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PubMed2026

Influence of Major Histocompatibility Complex (MHC) Diversity on Immune Modulation, Pathogenesis, and Control of Lumpy Skin Disease Virus.

INTRODUCTION: Lumpy Skin Disease Virus (LSDV), a member of the genus Capripoxvirus within the family Poxviridae, is an economically important transboundary viral pathogen affecting cattle and water buffalo. The disease causes severe production losses through decreased milk yield, infertility, hide damage, reduced growth performance, and occasional mortality. The rapid geographic spread of LSDV, together with its vectorborne transmission and emerging recombinant strains, has intensified the need for improved understanding of viral pathogenesis, host immune responses, and effective prevention strategies. In particular, the role of the bovine Major Histocompatibility Complex (BoLA/MHC) in regulating antiviral immunity, disease susceptibility, and vaccine responsiveness has gained increasing scientific attention. METHODS: This review summarises the published literature related to the epidemiology, transmission, structure, pathogenesis, diagnosis, prevention, and control of LSDV, with special emphasis on the immunological and molecular role of bovine MHC molecules. Relevant studies concerning BoLA-mediated antigen presentation, immunoinformaticsbased epitope prediction, vaccine development, antiviral drug repurposing, molecular docking, genomic surveillance, and diagnostic approaches, including PCR- and ELISAbased assays, were critically evaluated. Recent advances in computational biology, molecular virology, and host-pathogen interaction studies were also reviewed. RESULTS: The reviewed studies demonstrate that Lumpy Skin Disease Virus (LSDV) possesses a complex double-stranded DNA genome enabling immune modulation and efficient transmission through arthropod vectors such as mosquitoes, ticks, and biting flies. Disease progression involves systemic viral replication, vascular injury, dermal necrosis, and inflammatory skin lesions. Real-time PCR remains the most sensitive diagnostic method for early detection, while ELISA supports surveillance. Evidence highlights the central role of bovine Major Histocompatibility Complex (BoLA) molecules in antigen presentation and T-cell activation. Computational studies identified promising BoLA-binding epitopes and repurposed antiviral candidates, including ivermectin, theaflavin, canagliflozin, and tepotinib, for future therapeutic development. DISCUSSION: Current evidence indicates that effective LSDV control requires integration of molecular diagnostics, vector management, vaccination, and host immunogenetics. BoLAguided immunoinformatics provides promising opportunities for developing multi-epitope vaccines, although experimental validation remains essential. Similarly, repurposed antiviral candidates require comprehensive in vivo and pharmacological evaluation before clinical application. Future research should focus on elucidating viral immune-evasion mechanisms, validating predicted epitopes, and translating computational findings into practical vaccines and therapeutics for sustainable disease control. CONCLUSION: Lumpy Skin Disease continues to pose a major threat to global cattle health and livestock economies. Advances in molecular diagnostics, genomic surveillance, antiviral drug discovery, and BoLA-guided vaccine design provide promising opportunities for improved disease control. Understanding the interaction between LSDV and the bovine MHC system is essential for developing next-generation vaccines, immunotherapeutics, and precision disease-management strategies. Future research should prioritise experimental validation of predicted epitopes, large-scale vaccine trials, and mechanistic studies on host-virus immune interactions to establish effective and sustainable global control programs for LSDV.

BoLA↗
PubMed2026

An immunoinformatics-based multi-epitope vaccine candidate confers cross-protection against two Actinobacillus pleuropneumoniae serovars.

Porcine contagious pleuropneumonia (PCP) is caused by Actinobacillus pleuropneumoniae (APP) and inflicts heavy economic losses on the swine industry. However, existing inactivated vaccines provide limited cross-protection, highlighting the need for improved vaccine strategies. In this study, we combined pangenome analysis with subtractive proteomics to screen the APP core genome and identified 11 potential antigens. Seven of them showed immunoreactivity by ELISA and Western blotting. These antigens, together with the ApxI-III toxins, were used for T and B cell epitope prediction. On this basis, a multi-epitope fusion protein MVAPP was constructed. In silico molecular docking with swine immune receptors and immune simulations suggested that MVAPP has the potential to induce immune responses. In the mouse model, that MVAPP elicited specific antibody responses, shifted the splenic T-cell subset distribution toward CD4+ T cells, and provided partial protection against challenge with strains from two serovars. In conclusion, MVAPP represents a potential multi-epitope vaccine candidate for further development against APP.

