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PubMed2027

Epitope Tagging and Coimmunoprecipitation to Identify Viral Protein Interactors.

Affinity purification-mass spectrometry (AP-MS) is a powerful proteomic approach for dissecting the interaction network between virus and host. Traditional AP-MS employs overexpression of viral proteins as baits to enrich host interactors. However, overexpressed viral proteins may mislocalize to inappropriate cellular compartments and trigger endoplasmic reticulum stress by overwhelming the protein-folding machinery, which leads to false identification of host factors. To overcome these limitations, we introduce an AP-MS strategy based on direct infection with an epitope-tagged chikungunya virus (CHIKV/myc-E2), which we used to successfully uncover two new antiviral factors in CHIKV cellular reservoirs-macrophages. In this protocol, we will describe this technique step by step: (1) design and construction of myc-tagged virus by advanced multi-fragment assembly, (2) in vitro transcription and preparation of infectious myc-tagged virus stocks, and (3) immunoprecipitation of myc-tagged viral protein and its interactome for mass spectrometry analysis. This strategy enables accurate identification of viral interactors in a physiologically relevant context, providing a framework for future proteomic studies using tagged viruses.

Chikungunya virus↗

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↗

PubMed2025

mamp-ml: A deep learning approach to epitope immunogenicity in plants.

Eukaryotes detect biomolecules through surface-localized receptors, key signaling components. A subset of receptors survey for pathogens, induce immunity, and restrict pathogen growth. Comparative genomics of both hosts and pathogens has unveiled vast sequence variation in receptors and potential ligands, creating an experimental bottleneck. We have developed mamp-ml, a machine learning framework for predicting plant receptor-ligand interactions. We leveraged existing functional data from over two decades of foundational research, together with the large protein language model ESM-2, to build a pipeline and model that predicts immunogenic outcomes using a combination of receptor-ligand features. Our model achieves 73% prediction accuracy on a held-out test set, even when an experimental structure is lacking. Our approach enables high-throughput screening of LRR receptor-ligand combinations and provides a computational framework for engineering plant immune systems.

Journal Article↗

PubMed2026

Balancing under constraint: Structural insights into norovirus evolution and antigenic innovation.

Norovirus is the leading cause of acute viral gastroenteritis worldwide. While genomic studies have revealed its diversity and evolutionary patterns, the structural mechanisms driving viral adaptation remain poorly understood. Here, we establish a comprehensive structural database of norovirus VP1 P-domains across nine genogroups (GI-GIX) through large-scale AlphaFold2 predictions. By integrating phylogenetic analysis of VP1 sequences and structures, we demonstrate that sequence and structural evolution show overall concordance under purifying selection, yet significant local discrepancies reveal distinct patterns of convergent evolution shaped by structural constraints and functional divergence. Focusing on the predominant GII.4 genotype, we found that compared to near-full-genome and nucleotide trees, only the VP1 amino acid tree reliably clustered GII.4 variants in chronological order as monophyletic groups. We further identify a hierarchical evolutionary strategy: positive selection may drive structural hypervariability in major antigenic epitopes D and C for immune escape, with epitope D exhibiting pronounced structural flexibility that complicates its structural characterization, whereas coevolutionary analysis uncovers a broad network of compensatory interactions spanning multiple epitopes, with striking enrichment in epitope A. These epitopes exhibited a pattern of "sequence plasticity with structural conservation", maintained by coevolutionary constraints that preserve conformational integrity. Together, these findings suggest that norovirus vaccine strategies targeting the structurally conserved conformations of epitopes A and G could overcome the limitations of traditional strain-specific approaches, offering a pathway toward broad protection against evolving viral diversity.

Norovirus↗

PubMed2026

Chimeric vaccine based on Iraqi HLA alleles against a predominant local Escherichia coli phylogroup.

