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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

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Pseudotargeted peptidomics approach for identifying species-specific biomarkers in fermented Cordyceps products: A case study on Bailing Capsule.

Bailing Capsule, a fermented Cordyceps product used as an adjunctive treatment for chronic kidney disease and chronic bronchitis, is a crucial substitute for wild Ophiocordyceps. However, its current quality control relies on non-specific small-molecule markers, making it hard to distinguish from other analogous products. In this study, a pseudotargeted peptidomics strategy was developed to discover characteristic peptides for differentiation. Firstly, digested peptides were obtained by trypsin digestion (37 °C, 24 h, enzyme/protein ratio 1: 50) and profiled by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS). Subsequently, a multiple reaction monitoring (MRM) transition list was generated from the Q-TOF data using a "MRM-Ion Pair Finder" tool. These transitions were validated by ultra-high performance liquid chromatography triple-quadrupole mass spectrometry (UPLC-QQQ-MS) with 48 batches of samples from Bailing Capsule and four other analogous products. As a result, a total of 150 characteristic transitions specific to Bailing Capsule were identified, of which 76 peptide sequences were elucidated, and 12 peptide biomarkers were confirmed using synthetic standards. This pseudotargeted approach exhibits broad coverage and good sensitivity. Without requiring prior knowledge of peptide sequence, the transition-driven strategy reduces redundancy and enables focused, transition-based peptide differentiation. Compared to conventional small-molecule biomarkers, this peptide-based approach offers species-specific identification. This study demonstrates that a pseudotargeted peptidomics strategy may aid in the quality control of fermented Cordyceps products.

Cordyceps↗

PubMed2026

Development and validation of a serum peptidomic signature for early detection of asymptomatic ovarian cancer: A multi-center prospective study.

Early detection of asymptomatic ovarian cancer (asym-OC) remains a critical challenge, the failure of which underlies its high mortality. Performing serum peptidomic profiling of 843 participants in the cohort SOCFCP, we distill 1,081 initial features into a 7-marker panel for asym-OC detection via a biology-informed machine-learning (ML)-based feature selection strategy. Three markers significantly revert toward non-OC levels after surgery. Integrating the panel with age, CA125, and HE4, we develop and externally validate (n = 159) a LightGBM model, ProMS+. For early-stage OC detection, ProMS+ shows a specificity of 92.6% at 95.0% sensitivity, outperforming CA125 (44.7%), HE4 (11.2%), and Risk of Ovarian Malignancy Algorithm (ROMA) (24.0%), with an area under the curve (AUC) of 0.993. In a simulated high-risk population (n = 100,000; OC prevalence = 1%), ProMS+ yields a high AUC (0.983) and a higher positive predictive value than CA125, HE4, and Age + CA125 + HE4 combined model (0.201 vs. 0.027, 0.090, and 0.064). ProMS+ offers a promising, non-invasive, and interpretable approach for the early detection of asym-OC.

Humans↗

PubMed2026

Olive leaf protein hydrolysates yield gastro-resistant peptides with antioxidant and anti-inflammatory potential: peptidomics, in vitro validation and molecular docking analyses.

Olive (Olea europaea L.) leaves are an abundant olive-oil by-product and a promising feedstock for sustainable valorisation. An olive leaf protein isolate (OLPI) from olive-leaf powder (OLP) was enzymatically hydrolysed to yield seven hydrolysates (OLPHs). All showed notable antioxidant activity as whole hydrolysate matrices (EC₅₀ = 0.11-0.28 mg mL-1); likely reflecting the combined contribution of released peptides and co-extracted phenolic compounds; the 15-min Alcalase product (OLPH15A) showed high activity with the shortest processing time. Its INFOGEST digest (dOLPH15A) attenuated LPS-induced inflammation in Caco-2 cells, down-regulating pro-inflammatory and up-regulating anti-inflammatory genes. Peptidomics identified 7037 peptides in OLPH15A and 534 in dOLPH15A, from which twenty gastro-resistant sequences were prioritised for in silico analysis. Multi-tool prediction and docking highlighted four peptides, GAAGGIGQPL, QSAYPGTGPL, GGGAGGGDGGIL and LDAQFPGVN, with favourable predicted affinity for the TLR4/MD2 complex, suggesting that they may contribute to the observed immunomodulatory response. These findings position olive leaves as a viable source of protein hydrolysate-based ingredients with antioxidant and anti-inflammatory potential, advancing the valorisation of olive-oil by-products.

