polyunsaturated fatty acid oxidation, and histamine metabolism. Injury-comparison experiments revealed that the observed proteomic changes as a result of limb amputation are different than crush injury, denervation, or tail amputation. This study proposes axolotl P-CSF as a reservoir for limb amputation-associated systemic signaling and as a potential conduit of signals involved in limb regeneration.

Euglena longa is a heterotrophic model euglenid, of significant research interest as a unicellular eukaryote. To provide broad insight into the localisation of its proteome we used subcellular spatial proteomics (SSP), based on a label-free version of LOPIT-DC (Localisation of Organelle Proteins by Isotope Tagging after Differential Centrifugation), in which organelles are separated by differential centrifugation and each protein is assigned to a compartment from its abundance profile across the fractions. We detected 5,909 proteins, using protein abundance profiles across fractions to resolve 16 different subcellular compartments, such as the plastid, pellicle, and peroxisomes, and assigned high-confidence localisations to 2,955 of them. This study serves as a proteomic dataset to resolve protein compartmentalisation for this euglenid, enabling evolutionary, biological and functional insight and analysis. We are drafting manuscripts concerning the metabolic nature of the plastid, the evolutionary origins of the pellicle, and the functions of the peroxisome. Investigators interested in using this data prior to publication are encouraged to contact us to avoid overlap and to facilitate coordinated and collaborative use of this resource.

Multicenter studies are essential for benchmarking analytical workflows, yet their interpretation is often confounded by the combined effects of experimental protocols and instrumentation. To address this challenge, we introduce a simple normalization-based analytical framework, the recovery metric ({rho}), designed to decouple protocol driven effects from instrument dependent variability. We applied this framework to the 13th Proteomics Multicentric Experiment (PME13), a large multicentric proteomics dataset generated across 27 laboratories using high sensitivity workflows and varying sample preparation protocols. By leveraging a common digested reference sample, {rho} enables direct cross-comparison of all datasets on a unified scale, effectively minimizing instrument-related biases. Using this approach, we demonstrate that apparent instrument dependent trends are largely removed when evaluated through {rho}, revealing consistent protocol driven effects across laboratories. Statistical modeling identified key variables influencing {rho}, including sample input amount, reduction and alkylation, and the use of n-dodecyl-{beta}-D-maltoside (DDM). While DDM was associated with improved {rho}, reduction and alkylation and additional handling steps led to reduced performance, particularly at low input levels. We further highlight practical considerations for the application of ratio based normalization, including the occurrence of values exceeding theoretical bounds, which reflect deviations from underlying assumptions and require appropriate filtering. Overall, this work establishes a generalizable analytical strategy for disentangling confounding factors in multicentric datasets and provides practical guidelines for optimizing high sensitivity proteomics (HSP) workflows. The proposed framework is broadly applicable to other analytical fields where cross laboratory comparability is required.

Background: Macrophages play a central role in systemic iron homeostasis by recycling iron from senescent erythrocytes through the only known cellular iron exporter, ferroportin (Fpn). Previous studies have shown that Fpn localizes to membrane microdomains, or lipid rafts, which are important for its function and regulation by hepcidin. Iron strongly promotes the enrichment of Fpn in lipid rafts. However, the proteomic composition of these domains during iron overload remains largely unexplored. Objective: This study aimed to characterize iron-induced changes in the macrophage lipid raft proteome in order to identify potential functional partners of Fpn and better define the cellular mechanisms involved in the response to iron overload. Methods: Quantitative iTRAQ-based proteomic analysis was performed on detergent-resistant membranes (DRMs) isolated by iodixanol density-gradient ultracentrifugation from J774a.1 macrophages treated with iron-NTA (FeNTA). Key proteomic observations were further validated in both J774a.1 cells and bone marrow-derived macrophages (BMDMs) using western blot, cell-surface biotinylation, and confocal immunofluorescence microscopy. The regulatory role of the transcription factor Nrf2 was also assessed using Nrf2-knockout mouse models. Results: In addition of Fpn, our lipid raft proteome identified 79 proteins significatively upregulated upon iron treatment, including, antioxidant proteins like the peroxiredoxin-1 (Prdx1), the glucose-6-phosphate dehydrogenase X-linked (G6pdx), as well as heme oxygenase-1 (Hmox1). Bioinformatic and functional analyses indicated that this response is associated with nuclear translocation of Nrf2, which is required for the transcriptional induction of Fpn and Hmox1. Whereas Fpn was detected in lipid rafts under basal conditions, Hmox1 was recruited to these domains only after iron or heme treatment. Confocal microscopy and cell-surface biotinylation assays confirmed that Hmox1 and Fpn colocalize at the plasma membrane, particularly within caveolae, specialized invaginated lipid raft domains. Conclusions: Iron or heme overload induces a major remodeling of the macrophage membrane, leading to the formation of specialized lipid raft platforms enriched in antioxidant and iron handling proteins. The coordinated localization of Hmox1 and Fpn at the cell surface suggests a coupled mechanism linking heme catabolism to iron export. This organization may help limit intracellular iron accumulation and protect the plasma membrane from iron-mediated lipid peroxidation.