INTRODUCTION: Escherichia coli remains amongst the most globally important pathogens implicated in severe clinical manifestations. The progressive rise in multidrug-resistant strains highlights the urgent need for new vaccines. Therefore, this study was designed to develop a new multi-epitope vaccine containing the most conserved epitopes across E. coli pathotypes. Consequently, the study aimed to investigate the immunoadjuvant role of faecal microbiota transplantation in enhancing vaccine efficacy. METHODS: Eighteen of the most conserved B-cell and T-cell epitopes of FimH, LptD, and BamA proteins were selected and included in a single construct. During the epitope selection process, HLA alleles predominant in the Iraqi population, as reported in previous studies, were used as criteria for selecting T-cell epitopes. The chimeric protein was expressed in BL21 E. coli and purified using affinity chromatography. Vaccine cross-protective immunity and protection were tested in in vivo experiments. Different formulations were used in the experimental evaluation: three doses of 100 μg of purified chimeric protein, injected intraperitoneally alone or encapsulated in PLGA nanoparticles, after faecal microbiota transplantation with and without gut microbiota modulation mediated by a cocktail of antibiotics. IgG1, IL-4, INF-γ, and NLRP3 levels were measured at 30 and 75 days after the first immunisation dose. Immunised mice were challenged with the local B2 UPEC phylogroup, and protection efficacy was considered 48 h later. Finally, the histological effects of the different chimeric protein formulations on the liver were assessed. RESULTS: All vaccine formulations except those after faecal microbiota transplantation without gut microbiota modulation induce significant increases in IgG1, IL-4, and INF-γ levels at different times. Only vaccination after faecal microbiota transplantation with gut microbiota modulation elicited robust NLRP3 levels at 30 and 75 days after, and this was linked to the highest reduction in bladder bacterial load by 813-fold compared to the other formulations, as well as the mildest effect on liver histological changes. DISCUSSION: These results demonstrated that the chimeric vaccine provides preliminary protection against a local B2 UPEC isolate. Furthermore, modulating gut microbiota via faecal transplantation markedly enhances the immunogenicity and protective efficacy of vaccination, suggesting its adjuvanticity.

Animals↗

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↗

PubMed2016

Identification of food-grade subtilisins as gluten-degrading enzymes to treat celiac disease.

Gluten are proline- and glutamine-rich proteins present in wheat, barley, and rye and contain the immunogenic sequences that drive celiac disease (CD). Rothia mucilaginosa, an oral microbial colonizer, can cleave these gluten epitopes. The aim was to isolate and identify the enzymes and evaluate their potential as novel enzyme therapeutics for CD. The membrane-associated R. mucilaginosa proteins were extracted and separated by DEAE chromatography. Enzyme activities were monitored with paranitroanilide-derivatized and fluorescence resonance energy transfer (FRET) peptide substrates, and by gliadin zymography. Epitope elimination was determined in R5 and G12 ELISAs. The gliadin-degrading Rothia enzymes were identified by LC-ESI-MS/MS as hypothetical proteins ROTMU0001_0241 (C6R5V9_9MICC), ROTMU0001_0243 (C6R5W1_9MICC), and ROTMU0001_240 (C6R5V8_9MICC). A search with the Basic Local Alignment Search Tool revealed that these are subtilisin-like serine proteases belonging to the peptidase S8 family. Alignment of the major Rothia subtilisins indicated that all contain the catalytic triad with Asp (D), His (H), and Ser (S) in the D-H-S order. They cleaved succinyl-Ala-Ala-Pro-Phe-paranitroanilide, a substrate for subtilisin with Pro in the P2 position, as in Tyr-Pro-Gln and Leu-Pro-Tyr in gluten, which are also cleaved. Consistently, FRET substrates of gliadin immunogenic epitopes comprising Xaa-Pro-Xaa motives were rapidly hydrolyzed. The Rothia subtilisins and two subtilisins from Bacillus licheniformis, subtilisin A and the food-grade Nattokinase, efficiently degraded the immunogenic gliadin-derived 33-mer peptide and the immunodominant epitopes recognized by the R5 and G12 antibodies. This study identified Rothia and food-grade Bacillus subtilisins as promising new candidates for enzyme therapeutics in CD.

Bacteria↗

PubMed2025

One thousand SARS-CoV-2 antibody structures reveal convergent binding and near-universal immune escape.

