Predictions versus high-throughput experiments in T-cell epitope discovery: competition or synergy?

TCR-ESM: Employing protein language embeddings to predict TCR-peptide-MHC binding

Cognate target identification for T-cell receptors (TCRs) is a significant barrier in T-cell therapy development, which may be overcome by accurately predicting TCR interaction with peptide-bound major histocompatibility complex (pMHC). In this study, we have employed peptide embeddings learned from a large protein language model- Evolutionary Scale Modeling (ESM), to predict TCR-pMHC binding. The TCR-ESM model presented outperforms existing predictors. The complementarity-determining region 3 (CDR3) of the hypervariable TCR is located at the center of the paratope and plays a crucial role in peptide recognition. TCR-ESM trained on paired TCR data with both CDR3α and CDR3β chain information performs significantly better than those trained on data with only CDR3β, suggesting that both TCR chains contribute to specificity, the relative importance however depends on the specific peptide-MHC targeted. The study illuminates the importance of MHC information in TCR-peptide binding which remained inconclusive so far and was thought dependent on the dataset characteristics. TCR-ESM outperforms existing approaches on external datasets, suggesting generalizability. Overall, the potential of deep learning for predicting TCR-pMHC interactions and improving the understanding of factors driving TCR specificity are highlighted. The prediction model is available at http://tcresm.dhanjal-lab.iiitd.edu.in/ as an online tool.

Epitope mapping and a candidate vaccine design from canine distemper virus

Background

Canine distemper (CD) is a worldwide spread disease that has been described in 12 families of mammals, especially in the Carnivora order, being better studied in domestic canines where vaccination represents the best means of control. CD is controlled by vaccination, but many cases of the disease still occur in vaccinated animals.

Aim

The aim of this work was to study antigen-specific epitopes that can subsidize the development of a new vaccine approach.

Methods

Mapping of T cell reactive epitopes for CD virus (CDV) was carried out through enzyme-linked immunospot assays using 119 overlapped synthetic peptides from the viral hemagglutinin protein, grouped in 22 pools forming a matrix to test the immune response of 32 animals.

Results

Evaluations using the criteria established to identify reactive pools, demonstrated that 26 animals presented at least one reactive pool, that one pool was not reactive to any animal, and six pools were the most frequent among the reactive peptides. The crisscrossing of the most reactive pools in the matrix revealed nine peptides considered potential candidate epitopes for T cell stimulation against the CDV and those were used to design an in-silico protein, containing also predicted epitopes for B cell stimulation, and further analyzed using immune epitope databases to ensure protein quality and stability.

Conclusion

The final in silico optimized protein presents characteristics that qualify it to be used to develop a new prototype epitope-based anti-CDV vaccine.

Riding the wave of innovation: immunoinformatics in fish disease control

The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.

Personalised neoantigen-based therapy in colorectal cancer

Colorectal cancer (CRC) has become one of the most common tumours with high morbidity, mortality and distinctive evolution mechanism. The neoantigens arising from the somatic mutations have become considerable treatment targets in the management of CRC. As cancer-specific aberrant peptides, neoantigens can trigger the robust host immune response and exert anti-tumour effects while minimising the emergence of adverse events commonly associated with alternative therapeutic regimens. In this review, we summarised the mechanism, generation, identification and prognostic significance of neoantigens, as well as therapeutic strategies challenges of neoantigen-based therapy in CRC. The evidence suggests that the establishment of personalised neoantigen-based therapy holds great promise as an effective treatment approach for patients with CRC.

Hemophilia A subjects with an intron-22 gene inversion mutation show CD4+ T-effector responses to multiple epitopes in FVIII

Background

Almost half of severe hemophilia A (HA) is caused by an intron 22 inversion mutation (Int22Inv), which disrupts the 26-exon F8 gene. Inverted F8 mRNA exons 1-22 are transcribed, while F8B mRNA, containing F8 exons 23-26, is transcribed from a promoter within intron 22. Neither FVIII activity nor FVIII antigen (cross-reacting material, CRM) are detectable in plasma of patients with an intron-22 inversion.

Objectives

To test the hypothesis that (putative) intracellular synthesis of FVIII proteins encoded by inverted F8 and F8B mRNAs confers T-cell tolerance to almost the entire FVIII sequence, and to evaluate the immunogenicity of the region encoded by the F8 exon 22-23 junction sequence.

Patients/Methods

Peripheral blood mononuclear cells (PBMCs) from 30 severe or moderate HA subjects (17 with an Int22Inv mutation) were tested by ELISPOT assays to detect cytokine secretion in response to FVIII proteins and peptides and to map immunodominant T-cell epitopes. Potential immunogenicity of FVIII sequences encoded by the F8 exon 22-23 junction region was also tested using peptide-MHCII binding assays.