Animals↗
PubMed2026

Integrated molecular and immune profiling identifies FOXA1 as a complementary co-target to MUC1 for bispecific immunotherapy in breast cancer.

In breast cancer immunotherapy, Mucin 1 (MUC1) is a well-established target with promising preclinical results; however, single targeting of MUC1 has demonstrated limited efficacy in clinical trials, largely due to tumor heterogeneity, diverse glycosylation patterns, and an immunosuppressive TME. Identification of complementary co-targets enables bi-specific or dual-target immunotherapy, limiting antigen escape, improving specificity, and reducing relapse. Here, we employed a comprehensive multi-layered analytical approach to evaluate MUC1 expression, clinical relevance, and methylation status, followed by systematic screening of MUC1-correlated genes. Antigenicity prediction and protein-protein interaction analyses identified Forkhead Box A1 (FOXA1) as a potential functional partner. Expression analysis revealed concordant patterns of MUC1 and FOXA1 across breast cancer samples, while network mapping demonstrated shared interactions with adhesion-associated proteins, including CTNNB1, CTNND1, and CDH1, suggesting roles in epithelial organization and tumor progression. Further validation using gene expression datasets from Indian breast cancer cohorts confirmed consistent expression and correlation patterns, supporting reproducibility across populations. Immune profiling revealed an inverse association between MUC1-FOXA1 co-expression and immune-related gene signatures, with high co-expression linked to reduced infiltration of dendritic cells, CD4⁺ and CD8⁺ T cells, macrophages, and natural killer cells, indicative of an immunosuppressive microenvironment. Negative correlations with MHC Class I genes further suggested impaired antigen presentation. Epitope prediction identified high-affinity peptides from both targets with strong MHC Class I binding potential. Collectively, these findings support the associated role of MUC1 and FOXA1 as dual immunotherapeutic targets in breast cancer.

Hepatocyte Nuclear Factor 3-alpha↗
PubMed2026

Therapeutic melanoma vaccines: Platforms, neoantigen strategies, and emerging combination immunotherapies.

Melanoma has emerged as a major focus of cancer immunotherapy research because of its highly immunogenic nature and responsiveness to immune-based treatments. Therapeutic melanoma vaccines are designed to stimulate tumor-specific immune responses through the delivery of Tumor-Associated Antigens (TAAs), Tumor-Specific Antigens (TSAs), and personalized neoantigens. This narrative review provides an overview of current melanoma vaccine strategies, including peptide-based vaccines, dendritic cell vaccines, nucleic acid-based platforms such as mRNA, DNA, and viral vector vaccines. Recent advances in vaccine engineering and tumor genomics have accelerated the development of personalized neoantigen vaccines capable of targeting mutations unique to individual tumors. In parallel, Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being incorporated into neoantigen identification pipelines to improve epitope prediction and optimize vaccine design. Combination strategies involving Immune Checkpoint Inhibitors (ICIs), particularly anti-PD-1 and anti-CTLA-4 therapies, have further enhanced interest in melanoma vaccines by helping overcome tumor-induced immune suppression and augment T-cell activation. In addition to reviewing vaccine mechanisms and emerging technologies, this manuscript examines the evolving clinical trial landscape through analysis of melanoma vaccine studies registered on ClinicalTrials.gov. Although many studies have reported encouraging safety and immunogenicity findings, challenges related to tumor heterogeneity, immune evasion, biomarker selection, and manufacturing complexity continue to limit widespread clinical implementation. Ongoing advances in computational immunology, biomaterial engineering, and precision oncology are expected to further refine melanoma vaccine development and improve therapeutic efficacy. Collectively, these innovations may help establish melanoma vaccines as an increasingly important component of future personalized cancer immunotherapy strategies.

DNA vaccines↗
PubMed2026

Genetic polymorphism in Plasmodium falciparum MSPDBL1 and MSPDBL2 and their impact on B- and T-cell immunodominant epitopes in Brazilian malaria-endemic areas.