Understanding antibody recognition and adaptation to viral evolution is central to vaccine and therapeutic development. Over 1,100 SARS-CoV-2 antibody structures have been resolved, marking the largest structural biology effort for a single pathogen. We present a comprehensive analysis of this landmark dataset to investigate the principles of antibody recognition and immune escape. Human immunoglobulins and camelid single-chain antibodies dominate, collectively mapping 99% of the receptor-binding domain. Despite remarkable sequence and conformational diversity, antibodies exhibit convergence in their paratope structures, revealing evolutionary constraints in epitope selection. Analyses reveal near-universal immune escape of antibodies, including all clinical monoclonals, by advanced variants such as KP3.1.1. On average, over one-third of antibody epitope residues are mutated. These findings support pervasive immune escape, underscoring the need to effectively leverage multi-epitope-targeting strategies to achieve durable immunity. To support community accessibility, we developed an interactive web server for visualization and analysis of antibody-antigen complexes and mutational data.

SARS-CoV-2↗

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↗

PubMed2025

PhIP-Seq uncovers marked heterogeneity in acute rheumatic fever autoantibodies.

Acute rheumatic fever (ARF) and associated rheumatic heart disease are serious sequelae after infection with group A Streptococcus (Strep A). Autoantibodies are thought to contribute to pathogenesis, with deeper exploration of the autoantibody repertoire needed to improve mechanistic understanding and identify new biomarkers. Phage immunoprecipitation sequencing (PhIP-Seq) with the HuScan library (>250,000 overlapping 90-mer peptides spanning the human proteome) was utilized to analyze autoreactivity in sera from children with ARF, uncomplicated Strep A pharyngitis, and matched healthy controls. A global proteome-wide increase in autoantigen reactivity was observed in ARF, as was marked heterogeneity between patients. Public epitopes, common between individuals with ARF were rare, and comprised less than 1% of all enriched peptides. Differential analysis identified both unknown and previously identified ARF autoantigens, including PPP1R12B, a myosin phosphatase complex regulatory subunit expressed in cardiac muscle, and members of the collagen protein family, respectively. Pathway analysis found antigens from the disease-relevant processes encompassing sarcomere and heart morphogenesis were targeted. In sum, PhIP-Seq has substantially expanded the spectrum of autoantigens in ARF, and reveals the rarity of public epitopes in the disease. It provides further support for the role of epitope spreading in pathogenesis and has identified PPP1R12B as an enriched autoantigen.

Humans↗

PubMed2025

Multi-criteria decision making and its application to in silico discovery of vaccine candidates for Toxoplasma gondii.

Vaccine discovery against eukaryotic parasites is not trivial and few exist. Reverse vaccinology is an in silico vaccine discovery approach, designed to identify vaccine candidates from the thousands of protein sequences encoded by a target genome. Previously, we produced the Vacceed bioinformatics pipeline for identification of parasite membrane and excreted/secreted proteins that were likely be exposed to the hosts immune system. More recently, we improved upon machine learning as the final decision-making process to identify parasite proteins that induce a protective response in an animal model. Subsequently, we combined Vacceed with metrics on B and T cell epitope types to produce a new in silico discovery workflow. In this study we extend this in silico workflow to the developability of proteins as vaccines by the incorporation of metrics on the physicochemical properties of proteins. To demonstrate this process, every Toxoplasma gondii protein was ranked in its capacity to provide exposure to the immune system (Vacceed exposure score), presence of epitopes and solubility characteristics by several multicriteria decision making (MCDM) tools (such as TOPSIS, VIKOR and MABAC). A consensus rank was subsequently generated from the results of these tools using a variety of aggregate ranking methods. Levels of uncertainty in the aggregate protein rankings was assessed by conformal interval prediction in association with a machine learning model. Several of the top ranked proteins identified by this approach were novel, uncharacterized membrane transporters or proteins associated with RNA metabolism. In conclusion, MCDM automated the decision making using well known algorithms while conformal prediction intervals varied significantly across the 8000+ proteins of T. gondii. Highly ranked proteins (e.g. the top 100) typically generated low prediction intervals, providing high levels of confidence in their ranks.

Toxoplasma↗

PubMed2024

Nanobodies: From High-Throughput Identification to Therapeutic Development.

