Design of a novel multi-epitope vaccine against Marburg virus using immunoinformatics studies.

Marburg virus (MARV) is a highly contagious and virulent agent belonging to Filoviridae family. MARV causes severe hemorrhagic fever in humans and non-human primates. Owing to its highly virulent nature, preventive approaches are promising for its control. There is currently no approved drug or vaccine against MARV, and management mainly involves supportive care to treat symptoms and prevent complications. Our aim was to design a novel multi-epitope vaccine (MEV) against MARV using immunoinformatics studies. In this study, various proteins (VP35, VP40 and glycoprotein precursor) were used and potential epitopes were selected. CTL and HTL epitopes covered 79.44% and 70.55% of the global population, respectively. The designed MEV construct was stable and expressed in Escherichia coli (E. coli) host. The physicochemical properties were also acceptable. MARV MEV candidate could predict comprehensive immune responses such as those of humoral and cellular in silico. Additionally, efficient interaction to toll-like receptor 3 (TLR3) and its agonist (ß-defensin) was predicted. There is a need for validation of these results using further in vitro and in vivo studies.

Characterization of Peptide Antibodies by Epitope Mapping Using Resin-Bound and Soluble Peptides.

Characterization of peptide antibodies through identification of their target epitopes is of utmost importance, as information about epitopes provide important knowledge, among others, for discovery and development of new therapeutics, vaccines, and diagnostics.This chapter describes a strategy for mapping of continuous peptide antibody epitopes using resin-bound and soluble peptides. The approach combines three different types of peptide sets for full characterization of peptide antibodies; (i) overlapping peptides, used to locate antigenic regions; (ii) truncated peptides, used to identify the minimal peptide length required for antibody binding; and (iii) substituted peptides, used to identify the key residues important for antibody binding and to determine the specific contribution of key residues. For initial screening, resin-bound peptides are used for epitope estimation, while soluble peptides subsequently are used for final epitope characterization and identification of critical hot spot residues. The combination of resin-bound peptides and soluble peptides for epitope mapping provides a time-saving and straightforward approach for characterization of antibodies recognizing continuous epitopes, which applies to peptide antibodies and occasionally antibodies directed to larger proteins as well.

Geometric epitope and paratope prediction.

MOTIVATION: Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the importance of geometric information. RESULTS: Specifically, we compare different geometric deep learning methods applied to proteins' inner (I-GEP) and outer (O-GEP) structures. We incorporate 3D coordinates and spectral geometric descriptors as input features to fully leverage the geometric information. Our research suggests that different geometrical representation information is useful for different tasks. Surface-based models are more efficient in predicting the binding of the epitope, while graph models are better in paratope prediction, both achieving significant performance improvements. Moreover, we analyze the impact of structural changes in antibodies and antigens resulting from conformational rearrangements or reconstruction errors. Through this investigation, we showcase the robustness of geometric deep learning methods and spectral geometric descriptors to such perturbations. AVAILABILITY AND IMPLEMENTATION: The python code for the models, together with the data and the processing pipeline, is open-source and available at https://github.com/Marco-Peg/GEP.

Structure-based design of a Plasmodium vivax Duffy-binding protein immunogen focuses the antibody response to functional epitopes.

The Duffy-binding protein (DBP) is a promising antigen for a malaria vaccine that would protect against clinical symptoms caused by Plasmodium vivax infection. Region II of DBP (DBP-II) contains the receptor-binding domain that engages host red blood cells, but DBP-II vaccines elicit many non-neutralizing antibodies that bind distal to the receptor-binding surface. Here, we engineered a truncated DBP-II immunogen that focuses the immune response to the receptor-binding surface. This immunogen contains the receptor-binding subdomain S1S2 and lacks the immunodominant subdomain S3. Structure-based computational design of S1S2 identified combinatorial amino acid changes that stabilized the isolated S1S2 without perturbing neutralizing epitopes. This immunogen elicited DBP-II-specific antibodies in immunized mice that were significantly enriched for blocking activity compared to the native DBP-II antigen. This generalizable design process successfully stabilized an integral core fragment of a protein and focused the immune response to desired epitopes to create a promising new antigen for malaria vaccine development.

Development of a first-in-class antibody and a specific assay for α-1,6-fucosylated prostate-specific antigen.