Results

Eight of the Int22Inv subjects showed robust cytokine secretion from PBMCs stimulated with FVIII proteins and/or peptides, consistent with earlier publications from the Conti-Fine group. Peptide ELISPOT assays identified immunogenic regions of FVIII. Specificity for sequences encoded within F8 mRNA exons 1-22 and F8B mRNA was confirmed by staining Int22Inv CD4⁺ T cells with peptide-loaded HLA-Class II tetramers. FVIII peptides spanning the F8 exon 22-23 junction (encoding M2124-V2125) showed limited binding to MHCII proteins and low immunogenicity, with cytokine secretion from only one Int22Inv subject.

Conclusions

PBMCs from multiple subjects with an Int22Inv mutation, with and without a current FVIII inhibitor, responded to FVIII epitopes. Furthermore, the FVIII region encoded by the exon 22-23 junction sequence was not remarkably immunoreactive and is therefore unlikely to contain an immunodominant, promiscuous CD4⁺ T-cell epitope. Our results indicate that putative intracellular expression of partial FVIII proteins does not confer T-cell tolerance to FVIII regions encoded by inverted F8 mRNA or F8B mRNA.

Designing and development of epitope-based vaccines against Helicobacter pylori

Helicobacter pylori infection is the principal cause of serious diseases (e.g. gastric cancer and peptic ulcers). Antibiotic therapy is an inadequate strategy in H. pylori eradication because of which vaccination is an inevitable approach. Despite the presence of countless vaccine candidates, current vaccines in clinical trials have performed with poor efficacy which makes vaccination extremely challenging. Remarkable advancements in immunology and pathogenic biology have provided an appropriate opportunity to develop various epitope-based vaccines. The fusion of proper antigens involved in different aspects of H. pylori colonization and pathogenesis as well as peptide linkers and built-in adjuvants results in producing epitope-based vaccines with excellent therapeutic efficacy and negligible adverse effects. Difficulties of the in vitro culture of H. pylori, high genetic variation, and unfavourable immune responses against feeble epitopes in the complete antigen are major drawbacks of current vaccine strategies that epitope-based vaccines may overcome. Besides decreasing the biohazard risk, designing precise formulations, saving time and cost, and induction of maximum immunity with minimum adverse effects are the advantages of epitope-based vaccines. The present article is a comprehensive review of strategies for designing and developing epitope-based vaccines to provide insights into the innovative vaccination against H. pylori.

Current and prospective computational approaches and challenges for developing COVID-19 vaccines

SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.

Therapeutic cancer vaccines for pediatric malignancies: advances, challenges, and emerging technologies

Though outcomes for pediatric cancer patients have significantly improved over the past several decades, too many children still experience poor outcomes and survivors suffer lifelong, debilitating late effects after conventional chemotherapy, radiation, and surgical treatment. Consequently, there has been a renewed focus on developing novel targeted therapies to improve survival outcomes. Cancer vaccines are a promising type of immunotherapy that leverage the immune system to mediate targeted, tumor-specific killing through recognition of tumor antigens, thereby minimizing off-target toxicity. As such, cancer vaccines are orthogonal to conventional cancer treatments and can therefore be used alone or in combination with other therapeutic modalities to maximize efficacy. To date, cancer vaccination has remained largely understudied in the pediatric population. In this review, we discuss the different types of tumor antigens and vaccine technologies (dendritic cells, peptides, nucleic acids, and viral vectors) evaluated in clinical trials, with a focus on those used in children. We conclude with perspectives on how advances in combination therapies, tumor antigen (eg, neoantigen) selection, and vaccine platform optimization can be translated into clinical practice to improve outcomes for children with cancer.

CD4+ Th immunogenicity of the Ascaris spp. secreted products

Ascaris spp. is a major health problem of humans and animals alike, and understanding the immunogenicity of its antigens is required for developing urgently needed vaccines. The parasite-secreted products represent the most relevant, yet complex (>250 proteins) antigens of Ascaris spp. as defining the pathogen-host interplay. We applied an in vitro antigen processing system coupled to quantitative proteomics to identify potential CD4⁺ T_h cell epitopes in Ascaris-secreted products. This approach considerably restricts the theoretical list of epitopes using conventional CD4⁺ T_h cell epitope prediction tools. We demonstrate the specificity and utility of our approach on two sets of candidate lists, allowing us identifying hits excluded by either one or both computational methods. More importantly, one of the candidates identified experimentally, clearly demonstrates the presence of pathogen-reactive T cells in healthy human individuals against these antigens. Thus, our work pipeline identifies the first human T cell epitope against Ascaris spp. and represents an easily adaptable platform for characterization of complex antigens, in particular for those pathogens that are not easily amenable for in vivo experimental validation.