Merozoite Surface Protein Duffy Binding-like 1 and 2 (MSPDBL1 and MSPDBL2) are involved in erythrocyte invasion by Plasmodium falciparum. Antibodies targeting PfMSPDBL1 and PfMSPDBL2 show strong opsonizing and growth-inhibitory activities, supporting their potential as asexual blood-stage vaccine candidates. Given that the extensive genetic diversity of P. falciparum contributes to immune evasion, identifying polymorphisms in regions encoding PfMSPDBL1 and PfMSPDBL2 is essential to assess their relevance as vaccine targets. In this study, we investigated polymorphisms in the pfmspdbl1 and pfmspdbl2 genes and their impact on potentially antigenic regions within the Duffy Binding-like (DBL) and Secreted Polymorphic Antigen Associated with Merozoite (SPAM) domains. Blood samples were collected from 47 P falciparum-infected individuals from three malaria-endemic areas of the Brazilian Amazon. Genomic DNA was extracted, PCR-amplified, and sequenced. Intrapopulation genetic diversity and Tajima's D values were estimated using bioinformatics tools. Linear B- and T-cell epitopes were predicted using BCPreds and IEDB (Immune Epitope Database), respectively. Two and thirty-two polymorphisms were identified in pfmspdbl1 within the SPAM and DBL domains, respectively, whereas pfmspdbl2 presented two polymorphisms across both domains and a 12 bp insertion in the SPAM domain. Tajima's D values were positive across domains, except for the DBL domain of pfmspdbl2 in Mâncio Lima. Fifteen B-cell and fifteen T-cell epitopes were predicted, with polymorphisms in three B-cell epitopes affecting Vaxijen scores. Together, these findings reveal contrasting evolutionary patterns between PfMSPDBL1 and PfMSPDBL2, with potential implications for antigenicity, and highlight PfMSPDBL2 as a potential candidate for further evaluation in multicomponent blood-stage malaria vaccine development.

Genetic diversity↗
PubMed2026

Computational prediction of a multi-epitope Human Metapneumovirus vaccine candidate through integrated reverse vaccinology and pan-genomic approaches.

Human metapneumovirus (HMPV) is a primary cause of global respiratory infections yet no approved vaccine currently exists. This study computationally predicts a multi-epitope vaccine candidate using a diverse dataset of 65 HMPV sequences spanning five continents. Following the screening of lead proteins for antigenicity and virulence, fifteen highly conserved MHC-I, MHC-II and B-cell epitopes were prioritized. These were integrated with a putative L7/L12 adjuvant using optimized AAY, GPGPG, and KK linkers to design three constructs (HMPV_V1-V3). Structural validation identified HMPV-V2 as the lead candidate that exhibits a Z-score of-5.24 and 87.7% of residues in favored Ramachandran regions indicating excellent stereochemical quality and structural stability. In silico docking indicated a strong predicted binding affinity between HMPV-V2 and the TLR4 receptor (energy: -969.2). Immune simulations predicted a robust adaptive response characterized by high IgG1 titers, memory B-cell maturation, and a Th1-dominant cytokine profile. Furthermore, molecular dynamics simulations suggested exceptional structural integrity for HMPV-V2, maintaining a low RMSD of 8.213 and RMSF of 0.737 throughout the simulation. Optimized in silico cloning into the pET28a (+) vector indicated a high potential for protein expression in E. coli systems. While these findings provide a theoretically grounded blueprint for vaccine development, this study is entirely computational and lacks experimental validation. Further in vitro and in vivo testing is required to confirm the actual safety and immunogenicity of the proposed candidate.

Metapneumovirus↗
PubMed2026

Micropeptides encoded by lncRNAs associated with cancer progression reveal novel immunogenic epitopes.

