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PubMed2026

Transpulmonary proteomic gradient analysis in women with pulmonary arterial hypertension associated with systemic sclerosis.

This study investigated proteomic alterations in the pulmonary circulation of patients with pulmonary arterial hypertension associated with systemic sclerosis (PAH-SSc) by analyzing the transpulmonary protein gradient and comparing the proteomic profiles with systemic sclerosis (SSc) without PAH. Twenty women were included (10 PAH-SSc, 64.6 ± 10.8 years; 10 SSc, 62.8 ± 11.5 years). The transpulmonary gradient was defined as the difference in biomarker concentrations between wedge-position and pulmonary artery blood samples. Peptides were analysed using liquid chromatography-mass spectrometry, and differentially abundant proteins were identified with Proteome Discoverer. Protein-protein interaction networks were generated with STRING and visualized in Cytoscape. A total of 270 proteins were detected, with no significant transpulmonary gradient alterations. However, patients with PAH-SSc showed distinct proteomic profiles compared to SSc. Multivariate analysis identified 48 differentially abundant proteins in pulmonary artery plasma, with 15 overrepresented and 33 downregulated in PAH-SSc. Among these, the downregulation of transforming growth factor-beta-induced protein ig-h3 (TGFβI/ig-h3) points to a potential involvement of the TGF-β-related extracellular matrix remodelling pathway in PAH-SSc. However, further validation in larger and independent cohorts is required before its relevance as a biomarker or therapeutic target can be established. In conclusion, while no transpulmonary proteomic gradient was observed, the proteomic profiles of PAH-SSc and SSc were different. The profile in PAH-SSc was characterized by differences in immune response, lipid metabolism, and hemostatic proteins. SIGNIFICANCE: This study offers the first proteomic characterization of the transpulmonary gradient in PAH-SSc and SSc. Although no differences in the gradient were found, the pulmonary artery plasma proteome of PAH-SSc patients showed a distinct pattern compared to SSc. Several proteins associated with immune function, haemostasis, and cellular processes were altered, which may indicate specific pathophysiological features of PAH-SSc or suggest how lung dysfunction develops in SSc. Targeting dysregulated proteins like TGFβI/ig-h3 or addressing immune-coagulation imbalances may support future research studies. Overall, these findings refine the molecular profile of PAH-SSc and provide a basis for future large-scale studies aimed at clarifying disease mechanisms and identifying clinically relevant molecular signatures.

Humans↗

PubMed2026

ECLIPSE: exploring the dark proteome of ESKAPE pathogens through the sequence similarity network of the Protein Universe Atlas.

MOTIVATION: The accelerating crisis of antimicrobial resistance among the critical so-called ESKAPE pathogens demands the urgent identification of novel molecular targets. However, a substantial fraction of ESKAPE proteomes remains functionally uncharacterized, with many genes annotated as encoding hypothetical proteins. These protein sequences often lack significant similarity to known protein families when conventional homology-based annotation methods are used and thus remain "dark". This limits our ability to explore their roles in pathogenicity, and it is thus crucial to bridge this substantial gap in pathogen biology by developing new strategies to illuminate these "dark" regions of the ESKAPE pan-proteome. RESULTS: We introduce ECLIPSE (ESKAPE Connectome Linkage and Inference for Proteome Sequence Exploration), a network-based computational framework that systematically identifies and prioritizes functionally dark protein families in ESKAPE pan-proteomes. ECLIPSE embeds target ESKAPE pathogen proteomes within the global sequence similarity network of the Protein Universe Atlas. It detects connected components composed entirely of unannotated proteins, called the "dark proteome." As a case study, we applied ECLIPSE to a pan-proteome of 3 460 657 protein sequences from 635 strains of Pseudomonas aeruginosa (PA). ECLIPSE identified 120 985 proteins (4%) residing in completely dark connected components. Furthermore, we have performed a taxonomic diversity analysis using normalized Shannon indices to characterize each dark component by its enrichment in ESKAPE pathogens. The analysis utilized the evenness (E) value (see Methods 2.1), which distinguishes Pseudomonas-specific (target-specific) from ESKAPE-enriched dark components. We then developed the Dark Proteome Prioritization Score (DPPS), a composite multidimensional scoring framework (see Methods 2.5). It ranks these dark components by biological relevance across four orthogonal axes: (i) functional darkness, (ii) P. aeruginosa proportion in the Atlas, (iii) AMR-clade taxonomic restriction, and (iv) conservation across the 635 P. aeruginosa strains. This framework outputs a robust four-tier scoring system; the prioritized Tier I components were validated by weight sensitivity analysis and remained stable across 500 Monte Carlo weight perturbations. Structural characterization of one of the top-ranked ESKAPE-enriched dark components revealed that it belongs to the beta-barrel fold DUF1302 (PF06980) family, for which no experimentally solved three-dimensional structure exists in the PDB. The genomic context analysis indicates that it is co-localized with a LuxR-type transcriptional regulator. Collectively, ECLIPSE identifies evolutionarily conserved, structurally defined, and functionally dark proteins enriched across ESKAPE pathogens; these dark proteins can further be utilized as alternative antimicrobial targets for experimental characterization. AVAILABILITY AND IMPLEMENTATION: The source code and dataset are available for free at: Github: https://github.com/surabhilata/ECLIPSE.git, Zenodo: DOI: 10.5281/zenodo.21064323.

