Porcine circovirus type 2 (PCV2) is strongly linked to a group of syndromes referred to as porcine-circovirus-associated diseases (PCVADs), which are controlled through vaccination; however, this does not induce sterilizing immunity but is instead involved in the evolution of the virus and is considered a factor in vaccine failure. This study sampled 84 herds (167 pigs) vaccinated against PCV2 and with clinical signs of PCVADs in five provinces across Colombia. PCV2 was identified and further characterized at the molecular level via genotyping and phylogenetic reconstructions. In addition, PCV2-associated lesions were examined via histopathology. Furthermore, the PCV2-Cap sequences retrieved were compared with three vaccines via the EpiCC tool and T cell epitope coverage. The prevalence of PCV2 was 82% in pigs and 92.9% in herds. The highest viral loads were identified in lymphoid tissue, and PCV2d emerged as the most predominant in pigs and herds (93.4% and 92.3%). Sequences for PCV2-ORF2 (n = 57; 55 PCV2d and 2 PCV2a) were determined, and PCV2d sequences were highly similar. The most common pneumonia pattern was suppurative bronchopneumonia, while the most common lung lesion was exudation in the airways; in lymphoid tissue, there was lymphoid depletion. The bivalent vaccine (PCV2a and PCVb) exhibited a higher EpiCC score (8.36) and T cell epitope coverage (80.6%) than monovalent PCV2a vaccines. In conclusion, PCV2d currently circulates widely in Colombia. Despite vaccination, there are clinical cases of PCV2, and immunoinformatic analyses demonstrate that bivalent vaccines improved the average coverage.

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.

HypothesisWhile conventional in silico immunogenicity risk assessments focus on measuring immunogenicity based on the potential of therapeutic proteins to be processed and presented by a global population-wide set of human leukocyte antigen (HLA) alleles to T cells, future refinements might adjust for HLA allele frequencies in different geographic regions or populations, as well for as individuals in those populations. Adjustment by HLA allele distribution may reveal risk patterns that are specific to population groups or individuals, which current methods that rely on global-population HLA prevalence may obscure.Key findingsThis analysis uses HLA frequency-weighted binding predictions to define immunogenicity risk for global and sub-global populations. A comparison of assessments tuned for North American/European versus Japanese/Asian populations suggests that the potential for anti-therapeutic responses (anti-therapeutic antibodies or ATA) for several commonly prescribed Rheumatoid Arthritis (RA) therapeutic biologics may differ, significantly, between the Caucasian and Japanese populations. This appears to align with reports of differing product-related immunogenicity that is observed in different populations.Relevance to clinical practiceFurther definition of population-level (regional) and individual patient-specific immunogenic risk profiles may enable prescription of the RA therapeutic with the highest probability of success to each patient, depending on their population of origin and/or their individual HLA background. Furthermore, HLA-specific immunogenicity outcomes data are limited, thus there is a need to expand HLA-association studies that examine the relationship between HLA haplotype and ATA in the clinic.

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.