Olea↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

PubMed2026

Innovative CRISPR/Cas9-Based Strategy for Allele-Specific HLA Peptidome Analysis Using a Pan-HLA Antibody.

Human leukocyte antigen (HLA) immunopeptidomics is restricted by the limited availability of allele-specific antibodies and by potential artifacts introduced by HLA overexpression systems. To address these challenges, we developed a CRISPR/Cas9-based strategy that selectively deletes undesired classical class I alleles while preserving a single endogenous allele, thereby enabling allele-resolved peptidome profiling with a pan-HLA class I antibody. As a proof of concept, we edited JY cells to eliminate HLA-B∗07:02 and HLA-C∗07:02 while retaining HLA-A∗02:01 (ΔBC clones). Peptide-HLA complexes were immunoprecipitated from WT and ΔBC clones using either the pan-HLA class I antibody W6/32 or the A∗02:01-specific antibody PA2.1, followed by nanoLC-MS/MS and computational HLA assignment. Deletion of HLA-B and HLA-C alleles caused an expected ∼55% reduction in total class I surface expression. Despite this, W6/32 immunoprecipitation from ΔBC clones recovered a comparable peptide yield to PA2.1 in WT cells. Binding predictions showed that most peptides identified in ΔBC clones using W6/32 were assigned to HLA-A∗02:01, with near-complete loss of HLA-B∗07:02- and HLA-C∗07:02-derived peptides. Sequence logo analysis confirmed the canonical A∗02:01 motif across conditions. The ΔBC W6/32 immunopeptidome exhibited a high degree of overlap (∼88%) with the WT PA2.1 repertoire, supporting the specificity and fidelity of the approach. These findings establish CRISPR-based editing of HLA alleles as a viable strategy for allele-specific immunopeptidome analysis using pan-HLA antibodies, supporting its potential application beyond this proof-of-concept system, reducing reliance on allele-specific reagents and facilitating the study of underrepresented HLA alleles.

Humans↗

PubMed2026

Immunopeptidomics in gliomas: Decoding antigen presentation for precision immunotherapy.

Gliomas and particularly glioblastomas, represent the most aggressive and treatment-resistant brain tumours. Current standard treatments, including surgical resection, radiotherapy and chemotherapy, offer only limited long-term survival benefits. The highly immunosuppressive tumour microenvironment that characterizes gliomas enables immune evasion and limits the effectiveness of anti-tumour immune response, indicating the urgent need for identification of tumour antigens with clinical relevance to improve current immunotherapeutic strategies and enhance glioma immunogenicity. Immunopeptidomics, a mass spectrometry-based identification of peptides presented by HLA molecules, is a growing field of research for understanding the immunosurveillance of gliomas. By enabling the direct identification of naturally presented HLA-bound peptides from tumour tissue for T cell recognition, immunopeptidomics provide valuable insights into tumour antigen presentation and immune targeting. This review highlights the emerging role of immunopeptidomics in gliomas, covering the mechanisms of antigen processing and presentation by HLA class I and II molecules, the identification of glioma-associated antigens, the development of personalised peptide vaccines and the discovery of new targets for T cell-based immunotherapies. The potential of plasma-derived soluble HLA (sHLA) peptidomes as minimally invasive liquid-biopsy biomarkers is further discussed for disease monitoring and response to treatment. Overall, immunopeptidomics are foreseen as a powerful tool for the discovery of new tumour antigens leading to the development of more effective personalised glioma immunotherapies.

Humans↗

PubMed2026

Estimating protein isoform abundances with [Formula: see text].

A single gene can encode multiple versions of a protein, dubbed isoforms, with varying functionality. Cellular control of isoform abundances is critical for multiple aspects of biology and is only partially regulated by transcript levels. While long-read sequencing facilitates transcript quantification, quantifying the resulting protein isoforms on a large scale is a major challenge, complicating biological interpretation of transcript alterations. Standard "bottom up" mass spectrometry can assess only short portions of isoforms called peptides, and these peptides often map onto more than one isoform. We introduce [Formula: see text] (Protein isoform Abundance Quantification), a Bayesian method that leverages multiomic information from the peptidome and transcriptome to provide accurate estimates of isoform abundance even when peptide mapping is ambiguous. [Formula: see text] offers several advantages over existing methods in a unified framework. It provides uncertainty quantification, integrates multiomic information for improved accuracy, and provides a rigorous framework for hypothesis testing. Extensive simulations show that [Formula: see text] consistently outperforms competing methods in detecting differentially abundant protein isoforms and estimating their abundances. We use [Formula: see text] to investigate differences in isoform abundance levels between people with schizophrenia and control subjects, confirming a long-held hypothesis that levels of the C4A isoform of Complement Component 4 are increased in schizophrenia while C4B is not. These results demonstrate that [Formula: see text] can identify significant variations in isoform abundance levels not previously possible.

