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Computational vaccinology includes epitope mapping, antigen selection, and immunogen design using computational tools. Tools that facilitate the prediction of immune response to biothreats, emerging infectious diseases, and cancers can accelerate the design of novel and next generation vaccines and their delivery to the clinic. Over the past 20 years, vaccinologists, bioinformatics experts, and advanced programmers based in Providence, Rhode Island, USA have advanced the development of an integrated toolkit for vaccine design called iVAX, that is secure and user-accessible by internet. This integrated set of immunoinformatic tools comprises algorithms for scoring and triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, re-engineering or eliminating regulatory T cell epitopes, and re-designing antigens to induce immunogenicity and protection against disease for humans and livestock. Commercial and academic applications of iVAX have included identifying immunogenic T cell epitopes in the development of a T-cell based human multi-epitope Q fever vaccine, designing novel influenza vaccines, identifying cross-conserved T cell epitopes for a malaria vaccine, and analyzing immune responses in clinical vaccine studies. Animal vaccine applications to date have included viral infections of pigs such as swine influenza A, PCV2, and African Swine Fever. \"Rapid-Fire\" applications for biodefense have included a demonstration project for Lassa Fever and Q fever. As recent infectious disease outbreaks underscore the significance of vaccine-driven preparedness, the integrated set of tools available on the iVAX toolkit stand ready to help vaccine developers deliver genome-derived, epitope-driven vaccines.

The beginning of 2020 has seen the emergence of COVID-19 outbreak caused by a novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). There is an imminent need to better understand this new virus and to develop ways to control its spread. In this study, we sought to gain insights for vaccine design against SARS-CoV-2 by considering the high genetic similarity between SARS-CoV-2 and SARS-CoV, which caused the outbreak in 2003, and leveraging existing immunological studies of SARS-CoV. By screening the experimentally-determined SARS-CoV-derived B cell and T cell epitopes in the immunogenic structural proteins of SARS-CoV, we identified a set of B cell and T cell epitopes derived from the spike (S) and nucleocapsid (N) proteins that map identically to SARS-CoV-2 proteins. As no mutation has been observed in these identified epitopes among the 120 available SARS-CoV-2 sequences (as of 21 February 2020), immune targeting of these epitopes may potentially offer protection against this novel virus. For the T cell epitopes, we performed a population coverage analysis of the associated MHC alleles and proposed a set of epitopes that is estimated to provide broad coverage globally, as well as in China. Our findings provide a screened set of epitopes that can help guide experimental efforts towards the development of vaccines against SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.

Streptococcus agalactiae (Group B Streptococcus, GBS) is a multi-host pathogen, even causing life-threatening infections in newborns. Vaccination with GBS crossed serotypes vaccine is one of the best options for long-term infection control. Here we built a comprehensive in silico epitope-prediction workflow pipeline to design a multivalent m ultiepitope-based subunit v accine containing 11 epitopes against S treptococcus a galactiae (MVSA). All epitopes in MVSA came from the proteins which were antigenic-confirmed, virulent-associated, surface-exposed and conserved in ten GBS serotypes. The in-silico analysis showed MVSA had potential to evoke strong immune responses and enable worldwide population coverage. To validate MVSA protection efficacy against GBS infection, immune protection experiments were performed in a mouse model. Importantly, MVSA induced a high titre of antibodies, significant proliferation of mice splenocytes and elicited strong protection against lethal-dose challenge with a survival rate of 100% in mice after three vaccinations. Meanwhile, the polyclonal antibody against MVSA did not only inhibit for growth of GBS from six crucial serotypes in vitro, but also protect 100% naive mice from GBS lethal challenge. These active and passive immunity assay results suggested that MVSA could therefore be an efficacious multi-epitope vaccine against GBS infection.

An effective vaccine against syphilis could aid current control measures to reduce the incidence of infection. Protective immunity from the syphilis agent, Treponema pallidum subsp. pallidum (T. pallidum), is associated with pathogen clearance by phagocytosis, supporting that immunization with an effective vaccine candidate should elicit opsonic antibodies to key epitopes at the host-pathogen interface. The T. pallidumrepeat (Tpr) proteins are putative β-barrel outer membrane porins with ten predicted extracellular loops. Here, we immunized three groups of eight rabbits with either a combination of three recombinant variants of the full-length TprC antigen, the TprD2 protein, or the conserved NH2-terminal region of TprK, with the latter antigen already known to induce incomplete protection in immunized rabbits. Compared to unimmunized controls, rabbits immunized with the three TprC variants or the TprK fragment exhibited attenuated primary chancres, reduced treponemal burden at the challenge sites, and limited pathogen dissemination to lymph nodes. Immunization with TprD2, alone did not produce comparable results. Strong humoral and cellular responses against TprC and TprK were elicited by immunization, and functional analyses supported the induction of opsonizing antibodies. Epitope mapping performed using TprC- and TprK-specific synthetic peptides and phage immunoprecipitation-sequencing identified a subset of highly reactive sequences and demonstrated immunity to predicted surface-exposed epitopes across multiple Tpr paralogs, which explained the significant, albeit incomplete protection measured post-challenge. These data advance TprC and TprK as syphilis vaccine candidates and highlight several correlates of their protection that deserve further examination.