Porcine circovirus type 2 (PCV2) is a globally important pathogen of swine with a high capacity for genetic change, potentially including evolution of strains less susceptible to vaccine induced immunity. Starting with DNA sequences, in silico tools can be used to predict the T cell epitope content of the PCV2 capsid protein in vaccines and field strains, allowing calculation of Epitope Content Comparison (EpiCC) scores reflecting the number of T-cell epitopes held in common. Previous work has shown that a bivalent PCV2a and PCV2b vaccine gave greater T cell epitope coverage (higher EpiCC scores) than either PCV2a or PCV2b as a monovalent, with the more complete match potentially helping to preserve or enhance vaccine efficacy. This study extends the above, using refined methodology to compare the putative T-cell epitope content of 4 PCV2 vaccines (3 based on PCV2a, and one a PCV2a and PCV2b bivalent) to a larger and more contemporary global sample of PCV2 field strains. 746 PCV2, ORF2 nucleotide sequences from diagnostic submissions dating from 2017 to 2021 were included. These comprised PCV2a (129), PCV2b (109) and PCV2d (508), and originated from Asia (185), Europe (269), North America (235) and South America (57). Phylogenetic classification confirmed the predominance of PCV2d in all regions, but with continuing presence of PCV2a and PCV2b. An interesting regional divergence was noted for PCV2a, with all strains from Europe grouped within a single phylogenetic cluster (cluster 10) and all but one from North America being in a different phylogenetic cluster (cluster 6). EpiCC scores for the bivalent vaccine were significantly higher than for the monovalents for all genotypes in all regions, showing the global relevance of the bivalent approach. Calculation of the relative contributions of the PCV2a and PCV2b components showed that, while most T-cell epitopes were present in both, each also made substantial unique contributions. Of most practical relevance, given that most commercial vaccines are based on PCV2a, the addition of PCV2b increased T-cell epitope coverage by 33% and 21% for PCV2b and PCV2d respectively.

Pathogens escape host defenses by T-cell epitope mutation or deletion (immune escape) and by simulating the appearance of human T cell epitopes (immune camouflage). We identified a highly conserved, human-like T cell epitope in non-structural protein 7 (NSP7) of SARS-CoV-2, RNA-dependent RNA polymerase (RdRp) hetero-tetramer complex. Remarkably, this T cell epitope has significant homology to a T regulatory cell epitope (Tregitope) previously identified in the Fc region of human immunoglobulin G (IgG) (Tregitope 289). We hypothesized that the SARS-CoV-2 NSP7 epitope (NSP7-289) may induce suppressive responses by engaging and activating pre-existing regulatory T cells. We therefore compared NSP7-289 and IgG Tregitopes (289 and 289z, a shorter version of 289 that isolates the shared NSP7 epitope) in vitro. Tregitope peptides 289, 289z and NSP7-289 bound to multiple HLA-DRB1 alleles in vitro and suppressed CD4+ and CD8+ T cell memory responses. Identification and in vitro validation of SARS-CoV-2 NSP7-289 provides further evidence of immune camouflage and suggests that pathogens can use human-like epitopes to evade immune response and potentially enhance host tolerance. Further exploration of the role of cross-conserved Tregs in human immune responses to pathogens such as SARS-CoV-2 is warranted.

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.

Background: Quantitative PCR (qPCR) can be used to detect and quantify a load of a pathogen.It is a good indicator of the degree of transmissibility.While performing routine qPCR, we observed an unusually short cycle threshold (Ct) value of SARS-CoV-2 for a clinical specimen obtained in Bamako, Mali.This prompted us to sequence the short-cycle SARS-CoV-2 sample to identify potential mutations in the Spike gene (S gene) gene.Methods: Post-infection, Quantitative Reverse Transcription (qRT-PCR) was performed over a defined time course to estimate the Ct of the SARS-CoV-2 specimen collected from the patient.Sanger sequencing was done on the entire fragment of the S gene to identify mutations.Findings: Sanger sequencing revealed mutations in the lineage of interest, designated B.1.525by Pango, and also known as "Eta" using the nomenclature defined by WHO.This variant was originally found in Nigeria and Italy.The four novel mutations identified in Eta (D228N, Y451N, I1172M, and C1250F) were otherwise observed with a low frequency worldwide.Although the initial Ct was 10 in the case study patient, he did not exhibit severe symptoms of SARS-CoV-2, for example, pneumonia.However, we observed a longer viral clearance period than usual, of 3 weeks.We note that as compared to SARS-CoV-2 samples obtained during the first peaks of SARS-CoV-2 infection in Mali, when the

