In silico methods for immunogenicity risk assessment and human homology screening for therapeutic antibodies.

In silico immunogenicity risk assessment has been an important step in the development path for many biologic therapeutics, including monoclonal antibodies. Even if the source of a given biologic is 'fully human', T cell epitopes that are contained in the sequences of the biologic may activate the immune system, enabling the development of anti-drug antibodies that can reduce drug efficacy and may contribute to adverse events. Computational tools that identify T cell epitopes from primary amino acid sequences have been used to assess the immunogenic potential of therapeutic candidates for several decades. To facilitate larger scale analyses and accelerate preclinical immunogenicity risk assessment, our group developed an integrated web-based platform called ISPRI, (Immunogenicity Screening and Protein Re-engineering Interface) that provides hands-on access through a secure web-based interface for scientists working in large and mid-sized biotech companies in the US, Europe, and Japan. This toolkit has evolved and now contains an array of algorithms that can be used individually and/or consecutively for immunogenicity assessment and protein engineering. Most analyses start with the advanced epitope mapping tool (EpiMatrix), then proceed to identify epitope clusters using ClustiMer, and then use a tool called JanusMatrix to define whether any of the T cell epitope clusters may generate a regulatory T cell response which may diminish or eliminate anti-drug antibody formation. Candidates can be compared to similar products on a normalized immunogenicity scale. Should modifications to the biologic sequence be an option, a tool for moderating putative immunogenicity by editing T cell epitopes out of the sequence is available (OptiMatrix). Although this perspective discusses the in-silico immunogenicity risk assessment for monoclonal antibodies, bi-specifics, multi-specifics, and antibody-drug conjugates, the analysis of additional therapeutic modalities such as enzyme replacement proteins, blood factor proteins, CAR-T, gene therapy products, and peptide drugs is also made available on the ISPRI platform.

ISPRI (Interactive Screening and Protein Reengineering Interface): Integrated, cloud-based, comprehensive toolkit for Immunogenicity Risk Assessment.EpiMatrix Immunogenicity Score: Combined T effector and Treg Epitope Content per unit protein.Tregitopes: Treg Epitopes found in IgG Framework that have been shown to modulate antigen-specific effector T cell responses.ClustiMer: Tool for identifying epitope rich polypeptides from within a given protein sequence.JanusMatrix: Tool for Predicting Tolerance, Putative Treg Epitopes, and Anti-self-immune responses.OptiMatrix: Tool for modifying T cell epitope sequences to reduce (or enhance) MHC binding.

Neoadjuvant personalized cancer vaccines: the final frontier?

INTRODUCTION: Clinical trials of personalized cancer vaccines have shown that on-demand therapies that are manufactured for each patient, result in activated T cell responses against individual tumor neoantigens. However, their use has been traditionally restricted to adjuvant settings and late-stage cancer therapy. There is growing support for the implementation of PCV earlier in the cancer therapy timeline, for reasons that will be discussed in this review. AREAS COVERED: The efficacy of cancer vaccines may be to some extent dependent on treatment(s) given prior to vaccine administration. Tumors can undergo radical immunoediting following treatment with immunotherapies, such as checkpoint inhibitors, which may affect the presence of the very mutations targeted by cancer vaccines. This review will cover the topics of neoantigen cancer vaccines, tumor immunoediting, and therapy timing. EXPERT OPINION: Therapy timing remains a critical topic to address in optimizing the efficacy of personalized cancer vaccines. Most personalized cancer vaccines are being evaluated in late-stage cancer patients and after treatment with checkpoint inhibitors, but they may offer a greater benefit to the patient if administered in earlier clinical settings, such as the neoadjuvant setting, where patients are not facing T cell exhaustion and/or a further compromised immune system.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning.

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

Does human homology reduce the potential immunogenicity of non-antibody scaffolds?