Melittin, the principal bioactive peptide of bee venom, exhibits promising antitumor activity, whereas its molecular mechanisms in cervical cancer remain incompletely understood. In this study, the biological effects and molecular responses of melittin in U14 cervical cancer cells were investigated using Astral data-independent acquisition (Astral-DIA)-based quantitative proteomics combined with molecular validation. The effects of melittin on cell migration, invasion, and cell death were evaluated by Transwell assays and PI/Hoechst staining. Differentially expressed proteins (DEPs) were screened and subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses. Representative oxidative stress-related genes and proteins were further validated by RT-qPCR and Western blotting. Melittin significantly inhibited the migration and invasion of U14 cervical cancer cells and increased cell death. Quantitative proteomics identified 9,782 protein groups and 187 DEPs, including 71 up- and 116 down-regulated proteins. KEGG pathway enrichment analysis revealed oxidative phosphorylation (OXPHOS) as the most significantly enriched pathway, together with glutathione metabolism, ferroptosis-related pathways, reactive oxygen species signaling, and mitophagy. GO term enrichment analysis indicated that DEGs were mainly engaged in mitochondrial function, electron transport, oxidoreductase activity, and energy metabolism. RT-qPCR assay demonstrated altered expression of Duox1, Gpx4, Gsx2, Nfe2l2, and Gstp2. Additionally, PPI analysis identified Gstp2 and ODC1 as representative hub proteins involved in redox regulation and metabolic adaptation. Furthermore, Western blotting confirmed increased GSTP2 expression following melittin treatment. Overall, these findings provide a comprehensive proteomic landscape of melittin-treated U14 cervical cancer cells and suggest that mitochondrial OXPHOS remodeling and redox-associated pathways may contribute to the antitumor activity of melittin.

Data-independent acquisition (DIA) mass spectrometry has emerged as a powerful tool for neuropeptidomics, but its success relies heavily on the quality of spectral libraries used for peptide identification. There are inherent challenges to mass spectrometry analysis of crustacean neuropeptides, including the endogenous nature in which they are analyzed, extensive post-translational modification (PTM), and atypical fragmentation patterns. Thus, general-purpose proteomic spectral prediction tools may not perform optimally in the endogenous peptide domain. In this study, we benchmark four widely used spectral prediction platforms, Prosit, MS2PIP, AlphaPeptDeep, and UniSpec, to evaluate their performance in predicting the fragmentation of neuropeptides. Using an empirically derived spectral library from crustacean tissues as reference, we assess model compatibility, dot-product similarity, Pearson correlation, and DIA-based identifications across brain, sinus gland, and pericardial organ samples. Our results reveal that no single model comprehensively captures neuropeptide fragmentation characteristics. While UniSpec showed unexpected strengths due to its inclusion of neutral loss ions, AlphaPeptDeep demonstrated the highest spectral similarity, and MS2PIP and Prosit outperformed in DIA-NN identifications. We further highlight the critical impact of neutral loss fragments, present in over 50% of empirical spectra, and emphasize the need for hybrid spectral libraries that integrate complementary strengths across models. This work provides a foundational framework for optimizing spectral library selection in neuropeptidomics and underscores the importance of model-specific biases when analyzing structurally diverse endogenous peptides.

