A combined view of B-cell epitope features in antigens

Exploring the genetic diversity pattern of PvEBP/DBP2: A promising candidate for an effective Plasmodium vivax vaccine

Malaria remains a public health challenge. Since many control strategies have proven ineffective in eradicating this disease, new strategies are required, among which the design of a multivalent vaccine stands out. However, the effectiveness of this strategy has been hindered, among other reasons, by the genetic diversity observed in parasite antigens. In Plasmodium vivax, the Erythrocyte Binding Protein (PvEBP, also known as DBP2) is an alternate ligand to Duffy Binding Protein (DBP); given its structural resemblance to DBP, EBP/DBP2 is proposed as a promising antigen for inclusion in vaccine design. However, the extent of genetic diversity within the locus encoding this protein has not been comprehensively assessed. Thus, this study aimed to characterize the genetic diversity of the locus encoding the P. vivax EBP/DBP2 protein and to determine the evolutionary mechanisms modulating this diversity. Several intrapopulation genetic variation parameters were estimated using 36 gene sequences of PvEBP/DBP2 from Colombian P. vivax clinical isolates and 186 sequences available in databases. The study then evaluated the worldwide genetic structure and the evolutionary forces that may influence the observed patterns of genetic variation. It was found that the PvEBP/DBP2 gene exhibits one of the lowest levels of genetic diversity compared to other vaccine-candidate antigens. Four major haplotypes were shared worldwide. Analysis of the protein's 3D structure and epitope prediction identified five regions with potential antigenic properties. The results suggest that the PvEBP/DBP2 protein possesses ideal characteristics to be considered when designing a multivalent effective antimalarial vaccine against P. vivax.

Brewpitopes: a pipeline to refine B-cell epitope predictions during public health emergencies

The application of B-cell epitope identification to develop therapeutic antibodies and vaccine candidates is well established. However, the validation of epitopes is time-consuming and resource-intensive. To alleviate this, in recent years, multiple computational predictors have been developed in the immunoinformatics community. Brewpitopes is a pipeline that curates bioinformatic B-cell epitope predictions obtained by integrating different state-of-the-art tools. We used additional computational predictors to account for subcellular location, glycosylation status, and surface accessibility of the predicted epitopes. The implementation of these sets of rational filters optimizes in vivo antibody recognition properties of the candidate epitopes. To validate Brewpitopes, we performed a proteome-wide analysis of SARS-CoV-2 with a particular focus on S protein and its variants of concern. In the S protein, we obtained a fivefold enrichment in terms of predicted neutralization versus the epitopes identified by individual tools. We analyzed epitope landscape changes caused by mutations in the S protein of new viral variants that were linked to observed immune escape evidence in specific strains. In addition, we identified a set of epitopes with neutralizing potential in four SARS-CoV-2 proteins (R1AB, R1A, AP3A, and ORF9C). These epitopes and antigenic proteins are conserved targets for viral neutralization studies. In summary, Brewpitopes is a powerful pipeline that refines B-cell epitope bioinformatic predictions during public health emergencies in a high-throughput capacity to facilitate the optimization of experimental validation of therapeutic antibodies and candidate vaccines.

Novel insights into the somatic proteome of Strongyloides stercoralis infective third-stage larvae

BACKGROUND

Strongyloidiasis is a neglected tropical disease affecting an estimated 600 million people, particularly in resource-limited settings. The infection can persist lifelong due to unusual auto-infective cycle of Strongyloides stercoralis. The lack of a diagnostic gold standard and limited knowledge of the mechanisms underpinning this chronic infection are key issues in disease management. To date, only a few proteomics studies have been conducted to elucidate the molecular mechanisms associated with Strongyloides parasitism or to highlight novel immunological markers, with the result that our knowledge of S. stercoralis proteome remains limited. This study aims at expanding the characterization of S. stercoralis infective larvae (iL3) in order to further explore the mechanisms of parasitism and to highlight possible novel targets for serodiagnosis.

METHODS

iL3 obtained from an infected subject were analysed by high-throughput tandem mass spectrometry. To achieve a more comprehensive characterization of the iL3 proteome we analysed the experimental dataset using an automatic search strategy combined with manual annotation, which included gene ontology (GO) analysis, InterPro annotation, assessment of the homology with Homo sapiens and other pathogens of clinical importance and B-cell epitope prediction.