Prostate-specific antigen (PSA) levels are widely used to screen for prostate cancer, yet the test has poor sensitivity, specificity and predictive value, which leads to overdiagnosis and overtreatment. Alterations in the glycosylation status of PSA, including fucosylation, may offer scope for an improved biomarker. We sought to generate a monoclonal antibody (mAb) targeting α-1,6-fucosylated PSA (fuc-PSA) and to develop a tissue-based immunological assay for fuc-PSA detection. Immunogens representing fuc-PSA were used for immunisation and resultant mAbs were extensively characterised. The mAbs reacted specifically with fuc-PSA-specific glycopeptide, but not with aglycosylated PSA or glycan without the PSA peptide. Reactivity was confirmed using high-throughput surface plasmon resonance spectroscopy. X-ray crystallography investigations showed that the mAbs bound to an α-helical form of the peptide, whereas the native PSA epitope is linear. Protein unfolding was required for detection of fuc-PSA in patient samples. Peptide inhibition of fuc-PSA mAbs was observed with positive screening reagents, and target epitope specificity was observed in formalin-fixed, paraffin-embedded tissue samples. This research introduces a well-characterised, first-in-class antibody targeting fuc-PSA and presents the first crystal structure of an antibody demonstrating glycosylation-specific binding to a peptide.

GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity.

The interaction between T-cell receptors (TCRs) and peptides (epitopes) presented by major histocompatibility complex molecules (MHC) is fundamental to the immune response. Accurate prediction of TCR-epitope interactions is crucial for advancing the understanding of various diseases and their prevention and treatment. Existing methods primarily rely on sequence-based approaches, overlooking the inherent topology structure of TCR-epitope interaction networks. In this study, we present $GTE$, a novel heterogeneous Graph neural network model based on inductive learning to capture the topological structure between TCRs and Epitopes. Furthermore, we address the challenge of constructing negative samples within the graph by proposing a dynamic edge update strategy, enhancing model learning with the nonbinding TCR-epitope pairs. Additionally, to overcome data imbalance, we adapt the Deep AUC Maximization strategy to the graph domain. Extensive experiments are conducted on four public datasets to demonstrate the superiority of exploring underlying topological structures in predicting TCR-epitope interactions, illustrating the benefits of delving into complex molecular networks. The implementation code and data are available at https://github.com/uta-smile/GTE.

Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis.

The polymorphic membrane proteins (Pmps) are a family of autotransporters that play an important role in infection, adhesion and immunity in Chlamydia trachomatis. Here we show that the characteristic GGA(I,L,V) and FxxN tetrapeptide repeats fit into a larger repeat sequence, which correspond to the coils of a large beta-helical domain in high quality structure predictions. Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. While the tetrapeptide motifs themselves are predicted to play a structural role in folding and close stacking of the beta-helical backbone of the passenger domain, we found many of the interesting features of Pmps are localized to the side loops jutting out from the beta helix including protease cleavage, host cell adhesion, and B-cell epitopes; while T-cell epitopes are predominantly found in the beta-helix itself. This analysis more accurately defines the Pmp family of Chlamydia and may better inform rational vaccine design and functional studies.

Genetically Encoded Epitope Tag for Probing Lysine Acylation-Mediated Protein-Protein Interactions.

Histone lysine acetylation (Kac) and crotonylation (Kcr) marks mediate the recruitment of YEATS domains to chromatin. In this way, YEATS domain-containing proteins such as AF9 participate in the regulation of DNA-templated processes. Our previous study showed that the replacement of Kac/Kcr by a 2-furancarbonyllysine (Kfu) residue led to greatly enhanced affinity toward the AF9 YEATS domain, rendering Kfu-containing peptides useful chemical tools to probe the AF9 YEATS-Kac/Kcr interactions. Here, we report the genetic incorporation of Kfu in Escherichia coli and mammalian cells through the amber codon suppression technology. We develop a Kfu-containing epitope tag, termed RAY-tag, which can robustly and selectively engage with the AF9 YEATS domain in vitro and in cellulo. We further demonstrate that the fusion of RAY-tag to different protein modules, including fluorescent proteins and DNA binding proteins, can facilitate the interrogation of the histone lysine acylation-mediated recruitment of the AF9 YEATS domain in different biological contexts.

Investigation into Potential Allergenicity and Digestion-Resistant Linear Epitopes of Fish Skin Gelatin in Cell-Cultured Meat Scaffolds.