MOTIVATION: Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin organization, and cellular signaling. Recent studies indicate that ∼20% of the ∼36 000 human lncRNA genes harbor small open reading frames (sORFs) capable of producing micropeptides (MPs), whose functions remain largely unknown. Whether these peptides contribute to the cancer immunopeptidome is largely unexplored. RESULTS: We systematically analyzed lncRNAs with strong experimental and computational evidence of MP-encoding potential (∼13% of the initial MP collection). Using The Cancer Genome Atlas (TCGA), we identified 2606 high-confidence lncRNA-derived MPs encoded by 647 genes across 16 cancer types. We then focused on 501 MPs from 124 lncRNA genes whose expression changes significantly across tumor stages and metastatic transitions, representing cancer transitional lncRNAs (Tr-lncRNAs). Dipeptide composition and conservation analyses showed that these MPs differ from a size-matched human coding proteome, supporting their potential as neoantigens. All possible 9-mer peptides were evaluated for predicted binding to prevalent European HLA class I alleles. Approximately 60% of Tr-lncRNA genes and 184 (37%) of derived peptides exhibited strong predicted HLA binding. Peptides from XIST, PCAT7, PVT1, HAND2-AS1 showed broad HLA coverage. Notably, TTN-AS1, encoded an MP (79 aa) generated 33 predicted distinct epitopes spanning all 27 HLA alleles. Our analysis identifies lncRNA-derived MPs as a previously underexplored source of potential cancer neoantigens, highlighting their promise as biomarkers and targets for immunotherapy. AVAILABILITY: Data, code and supplementary materials are available in https://doi.org/10.5281/zenodo.20167452 and GitHub: https://github.com/stavzok1/lncrna_peptide_analysis.

Humans↗
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↗
PubMed2026

EPIC: multi-objective guided diffusion for epitope design in TCR-pMHC complexes.

MOTIVATION: T cell receptor (TCR) recognition of peptide-major histocompatibility complex (pMHC) complexes is central to adaptive immunity, yet rational design of immunogenic epitopes remains elusive due to complex triplet binding constraints and data scarcity. No existing method can generate epitopes satisfying simultaneous requirements for antigenicity, MHC presentation, and TCR specificity. RESULTS: We present EPIC, a multi-objective diffusion framework that decomposes TCR-pMHC binding into three biologically grounded sub-tasks, enabling training-free gradient guidance without end-to-end retraining. By integrating ESM-based classifiers with a peptide diffusion generator, EPIC leverages heterogeneous immunological interaction datasets to generate diverse, context-aware epitopes. EPIC-designed top-three epitopes achieve lower predicted interface energies compared to ground-truth epitopes in 78.31% of test cases, while maintaining 80.1% sequence novelty and comparable structural confidence. Generated epitopes exhibit 100% uniqueness, high diversity (64.05%), and high antigenicity scores (0.4723). To our knowledge, EPIC is the first computational framework capable of de novo epitope design while explicitly integrating the triplet constraints of TCR-pMHC binding. This paradigm shift from discovery to design unlocks new potential for personalized cancer vaccines, precision adoptive T cell therapy, and rapid response to emerging infectious diseases. AVAILABILITY AND IMPLEMENTATION: The source code of EPIC is available at https://github.com/Octopus125/EPIC and archived on Zenodo (DOI: 10.5281/zenodo.18537646).

Receptors, Antigen, T-Cell↗
PubMed2026

Immunopeptidomics-guided cancer vaccine design: Advances, challenges, and emerging opportunities.

Selecting clinically relevant tumor antigens remains a major challenge in the development of therapeutic cancer vaccines. Although computational approaches have considerably improved neoantigen prediction, many candidate epitopes identified in silico are not ultimately presented on the tumor cell surface. The emergence of immunopeptidomics has provided direct access to naturally processed HLA-associated peptides and has offered new opportunities for antigen discovery. Increasing evidence has shown that information derived from the immunopeptidome becomes considerably more informative when interpreted alongside genomic, transcriptomic, and proteomic data. This integrative view has broadened the spectrum of targetable antigens and has also revealed important limitations related to peptide abundance, HLA diversity, tumor heterogeneity, and the imperfect relationship between antigen presentation and immunogenicity. These issues have renewed interest in multi-antigen vaccine strategies designed to better reflect the complexity of tumor antigen landscapes. Advances in bioinformatics and artificial intelligence are facilitating the interpretation of increasingly complex datasets and are beginning to support more systematic approaches to antigen prioritization. In this review, we discuss how immunopeptidomics is contributing to next-generation cancer vaccine development, summarize the major translational challenges, and highlight emerging concepts that may improve the clinical applicability of immunopeptidomics-guided immunotherapy.