RESULTS

Our pipeline identified 430 S. stercoralis proteins, 187 (43%) of which were uncharacterized. Oxidoreductases and peptidases were amongst the most represented protein categories, as highlighted by molecular function GO analyses, while membrane and mitochondrial proteins were the most represented cellular component GO categories. A high proportion of proteins bearing the CAP, SCP or thioredoxin domain or belonging to cysteine-rich secretory, transthyretin-like or peptidase protein families were also identified. Additionally, we highlighted nine proteins displaying low homology with H. sapiens or other related pathogens and bearing amino acid sequences with immunogenic properties.

CONCLUSIONS

Our comprehensive description and annotation of the S. stercoralis iL3 proteome contribute to expanding the 'omics characterization of this parasite and provide experimental evidence on the most represented proteins associated with S. stercoralis parasitism, as inferred from genomic and transcriptomic data. Moreover, novel candidate immunogenic proteins to be evaluated as novel serological diagnostic markers are highlighted.

NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-cell Epitopes

Identification of B-cell epitopes (BCEs) plays an essential role in the development of peptide vaccines and immuno-diagnostic reagents, as well as antibody design and production. In this work, we generated a large benchmark dataset comprising 124,879 experimentally supported linear epitope-containing regions in 3567 protein clusters from over 1.3 million B cell assays. Analysis of this curated dataset showed large pathogen diversity covering 176 different families. The accuracy in linear BCE prediction was found to strongly vary with different features, while all sequence-derived and structural features were informative. To search more efficient and interpretive feature representations, a ten-layer deep learning framework for linear BCE prediction, namely NetBCE, was developed. NetBCE achieved high accuracy and robust performance with the average area under the curve (AUC) value of 0.8455 in five-fold cross-validation through automatically learning the informative classification features. NetBCE substantially outperformed the conventional machine learning algorithms and other tools, with more than 22.06% improvement of AUC value compared to other tools using an independent dataset. Through investigating the output of important network modules in NetBCE, epitopes and non-epitopes tended to be presented in distinct regions with efficient feature representation along the network layer hierarchy. The NetBCE is freely available at https://github.com/bsml320/NetBCE.

The Correlation between Subolesin-Reactive Epitopes and Vaccine Efficacy

Vaccination is an environmentally-friendly alternative for tick control. The tick antigen Subolesin (SUB) has shown protection in vaccines for the control of multiple tick species in cattle. Additionally, recent approaches in quantum vaccinomics have predicted SUB-protective epitopes and the peptide sequences involved in protein−protein interactions in this tick antigen. Therefore, the identification of B-cell−reactive epitopes by epitope mapping using a SUB peptide array could be essential as a novel strategy for vaccine development. Subolesin can be used as a model to evaluate the effectiveness of these approaches for the identification of protective epitopes related to vaccine protection and efficacy. In this study, the mapping of B-cell linear epitopes of SUB from three different tick species common in Uganda (Rhipicephalus appendiculatus, R. decoloratus, and Amblyomma variegatum) was conducted using serum samples from two cattle breeds immunized with SUB-based vaccines. The results showed that in cattle immunized with SUB from R. appendiculatus (SUBra) all the reactive peptides (Z-score > 2) recognized by IgG were also significant (Z-ratio > 1.96) when compared to the control group. Additionally, some of the reactive peptides recognized by IgG from the control group were also recognized in SUB cocktail−immunized groups. As a significant result, cattle groups that showed the highest vaccine efficacy were Bos indicus immunized with a SUB cocktail (92%), and crossbred cattle were immunized with SUBra (90%) against R. appendiculatus ticks; the IgG from these groups recognized overlapping epitopes from the peptide SPTGLSPGLSPVRDQPLFTFRQVGLICERMMKERESQIRDEYDHVLSAKLAEQYDTFVKFTYDQKRFEGATPSYLS (Z-ratio > 1.96), which partially corresponded to a Q38 peptide and the SUB protein interaction domain. These identified epitopes could be related to the protection and efficacy of the SUB-based vaccines, and new chimeras containing these protective epitopes could be designed using this new approach.