Proteome↗

PubMed2026

Proteomic Signatures Related to Physical Activity Are Associated with Risks of Future Disease.

PURPOSE: Physical activity (PA) can lower the risk of developing chronic diseases. However, few studies have examined the proteomic signatures linked to PA, and the role of these signatures in the connection between PA levels and future disease risk remains unclear. This study aimed to investigate whether proteomic signatures indicative of PA are associated with the risk of developing common chronic diseases and to explore their role as statistical links in the relationship between PA levels and disease development. METHODS: We used data from a subcohort of UK Biobank participants. PA intensity data were collected from accelerometers worn by each participant. Plasma proteomics results were obtained through Olink analysis. The risks of developing each primary chronic disease were evaluated for types of PA and their associated proteomic signatures, adjusting for age, sex, ethnicity, socioeconomic status, lifestyle factors, and key measurement time-lag covariates. RESULTS: Based on the UK Biobank, we identified significant differences among the proteomic signatures of accelerometer-measured light PA, moderate-to-vigorous PA, and total PA. The main enriched pathways of these proteomic signatures included cell adhesion, cell migration, and immune response. Higher levels of accelerometer-measured PA and their associated proteomic signatures correlated with a lower risk of developing cardiometabolic disorders, cancers, psychological or neurological disorders, and respiratory diseases. CONCLUSIONS: Our findings show that PA and PA-related proteomic signatures are statistically associated with lower risks of chronic diseases. Further analyses identified proteins that were correlated with both PA and disease risk. These results need to be confirmed through longitudinal studies involving diverse populations.

Humans↗

PubMed2026

A Robust, Self-Digestion-Resistant LysN with Superior Activity and Cleavage Fidelity for Advanced Proteomic Workflows.

LysN is a valuable protease in proteomics because it cleaves peptide bonds N-terminal to lysine, generating peptides with physicochemical properties complementary to those produced by LysC and trypsin. However, the broader adoption of LysN in proteomic workflows has been limited by the lack of commercially available enzymes that combine high activity, low missed-cleavage rates, and sufficient stability under practical sample-processing conditions. Here, we report the recombinant production and proteomic characterization of a self-digestion-resistant and highly active LysN from Shewanella loihica (SL-LysN). Using terminomics, we mapped the mature N- and C-termini of the enzyme and established the primary structure of the active protease. We further developed a high-density fermentation, refolding, and purification workflow to obtain highly purified recombinant SL-LysN. Biochemical and proteomic benchmarking showed that SL-LysN displayed 3.3-fold higher specific activity than commercial LysN and reduced missed cleavages by approximately 80%. Notably, SL-LysN retained high activity in the presence of 8 M urea or 1% SDS and showed strong resistance to autolysis, indicating exceptional robustness for proteomic sample preparation. In complex mammalian proteome digests, SL-LysN achieved >95% cleavage specificity and a missed-cleavage rate of only 5.9%. These features address a long-standing bottleneck in N-terminal proteolysis and establish SL-LysN as a high-performance enzymatic tool for advanced proteomic workflows, including deep protein sequencing, quantitative proteomics, terminomics, de novo sequencing and analyses requiring efficient digestion under denaturing conditions.

Shewanella↗

PubMed2024

Multilevel Proteomics Reveals Epigenetic Signatures in BCG-Mediated Macrophage Activation.