Biologics developers are moving beyond antibodies for delivery of a wide range of therapeutic interventions. These non-antibody modalities are often based on 'natural' protein scaffolds that are modified to deliver bioactive sequences. Both human-derived and non-human-sourced scaffold proteins have been developed. New types of "non-antibody" scaffolds are still being discovered, as they offer attractive alternatives to monoclonals due to their smaller size, improved stability, and ease of synthesis. They are believed to have low immunogenic potential. However, while several human-sourced protein scaffolds have not been immunogenic in clinical studies, this may not predict their overall performance in other therapeutic applications. A preliminary evaluation of their potential for immunogenicity is warranted. Immunogenicity risk potential has been clearly linked to the presence of T "helper" epitopes in the sequence of biologic therapeutics. In addition, tolerogenic epitopes are present in some human proteins and may decrease their immunogenic potential. While the detailed sequences of many non-antibody scaffold therapeutic candidates remain unpublished, their backbone sequences are available for review and analysis. We assessed 12 example non-antibody scaffold backbone sequences using our epitope-mapping tools (EpiMatrix) for this perspective. Based on EpiMatrix scoring, their HLA DRB1-restricted T cell epitope content appears to be lower than the average protein, and sequences that may act as tolerogenic epitopes are present in selected human-derived scaffolds. Assessing the potential immunogenicity of scaffold proteins regarding self and non-self T cell epitopes may be of use for drug developers and clinicians, as these exciting new non-antibody molecules begin to emerge from the preclinical pipeline into clinical use.

Identification of immunodominant T cell epitopes induced by natural Zika virus infection.

Zika virus (ZIKV) is a flavivirus primarily transmitted by Aedes species mosquitoes, first discovered in Africa in 1947, that disseminated through Southeast Asia and the Pacific Islands in the 2000s. The first ZIKV infections in the Americas were identified in 2014, and infections exploded through populations in Brazil and other countries in 2015/16. ZIKV infection during pregnancy can cause severe brain and eye defects in offspring, and infection in adults has been associated with higher risks of Guillain-Barré syndrome. We initiated a study to describe the natural history of Zika (the disease) and the immune response to infection, for which some results have been reported. In this paper, we identify ZIKV-specific CD4+ and CD8+ T cell epitopes that induce responses during infection. Two screening approaches were utilized: an untargeted approach with overlapping peptide arrays spanning the entire viral genome, and a targeted approach utilizing peptides predicted to bind human MHC molecules. Immunoinformatic tools were used to identify conserved MHC class I supertype binders and promiscuous class II binding peptide clusters predicted to bind 9 common class II alleles. T cell responses were evaluated in overnight IFN-γ ELISPOT assays. We found that MHC supertype binding predictions outperformed the bulk overlapping peptide approach. Diverse CD4+ T cell responses were observed in most ZIKV-infected participants, while responses to CD8+ T cell epitopes were more limited. Most individuals developed a robust T cell response against epitopes restricted to a single MHC class I supertype and only a single or few CD8+ T cell epitopes overall, suggesting a strong immunodominance phenomenon. Noteworthy is that many epitopes were commonly immunodominant across persons expressing the same class I supertype. Nearly all of the identified epitopes are unique to ZIKV and are not present in Dengue viruses. Collectively, we identified 31 immunogenic peptides restricted by the 6 major class I supertypes and 27 promiscuous class II epitopes. These sequences are highly relevant for design of T cell-targeted ZIKV vaccines and monitoring T cell responses to Zika virus infection and vaccination.

Immunogenicity risk assessment of synthetic peptide drugs and their impurities.

Peptide drugs play an important part in medicine owing to their many therapeutic applications. Of the 80 peptide drugs approved for use in humans, at least five are now off-patent and are consequently being developed as generic alternatives to the originator products. To accelerate access to generic products, the FDA has proposed new regulatory pathways that do not require direct comparisons of generics to originators in clinical trials. The 'Abbreviated New Drug Application' (ANDA) pathway recommends that sponsors provide information on any new impurities in the generic drug, compared with the originator product, because the impurities can have potential to elicit unwanted immune responses owing to the introduction of T-cell epitopes. This review describes how peptide drug impurities can elicit unexpected immunogenicity and describes a framework for performing immunogenicity risk assessment of all types of bioactive peptide products. Although this report primarily focuses on generic peptides and their impurities, the approach might also be of interest for developers of novel peptide drugs who are preparing their products for an initial regulatory review.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements.