Cancer immunotherapy↗
PubMed2025

Two CENH3 paralogs in the green alga Chlamydomonas reinhardtii have a redundantly essential function and associate with ZeppL-LINE1 elements.

Centromeres in eukaryotes are defined by the presence of histone H3 variant CENP-A/CENH3. Chlamydomonas encodes two predicted CENH3 paralogs, CENH3.1 and CENH3.2, that have not been previously characterized. We generated peptide antibodies to unique N-terminal epitopes for each of the two predicted Chlamydomonas CENH3 paralogs as well as an antibody against a shared CENH3 epitope. All three CENH3 antibodies recognized proteins of the expected size on immunoblots and had punctate nuclear immunofluorescence staining patterns. These results are consistent with both paralogs being expressed and localized to centromeres. CRISPR-Cas9-mediated insertional mutagenesis was used to generate predicted null mutations in either CENH3.1 or CENH3.2. Single mutants were viable but cenh3.1 cenh3.2 double mutants were not recovered, confirming that the function of CENH3 is essential. We sequenced and assembled two chromosome-scale Chlamydomonas genomes from strains CC-400 and UL-1690 (a derivative of CC-1690) with complete centromere sequences for 17/17 and 14/17 chromosomes respectively, enabling us to compare centromere evolution across four isolates with near complete assemblies. These data revealed significant changes across isolates between homologous centromeres including mobility and degeneration of ZeppL-LINE1 (ZeppL) transposons that comprise the major centromere repeat sequence in Chlamydomonas. We used cleavage under targets and tagmentation (CUT&Tag) to purify and map CENH3-bound genomic sequences and found enrichment of CENH3-binding almost exclusively at predicted centromere regions. An interesting exception was chromosome 2 in UL-1690, which had enrichment at its genetically mapped centromere repeat region as well as a second, distal location, centered around a single recently acquired ZeppL insertion. The CENH3-bound regions of the 17 Chlamydomonas centromeres ranged from 63.5 kb (average lower estimate) to 175 kb (average upper estimate). The relatively small size of its centromeres suggests that Chlamydomonas may be a useful organism for testing and deploying artificial chromosome technologies.

Chlamydomonas reinhardtii↗
PubMed2026

Immunoinformatics Approach for Optimization of Targeted Vaccine Design: New Paradigm in Clinical Trials and Healthcare Management.

INTRODUCTION: The immunoinformatics approach combines bioinformatics and computational tools, offering a revolutionary method for improving vaccine development by analyzing immune responses at the molecular level. Immunoinformatics enables the creation of customized vaccines designed for specific infections or cancer cells. OBJECTIVE: The primary objective of immunoinformatics is to enhance the vaccine development process by predicting and boosting the body's immune response. It aims to identify potential immunogenic epitopes and biomarkers that are important for creating vaccines with greater specificity and efficacy, especially when dealing with large-scale data. METHODS: Immunoinformatics utilizes a combination of proteomic, genomic, and epigenomic data, as well as machine learning algorithms and artificial intelligence techniques. These tools predict how various immunological components, e.g., T-cell and B-cell epitopes, interact with the immune system. This approach allows researchers to avoid traditional trial-and-error methods, enabling the efficient identification of potential vaccine candidates. Additionally, personalized vaccines can be developed by considering individual genetic and immunological characteristics. RESULTS: The use of immunoinformatics techniques accelerates the screening of vaccine candidates, enhances patient stratification, and optimizes formulations for clinical trials. This approach has been shown to improve vaccine safety, efficacy, and development speed. It also holds promise for managing healthcare on a large scale by producing vaccines tailored to specific populations, thereby improving the overall effectiveness of vaccination programs. CONCLUSION: Immunoinformatics represents a transformative approach to vaccine research, improving clinical trial efficiency and enabling the development of more reliable, flexible, and personalized vaccines. This approach has the potential to significantly enhance global healthcare outcomes by accelerating the vaccine development process and optimizing vaccination strategies.

Immunoinformatics↗
PubMed2025

Subcellular proteomics of the protist Paradiplonema papillatum reveals the digestive capacity of the cell membrane and the plasticity of peroxisomes across euglenozoans.