The bacillus Calmette-Guérin BCG vaccine (Mycobacterium bovis) is primarily used to prevent tuberculosis (TB) infections but has wide-ranging immunogenic effects. One of its most notable properties is its ability to induce trained immunity, a memory-like response in innate immune cells such as macrophages. Through targeted analyses of well-established histone marks, prior research has shown that these changes are generated through epigenetic modification. Mass spectrometry-based proteomic approaches provide a way to globally profile various aspects of the proteome, providing data to further identify unexplored mechanisms of BCG-mediated immunomodulation. Here we use multi-level proteomics (total, histone, and phospho to identify networks and potential mechanisms that mediate BCG-induced immunomodulation in macrophages. Histone-focused proteomics and total proteomics were performed at the University of Cape Town (data available via ProteomeXchange with identifier PXD051187), while phosphoproteomics data was retrieved from the ProteomeXchange Repository (identifier PXD013171). We identify several epigenetic mechanisms that may drive BCG-induced training phenotypes. Evidence across the proteomics and histone-focused proteomics data set pair 6 epigenetic effectors (NuA4, NuRD, NSL, Sin3A, SIRT2, SIRT6) and their substrates.

Epigenesis, Genetic↗

PubMed2026

Blood Plasma Analysis in Ovarian Cancer Patients Using an AFM/MS Approach: Effect of Sample Dilution on Proteome Depth.

Early detection of ovarian cancer remains challenging because of the lack of sensitive and reproducible blood-based biomarkers. A major challenge in plasma proteomics is the extremely wide dynamic range of protein concentrations, which prevents simultaneous detection of both high- and low abundance proteins and limits the identification of disease-associated signals. In this study, we applied a combined atomic force microscopy and mass spectrometry (AFM/MS) approach to investigate how sample dilution affects plasma proteome coverage and the detection of differences between healthy donors and patients with stage I and stage III ovarian cancer. Plasma samples were analyzed at two dilution levels (1:100 and 1:10,000). At 1:100 dilution, a total of 235 proteins were identified across all samples, representing the union of all replicates and groups. The reproducible CORE proteome comprised 169 proteins in the Healthy group, 183 in the Stage I group, and 193 in the Stage III group. Differential analysis revealed distinct, non-overlapping protein sets at each dilution level. At 1:100 dilution, most altered proteins were decreased in patients and corresponded to major plasma components, including complement proteins and protease inhibitors. At 1:10,000 dilution, most altered proteins were increased and were predominantly immunoglobulin-related proteins, along with complement regulatory components. These findings show that sample dilution determines which fraction of the plasma proteome is observable. Here, proteome depth refers to the total number of non-redundant proteins accessible within the analytical workflow. When CORE sets from all groups were combined, 216 proteins were identified at 1:100 and 149 at 1:10,000, with 133 shared between the two dilution conditions. The higher dilution contributed 16 additional CORE proteins not detected in the 1:100 CORE union, increasing the combined CORE set to 232 proteins. Thus, higher dilution alone did not increase proteome depth, but provided complementary protein identifications that increased cumulative proteome depth when both dilution conditions were considered together. This effect reflects dilution-dependent selectivity in the composition of the detectable protein subset.

Humans↗

PubMed2024

Single-tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles.

The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry (MS)-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single-tissue MS-based proteomic analysis in small organisms and in its future utility.

Animals↗

PubMed2025

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Single-Cell Analysis↗

PubMed2026

LCM-Enriched Proteomic Characterization of Antibody-Mediated Glomerular Damage and Complement Activation in Pre-Clinical Models.

Biologics, lipid nanoparticles, and other therapeutic modalities can result in adverse events, often detected as lesions during preclinical pathology assessments. Characterization of these lesions provides valuable information during drug development to contextualize mechanisms of injury and assess species translatability. Here, we investigated the utility of a laser capture microdissection (LCM)-enriched mass spectrometry proteomics approach to analyze two well-characterized preclinical models of regional (glomerular) injury: Passive Heyman Nephritis in rats and bovine gamma globulin-induced glomerular injury in nonhuman primates (NHPs). Using LCM-enriched proteomics, glomeruli were isolated from formalin-fixed paraffin-embedded kidney tissue in the rat model, enabling identification of 4,661 proteins and quantification of 3,410. Proteinuria measurements were compared with digital pathology metrics of glomerular morphology and proteomics results, with all modalities yielding concordant evidence of glomerular injury and proteomics confirming the role of complement activation. The same LCM- enriched proteomics workflow was applied to an NHP model of induced glomerular damage, identifying 4,623 proteins, quantifying 3,000, and confirming qualitative concordance with established features of complement-mediated glomerular injury. Together, these findings illustrate the applicability of LCM-enriched proteomics for region-specific characterization of antibody-mediated tissue injury and support its use as a hypothesis-generating platform in translational toxicologic pathology.