The camelid single-domain antibody fragment, commonly referred to as a nanobody, achieves the targeting power of conventional monoclonal antibodies (mAbs) at only a fraction of their size. Isolated from camelid species (including llamas, alpacas, and camels), their small size at ∼15 kDa, low structural complexity, and high stability compared with conventional antibodies have propelled nanobody technology into the limelight of biologic development. Nanobodies are proving themselves to be a potent complement to traditional mAb therapies, showing success in the treatment of, for example, autoimmune diseases and cancer, and more recently as therapeutic options to treat infectious diseases caused by rapidly evolving biological targets such as the SARS-CoV-2 virus. This review highlights the benefits of applying a proteomic approach to identify diverse nanobody sequences against a single antigen. This proteomic approach coupled with conventional yeast/phage display methods enables the production of highly diverse repertoires of nanobodies able to bind the vast epitope landscape of an antigen, with epitope sampling surpassing that of mAbs. Additionally, we aim to highlight recent findings illuminating the structural attributes of nanobodies that make them particularly amenable to comprehensive antigen sampling and to synergistic activity-underscoring the powerful advantage of acquiring a large, diverse nanobody repertoire against a single antigen. Lastly, we highlight the efforts being made in the clinical development of nanobodies, which have great potential as powerful diagnostic reagents and treatment options, especially when targeting infectious disease agents.

Animals↗

PubMed2024

Assessing nanobody interaction with SARS-CoV-2 Nsp9.

The interaction between SARS-CoV-2 non-structural protein Nsp9 and the nanobody 2NSP90 was investigated by NMR spectroscopy using the paramagnetic perturbation methodology PENELOP (Paramagnetic Equilibrium vs Nonequilibrium magnetization Enhancement or LOss Perturbation). The Nsp9 monomer is an essential component of the replication and transcription complex (RTC) that reproduces the viral gRNA for subsequent propagation. Therefore preventing Nsp9 recruitment in RTC would represent an efficient antiviral strategy that could be applied to different coronaviruses, given the Nsp9 relative invariance. The NMR results were consistent with a previous characterization suggesting a 4:4 Nsp9-to-nanobody stoichiometry with the occurrence of two epitope pairs on each of the Nsp9 units that establish the inter-dimer contacts of Nsp9 tetramer. The oligomerization state of Nsp9 was also analyzed by molecular dynamics simulations and both dimers and tetramers resulted plausible. A different distribution of the mapped epitopes on the tetramer surface with respect to the former 4:4 complex could also be possible, as well as different stoichiometries of the Nsp9-nanobody assemblies such as the 2:2 stoichiometry suggested by the recent crystal structure of the Nsp9 complex with 2NSP23 (PDB ID: 8dqu), a nanobody exhibiting essentially the same affinity as 2NSP90. The experimental NMR evidence, however, ruled out the occurrence in liquid state of the relevant Nsp9 conformational change observed in the same crystal structure.

Viral Nonstructural Proteins↗

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

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↗

PubMed2025

Investigating genetic, antigenic, and structural diversity in the Neisseria gonorrhoeae outer membrane protein, PorB: implications for vaccine design.

UNLABELLED: Vaccines targeting Neisseria gonorrhoeae are needed to reduce disease burden and help address the problem of antimicrobial resistance, with an understanding of relationships between gonococcal genetics and molecules influencing diversity, infection, and the immune response essential for developing effective vaccine formulations. Whole-genome sequence data can be used to investigate these relationships among thousands of gonococcal isolates, allowing the study of antigenic diversity on a population scale. Such analyses typically examine antigenic diversity occurring in complete protein sequences, generating mean diversity indices and phylogenetic analyses that can inform on vaccine potential; however, to detect and measure the immune responses elicited, epitope characterization within an antigen helps guide vaccine formulations, with epitopes commonly located in surface-exposed regions of a protein. Here, we analyzed the genetic diversity of the major gonococcal antigen, PorB, in WGS from 22,227 N. gonorrhoeae isolates. We characterized the diversity of all eight surface-exposed outer membrane loops, or variable regions (VRs), and generated a PorB VR subtyping scheme to facilitate the global and temporal detection of circulating PorB subtypes. These analyses identified the presence of dominant VR combinations that persisted over time, indicative of (i) epistatic interactions between VRs and (ii) positive selection. Strain-specific, anti-PorB IgG responses directed toward distinct VR subtypes were detected in sera obtained from participants vaccinated with 4CMenB. The deconstruction of PorB into each surface-exposed loop provides a powerful approach for evaluating vaccine candidates: the methods used here allow immunodominant regions to be detected, which is invaluable for further vaccine investigations. IMPORTANCE: In the context of rising global gonorrhea cases, the development of vaccines becomes a priority; however, N. gonorrhoeae antigenic diversity and its ability to evade the immune system complicate vaccine development. This study characterizes the genetic diversity of the outer membrane protein, PorB, a key component of the outer membrane and a major gonococcal antigen. Using genomics and machine-learning techniques, this research identified dominant PorB variants that drive the immune response, proposing potential vaccine candidates and improving our understanding of the evolutionary forces maintaining genome structure and biological fitness. Understanding these processes is crucial for designing vaccines that effectively target N. gonorrhoeae and combat the spread of multidrug-resistant gonococci.