Diplonemids are among the most diverse and abundant protists in the deep ocean, have extremely complex and ancient cellular systems, and exhibit unique metabolic capacities. Despite this, we know very little about this major group of eukaryotes. To establish a model organism for comprehensive investigation, we performed subcellular proteomics on Paradiplonema papillatum and localized 4,870 proteins to 22 cellular compartments. We additionally confirmed the predicted location of several proteins by epitope tagging and fluorescence microscopy. To probe the metabolic capacities of P. papillatum, we explored the proteins predicted to the cell membrane compartment in our subcellular proteomics dataset. Our data revealed an accumulation of many carbohydrate-degrading enzymes (CDZymes). Our predictions suggest that these CDZymes are exposed to the extracellular space, supporting proposals that diplonemids may specialize in breaking down carbohydrates in plant and algal cell walls. Further exploration of carbohydrate metabolism revealed an evolutionary divergence in the function of glycosomes (modified peroxisomes) in diplonemids versus kinetoplastids. Our subcellular proteome provides a resource for future investigations into the unique cell biology of diplonemids.

Peroxisomes↗
PubMed2026

Complete genome characterization, phylogenetic analysis, and capsid P2 variation of a goose astrovirus genotype 2 isolate from Guizhou, China.

Goose astrovirus genotype 2 (GAstV-2) is associated with gout and renal disease in goslings, but its occurrence in Guizhou Province remains poorly documented. We isolated a GAstV-2 strain, designated GZJP2024, from goslings with visceral gout on a farm in Jinping County, Guizhou Province, China. PCR detected GAstV-2 but not goose parvovirus, goose reovirus, Tembusu virus, fowl adenovirus, or goose astrovirus genotype 1. Serial passage in goose embryos produced mortality and hemorrhagic lesions during the third passage. Whole-genome sequencing yielded a 7,251-nt genome containing three overlapping open reading frames (ORF1a, ORF1b, and ORF2). Sequence identity and phylogenetic analyses assigned GZJP2024 to the GAstV-2 lineage. ORF1b was the most conserved coding region, whereas ORF2 was more variable. Comparison with consensus sequences from representative GAstV-2 strains identified five amino acid substitutions in ORF1a and ten in ORF2. Four ORF2 substitutions (E456D, L540Q, S608T, and A614T) occurred in the capsid P2 domain and overlapped or neighbored predicted B-cell epitope-rich regions. Template-based mapping placed E456D, S608T, and A614T on exposed regions of a spike-like capsid structure. These findings document a GAstV-2 isolate from a gout-affected goose farm in Guizhou and provide sequence data for future regional surveillance.

Capsid P2↗
PubMed1977

Immune response against two epitopes on the same thymus-independent polysaccharide carrier. 1. Role of epitope density in carrier-dependent immunity and tolerance.

Immunogenicity and tolerogenicity of two epitopes (alpha 1-6 and FITC) on the same dextran B 512 carrier were investigated. The following conclusions were made: (1) Both epitopes were thymus-independent and immunogenic and tolerogenic as well. (2) The marked dose differences between the two epitopes with regard to tolerance induction were found to be a consequence of the affinity and the heterogeneity of the responding B cells as well as the epitope density employed for detecting the PFC in a predictable way. (3) The alpha 1-6 response, in contrast to the anti-FITC response, was homogeneous and of low affinity and the number of precursor B cells was low. (4) Different mouse strains were found to be high-, low- or non-responders to alpha 1-6, but all the strains tested responded to the FITC epitope coupled to dextran. (5) Dextran and FITC-dextran were polyclonal B cell activators in the strains tested, irrespective of their ability to respond to the alpha 1-6 epitope. The findings indicate that epitope density and mol. wt of the immunogen as well as Ig receptor affinity for the epitope on the B cells are variables which markedly influence the binding of the immunogen to the specific B cells and therefore affect the delivery of the non-specific triggering signal.

Animals↗
PubMed2025

Maternal-Foetal HLA-DQB1 Incompatibility Is Associated With Pregnancy-Induced Hypertensive Disorders in a Genetically Isolated Population.