Animals↗

PubMed2025

T cell population size control by coronin 1 uncovered: from a spot identified by two-dimensional gel electrophoresis to quantitative proteomics.

INTRODUCTION: Recent work identified members of the evolutionarily conserved coronin protein family as key regulators of cell population size. This work originated ~25 years ago through the identification, by two-dimensional gel electrophoresis, of coronin 1 as a host protein involved in the virulence of Mycobacterium tuberculosis. We here describe the journey from a spot on a 2D gel to the recent realization that coronin proteins represent key controllers of eukaryotic cell population sizes, using ever more sophisticated proteomic techniques. AREAS COVERED: We discuss the value of 'old school' proteomics using relatively simple and cost-effective technologies that allowed to gain insights into subcellular proteomes and describe how label-free quantitative (phospho)proteomics using mass spectrometry allowed to disentangle the role for coronin 1 in eukaryotic cell population size control. Finally, we mention potential implications of coronin-mediated cell population size control for health and disease. EXPERT OPINION: Proteome analysis has been revolutionized by the advent of modern-day mass spectrometers and is indispensable for a better understanding of biology. Here, we discuss how careful dissection of physio-pathological processes by a combination of proteomics, genomics, biochemistry and cell biology may allow to zoom in on the unexplored, thereby possibly tackling hitherto unasked questions and defining novel mechanisms.

Proteomics↗

PubMed2026

Proteomics-based approaches to neutrophil biology.

INTRODUCTION: Neutrophils are central effectors of innate immunity and key contributors to inflammation, host defense, and tissue injury across a wide range of physiological and pathological contexts. Due to their short lifespan, rapid activation, and extensive post-translational regulation, comprehensive molecular characterization of neutrophil function requires approaches that go beyond transcriptomics or marker-based analyses. AREAS COVERED: This review summarizes how proteomic technologies have advanced the understanding of neutrophil biology by enabling unbiased, system-wide profiling of protein abundance, subcellular organization, post-translational modifications, and functional heterogeneity. We discuss global and subcellular proteomics, PTM-centric analyses, and emerging low-input and single-cell proteomic strategies, highlighting recent studies of infection, cancer, metabolic disorders, aging, autoimmune disease, and inflammation. The literature covered includes current large-scale quantitative proteomics, targeted PTMs, and integrative multi-omics studies in both human samples and relevant experimental models. EXPERT OPINION: Proteomics has established neutrophils as highly plastic and context-dependent cells whose functions are governed by coordinated remodeling of signaling, metabolism, and effector pathways. Future progress will depend on expanding neutrophil-specific PTM maps, improving low-input workflows, and integrating single-cell and spatial proteomics. Together, these advances are expected to redefine neutrophil functional states and accelerate translation toward clinically meaningful biomarkers and therapeutic strategies.

Humans↗

PubMed2026

Proteome-level evidence that tebuconazole, both alone and in interaction with thiacloprid, affects epigenetic events in bumblebee heads.