Protein Isoforms↗

PubMed2026

Immunopeptidomics-driven MHC class II peptide-binding motif discovery for 2 common canine DR alleles.

Despite the central role of major histocompatibility complex (MHC) class II in adaptive immunity, peptide-binding motifs have yet to be characterized for any canine MHC class II allele. Here, we report the first immunopeptidomics-derived binding motifs for DLA-DRB1*015:01 (DLA-DR15) and DLA-DRB1*012:01 (DLA-DR12), 2 alleles overrepresented in breeds predisposed to immune-mediated diseases. Because dogs co-express DLA-DR and DLA-DQ, the MHC class II Ab clone YKIX334.2 was validated to be DLA-DR-specific, enabling allele-selective immunoaffinity purification of DLA-DR molecules from homozygous DLA-DR15 and DLA-DR12 donor spleens. Mass spectrometry and GibbsCluster motif deconvolution of 838 DLA-DR15-associated and 644 DLA-DR12-associated peptides eluted from their respective peptide-binding grooves revealed distinct allele-specific binding motifs, with characterization of anchor residue preferences, peptide-length distributions, cross-species comparisons with human and murine MHC class II motifs, and source protein composition of the eluted self-peptidome. To evaluate the translational utility of these motifs, recombinant DLA-DR15 and DLA-DR12 molecules were used to screen rabies virus glycoprotein and nucleoprotein peptide libraries via fluorescence-based peptide competition assays, identifying high-affinity candidate binders for both alleles. Spearman rank correlation between immunopeptidomics-derived position-specific scoring matrix scores and peptide competition assay rankings demonstrated modest associations, consistent with these approaches capturing complementary dimensions of peptide-MHC class II interaction. Ultimately, these findings establish what we believe is the first allele-specific peptide-binding motif framework for canine MHC class II, providing a foundation for DLA-allele-informed CD4+ T-cell epitope discovery studies and Ag-specific immune response characterization in the dog.

Animals↗

PubMed2024

Multiple urinary peptides are associated with hypertension: a link to molecular pathophysiology.

OBJECTIVES: Hypertension is a common condition worldwide; however, its underlying mechanisms remain largely unknown. This study aimed to identify urinary peptides associated with hypertension to further explore the relevant molecular pathophysiology. METHODS: Peptidome data from 2876 individuals without end-organ damage were retrieved from the Human Urinary Proteome Database, belonging to general population (discovery) or type 2 diabetic (validation) cohorts. Participants were divided based on systolic blood pressure (SBP) and diastolic BP (DBP) into hypertensive (SBP ≥140 mmHg and/or DBP ≥90 mmHg) and normotensive (SBP <120 mmHg and DBP <80 mmHg, without antihypertensive treatment) groups. Differences in peptide abundance between the two groups were confirmed using an external cohort ( n  = 420) of participants without end-organ damage, matched for age, BMI, eGFR, sex, and the presence of diabetes. Furthermore, the association of the peptides with BP as a continuous variable was investigated. The findings were compared with peptide biomarkers of chronic diseases and bioinformatic analyses were conducted to highlight the underlying molecular mechanisms. RESULTS: Between hypertensive and normotensive individuals, 96 (mostly COL1A1 and COL3A1) peptides were found to be significantly different in both the discovery (adjusted) and validation (nominal significance) cohorts, with consistent regulation. Of these, 83 were consistently regulated in the matched cohort. A weak, yet significant, association between their abundance and standardized BP was also observed. CONCLUSION: Hypertension is associated with an altered urinary peptide profile with evident differential regulation of collagen-derived peptides. Peptides related to vascular calcification and sodium regulation were also affected. Whether these modifications reflect the pathophysiology of hypertension and/or early subclinical organ damage requires further investigation.

Humans↗

PubMed2019

Distinct types of short open reading frames are translated in plant cells.