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Neoantigen-based personalized cancer vaccines: the emergence of precision cancer immunotherapy.

INTRODUCTION: The field of cancer therapy has undergone a major transformation in less than a decade due to the introduction of checkpoint inhibitors, the advent of next generation sequencing and the discovery of neoantigens. The key observation that the breadth of each patient's immune response to the unique mutations or neoantigens present in their tumor is directly related to their survival has led oncologists to focus on driving immune responses to neoantigens through vaccination. Oncology has entered the era of precision immunotherapy, and cancer vaccine development is undergoing a paradigm shift. AREAS COVERED: Neoantigens are short peptide sequences found in tumors, but not noncancerous tissues, the vast majority of which are unique to each patient. In addition to providing a description of the distinguishing features of neoantigen discovery platforms, this review will address cross-cutting personalized cancer vaccine design themes and developmental stumbling blocks. EXPERT OPINION: Immunoinformatic pipelines that can rapidly scan cancer genomes and identify 'the best' neoantigens are in high demand. Despite the need for such tools, immunoinformatic methods for identifying neoepitopes in cancer genomes are diverse and have not been well-validated. Validation of 'personalized vaccine design pipelines' will bring about a revolution in neoantigen-based vaccine design and delivery.

Immune Tolerance-Adjusted Personalized Immunogenicity Prediction for Pompe Disease.

Infantile-onset Pompe disease (IOPD) is a glycogen storage disease caused by a deficiency of acid alpha-glucosidase (GAA). Treatment with recombinant human GAA (rhGAA, alglucosidase alfa) enzyme replacement therapy (ERT) significantly improves clinical outcomes; however, many IOPD children treated with rhGAA develop anti-drug antibodies (ADA) that render the therapy ineffective. Antibodies to rhGAA are driven by T cell responses to sequences in rhGAA that differ from the individuals' native GAA (nGAA). The goal of this study was to develop a tool for personalized immunogenicity risk assessment (PIMA) that quantifies T cell epitopes that differ between nGAA and rhGAA using information about an individual's native GAA gene and their HLA DR haplotype, and to use this information to predict the risk of developing ADA. Four versions of PIMA have been developed. They use EpiMatrix, a computational tool for T cell epitope identification, combined with an HLA-restricted epitope-specific scoring feature (iTEM), to assess ADA risk. One version of PIMA also integrates JanusMatrix, a Treg epitope prediction tool to identify putative immunomodulatory (regulatory) T cell epitopes in self-proteins. Using the JanusMatrix-adjusted version of PIMA in a logistic regression model with data from 48 cross-reactive immunological material (CRIM)-positive IOPD subjects, those with scores greater than 10 were 4-fold more likely to develop ADA (p<0.03) than those that had scores less than 10. We also confirmed the hypothesis that some GAA epitopes are immunomodulatory. Twenty-one epitopes were tested, of which four were determined to have an immunomodulatory effect on T effector response in vitro. The implementation of PIMA V3J on a secure-access website would allow clinicians to input the individual HLA DR haplotype of their IOPD patient and the GAA pathogenic variants associated with each GAA allele to calculate the patient's relative risk of developing ADA, enhancing clinical decision-making prior to initiating treatment with ERT. A better understanding of immunogenicity risk will allow the implementation of targeted immunomodulatory approaches in ERT-naïve settings, especially in CRIM-positive patients, which may in turn improve the overall clinical outcomes by minimizing the development of ADA. The PIMA approach may also be useful for other types of enzyme or factor replacement therapies.

Identification and Immune Assessment of T Cell Epitopes in Five Plasmodium falciparum Blood Stage Antigens to Facilitate Vaccine Candidate Selection and Optimization.