Tebuconazole, a widely used ergosterol biosynthesis-inhibiting fungicide, can affect nontargets, especially when combined with insecticides. We employed label-free quantitative proteomics to investigate the effects of long-term exposure to sublethal concentrations (100 μg/L) of tebuconazole, either by itself or alongside the neonicotinoid thiacloprid (100 μg/L), on the heads of Bombus terrestris workers. A Bayesian factor power analysis revealed that the experiment produced conclusive proteomic results. Tebuconazole treatment revealed eleven differentially abundant proteins, which increased elevenfold with thiacloprid. The proteins that changed in the same direction in both treatments suggest the occurrence of epigenetic events because they are involved in histone trimethylation (H3K4me3), pre-mRNA processing, and folate (vitamin B9) metabolism. Following co-exposure, the abundance of histone H2A.V and its associated proteins was affected. Two important detoxification-related proteins, CYP6BE1 and CYP6AQ1 (honey bee homologs), were identified, as well as proteins that suggest hormonal and neurotoxic effects. Overall, this study suggests that tebuconazole affects key epigenetic processes in bumblebee heads at the proteome level, though this was not confirmed at the biological level or through orthogonal methods. The tested chemicals were previously found to affect trimethylations, but not H3K4me3. We suggest analyzing the different trimethylations, their interplay, and associated hallmarks, such as folate levels. SIGNIFICANCE: The effects of pesticides and their combinations on organisms can be unexpected until they are examined using modern, complex methods. High-throughput proteomics can provide data on important biochemical processes affected by pesticides, offering a different perspective to that at the expression level. Despite their low acute toxicity, a group of fungicides that inhibit (ergo)sterol biosynthesis (EBI or SBI) are considered dangerous to pollinators, including bumblebees. This is due to the increasing toxicity of insecticides through the inhibition of cytochrome P450 detoxification enzymes. We found that tebuconazole had a similar effect on epigenetic events when used alone or in combination with the insecticide thiacloprid. Key proteins suggest that H3K4 histone trimethylation (H3K4me3) was impacted. To our knowledge, this expands the existing evidence suggesting that tebuconazole/triazole fungicides affect histone trimethylation H3K27me3. Since literature shows that thiacloprid affects H3K9me3, it is possible that thiacloprid and tebuconazole interact in these epigenetic events that affect each other. Overall, our results suggest that tebuconazole affects proteins involved in histone trimethylation, pre-mRNA processing, and folate metabolism. These are all hallmarks of epigenetic processes and were further extended by the co-exposure of tebuconazole and thiacloprid to more differently abundant proteins. Additionally, the results provide data on cytochrome P450s of the CYP6 family, which act as detoxifying proteins, as well as proteins that indicate hormonal and neurotoxic effects in bumblebee heads. Finally, the results of the Bayesian power analysis confirmed the meaningfulness of the proteomic data analyzed in this study. If the new findings obtained at the proteome level are verified by different methods, the full extent of the side effects of tebuconazole can be revealed.

Animals↗

PubMed2026

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25 years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine↗

PubMed2024

MACSPI enables tissue-selective proteomic and interactomic analyses in multicellular organisms.

Multicellular organisms are composed of many tissue types that have distinct morphologies and functions, which are largely driven by specialized proteomes and interactomes. To define the proteome and interactome of a specific type of tissue in an intact animal, we developed a localized proteomics approach called Methionine Analog-based Cell-Specific Proteomics and Interactomics (MACSPI). This method uses the tissue-specific expression of an engineered methionyl-tRNA synthetase to label proteins with a bifunctional amino acid 2-amino-5-diazirinylnonynoic acid in selected cells. We applied MACSPI in Caenorhabditis elegans, a model multicellular organism, to selectively label, capture, and profile the proteomes of the body wall muscle and the nervous system, which led to the identification of tissue-specific proteins. Using the photo-cross-linker, we successfully profiled HSP90 interactors in muscles and neurons and identified tissue-specific interactors and stress-related interactors. Our study demonstrates that MACSPI can be used to profile tissue-specific proteomes and interactomes in intact multicellular organisms.

Animals↗

PubMed2026

Proteomic analysis identifies pathways related to immune dysregulation in patients with hematologic malignancies after COVID-19 infection.

Patients with hematologic malignancies (HMs) are particularly vulnerable to coronavirus disease 2019 (COVID-19) because of underlying immune dysfunction and treatment-related immunosuppression. However, proteomic features associated with different clinical trajectories in this population remain insufficiently characterized. We performed serum proteomic analysis in 40 HM patients with COVID-19 and 15 healthy controls. Compared with controls, HM patients showed impaired immune-related responses during the acute phase of COVID-19. Acute-phase proteomic patterns differed across outcome groups; however, because outcome groups were closely intertwined with initial COVID-19 severity, ICU admission, and systemic illness, and because multivariable adjustment was not performed due to the limited sample size, these patterns should be interpreted as severity- and outcome-associated profiles rather than independent trajectory-specific markers. Fatal cases showed evidence of dysregulated immune activation, whereas patients later classified as having long COVID exhibited broader suppression of immune-related pathways. In addition to immune alterations, pathways related to platelet activation and cardiac-related dysfunction were associated with adverse clinical trajectories. Enzyme-linked immunosorbent assay validation supported the association of selected proteins with outcome groups during acute infection. These findings provide a proteomic overview of COVID-19 in HM patients and offer a basis for future mechanistic studies and larger external validation cohorts.IMPORTANCEPatients with hematologic malignancies are highly vulnerable to severe coronavirus disease 2019 (COVID-19), acute death, and long COVID due to preexisting immune dysfunction. However, the proteomic signatures linked to adverse clinical trajectories remain poorly understood. Our serum proteomic study identifies distinct acute-phase immune profiles associated with different outcomes: broad immune suppression characterizes long COVID, while dysregulated immune activation is associated with fatal cases. Platelet activation and cardiac-related pathways are also linked to poor outcomes. These findings provide key molecular insights for this high-risk population, supporting future biomarker development, risk stratification, and targeted clinical management.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT05683353.