Background Pandemic influenza viruses may emerge from animal reservoirs and spread among humans in the absence of cross-reactive antibodies in the human population. Immune response to highly conserved T cell epitopes in vaccines may still reduce morbidity and limit the spread of the new virus even when cross-protective antibody responses are lacking. Methods We used an established epitope content prediction and comparison tool, Epitope Content Comparison (EpiCC), to assess the potential for emergent H1N1 G4 swine influenza A virus (G4) to impact swine and human populations. We identified and computed the total cross-conserved T cell epitope content in HA sequences of human seasonal and experimental influenza vaccines, swine influenza vaccines from Europe and the United States (US) against G4. Results The overall T cell epitope content of US commercial swine vaccines was poorly conserved with G4, with an average T cell epitope coverage of 35.7%. EpiCC scores for the comparison between current human influenza vaccines and circulating human influenza strains were also very low. In contrast, the T cell epitope coverage of a recent European swine influenza vaccine (HL03) was 65.8% against G4. Conclusions Poor T cell epitope cross-conservation between emergent G4 and swine and human influenza vaccines in the US may enable G4 to spread in swine and spillover to human populations in the absence of protective antibody response. One European influenza vaccine, HL03, may protect against emergent G4. This study illustrates the use of the EpiCC tool for prospective assessment of existing vaccine strains against emergent viruses in swine and human populations.

Natural and vaccine-induced SARS-CoV-2 immunity in humans has been described but correlates of protection are not yet defined. T cells support the SARS-CoV-2 antibody response, clear virus-infected cells, and may be required to block transmission. In this study, we identified peptide epitopes associated with SARS-CoV-2 T-cell immunity. Using immunoinformatic methods, T-cell epitopes from spike, membrane, and envelope were selected for maximal HLA-binding potential, coverage of HLA diversity, coverage of circulating virus, and minimal potential cross-reactivity with self. Direct restimulation of PBMCs collected from SARS-CoV-2 convalescents confirmed 66% of predicted epitopes, whereas only 9% were confirmed in naive individuals. However, following a brief period of epitope-specific T-cell expansion, both cohorts demonstrated robust T-cell responses to 97% of epitopes. HLA-DR3 transgenic mouse immunization with peptides co-formulated with poly-ICLC generated a potent Th1-skewed, epitope-specific memory response, alleviating safety concerns of enhanced respiratory disease associated with Th2 induction. Taken together, these epitopes may be used to improve our understanding of natural and vaccine-induced immunity, and to facilitate the development of T-cell-targeted vaccines that harness pre-existing SARS-CoV-2 immunity.

When swine flu vaccines and circulating influenza A virus (IAV) strains are poorly matched, vaccine-induced antibodies may not protect from infection. Highly conserved T cell epitopes may, however, have a disease-mitigating effect. The degree of T cell epitope conservation among circulating strains and vaccine strains can vary, which may also explain differences in vaccine efficacy. Here, we evaluate a previously developed conserved T cell epitope-based vaccine and determine the persistence of T cell epitope conservation over time. We used a pair-wise homology score to define the conservation between the vaccine’s swine leukocyte antigen (SLA) class I and II-restricted epitopes and T cell epitopes found in 1272 swine IAV strains sequenced between 2013 and 2017. Twenty-four of the 48 total T cell epitopes included in the epitope-based vaccine were highly conserved and found in >1000 circulating swine IAV strains over the 5-year period. In contrast, commercial swine IAV vaccines developed in 2013 exhibited a declining conservation with the circulating IAV strains over the same 5-year period. Conserved T cell epitope vaccines may be a useful adjunct for commercial swine flu vaccines and to improve protection against influenza when antibodies are not cross-reactive.

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.

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.

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.