Lipid droplets (LDs) play a central role in cellular carbon and energy homeostasis, in particular through the roles played by numerous LD-associated proteins. A long-standing question concerns how these proteins are molecularly organized at the seemingly overcrowded LD surface. Delayed in TAG Hydrolysis 1 (DTH1) has been identified as a key protein for efficient LD degradation in Chlamydomonas reinhardtii, however the underlying molecular mechanism remains unknown. DTH1 contains several structural features including a coiled-coil domain, a phosphatidylethanolamine (PE) specific lipid-binding domain, intrinsically disordered regions, and an alpha-helical C-terminal domain, that make it a compelling candidate for acting as a molecular scaffold in protein recruitment and/or organelle tethering. In this study, we used the Chlamydomonas knock-out mutant dth1 as an entry point to begin dissecting the molecular organization of proteins at the LD surface. Comparative lipidomic and proteomic analyses of isolated LDs from both WT and dth1 mutants revealed several key features associated with LD degradation during nutrient recovery. First, PE emerged as an important lipid species involved in LD degradation. Second, active communication occurs among multiple subcellular organelles particularly between LDs, peroxisomes and mitochondria. Third, DTH1 was found to play a critical role in remodeling both the LD proteome and lipidome. Furthermore, detailed analyses of LD degradation during nitrogen recovery uncovered the formation of micro-LDs, a phenomenon not yet reported in microalgae. Collectively, these results highlight the tight coordination of metabolic activities across subcellular compartments and emphasize the importance of intracellular carbon trafficking during stress recovery.

Novel serum peptidomics offers a direct insight into proteolytic activity, tissue injury, and systemic signaling. Nevertheless, existing workflows suffer from low peptide yields, low throughput, and limited recovery of low-abundance species. Here we present a native serum peptidomics protocol that integrates mild acid treatment, solid-phase extraction with molecular weight cutoff filtration and data-independent acquisition mass spectrometry (DIA-MS). The protocol requires less than 100 {micro}l of serum or plasma, is completed within hours, time-cost-effective and compatible with 96-well formats without specialized equipment. Applied to a proof-of-concept cohort of patients with acute ischemic stroke (AIS), intracranial haemorrhage (ICH), and healthy controls, the workflow identified over 12,000 peptides, exceeding the three-fold threshold of existing peptidomics approaches. DIA-MS analysis across independent batches demonstrated 78-83% peptide overlap and consistent fold-change directionality. We further introduce peptide locus analysis, which aggregates overlapping peptides within defined protein regions. This approach revealed bidirectional regulation within individual precursor proteins such as the fibrinogen alpha chain (FIBA), resolving intraprotein proteolytic dynamics. Three candidate peptides from TYB4, CO4B, and ITIH4 proteins accurately distinguished stroke subtypes and controls, while characteristic shifts in peptide physicochemical properties were observed across strokes. This workflow substantially advances the sensitivity, throughput, and biological resolution of serum peptidomics for quantitative multi-biomarker discovery, validation and its output promises effective implementation of AI/ML models aiming for new dimensions in diagnostics, prognostics, prediction and monitoring.

Phenylketonuria (PKU) is an autosomal recessive disorder caused by PAH gene defects and can cause irreversible neurological damage as early as the fetal period; however, non-invasive prenatal monitoring methods are lacking. In this study, Pah+/- female mice were mated with Pah+/-; male mice and wild-type male mice, respectively. Urine samples were collected longitudinally from pregnant mice at 10 time points during gestation from Day 1 to Day 19. Data-independent acquisition (DIA) quantitative proteomics combined with GO/KEGG analysis, WGCNA, and a dual-strategy LASSO-random forest approach was used to screen candidate biomarkers. The results showed that stable differentially expressed proteins between groups were detectable as early as Day 1, and the differences persisted throughout gestation and exhibited temporal dynamics. Permutation tests indicated that the probability of random generation of the differential protein combination was low (0.04-0.06), suggesting that it was not randomly generated. The intersection of the two strategies yielded five proteins, GINM1, PRG4, LY6A, NTM, and YIPF3, and after including GLO1, a total of six candidate biomarkers were obtained. The candidate proteins had interaction or co-expression associations with 14 proteins involved in PKU mechanisms, with GLO1 serving as a network hub. This study found that the maternal urine proteome can non-invasively reflect the systemic response induced by fetal-origin PKU, providing proof of concept and candidate biomarker resources for non-invasive early-pregnancy screening of PKU.