The hurdles to effective blood stage malaria vaccine design include immune evasion tactics used by the parasite such as redundant invasion pathways and antigen variation among circulating parasite strains. While blood stage malaria vaccine development primarily focuses on eliciting optimal humoral responses capable of blocking erythrocyte invasion, clinically-tested Plasmodium falciparum (Pf) vaccines have not elicited sterile protection, in part due to the dramatically high levels of antibody needed. Recent development efforts with non-redundant, conserved blood stage antigens suggest both high antibody titer and rapid antibody binding kinetics are important efficacy factors. Based on the central role of helper CD4 T cells in development of strong, protective immune responses, we systematically analyzed the class II epitope content in five leading Pf blood stage antigens (RH5, CyRPA, RIPR, AMA1 and EBA175) using in silico, in vitro, and ex vivo methodologies. We employed in silico T cell epitope analysis to enable identification of 67 HLA-restricted class II epitope clusters predicted to bind a panel of nine HLA-DRB1 alleles. We assessed a subset of these for HLA-DRB1 allele binding in vitro, to verify the in silico predictions. All clusters assessed (40 clusters represented by 46 peptides) bound at least two HLA-DR alleles in vitro. The overall epitope prediction to in vitro HLA-DRB1 allele binding accuracy was 71%. Utilizing the set of RH5 class II epitope clusters (10 clusters represented by 12 peptides), we assessed stimulation of T cells collected from HLA-matched RH5 vaccinees using an IFN-γ T cell recall assay. All clusters demonstrated positive recall responses, with the highest responses - by percentage of responders and response magnitude - associated with clusters located in the N-terminal region of RH5. Finally, a statistically significant correlation between in silico epitope predictions and ex vivo IFN-γ recall response was found when accounting for HLA-DR matches between the epitope predictions and donor HLA phenotypes. This is the first comprehensive analysis of class II epitope content in RH5, CyRPA, RIPR, AMA1 and EBA175 accompanied by in vitro HLA binding validation for all five proteins and ex vivo T cell response confirmation for RH5.

Bridging Computational Vaccinology and Vaccine Development Through Systematic Identification, Characterization, and Downselection of Conserved and Variable Circumsporozoite Protein CD4 T Cell Epitopes From Diverse Plasmodium falciparum Strains.

An effective malaria vaccine must prevent disease in a range of populations living in regions with vastly different transmission rates and protect against genetically-diverse Plasmodium falciparum (Pf) strains. The protective efficacy afforded by the currently licensed malaria vaccine, Mosquirix™, promotes strong humoral responses to Pf circumsporozoite protein (CSP) 3D7 but protection is limited in duration and by strain variation. Helper CD4 T cells are central to development of protective immune responses, playing roles in B cell activation and maturation processes, cytokine production, and stimulation of effector T cells. Therefore, we took advantage of recent in silico modeling advances to predict and analyze human leukocyte antigen (HLA)-restricted class II epitopes from PfCSP - across the entire PfCSP 3D7 sequence as well as in 539 PfCSP sequence variants - with the goal of improving PfCSP-based malaria vaccines. Specifically, we developed a systematic workflow to identify peptide sequences capable of binding HLA-DR in a context relevant to achieving broad human population coverage utilizing cognate T cell help and with limited T regulatory cell activation triggers. Through this workflow, we identified seven predicted class II epitope clusters in the N- and C-terminal regions of PfCSP 3D7 and an additional eight clusters through comparative analysis of 539 PfCSP sequence variants. A subset of these predicted class II epitope clusters was synthesized as peptides and assessed for HLA-DR binding in vitro. Further, we characterized the functional capacity of these peptides to prime and activate human peripheral blood mononuclear cells (PBMCs), by monitoring cytokine response profiles using MIMIC® technology (Modular IMmune In vitro Construct). Utilizing this decision framework, we found sufficient differential cellular activation and cytokine profiles among HLA-DR-matched PBMC donors to downselect class II epitope clusters for inclusion in a vaccine targeting PfCSP. Importantly, the downselected clusters are not highly conserved across PfCSP variants but rather, they overlap a hypervariable region (TH2R) in the C-terminus of the protein. We recommend assessing these class II epitope clusters within the context of a PfCSP vaccine, employing a test system capable of measuring immunogenicity across a broad set of HLA-DR alleles.