As a key component of cell-cultured fish, fish skin gelatin (FSG)-based cell scaffold provides support structures for cell growth, proliferation, and differentiation. However, there are potential allergenicity risks contained in FSG-based scaffolds. In this study, 3D edible scaffolds were prepared by phase separation method and showed a contact angle of less than 90°, which indicated that the scaffolds were favorable for cell adhesion. Besides, the swelling ratio was greater than 200%, implying a great potential to support cell growth. The sequence homology analysis indicated that FSG was prone to cross-reaction with collagen analogues. Additionally, a food allergic model was constructed and represented that mice gavaged with cod FSG exhibited higher levels of specific antibodies, mast cell degranulation, vascular permeability, and intestinal barrier impairment than those gavaged with pangasius and tilapias FSG. Its higher allergenicity might be attributed to a higher number of digestion-resistant linear epitopes. Moreover, the higher hydrolysis degree linked to the exposure of linear epitopes to promote the combination with IgE, which was also responsible for maintaining the higher allergenicity of cod FSG. This study clarifies allergenic risks in cell-cultured fish and further study will focus on the allergenicity reduction of FSG-based cell scaffolds.

N-glycosylation on hemagglutinin head reveals inter-branch antigenic variability of avian influenza virus H5-subtypes.

H5-subtype avian influenza virus (AIV) is globally prevalent and undergoes frequent antigenic drift, necessitating regular updates to vaccines. One of the many influencing elements that cause incompatibility between vaccinations and epidemic strains is the dynamic alteration of glycosylation sites. However, the biological significance of N-glycosylation in the viral evolution and antigenic changes is unclear. Here, we performed a systematic analysis of glycosylation sites on the HA1 subunit of H5N1, providing insights into the changes of primary glycosylation sites, including 140 N, 156 N, and 170 N within the antigenic epitopes of HA1 protein. Multiple recombinant viruses were then generated based on HA genes of historical vaccine strains and deactivated for immunizing SPF chickens. Inactivated recombinant strains showed relatively closer antigenicity compared to which has identical N-glycosylation patterns. The N-glycosylation modification discrepancy highlights the inter-branch antigenic diversity of H5-subtype viruses in avian influenza and serves as a vital foundation for improving vaccination tactics.

A Nanoparticle Vaccine Displaying Conserved Epitopes of the Preexisting Neutralizing Antibody Confers Broad Protection against SARS-CoV-2 Variants.

The rapid development of the SARS-CoV-2 vaccine has been used to prevent the spread of coronavirus 2019 (COVID-19). However, the ongoing and future pandemics caused by SARS-CoV-2 variants and mutations underscore the need for effective vaccines that provide broad-spectrum protection. Here, we developed a nanoparticle vaccine with broad protection against divergent SARS-CoV-2 variants. The corresponding conserved epitopes of the preexisting neutralizing (CePn) antibody were presented on a self-assembling Helicobacter pylori ferritin to generate the CePnF nanoparticle. Intranasal immunization of mice with CePnF nanoparticles induced robust humoral, cellular, and mucosal immune responses and a long-lasting immunity. The CePnF-induced antibodies exhibited cross-reactivity and neutralizing activity against different coronaviruses (CoVs). CePnF vaccination significantly inhibited the replication and pathology of SARS-CoV-2 Delta, WIV04, and Omicron strains in hACE2 transgenic mice and, thus, conferred broad protection against these SARS-CoV-2 variants. Our constructed nanovaccine targeting the conserved epitopes of the preexisting neutralizing antibodies can serve as a promising candidate for a universal SARS-CoV-2 vaccine.

Comparative Label-Free Proteomics Study on Celiac Disease-Active Epitopes in Common Wheat, Spelt, Durum Wheat, Emmer, and Einkorn.

Wheat species with various ploidy levels may be different regarding their immunoreactive potential in celiac disease (CD), but a comprehensive comparison of peptide sequences with known epitopes is missing. Thus, we used an untargeted liquid chromatography tandem mass spectrometry method to analyze the content of peptides with CD-active epitope in the five wheat species common wheat, spelt, durum wheat, emmer, and einkorn. In total, 494 peptides with CD-active epitope were identified. Considering the average of the eight cultivars of each species, spelt contained the highest number of different peptides with CD-active epitope (193 ± 12, mean ± SD). Einkorn showed the smallest variability of peptides (63 ± 4) but higher amounts of certain peptides compared to the other species. The wheat species differ in the presence and distribution of CD-active epitopes; hence, the entirety of peptides with CD-active epitope is crucial for the assessment of their immunoreactive potential.

Antigenic determinants driving serogroup-specific antibody response to Neisseria meningitidis C, W, and Y capsular polysaccharides: Insights for rational vaccine design.