Experimental bacterial meningitis is often analyzed as microbial burden and inflammation, but the tissue-level organization of host-pathogen interplay remains poorly resolved. Here, we use multimodal imaging to map Escherichia coli meningoencephalitis as a spatially organized process across infected rat brain tissue and cerebrospinal fluid (CSF). A low-dose intracerebral inoculum expands within 24 h into an anatomically structured infection involving ventricular, meningeal, and perivascular interfaces. Scanning electron microscopy reveals biofilm-like multicellular E. coli aggregates embedded in extracellular material, consistent with neutrophil extracellular traps. MALDI mass spectrometry imaging detects aerobactin and salmochelin-derived metabolites, whereas intact enterobactin is not detected despite favorable analytical sensitivity. These bacterial iron-acquisition signals partially overlap with calprotectin proteoforms, defining ventricular and periventricular metal-conflict microenvironments. Spatial peptidomics identifies infection-enriched antimicrobial territories dominated by rat neutrophil peptides RatNP-2, RatNP-3, and RatNP-4. Endogenous proenkephalin-derived neuropeptides are reduced in basal ganglia regions. Finally, cerebrospinal fluid captures both bacterial siderophores and host antimicrobial peptides with lipocalin-2 protein, linking tissue-resolved host-pathogen chemistry to a proximal diagnostic fluid. Together, these data show that experimental E. coli meningoencephalitis is a spatially organized host-pathogen process. Bacterial communities, nutritional immunity, antimicrobial peptides, and neuropeptide networks occupy distinct but connected CNS niches, components of which are recoverable in CSF.

Why was the work done?: Gluten-free (GF) beers typically exhibit poorer foam stability than conventional barley malt-based beers, yet the molecular basis underlying this difference remains poorly understood. This study aimed to investigate protein-level factors associated with foam stability in GF and barley beers. How was the work done?: Three commercially produced GF beers, comprising two lagers brewed from rice or sorghum, and one pale ale brewed from a millet-buckwheat-rice blend, were compared with two commercially produced barley-malt beers, comprising a lager and a pale ale. Soluble protein was isolated from freeze-dried beer powder using TCA-acetone. Protein profiles were examined using SDS-PAGE, and proteomes were characterised and compared using label-free quantitative LC-MS/MS. What are the main findings?: GF beers showed lower soluble protein concentrations and significantly lower foam stability than the barley beers. SDS-PAGE revealed fewer and weaker protein bands in GF beers compared with barley beers. Proteomic analysis showed that barley beers were enriched in known foam-active proteins, particularly lipid transfer protein 1 (LTP1) and Protein Z (serpin family members), whereas these proteins were not detected or were detected only at very low levels in GF beers.

Microglial inflammatory activation is accompanied by extensive molecular remodeling, yet proteomic, lipidomic, and metabolomic responses are often analyzed independently. Here, we applied an integrated mass spectrometry-based multiomic workflow to characterize proteomic, lipidomic, and polar metabolomic remodeling from matched BV-2 biological samples following stimulation with interferon-{gamma} and lipopolysaccharide (IFN-{gamma} and LPS). Inflammatory activation was confirmed by increased nitrite accumulation, elevated TNF- and IL-6 secretion, and treatment-associated morphological changes. Discovery proteomics quantified 8,676 proteins and identified 562 significantly altered proteins, including 344 increased and 218 decreased proteins. Increased proteins were enriched for interferon-responsive, innate immune, inflammatory effector, and antigen-associated pathways, whereas decreased proteins were associated with cellular organization, protein biogenesis, vesicular trafficking, and metabolic regulation. Targeted lipidomics identified 237 significantly altered lipid features out of 356 measured lipids, including increased triacylglycerols and diacylglycerols and broad remodeling of glycerophospholipids, lysophospholipids, and sphingolipid-related species. Targeted polar metabolomics identified 75 significantly altered metabolites out of 98 measured metabolites, including changes in nucleotide/NAD-related metabolism, amino acid metabolism, methylation-associated metabolites, acylcarnitine abundance, phospholipid precursors, polyamine metabolism, arginine/nitric oxide-associated metabolism, and redox-associated metabolites. Process-level integration of significant features revealed coordinated remodeling of inflammatory protein programs with lipid storage, membrane remodeling, nucleotide metabolism, amino acid availability, phospholipid precursor abundance, nitric oxide-associated metabolism, and redox/osmolyte pathways. These findings demonstrate that IFN-{gamma} and LPS-induced activation of BV-2 cells involves integrated immune, lipid, and metabolic adaptation rather than isolated induction of canonical inflammatory mediators. This integrated multiomic framework provides a resource for investigating how lipid and metabolic remodeling regulate microglial inflammatory states. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/741024v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@11dd431org.highwire.dtl.DTLVardef@155f107org.highwire.dtl.DTLVardef@1430e89org.highwire.dtl.DTLVardef@16f4a25_HPS_FORMAT_FIGEXP M_FIG C_FIG