Development of a novel fully functional coagulation factor VIII with reduced immunogenicity utilizing an in silico prediction and deimmunization approach.

BACKGROUND: Up to 30% of hemophilia A patients develop inhibitory antibodies against the infused factor VIII (FVIII). The development of a deimmunized FVIII is an unmet high medical need. Although improved recombinant FVIII (rFVIII) products evolved within the last years, the immunogenicity has not been solved. A deimmunized FVIII could reduce the probability of inhibitor development, providing safer therapy. OBJECTIVE: To develop a deimmunized FVIII molecule by modifying major histocompatibility complex (MHC) class II presentation, leading to a functional but less immunogenic molecule. METHODS: We performed (1) in silico prediction of potentially immunogenic T cell epitopes and their modification by amino acid substitutions in the FVIII sequence, (2) evaluation of functional and structural similarity of the modified rFVIII to unmodified FVIII and registered products, and (3) confirmation of the reduced immunogenicity by in vitro testing. RESULTS: A partially deimmunized fully functional FVIII molecule incorporating 19 amino acid substitutions was generated. The substitutions led to a reduction of the immunogenicity score, indicating a reduced immunogenicity based on in silico calculations. This was confirmed in an in vitro dendritic cell (DC)--T cell assay. Using this assay, cells from healthy donors proved the significantly reduced immunogenicity of the modified FVIII variant by revealing less proliferation of T helper cells to this variant than to the unmodified FVIII. CONCLUSION: In silico predictions resulted in a partially deimmunized FVIII. This FVIII is fully functional and was demonstrated to be less immunogenic in in vitro testing. This approach may result in a reduction of the inhibitor risk for patients with hemophilia A.

Identification, Selection and Immune Assessment of Liver Stage CD8 T Cell Epitopes From Plasmodium falciparum.

Immunization with radiation-attenuated sporozoites (RAS) has been shown to protect against malaria infection, primarily through CD8 T cell responses, but protection is limited based on parasite strain. Therefore, while CD8 T cells are an ideal effector population target for liver stage malaria vaccine development strategies, such strategies must incorporate conserved epitopes that cover a large range of class I human leukocyte antigen (HLA) supertypes to elicit cross-strain immunity across the target population. This approach requires identifying and characterizing a wide range of CD8 T cell epitopes for incorporation into a vaccine such that coverage across a large range of class I HLA alleles is attained. Accordingly, we devised an experimental framework to identify CD8 T cell epitopes from novel and minimally characterized antigens found at the pre-erythrocytic stage of parasite development. Through in silico analysis we selected conserved P. falciparum proteins, using P. vivax orthologues to establish stringent conservation parameters, predicted to have a high number of T cell epitopes across a set of six class I HLA alleles representative of major supertypes. Using the decision framework, five proteins were selected based on the density and number of predicted epitopes. Selected epitopes were synthesized as peptides and evaluated for binding to the class I HLA alleles in vitro to verify in silico binding predictions, and subsequently for stimulation of human T cells using the Modular IMmune In-vitro Construct (MIMIC®) technology to verify immunogenicity. By combining the in silico tools with the ex vivo high throughput MIMIC platform, we identified 15 novel CD8 T cell epitopes capable of stimulating an immune response in alleles across the class I HLA panel. We recommend these epitopes should be evaluated in appropriate in vivo humanized immune system models to determine their protective efficacy for potential inclusion in future vaccines.

Multi-step screening of neoantigens' HLA- and TCR-interfaces improves prediction of survival.