In pregnancy, semi-allogenic foetal trophoblasts express a specific HLA profile mediating maternal leukocyte contact, crucial for placentation. Paradoxically, maternal immunomodulation requires foetal antigen recognition, especially involving certain HLA molecules. Pre-eclampsia, a severe hypertensive complication, has been linked to antigenic similarity. Previously, we showed no selection for HLA (in)compatibility in uncomplicated naturally conceived pregnancies. However, pre-eclamptic pregnancies were associated with increased total maternal-foetal HLA and HLA-C matching. These associations suggest a role for HLA mismatches in immune regulation leading to an uncomplicated pregnancy. To better understand HLA homozygosity in human reproduction, we aimed to determine if there is a preferential selection for HLA compatibility in a genetically isolated population, and its relation to hypertensive complications. A nested case-control study, comprising 125 uncomplicated pregnancies and 50 with hypertensive complications (29 with pregnancy-induced hypertension, 21 with pre-eclampsia) was conducted in a genetically isolated Dutch population (FROH 1.3-3.1). Maternal and foetal HLA-A, -B, -C, -DRB1, -DQA1, -DQB1 and maternal killer-cell immunoglobulin-like receptor (KIR) genotyping were performed. Maternal-foetal HLA (mis)match counts were compared to expected values from randomisation of paternal HLA haplotypes over maternal haplotypes of the foetuses. Mismatched CD4+ T cell epitopes presented by maternal HLA class II were predicted using the PIRCHE-II algorithm. In uncomplicated pregnancies, no difference was found between observed and expected maternal-foetal HLA (mis)matches. However, pregnancies with hypertensive complications showed significantly higher observed HLA-DQB1 mismatches, reflected in PIRCHE-II scores. No significant differences were found in KIR/HLA-C frequencies. Interpretation is limited by the small sample size and the grouping of distinct hypertensive disorders. Nonetheless, maternal-foetal HLA-DQB1 mismatch seems to play a role in the aetiology of hypertensive complications during pregnancy in this population.

Humans↗
PubMed2026

Screening of Fermentative Strains for Reducing the Allergenicity of a Whey Protein-Soy Protein System and Genomic Characterization of the Selected Strain.

Dual-protein systems combining whey protein isolate (WPI) and soy protein isolate (SPI) offer complementary nutritional benefits but are limited by the presence of major allergens. Lactic acid bacteria (LAB) fermentation provides a promising strategy to mitigate this limitation. In this study, Lacticaseibacillus paracasei JM053, selected from 13 LAB strains based on phenotypic screening, significantly reduced the in vitro allergenicity of the dual-protein system, increasing the IgE-binding inhibition rate to 48.75%. Whole-genome sequencing and characterization of JM053 revealed a comprehensive proteolytic system, including the proline-specific peptidase genes pepX and pepQ, which may contribute to the degradation of allergenic peptide sequences. Combined with in silico bioinformatic analysis, potential cleavage sites within the linear epitopes of the dual-protein system were predicted based on the substrate specificity of the identified proteases, offering a testable hypothesis for the strain's mechanism of action. In addition, in vitro safety assessment and genomic analysis supported the safety potential, stress tolerance, and probiotic characteristics of JM053. Collectively, this study provides a valuable candidate strain for the development of hypoallergenic dual-protein products and offers preliminary genomic insights into LAB-mediated allergenicity reduction.

Lacticaseibacillus paracasei↗
PubMed2025

Assessing data size requirements for training generalizable sequence-based TCR specificity models via pan-allelic MHC-I point-mutation ligandome evaluation.

Rapid identification of T cell receptors (TCRs) that specifically bind patient-unique neoepitopes is a critical challenge for personalized TCR-based therapies in oncology. Due to enormous diversity of both TCR and neoepitope repertoires, a machine learning predictor of TCR-pMHC specificity for personalized therapy must generalize to TCRs and epitopes not seen in the training data. We estimate the necessary size of such training data. We first confirm that published models fail to generalize beyond a single-residue dissimilarity to the epitope training set distribution. We then impute the point-mutation ligandome across the 34 most prevalent human MHC alleles and represent it as a graph based on our established dissimilarity cutoff. By finding the dominating set of this graph, we estimate that between one and 100 million epitopes are required to train a generalizable sequence-based TCR specificity prediction model-1000 times the size of current public data.

Humans↗