Abstract Background: Intraductal papillary mucinous neoplasms (IPMNs) are recognized as precursor lesions to pancreatic ductal adenocarcinoma (PDAC). However, the molecular programs underlying progression from low-grade dysplasia to advanced disease remain incompletely characterized. Herein, we performed an integrated plasma and tissue-proteomic analyses coupled with spatial and single-cell transcriptomics to identify biologically coherent remodeling programs reflected in circulation that distinguish IPMN by dysplasia grade and invasive disease. Methods: Using the O-link proximity extension assay platform, a panel of 1,104 proteins were quantified in plasma samples collected from patients with low-grade (LG) IPMN (n=30), high-grade (HG) IPMN with or without associated PDAC (IPMN/PDAC; n=40) and PDAC without IPMN (n=8). Predictive performance of individual biomarkers were assessed; likelihood ratio testing was performed to identify protein biomarkers that were complementarity with CA19-9 for risk of malignancy of IPMN. Findings were intersected with available spatial (N= 13) and single-cell (N= 6) transcriptomic datasets of IPMN tissues as well as mass spectrometry-based proteomic profiles of an independent set of resected human IPMN tissues (N= 9). Results: A total of 28, 43, and 35 circulating proteins were found to be differential in HG, IPMN/PDAC, and HG + IPMN/PDAC cases compared to LG IPMN. Among differential proteins were known PDAC-associated markers CEACAM5, CTRC, and REG3A as well as several biomarkers reflecting cytoskeletal and extracellular matrix remodeling and inflammatory processes. Focusing on cytoskeletal and ECM-related proteins and using likelihood ratio testing, an OR rule considering CA19-9, BGN, and ITGB1BP1 achieved overall sensitivity of 48.7% for HG + IPMN/PDAC, including 38.1% sensitivity for HG IPMN, at an overall specificity of 90%, which was improved compared to that of CA19-9 alone (overall sensitivity of 28.2%; McNemar Exact test 1-sided p-value: 0.011). Integrated proteomic and spatial transcriptomic datasets of IPMN tissues revealed coordinated alterations cytoskeletal and ECM remodeling and elevated matrix stiffness as prominent features associated with IPMN/PDAC, which paralleled concordant increases in BGN and ITGB1BP1. Cell-type of origin analyses based on spatial and single-cell data further revealed fibroblasts and myeloid cells as primary contributors to expression levels of BGN whereas ITGB1BP1 was primarily expressed in neoplastic epithelium. Conclusion: Advanced IPMN dysplasia and invasive disease are characterized by coordinated tissue remodeling programs that are systemically reflected in circulating proteomic profiles. Blood-based biomarkers identified through our study, such as BGN and ITB1BP1, have potential to improve upon CA19-9 for risk stratification of IPMN to better guide clinical management.

Serum proteomics is increasingly used for minimally invasive biomarker discovery and disease phenotyping, and the choice of serum preprocessing workflow can shape proteome depth, quantitative characteristics, and downstream biological readouts. However, disease-oriented comparisons within a single cohort remain limited. Here, we compared four serum preprocessing workflows--Top14 depletion (TOP14D), tomato lectin affinity purification (TomAP), and two nanoparticle-based enrichment workflows (NPA and NPB)--using serum from six patients with systemic juvenile idiopathic arthritis (sJIA) and six age- and sex-matched healthy controls, and analyzed them using unified data-independent acquisition mass spectrometry (DIA-MS) and a statistical pipeline. We evaluated proteome depth, missingness, quantitative characteristics, group separation, differential abundance signatures, pathway enrichment, curated sJIA-related gene set coverage, pre-ranked gene set enrichment analysis (GSEA) results, and detection of inflammasome/interferon-related proteins. TomAP yielded the greatest proteome depth (7612 proteins), followed by NPB (6735 proteins) and NPA (6602 proteins), whereas TOP14D yielded the smallest protein set (3303 proteins). Principal component analysis (PCA) showed a separation between the sJIA and control groups for all workflows. Differentially expressed proteins (DEPs) showed limited overlap, with only 75 DEPs common to all four workflows. Functional enrichment patterns were workflow-dependent; TOP14D and TomAP mainly captured neutrophil/myeloid and inflammatory processes, whereas NPA and NPB captured RNA processing- and translation-related signals. TomAP showed relatively broad coverage and positive enrichment of curated sJIA-related gene sets associated with inflammation, innate immunity, and macrophage activation syndrome (MAS). Inflammasome/interferon-related proteins, including NLRC4, PYCARD, GSDMD, MEFV, IL-18, OAS3, and MYD88, showed workflow-dependent detectability and differential abundance. These findings support a disease-oriented benchmark for fit-for-purpose workflow selection according to the disease axis and analytical objective rather than proteome depth alone.