Improvement of risk stratification through prognostic biomarkers may enhance the personalization of cancer patient monitoring and treatment. We used Ancer, an immunoinformatic CD8, CD4, and regulatory T cell neoepitope screening system, to perform an advanced neoantigen analysis of genomic data derived from the urothelial cancer cohort of The Cancer Genome Atlas. Ancer demonstrated improved prognostic stratification and five-year survival prediction compared to standard analyses using tumor mutational burden or neoepitope identification using NetMHCpan and NetMHCIIpan. The superiority of Ancer, shown in both univariate and multivariate survival analyses, is attributed to the removal of neoepitopes that do not contribute to tumor immunogenicity based on their homology with self-epitopes. This analysis suggests that the presence of a higher number of unique, non-self CD8- and CD4-neoepitopes contributes to cancer survival, and that prospectively defining these neoepitopes using Ancer is a novel prognostic or predictive biomarker.

Identification of a potent regulatory T cell epitope in factor V that modulates CD4+ and CD8+ memory T cell responses.

Identification of T cell epitopes that are recognized by Tregs may elucidate the relative contributions of thymic Tregs and induced Tregs to control of autoimmune diseases and allergy. One such T regulatory cell epitope or 'Tregitope', derived from blood Factor V, is described here. Tregs responding to Tregitope FV621 are potent suppressors of CD4+ T effector responses to Tetanus Toxoid in an in vitro bystander suppression assay, strongly inhibit proliferation of effector CD8+ T cells, down-modulate CD86 and HLA DR on antigen-presenting cells, and enhance expression of granzyme B in Tregs. Tregitope FV621 also suppresses anti-OVA immune responses in vivo. The immunomodulatory effect of Tregitope FV621 is enhanced when conjugated to albumin, suggesting that the short half-life of Tregitope peptides can be prolonged. The in silico tools used to prospectively identify the FV Tregitope described here, when combined with in vitro /in vivo validating assays, may facilitate future Tregitope discoveries.

New Immunoinformatics Tools for Swine: Designing Epitope-Driven Vaccines, Predicting Vaccine Efficacy, and Making Vaccines on Demand.

Novel computational tools for swine vaccine development can expand the range of immunization approaches available to prevent economically devastating swine diseases and spillover events between pigs and humans. PigMatrix and EpiCC are two new tools for swine T cell epitope identification and vaccine efficacy analysis that have been integrated into an existing computational vaccine design platform named iVAX. The iVAX platform is already in use for the development of human vaccines, thus integration of these tools into iVAX improves and expands the utility of the platform overall by making previously validated immunoinformatics tools, developed for humans, available for use in the design and analysis of swine vaccines. PigMatrix predicts T cell epitopes for a broad array of class I and class II swine leukocyte antigen (SLA) using matrices that enable the scoring of sequences for likelihood of binding to SLA. PigMatrix facilitates the prospective selection of T cell epitopes from the sequences of swine pathogens for vaccines and permits the comparison of those predicted epitopes with "self" (the swine proteome) and with sequences from other strains. Use of PigMatrix with additional tools in the iVAX toolkit also enables the computational design of vaccines in silico, for testing in vivo. EpiCC uses PigMatrix to analyze existing or proposed vaccines for their potential to protect, based on a comparison between T cell epitopes in the vaccine and circulating strains of the same pathogen. Performing an analysis of T cell epitope relatedness analysis using EpiCC may facilitate vaccine selection when a novel strain emerges in a herd and also permits analysis of evolutionary drift as a means of immune escape. This review of novel computational immunology tools for swine describes the application of PigMatrix and EpiCC in case studies, such as the design of cross-conserved T cell epitopes for swine influenza vaccine or for African Swine Fever. We also describe the application of EpiCC for determination of the best vaccine strains to use against circulating viral variants of swine influenza, swine rotavirus, and porcine circovirus type 2. The availability of these computational tools accelerates infectious disease research for swine and enable swine vaccine developers to strategically advance their vaccines to market.