Meningococcal glycoconjugate vaccines sourced from capsular polysaccharides (CPSs) of pathogenic Neisseria meningitidis strains are well-established measures to prevent meningococcal disease. However, the exact structural factors responsible for antibody recognition are not known. CPSs of Neisseria meningitidis serogroups Y and W differ by a single stereochemical center, yet they evoke specific immune responses. Herein, we developed specific monoclonal antibodies (mAbs) targeting serogroups C, Y, and W and evaluated their ability to kill bacteria. We then used these mAbs to dissect structural elements responsible for carbohydrate-protein interactions. First, Men oligosaccharides were screened against the mAbs using ELISA to select putative lengths representing the minimal antigenic determinant. Next, molecular interaction features between the mAbs and serogroup-specific sugar fragments were elucidated using STD-NMR. Moreover, X-ray diffraction data with the anti-MenW CPS mAb enabled the elucidation of the sugar-antibody binding mode. Our findings revealed common traits in the epitopes of all three sialylated serogroups. The minimal binding epitopes typically comprise five to six repeating units. Moreover, the O-acetylation of the neuraminic acid moieties was fundamental for mAb binding. These insights hold promise for the rational design of optimized meningococcal oligosaccharides, opening new avenues for novel production methods, including chemical or enzymatic approaches.

Structural and functional characterization of nanobodies that neutralize Omicron variants of SARS-CoV-2.

The Omicron strains of SARS-CoV-2 pose a significant challenge to the development of effective antibody-based treatments as immune evasion has compromised most available immune therapeutics. Therefore, in the 'arms race' with the virus, there is a continuing need to identify new biologics for the prevention or treatment of SARS-CoV-2 infections. Here, we report the isolation of nanobodies that bind to the Omicron BA.1 spike protein by screening nanobody phage display libraries previously generated from llamas immunized with either the Wuhan or Beta spike proteins. The structure and binding properties of three of these nanobodies (A8, H6 and B5-5) have been characterized in detail providing insight into their binding epitopes on the Omicron spike protein. Trimeric versions of H6 and B5-5 neutralized the SARS-CoV-2 variant of concern BA.5 both in vitro and in the hamster model of COVID-19 following nasal administration. Thus, either alone or in combination could serve as starting points for the development of new anti-viral immunotherapeutics.

Allergenicity and Linear Epitope Analysis of Scy p 8, an Allergen from Mud Crab.

Scy p 8 (triosephosphate isomerase) as a crab allergen in inducing distinct T-helper (Th) cell differentiation and a linear epitope associated with allergenicity remain elusive. In this study, mice sensitized with Scy p 8 exhibited significantly upregulated levels of IgE, IgG1, and IL-4 release, inducing a Th2 immune response. Moreover, the release of IFN-γ (Th1) and the levels of Treg cells were downregulated, while IL-17A (Th17) was upregulated, indicating that Scy p 8 disrupted the Th1/Th2 balance and Th17/Treg balance in mice. Furthermore, bioinformatics prediction and serum samples from crab-allergic patients and mice enabled the discovery of 8 linear epitopes of Scy p 8. Meanwhile, the analysis of peptide similarity and tertiary superposition revealed that 8 epitopes of Scy p 8 exhibited conservation across various species, potentially resulting in cross-reactivity. These findings possess the potential to enhance the comprehension of crab allergens, thereby establishing a foundation for investigating cross-reactivity.

Predicting TCR sequences for unseen antigen epitopes using structural and sequence features.

T-cell receptor (TCR) recognition of antigens is fundamental to the adaptive immune response. With the expansion of experimental techniques, a substantial database of matched TCR-antigen pairs has emerged, presenting opportunities for computational prediction models. However, accurately forecasting the binding affinities of unseen antigen-TCR pairs remains a major challenge. Here, we present convolutional-self-attention TCR (CATCR), a novel framework tailored to enhance the prediction of epitope and TCR interactions. Our approach utilizes convolutional neural networks to extract peptide features from residue contact matrices, as generated by OpenFold, and a transformer to encode segment-based coded sequences. We introduce CATCR-D, a discriminator that can assess binding by analyzing the structural and sequence features of epitopes and CDR3-ß regions. Additionally, the framework comprises CATCR-G, a generative module designed for CDR3-ß sequences, which applies the pretrained encoder to deduce epitope characteristics and a transformer decoder for predicting matching CDR3-ß sequences. CATCR-D achieved an AUROC of 0.89 on previously unseen epitope-TCR pairs and outperformed four benchmark models by a margin of 17.4%. CATCR-G has demonstrated high precision, recall and F1 scores, surpassing 95% in bidirectional encoder representations from transformers score assessments. Our results indicate that CATCR is an effective tool for predicting unseen epitope-TCR interactions. Incorporating structural insights enhances our understanding of the general rules governing TCR-epitope recognition significantly. The ability to predict TCRs for novel epitopes using structural and sequence information is promising, and broadening the repository of experimental TCR-epitope data could further improve the precision of epitope-TCR binding predictions.