Neisseria gonorrhoeae↗

PubMed2025

Genome-to-genome analysis reveals associations between human and mycobacterial genetic variation in tuberculosis patients from Tanzania.

The risk and prognosis of tuberculosis (TB) are influenced by a complex interplay between human and bacterial genetic factors. While previous genomic studies have largely examined human and bacterial genomes separately, we adopted an integrated approach to uncover host-pathogen interactions. We leveraged paired human and Mycobacterium tuberculosis (M.tb) genomic data from 1000 adult TB patients from Tanzania and used a "genome-to-genome" approach to search for associations between human and M.tb genetic variants and to identify interacting genetic loci. Our analyses revealed two significant host-pathogen genetic associations. The first significant association (p = 4.7e-11) links a human intronic variant in PRDM15 (rs12151990), a gene involved in apoptosis regulation, with an M.tb variant in Rv2348c (I101M), which encodes a T cell-stimulating antigen. The second significant association (p = 6.3e-11) connects a human intergenic variant near TIMM21 and FBXO15 (rs75769176) - also associated with TB severity (p = 0.04) - with an M.tb variant in FixA (T67M). While FBXO15 is involved in the regulation of antigen processing and TIMM21 affects mitochondrial function, FixA's role remains undefined due to limited functional characterization. Additionally, we observed that a group of M.tb T cell epitope variants were significantly associated with HLA-DRB1 variation, suggesting that, despite their rarity, certain epitopes may still be subjected to immune selective pressure. Together, these findings identify previously unknown sites of genomic conflicts between humans and M.tb, advancing our understanding of how this pathogen evades selection pressure and persist in human populations.

Humans↗

PubMed2026

Identification of circulating parasite and host biomarkers in the serum proteome of Trypanosoma vivax-infected sheep under immunosuppression.

Bovine trypanosomiasis, caused by Trypanosoma vivax, presents a major threat to livestock health, primarily due to the lack of efficient field diagnostic tools. This study aimed to identify potential parasite and host-derived biomarkers through a longitudinal proteomic analysis of serum from sheep experimentally infected with a T. vivax isolate. Utilizing LC-MS/MS and bioinformatics, 154 proteins were identified, comprising 150 host (Ovis aries) and four pathogen proteins. Principal Component Analysis (PCA) demonstrated a clear separation of samples according to infection stages: Control, Infection (15 parasites/field), and Peak Infection (30-60 parasites/field) Among the parasite proteins, TvY486_0014340, TvY486_0040500, and TvY486_0042480 were identified as candidate antigens for future evaluation. In silico analysis revealed these proteins contain multiple B-cell epitopes with no cross-reactivity to related Trypanosoma species, supporting their potential for immunodiagnostic development. Additionally, three host proteins-folate receptor 3 (FOLR3) and complement components C1QA and C1QC-were significantly modulated across all infection phases. The upregulation of FOLR3 likely reflects a compensatory response to parasite-induced anemia, while the downregulation of C1Q components suggests immune evasion strategies. These findings highlight specific parasite antigens and host regulatory patterns that may serve as candidate biomarkers for the diagnosis and monitoring of T. vivax infection, facilitating the development of improved point-of-care assays.

Animals↗