Type 2 diabetes (T2D) is a prevalent metabolic disorder affecting millions worldwide, characterized by insulin resistance and impaired glucose homeostasis. While mammalian models are widely used, Drosophila melanogaster provides a powerful alternative due to its conserved insulin signaling pathways, genetic tractability, and suitability for high throughput studies. In addition to glucose dysregulation, lipid metabolism plays a crucial role in T2D pathophysiology, as alterations in lipid composition contribute to insulin resistance and metabolic dysfunction. Lipidomic studies have emerged as an essential approach to identify metabolic signatures and potential biomarkers for disease progression and therapeutic targeting. In this study, T2D like model was established by inducing insulin resistance through knockdown of the insulin receptor in brain insulin-producing cells using the dilp2-Gal4>UAS-InRRNAi system. This genetic manipulation resulted in significant metabolic dysregulation, including elevated glucose, trehalose, and triacylglyceride levels, along with increased oxidative stress indicators. Additionally, mRNA expression analysis of key insulin signaling components, including insulin receptor substrate 1, dilp2, dilp3, dilp5, and phosphorylated Akt, further validated the model. To further investigate metabolic alterations, Lipid profiling was performed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) in non targeted LC-MS-based metabolomics approach to identify lipid biomarkers associated with T2D. Multivariate statistical analyses, including PCA and PLS-DA, revealed distinct lipid signatures between wild-type and T2D flies. Notably, specific phosphatidylglycerol species PG 34:0, PG 34:4, PA 38:3, PIP 38:1, PIP2 38:6, and LPS 24:0 demonstrated an area under the curve (AUC) of 1, indicating their strong reliability as lipid biomarkers for T2D diagnosis.

The Arabidopsis thaliana nonhost resistance proteins 2A (AtNHR2A) and 2B (AtNHR2B) play crucial roles in plant immunity as the single mutants Atnhr2a and Atnhr2b and the double mutant Atnhr2bAtnhr2a are susceptible to the non-adapted pathogen Pseudomonas syringae pv. tabaci that is unable to infect wild-type Col-0 plants. The localization of fluorescent versions of AtNHR2A and AtNHR2B to compartments of the endomembrane system together with their interaction with secreted proteins suggested a function in endomembrane-mediated secretory processes participating in plant immunity. Comparative apoplastic proteomics analysis between wild type Col-0 and the double mutant Atnhr2bAtnhr2a after treatment P. syringae pv. tabaci, revealed that AtNHR2A and AtNHR2B are indeed required for the secretion of proteins containing N-terminal signal peptides that occurs through the conventional protein secretion pathway. In this work, we leveraged these apoplastic proteomics datasets to identify proteins lacking N-terminal signal peptide and expected to be secreted through unconventional secretion pathway(s). We discovered that AtNHR2A and AtNHR2B are also required for the secretion of proteins through an unconventional secretion pathway that, intriguingly, included proteins previously associated with abiotic stress. These findings led us to define the subcellular dynamics of AtNHR2A and AtNHR2B, and through co-localization analyses and the use of vesicle trafficking inhibitors, we uncovered their trafficking pathways transitioning through Golgi-dependent and Golgi-independent pathways to ultimately reach the central vacuole. Our findings suggest that AtNHR2A and AtNHR2B participate in a multivesicular bodies-vacuole-mediated unconventional secretion pathway that results in the release of proteins involved in plant responses to environmental stresses.