Reinvestigation of the internal glycan rearrangement of Lewis a and blood group type H1 epitopes.

Protonated ions of fucose-containing oligosaccharides are prone to undergo internal glycan rearrangement which results in chimeric fragments that obfuscate mass-spectrometric analysis. Lack of accessible tools that would facilitate systematic analysis of glycans in the gas phase limits our understanding of this phenomenon. In this work, we use density functional theory modeling to interpret cryogenic IR spectra of Lewis a and blood group type H1 trisaccharides and to establish whether these trisaccharides undergo the rearrangement during gas-phase analysis. Structurally unconstrained search reveals that none of the parent ions constitute a thermodynamic global minimum. In contrast, predicted collision cross sections and anharmonic IR spectra provide a good match to available experimental data which allowed us to conclude that fucose migration does not occur in these antigens. By comparing the predicted structures with those obtained for Lewis x and blood group type H2 epitopes, we demonstrate that the availability of the mobile proton and a large difference in the relative stability of the parent ions and rearrangement products constitute the prerequisites for the rearrangement reaction.

Characterization of a novel format scFv×VHH single-chain biparatopic antibody against metal binding protein MtsA.

Biparatopic antibodies (bpAbs) are engineered antibodies that bind to multiple different epitopes within the same antigens. bpAbs comprise diverse formats, including fragment-based formats, and choosing the appropriate molecular format for a desired function against a target molecule is a challenging task. Moreover, optimizing the design of constructs requires selecting appropriate antibody modalities and adjusting linker length for individual bpAbs. Therefore, it is crucial to understand the characteristics of bpAbs at the molecular level. In this study, we first obtained single-chain variable fragments and camelid heavy-chain variable domains targeting distinct epitopes of the metal binding protein MtsA and then developed a novel format single-chain bpAb connecting these fragment antibodies with various linkers. The physicochemical properties, binding activities, complex formation states with antigen, and functions of the bpAb were analyzed using multiple approaches. Notably, we found that the assembly state of the complexes was controlled by a linker and that longer linkers tended to form more compact complexes. These observations provide detailed molecular information that should be considered in the design of bpAbs.

A native mass spectrometry approach to qualitatively elucidate interfacial epitopes of transient protein-protein interactions.

Native mass spectrometric analysis of TPR2A and GrpE with unpurified peptides derived from limited proteolysis of their respective PPI partners (HSP90 C-terminus and DnaK) facilitated efficient, qualitative identification of interfacial epitopes involved in transient PPI formation. Application of this approach can assist in elucidating interfaces of currently uncharacterised transient PPIs.

Multimodal Mass Spectrometry Identifies a Conserved Protective Epitope in S. pyogenes Streptolysin O.

An important element of antibody-guided vaccine design is the use of neutralizing or opsonic monoclonal antibodies to define protective epitopes in their native three-dimensional conformation. Here, we demonstrate a multimodal mass spectrometry-based strategy for in-depth characterization of antigen-antibody complexes to enable the identification of protective epitopes using the cytolytic exotoxin Streptolysin O (SLO) from Streptococcus pyogenes as a showcase. We first discovered a monoclonal antibody with an undisclosed sequence capable of neutralizing SLO-mediated cytolysis. The amino acid sequence of both the antibody light and the heavy chain was determined using mass-spectrometry-based de novo sequencing, followed by chemical cross-linking mass spectrometry to generate distance constraints between the antibody fragment antigen-binding region and SLO. Subsequent integrative computational modeling revealed a discontinuous epitope located in domain 3 of SLO that was experimentally validated by hydrogen-deuterium exchange mass spectrometry and reverse engineering of the targeted epitope. The results show that the antibody inhibits SLO-mediated cytolysis by binding to a discontinuous epitope in domain 3, likely preventing oligomerization and subsequent secondary structure transitions critical for pore-formation. The epitope is highly conserved across >98% of the characterized S. pyogenes isolates, making it an attractive target for antibody-based therapy and vaccine design against severe streptococcal infections.