Humans↗

PubMed2026

Elucidating the In Vitro Adverse Effect of Functionalized Single-Walled Carbon Nanotubes Against Breast Cancer Cells at the Proteomics Level.

The tremendous therapeutic potential of carbon-based nanomaterials (CNMs) has been limited by inconsistent data regarding the nanotoxicity assessment. Although a bulk of studies have been performed to assess the in vitro cytotoxicity mechanism of CNMs, the exact factors responsible for the cytotoxicity of CNMs have not been fully understood. With the rapid advancement of mass spectrometry technologies, proteomics has emerged as a powerful strategy for systematically investigating the molecular and cellular mechanisms underlying toxicity induced by nanomaterials. This study examined the in vitro cytotoxicity of single-walled carbon nanotubes (SWCNTs) in human MCF-7 breast cancer cells by conducting a comparative proteome-level analysis using mass spectrometry. Initially, the characterized SWCNTs were incubated with MCF-7 cells for 3, 6, and 24 h. Proteins were subsequently extracted from each treatment group and subjected to nano-liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. The relative abundance of the identified proteins was determined by comparison with the control group, and differential expression patterns, including upregulated and downregulated proteins, were assessed. A total of 3482 unique protein groups were identified across all exposure periods. Among these, 3466 protein groups were detected following 3 h of exposure, 3469 following 6 h of exposure, and 3480 following 24 h of exposure. Compared with the control group, the identified differentially expressed proteins exhibited fold changes ranging from 2-fold to 20-fold across the incubation periods. In total, 70 proteins were found to be significantly regulated following SWCNT exposure. Of the differentially expressed proteins, 45 were significantly upregulated, whereas 25 were significantly downregulated. Visualization of these regulations over time was shown in a heatmap of log2-transformed fold-change values to explore time-specific proteomic alterations. Functional enrichment analysis of these proteins also showed that the regulated proteins were significantly associated with Reactome pathways, including ER-to-Golgi anterograde transport, Golgi-to-ER retrograde transport, COPI-mediated vesicle trafficking, regulation of insulin-like growth factor transport and uptake by insulin-like growth factor-binding proteins, protein metabolism, and posttranslational protein modification. Furthermore, a systematic comparison of previous studies within the present findings was provided to situate our study within the broader context of understanding CNT-induced cellular toxicity. Collectively, these findings provided an important proteomic evidence of the adverse effects of SWCNTs on MCF-7 cells. Furthermore, this study showed a comprehensive proteomic landscape of cellular responses to SWCNT exposure, contributing to a better understanding of the molecular mechanisms underlying SWCNT-induced cytotoxicity and bridging the gap between protein regulation and the resulting cellular responses. In this study, we characterized the proteomic landscape of MCF-7 cells following SWCNT exposure, revealing molecular mechanisms associated with cellular responses and cytotoxicity. The identified differentially expressed proteins established a link between altered protein regulation and SWCNT-induced cellular effects. Moreover, these proteins need to be further validated in different cell models and would potentially represent promising candidates for the identification of novel molecular targets involved in SWCNT-induced cytotoxicity.

MCF‐7 cells↗

PubMed2026

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics↗

PubMed2026

Canine Tear Proteomics: A New Frontier in Veterinary Ophthalmology.

Canine tear proteomics is an emerging field with significant potential for advancing both veterinary ophthalmology and comparative biomedical research. Tears are a readily accessible, non-invasive biofluid that contain a mixture of proteins involved in ocular surface protection, immune defense, and intercellular signaling. In dogs, tear proteomics studies have revealed biomarkers associated with various ocular and non-ocular diseases including keratoconjunctivitis sicca (KCS), glaucoma, neoplasia, and diabetes mellitus. This review compiles all previous studies conducted on the comprehensive canine tear proteome and highlights some of the key tear proteomic studies in human biomedical research. Tear film composition, study design, technological advancements, and select tear proteins are discussed along with key protein alterations and their use as potential biomarkers of disease. Fundamental challenges, clinical implications, and future directions of this rapidly growing field are discussed in detail. As proteomic technology and analytical techniques continue to evolve, canine tear proteomics will become a valuable tool for the veterinary ophthalmologist, enabling the early identification and diagnosis of ocular disease as well as providing a means for monitoring treatment outcomes, disease progression, and overall prognosis for the canine patient.

Animals↗