Better Epitope Discovery, Precision Immune Engineering, and Accelerated Vaccine Design Using Immunoinformatics Tools.

Computational vaccinology includes epitope mapping, antigen selection, and immunogen design using computational tools. Tools that facilitate the in silico 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.

T cell epitope content comparison (EpiCC) analysis demonstrates a bivalent PCV2 vaccine has greater T cell epitope overlap with field strains than monovalent PCV2 vaccines.

Porcine circovirus type 2 (PCV2) has one of the highest evolutionary rates among DNA viruses. Traditionally, PCV2 vaccines have been based on the 2a genotype as this was the first genotype discovered. Today, eight genotypes of PCV2 viruses have been identified, and, taken together with the rapid evolutionary rate, propensity to recombine, and high rate of vaccination, further variation in PCV2 is expected. For these reasons, there is a growing genetic gap between available vaccines and field strains. When selecting vaccines, it is important to consider vaccines that contain T cell epitopes that are well-matched to the circulating strains. To quantify the relatedness between PCV2 vaccines and field strains, we predicted and compared their T cell epitope content and calculated Epitope Content Comparison (EpiCC) scores using established in silico tools. T cell epitopes predicted to bind common class I and class II swine leukocyte antigen (SLA) alleles were identified from two major structural proteins, the capsid (encoded by ORF2) and the replicase (encoded by ORF1). The T cell epitope content of three commercial PCV2a-based vaccines (a baculovirus expressed PCV2a ORF2 [VacAlt], a PCV1-PCV2a chimeric virus vaccine [VacA] and a combination cPCV2a-cPCV2b chimeric virus vaccine [VacAB]) and an experimental PCV2b ORF2-based chimeric virus vaccine [VacB] (Table 1), were compared to that of 161 PCV2 field strains (representing genotypes a-f). The T cell epitope content and conservation between vaccine and field strains varied. While all vaccine strains provided broad coverage of the field strains including heterologous genotypes, none of the vaccines covered all the putative T cell epitopes identified in the field strains. PCV2a-based vaccine strains generally scored higher in terms of conserved epitope content against PCV2a field isolates but were not identical. The PCV2b-based vaccine strain had higher scores against PCV2b and PCV2d field strains. The combination PCV2a-PCV2b vaccine (VacAB) had, on average, the highest EpiCC score. PCV2 continues to evolve and EpiCC analysis provides a new tool to assess the possible impact of virus genetic divergence on T cell epitope coverage of vaccine strains. Given that multiple genotypes are currently found and may co-exist on farms, this analysis suggests that a combination of PCV2a and PCV2b vaccine strains may be required to provide optimal coverage of current and future field isolates.

In silico identification and modification of T cell epitopes in pertussis antigens associated with tolerance.

The resurgence of whooping cough since the introduction of acellular (protein) vaccines has led to a renewed interest in the development of improved pertussis vaccines; Outer Membrane Vesicles (OMVs) carrying pertussis antigens have emerged as viable candidates. An in silico immunogenicity screen was carried out on 49 well-known Bordetella pertussis proteins in order to better understand their potential role toward the efficacy of pertussis OMVs for vaccine design; seven proteins were identified as being good candidates for including in optimized cellular and acellular pertussis vaccines. We then screened these antigens for putative tolerance-inducing sequences, as proteins with reduced tolerogenicity have improved vaccine potency in preclinical models. We used specialized homology tools (JanusMatrix) to identify peptides in the proteins that were cross-reactive with human sequences. Four of the 19 identified cross-reactive peptides were detolerized in silico using a separate tool, OptiMatrix, which disrupted the potential of these peptides to bind to human HLA and murine MHC. Four selected cross-reactive peptides and their detolerized variants were synthesized and their binding to a set of eight common HLA class II alleles was assessed in vitro. Reduced binding affinity to HLA class II was observed for the detolerized variants compared to the wild-type peptides, highlighting the potential of this approach for designing more efficacious pertussis vaccines.