The outbreak of the 2019 Novel Coronavirus (SARS-CoV-2) rapidly spread from Wuhan, China to more than 150 countries, areas, or territories, causing staggering numbers of infections and deaths. In this study, bioinformatics analyses were performed on 5,568 complete genomes of SARS-CoV-2 virus to predict the T cell and B cell immunogenic epitopes of all viral proteins, which formed a systematic immune vulnerability landscape of SARS-CoV-2. The immune vulnerability and genetic variation profiles of SARS-CoV were compared with those of SARS-CoV and MERS-CoV. In addition, a web portal was developed to broadly share the data and results as a resource for the research community. Using this resource, we showed that genetic variations in SARS-CoV-2 are associated with loss of B cell immunogenicity, an increase in CD4+ T cell immunogenicity, and a minimum loss in CD8+ T cell immunogenicity, indicating the existence of a curious correlation between SARS-CoV-2 genetic evolutions and the immunity pressure from the host. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic/vaccine development and mechanistic research.

The RTS,S/AS01 malaria vaccine will undergo a pilot vaccination study in sub-Saharan Africa beginning in 2019. RTS,S/AS01 Phase III trials reported an efficacy of 28.3% (children 5-17 months) and 18.3% (infants 6-12 weeks), with substantial variability across study sites. We postulated that the relatively low efficacy of the RTS,S vaccine and variability across sites may be due to lack of T-cell epitopes in the vaccine antigen, and due to the HLA distribution of the vaccinated population, and/or due to 'immune camouflage', an immune escape mechanism. To examine these hypotheses, we used immunoinformatics tools to compare T helper epitopes contained in RTS,S vaccine antigens with Plasmodium falciparum circumsporozoite protein (CSP) variants isolated from infected individuals in Malawi. The prevalence of epitopes restricted by specific HLA-DRB1 alleles was inversely associated with prevalence of the HLA-DRB1 allele in the Malawi study population, suggesting immune escape. In addition, T-cell epitopes in the CSP of strains circulating in Malawi were more often restricted by low-frequency HLA-DRB1 alleles in the population. Furthermore, T-cell epitopes that were highly conserved across CSP variants in Malawi possessed TCR-facing residues that were highly conserved in the human proteome, potentially reducing T-cell help through tolerance. The CSP component of the RTS,S vaccine also exhibited a low degree of T-cell epitope relatedness to circulating variants. These results suggest that RTS,S vaccine efficacy may be impacted by low T-cell epitope content, reduced presentation of T-cell epitopes by prevalent HLA-DRB1, high potential for human-cross-reactivity, and limited conservation with the CSP of circulating malaria strains.

BackgroundPredicting 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.ObjectiveWe 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.MethodsT‐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.ResultsHigher 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.ConclusionEpiCC 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.

Swine influenza is a highly contagious respiratory viral infection in pigs that is responsible for significant financial losses to pig farmers annually. Current measures to protect herds from infection include: inactivated whole-virus vaccines, subunit vaccines, and alpha replicon-based vaccines. As is true for influenza vaccines for humans, these strategies do not provide broad protection against the diverse strains of influenza A virus (IAV) currently circulating in U.S. swine. Improved approaches to developing swine influenza vaccines are needed. Here, we used immunoinformatics tools to identify class I and II T cell epitopes highly conserved in seven representative strains of IAV in U.S. swine and predicted to bind to Swine Leukocyte Antigen (SLA) alleles prevalent in commercial swine. Epitope-specific interferon-gamma (IFNγ) recall responses to pooled peptides and whole virus were detected in pigs immunized with multi-epitope plasmid DNA vaccines encoding strings of class I and II putative epitopes. In a retrospective analysis of the IFNγ responses to individual peptides compared to predictions specific to the SLA alleles of cohort pigs, we evaluated the predictive performance of PigMatrix and demonstrated its ability to distinguish non-immunogenic from immunogenic peptides and to identify promiscuous class II epitopes. Overall, this study confirms the capacity of PigMatrix to predict immunogenic T cell epitopes and demonstrate its potential for use in the design of epitope-driven vaccines for swine. Additional studies that match the SLA haplotype of animals with the study epitopes will be required to evaluate the degree of immune protection conferred by epitope-driven DNA vaccines in pigs.