Designing an epitope vaccine against Dermatophagoides pteronyssinus: An in silico study

The house dust mite, Dermatophagoides pteronyssinus, is a major source of the inhaled allergen Der p 1, which causes immunoglobulin E (IgE)-mediated hypersensitivity reactions manifesting in allergic diseases. To date, no drugs or vaccines effectively treat or prevent Der p 1 sensitization. We applied in silico immunoinformatics to design T-cell and B-cell epitopes that were specified and developed from the allergen Der p 1 of D. pteronyssinus. We identified the conserved epitope areas by predicting the accessibility and flexibility of B-cell epitopes, and the percentage of human leukocyte antigen representing T cells. Molecular docking using HADDOCK software indicated three optimal clusters: cluster 6 (z-score: -2.1), cluster 1 (z-score: -1.2), and cluster 3 (z-score: -0.6). The most negative Z-score was found in cluster 6, which represented three epitopes. The interaction between A chain proteins (IgE protein residues) and B chains (Der p 1 protein residues) exhibited a knowledge-based FADE and contact value >1, suggesting the best protein interactions occurred in the conserved area. Molecular dynamic simulation further predicted the stable nature of Der p 1 protein. The IQRDNGYQP region is the best candidate to be utilized as a D. pteronyssinus epitope vaccine, which could be used in the development of allergen-specific immunotherapy.

Immunoinformatics prediction of overlapping CD8+ T-cell, IFN-γ and IL-4 inducer CD4+ T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2)

At the beginning of the year 2020, the world was struck with a global pandemic virus referred to as SARS-CoV-2 (COVID-19) which has left hundreds of thousands of people dead. To control this virus, vaccine design becomes imperative. In this study, potential epitopes-based vaccine candidates were explored. Six hundred (600) genomes of SARS-CoV-2 were retrieved from the viPR database to generate CD8⁺ T-cell, CD4+ T-cell and linear B-cell epitopes which were screened for antigenicity, immunogenicity and non-allergenicity. The results of this study provide 19 promising candidate CD8⁺ T-cell epitopes that strongly overlap with 8 promising B-cells epitopes. Another 19 CD4⁺ T-cell epitopes were also identified that can induce IFN-γ and IL-4 cytokines. The most conserved MHC-I and MHC-II for both CD8⁺ and CD4⁺ T-cell epitopes are HLA-A*02:06 and HLA-DRB1*01:01 respectively. These epitopes also bound to Toll-like receptor 3 (TLR3). The population coverage of the conserved Major Histocompatibility Complex Human Leukocyte Antigen (HLA) for both CD8⁺ T-cell and CD4⁺ T-cell ranged from 65.6% to 100%. The detailed analysis of the potential epitope-based vaccine and their mapping to the complete COVID-19 genome reveals that they are predominantly found in the location of the surface (S) and membrane (M) glycoproteins suggesting the potential involvement of these structural proteins in the immunogenic response and antigenicity of the virus. Since the majority of the potential epitopes are located on M protein, the design of multi-epitope vaccine with the structural protein is highly promising though the whole M protein could also serve as a viable epitope for the development of an attenuated vaccine. Our findings provide a baseline for the experimental design of a suitable vaccine against SARS-CoV-2.

Exploring the out of sight antigens of SARS-CoV-2 to design a candidate multi-epitope vaccine by utilizing immunoinformatics approaches

SARS-CoV-2 causes a severe respiratory disease called COVID-19. Currently, global health is facing its devastating outbreak. However, there is no vaccine available against this virus up to now. In this study, a novel multi-epitope vaccine against SARS-CoV-2 was designed to provoke both innate and adaptive immune responses. The immunodominant regions of six non-structural proteins (nsp7, nsp8, nsp9, nsp10, nsp12 and nsp14) of SARS-CoV-2 were selected by multiple immunoinformatic tools to provoke T cell immune response. Also, immunodominant fragment of the functional region of SARS-CoV-2 spike (400-510 residues) protein was selected for inducing neutralizing antibodies production. The selected regions' sequences were connected to each other by furin-sensitive linker (RVRR). Moreover, the functional region of β-defensin as a well-known agonist for the TLR-4/MD complex was added at the N-terminus of the vaccine using (EAAAK)3 linker. Also, a CD4 + T-helper epitope, PADRE, was used at the C-terminal of the vaccine by GPGPG and A(EAAAK)2A linkers to form the final vaccine construct. The physicochemical properties, allergenicity, antigenicity, functionality and population coverage of the final vaccine construct were analyzed. The final vaccine construct was an immunogenic, non-allergen and unfunctional protein which contained multiple CD8 + and CD4 + overlapping epitopes, IFN-γ inducing epitopes, linear and conformational B cell epitopes. It could form stable and significant interactions with TLR-4/MD according to molecular docking and dynamics simulations. Global population coverage of the vaccine for HLA-I and II were estimated 96.2% and 97.1%, respectively. At last, the final vaccine construct was reverse translated to design the DNA vaccine. Although the designed vaccine exhibited high efficacy in silico, further experimental validation is necessary.