Background CD4⁺ T cell responses are key to adaptive immunity, yet the mechanisms underlying peptide selection and immunodominance across MHC class II variants in humans remain poorly defined. Two non-mutually exclusive models — First Bind-then cut (FBtc) and First Cut-then bind (FCtb) — have been proposed to explain immunodominant peptide selection, but experimental evidence in humans is mostly limited to a single allotype (HLA-DRB1*01:01). Methods To generalize processing mechanisms across DRB1 alleles we developed an integrative strategy combining in silico prediction and a reconstituted antigen processing system. The independent and combined outcome of both approaches was validated on curated SARS-CoV-2 epitope data (IEDB) for responses to the Spike and Nucleocapsid proteins across a panel of 11 DRB1 allotypes, covering over 90% of European Caucasian populations. Potential immunogenic regions identified by the combination of both methods enabled the design of minimalistic peptide pools whose performance was validated via flow cytometry and ELISpot assays in post-Covid19 and pre-pandemic donors. Mechanistic insights for the selection of immunodominant peptides were derived analyzing biophysical parameters and proteolysis of the model antigens. Results Three prediction tools used showed limited concordance for some allotypes (< 5%), but their combined output for all allotypes considered revealed potential immunogenic hotspots in the model antigens. Complementary, the reconstituted in vitro system identified allotype-dependent and promiscuous peptide candidates. Minimal peptide pools designed from the overlap of both methods featured improved performance to identify IEDB entries and induced robust CD4⁺ T cell activation in post-COVID-19 donors. Mechanistic modeling classified most immunodominant peptides from the Spike protein as arising via FCtb while FBtc predominated for Nucleocapsid. Epitope selection pathways are therefore antigen-dependent defined by proteolytic resistance and solvent accessibility. Conclusions We establish a scalable, genomics-informed framework for decoding CD4⁺ T cell immunodominance across diverse HLA contexts. Our findings reveal that antigen-intrinsic features govern the preferential processing pathway — FCtb for Spike and FBtc for Nucleocapsid — and validate the utility of minimal peptide pools for population-level immune-monitoring. These insights inform the design of personalized immunotherapies and broadly effective vaccines.

Background Predicting vaccine efficacy against emerging pathogen strains is a significant problem in human and animal vaccine design. T‐cell epitope cross‐conservation may play an important role in cross‐strain vaccine efficacy. While influenza A virus (IAV) hemagglutination inhibition (HI) antibody titers are widely used to predict protective efficacy of 1 IAV vaccine against new strains, no similar correlate of protection has been identified for T‐cell epitopes. Objective We developed a computational method (EpiCC) that facilitates pairwise comparison of protein sequences based on an immunological property—T‐cell epitope content—rather than sequence identity, and evaluated its ability to classify swine IAV strain relatedness to estimate cross‐protective potential of a vaccine strain for circulating viruses. Methods T‐cell epitope relatedness scores were assessed for 23 IAV HA sequences representing the major H1 swine IAV phylo‐clusters circulating in North American swine and HA sequences in a commercial inactivated vaccine (FluSure XP®). Scores were compared to experimental data from previous efficacy studies. Results Higher EpiCC scores were associated with greater protection by the vaccine against strains for 23 field IAV strain vaccine comparisons. A threshold for EpiCC relatedness associated with full or partial protection in the absence of cross‐reactive HI antibodies was identified. EpiCC scores for field strains for which FluSure protective efficacy is not yet available were also calculated. Conclusion EpiCC thresholds can be evaluated for predictive accuracy of protection in future efficacy studies. EpiCC may also complement HI cross‐reactivity and phylogeny for selection of influenza strains in vaccine development.

Background We previously introduced PCPS (Proteasome Cleavage Prediction Server), a web-based tool to predict proteasome cleavage sites using n-grams . Here, we evaluated the ability of PCPS immunoproteasome cleavage model to discriminate CD8 + T cell epitopes. Results We first assembled an epitope dataset consisting of 844 unique virus-specific CD8 + T cell epitopes and their source proteins. We then analyzed cleavage predictions by PCPS immunoproteasome cleavage model on this dataset and compared them with those provided by a related method implemented by NetChop web server. PCPS was clearly superior to NetChop in term of sensitivity (0.89 vs. 0.79) but somewhat inferior with regard to specificity (0.55 vs. 0.60). Judging by the Mathew’s Correlation Coefficient, PCPS predictions were overall superior to those provided by NetChop (0.46 vs. 0.39). We next analyzed the power of C-terminal cleavage predictions provided by the same PCPS model to discriminate CD8 + T cell epitopes, finding that they could be discriminated from random peptides with an accuracy of 0.74. Following these results, we tuned the PCPS web server to predict CD8 + T cell epitopes and predicted the entire SARS-CoV-2 epitope space. Conclusions We report an improved version of PCPS named iPCPS for predicting proteasome cleavage sites and peptides with CD8 + T cell epitope features. iPCPS is available for free public use at https://imed.med.ucm.es/Tools/pcps/ .

[This corrects the article DOI: 10.3389/fimmu.2021.621138.].[This corrects the article DOI: 10.3389/fimmu.2021.621138.].