Proteolysis can be completed in a single-step, rapid (5-30 minutes) reaction using hyperthermoacidic archaeal (HTA) proteases. Protocol simplicity and stability of HTA proteases in ambient storage conditions removes many logistical barriers to widespread deployment of proteomic analysis. HTA protease cleavage selectivity is complicated but quantitatively reproducible and generates peptides that negligibly overlap with trypsin. Tryptic and HTA protease peptides emphasize different proteins and provide complementary coverage of amino acid sequence and post-translational modification (PTM) sites. Digestion of a sample's separate aliquot with HTA protease is a minor addition to trypsin-based workflows, but LC-MS analysis of both sets of peptides is not practical for large cohorts. This manuscript evaluates the identifications and reproducibility of LC-MS analysis of tryptic and HTA protease peptide mixtures. Adding HTA protease peptides to 20% increased total protein identifications by 24% on average in neat plasma and identified 216 additional non-artifact modifications compared to conventional trypsin-only bottom-up proteomic analysis. This approach is reproducible and does not increase sample preparation or analysis time. Peptides from each protease present independent opportunities to quantify overlapping proteins and a quantification model was developed in which the protease with the most complete data is selected for each protein while the second protease is used to infer missing values. This cross-protease inference is more accurate than the alternative minimum, mean, or nearest neighbor imputations. Finally, biomarkers discovered through HTA protease peptides are amenable to rapid HTA protease only proteomic workflows thus streamlining translation from discovery to fieldable applications.

Cloudberry (Rubus chamaemorus L.)-derived nanovesicles (NVs) represent a promising but still poorly characterized class of plant-derived vesicles with potential relevance for skin-related applications. Here, we isolated cloudberry fruit-derived NVs and investigated their physicochemical and molecular properties, cellular uptake, cytocompatibility, and functional effects in human dermal fibroblasts (HDF) and HaCaT keratinocytes. Nanoparticle tracking analysis and transmission electron microscopy confirmed a nanosized vesicle preparation with characteristic round morphology, while protein quantification supported reproducible isolation of NV-associated material. In vitro, cloudberry NVs showed concentration-dependent effects on cell viability and proliferation, with lower doses being better tolerated. Labelled NVs were internalized by both HDF and HaCaT cells in a time-dependent manner. Under oxidative stress conditions, cloudberry NVs reduced H2O2-induced senescence-associated {beta}-galactosidase staining in HDFs and exerted cytoprotective effects in both cell lines, alongside measurable cell-free antioxidant activity in the DPPH assay. In scratch wound-healing assays, cloudberry NVs modulated wound closure in a dose-dependent manner, with the lowest tested concentration showing the most favorable response. UHPLC-MS/MS-based proteomics and metabolomics further indicated the presence of diverse secondary metabolites and stress-related protein cargo. Together, these results support the view that cloudberry-derived NVs are biologically active plant nanovesicles with potential utility in skin-related regenerative applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/741293v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@c9094dorg.highwire.dtl.DTLVardef@81a1b5org.highwire.dtl.DTLVardef@9fafe2org.highwire.dtl.DTLVardef@1d421d3_HPS_FORMAT_FIGEXP M_FIG C_FIG

ABSTRACT Background: The esophageal String Test (EST) is emerging as a minimally invasive alternative for assessing disease activity in eosinophilic esophagitis (EoE), yet the molecular composition of its protein content remains unknown. Objective: To comprehensively characterize the esophageal EST proteome, define an EoE-associated luminal protein signature, and evaluate its biological and clinical relevance. Methods: EST samples were obtained from patients with active EoE, healthy controls (C) and patients with gastroesophageal reflux disease (GERD). Label-free proteomic profiling was performed by liquid chromatography-tandem mass spectrometry. Differential protein accumulation, principal component analysis (PCA), pathway annotation, comparison with published esophageal tissue and salivary proteomes, receiver operating characteristic (ROC) analyses and correlations with clinical disease activity were performed. Results: More than 3,000 proteins were identified in esophageal EST samples. Global proteomic profiling clearly separated patients with EoE from both C and GERD, whereas only limited differences were observed between the latter two groups. This enabled the identification of an EoE-associated luminal protein signature comprising inflammatory, epithelial, and tissue remodeling proteins. Comparison with published proteomic datasets indicated that the EST samples a complex esophageal luminal protein microenvironment containing proteins represented in esophageal mucosa and saliva, together with inflammatory and extracellular components. Several individual proteins showed high discriminatory performance in this exploratory cohort for distinguishing EoE from non-EoE subjects, and multiple proteins correlated with eosinophil counts and endoscopic measures of disease activity. Conclusions: This study demonstrates that the EST provides access to a complex esophageal luminal protein microenvironment and establishes a molecular framework for its minimally invasive characterization in EoE. KEYWORDS: eosinophilic esophagitis, esophageal string test, esophageal luminal protein signature