Genomes contain millions of short (<100 codons) open reading frames (sORFs), which are usually dismissed during gene annotation. Nevertheless, peptides encoded by such sORFs can play important biological roles, and their impact on cellular processes has long been underestimated. Here, we analyzed approximately 70,000 transcribed sORFs in the model plant Physcomitrella patens (moss). Several distinct classes of sORFs that differ in terms of their position on transcripts and the level of evolutionary conservation are present in the moss genome. Over 5000 sORFs were conserved in at least one of 10 plant species examined. Mass spectrometry analysis of proteomic and peptidomic data sets suggested that tens of sORFs located on distinct parts of mRNAs and long noncoding RNAs (lncRNAs) are translated, including conserved sORFs. Translational analysis of the sORFs and main ORFs at a single locus suggested the existence of genes that code for multiple proteins and peptides with tissue-specific expression. Functional analysis of four lncRNA-encoded peptides showed that sORFs-encoded peptides are involved in regulation of growth and differentiation in moss. Knocking out lncRNA-encoded peptides resulted in a decrease of moss growth. In contrast, the overexpression of these peptides resulted in a diverse range of phenotypic effects. Our results thus open new avenues for discovering novel, biologically active peptides in the plant kingdom.

Bryopsida↗

PubMed2024

Innovations Toward Immunopeptidomics.

Over the past 30 years, immunopeptidomics has grown alongside improvements in mass spectrometry technology, genomics, transcriptomics, T cell receptor sequencing, and immunological assays to identify and characterize the targets of activated T cells. Together, multiple research groups with expertise in immunology, biochemistry, chemistry, and peptide mass spectrometry have come together to enable the isolation and sequence identification of endogenous major histocompatibility complex (MHC)-bound peptides. The idea to apply highly sensitive mass spectrometry techniques to study the landscape of peptide antigens presented by cell surface MHCs was innovative and continues to be successfully used and improved upon to deepen our understanding of how peptide antigens are processed and presented to T cells. Multiple research groups were involved in this bringing immunopeptidomics to the forefront of translational research, and we will highlight the contributions of one of the earliest developers, Professor Donald F. Hunt, and his research group at the University of Virginia. The Hunt laboratory applied cutting edge mass spectroscopy-based immunopeptidomics to study cancer, autoimmunity, transplant rejection, and infectious diseases. Across these diverse research areas, the Hunt laboratory and collaborators would characterize previously unknown MHC peptide-binding motifs and identify immunologically active antigens using ultra sensitive mass spectrometry techniques. Amazingly, many of the MHC-bound peptide antigens discovered in collaborations with the Hunt laboratory were sequenced by mass spectrometry before the completion of the human genome using manual de novo sequencing. In this perspective article, we will chronicle the work of the Hunt laboratory and their many collaborators that would be a major part of the foundation for mass spectrometry-based immunopeptidomics and its application to immunology research.

Animals↗

PubMed2026

Upregulation of Endogenous Serine Proteinases by SVMPs Contributes to Muscle Damage Induced by Bothrops atrox Venom.

In Brazil, approximately 25,000 snakebites occur annually, with Bothrops atrox responsible for most cases. Local morbidity is high, driven primarily by snake venom metalloproteases (SVMPs). The major SVMPs in B. atrox venom, Atroxlysin-Ia (ATXL) and Batroxrhagin (BATX), efficiently hydrolyze extracellular matrix proteins, inducing rapid hemorrhage and dermonecrosis. Thus, we characterized the composition of the exudate produced after SVMPs injection into the mice gastrocnemius muscle using proteomics. Muscle damage was evaluated by histological analysis. The composition of the exudate was analyzed by mass spectrometry. The SVMPs induced disorganization of muscle fibers and inflammatory cell migration. However, ATXL-induced a significantly higher neutrophil influx compared to BATX, likely triggered by an increase in CXCL16, suggesting a superior inflammatory capacity. In summary, despite being metalloproteases, these toxins exhibit distinct pathological profiles: ATXL is predominantly inflammatory, while BATX is more hemorrhagic. Interestingly, while endogenous serine proteinase levels were similar in both exudates, BATX showed significantly higher levels of proteinase inhibitors. Furthermore, identification of peptide bond cleavage sites revealed a pattern consistent with trypsin-like serine proteinases. These findings suggest that SVMPs not only damage tissue directly but also associate with the activation of host endogenous proteinases, which may contribute to the complex pathology of B. atrox envenomation, although direct causation remains to be established.

Animals↗