Analysis of peptide-SLA binding by establishing immortalized porcine alveolar macrophage cells with different SLA class II haplotypes

Primary porcine alveolar macrophages (PAM) are useful for studying viral infections and immune response in pigs; however, long-term use of these cells is limited by the cells’ short lifespan. We immortalized primary PAMs by transfecting them with both hTERT and SV40LT and established two immortalized cell lines (iPAMs) actively proliferating even after 35 passages. These cells possessed the characteristics of primary PAMs, including strong expression of swine leukocyte antigen (SLA) class II genes and the inability to grow anchorage-independently. We characterized their SLA genes and subsequently performed peptide-SLA binding assays using a peptide from porcine circovirus type 2 open reading frame 2 to experimentally measure the binding affinity of the peptide to SLA class II. The number of peptides bound to cells measured by fluorescence was very low for PK15 cells (7.0% ± 1.5), which are not antigen-presenting cells, unlike iPAM61 (33.7% ± 3.4; SLA-DQA*0201/0303, DQB1*0201/0901, DRB1*0201/1301) and iPAM303 (73.3% ± 5.4; SLA DQA*0106/0201, DQB1*0202/0701, DRB1*0402/0602). The difference in peptide binding between the two iPAMs was likely due to the allelic differences between the SLA class II molecules that were expressed. The development of an immortal PAM cell panel harboring diverse SLA haplotypes and the use of an established method in this study can become a valuable tool for evaluating the interaction between antigenic peptides and SLA molecules and is important for many applications in veterinary medicine including vaccine development.

Computational prediction of vaccine potential epitopes and 3-dimensional structure of XAGE-1b for non-small cell lung cancer immunotherapy

BACKGROUND

XAGE-1b is shown to be overexpressed in lung adenocarcinoma and to be a strong immunogenic antigen among non-small cell lung cancer (NSCLC) patients. However, 3D structure of XAGE-1b is not available and its confirmation has not been solved yet.

METHODS

Multiple sequence alignment was run to select the most reliable templates. Homology modeling technique was performed using computer-based tool to generate 3-dimensional structure models, eight models were generated and assessed on basis of local and global quality. Immune Epitope Database (IEDB) tools were then used to determine potential B-Cell epitopes while NetMHCpan algorithms were used to enhance the determination for potential epitopes of both Cytotoxic T-lymphocytes and T-helper cells.

RESULTS

Computational prediction was performed for B-Cell epitopes, prediction results generated; 3 linear epitopes where XAGE-1b (13-21) possessed the best score of 0.67, 5 discontinuous epitopes where XAGE-1b (40-52) possessed the best score of 0.67 based on the predicted model of the finest quality. For a potential vaccine design, computational prediction yielded potential Human Leukocyte Antigen (HLA) class I epitopes including HLA-B*08:01-restricted XAGE-1b (3-11) epitope which was the best with 0.2 percentile rank. Regarding HLA Class II epitopes, HLA-DRB1*12:01-restricted XAGE-1b (25-33) was the most antigenic epitope with 5.91 IC50 value. IC50 values were compared with experimental values and population coverage percentages of epitopes were computed.

CONCLUSIONS

This study predicted a model of XAGE-1b tertiary structure which could explain its antigenic function and facilitate usage of predicted peptides for experimental validation towards designing immunotherapies against NSCLC.

Host genotype and time dependent antigen presentation of viral peptides: predictions from theory

The rate of progression of HIV infected individuals to AIDS is known to vary with the genotype of the host, and is linked to their allele of human leukocyte antigen (HLA) proteins, which present protein degradation products at the cell surface to circulating T-cells. HLA alleles are associated with Gag-specific T-cell responses that are protective against progression of the disease. While Pol is the most conserved HIV sequence, its association with immune control is not as strong. To gain a more thorough quantitative understanding of the factors that contribute to immunodominance, we have constructed a model of the recognition of HIV infection by the MHC class I pathway. Our model predicts surface presentation of HIV peptides over time, demonstrates the importance of viral protein kinetics, and provides evidence of the importance of Gag peptides in the long-term control of HIV infection. Furthermore, short-term dynamics are also predicted, with simulation of virion-derived peptides suggesting that efficient processing of Gag can lead to a 50% probability of presentation within 3 hours post-infection, as observed experimentally. In conjunction with epitope prediction algorithms, this modelling approach could be used to refine experimental targets for potential T-cell vaccines, both for HIV and other viruses.

On the feasibility of mining CD8+ T cell receptor patterns underlying immunogenic peptide recognition

Current T cell epitope prediction tools are a valuable resource in designing targeted immunogenicity experiments. They typically focus on, and are able to, accurately predict peptide binding and presentation by major histocompatibility complex (MHC) molecules on the surface of antigen-presenting cells. However, recognition of the peptide-MHC complex by a T cell receptor (TCR) is often not included in these tools. We developed a classification approach based on random forest classifiers to predict recognition of a peptide by a T cell receptor and discover patterns that contribute to recognition. We considered two approaches to solve this problem: (1) distinguishing between two sets of TCRs that each bind to a known peptide and (2) retrieving TCRs that bind to a given peptide from a large pool of TCRs. Evaluation of the models on two HIV-1, B*08-restricted epitopes reveals good performance and hints towards structural CDR3 features that can determine peptide immunogenicity. These results are of particular importance as they show that prediction of T cell epitope and T cell epitope recognition based on sequence data is a feasible approach. In addition, the validity of our models not only serves as a proof of concept for the prediction of immunogenic T cell epitopes but also paves the way for more general and high-performing models.

The ADAMTS131239-1253 peptide is a dominant HLA-DR1-restricted CD4+ T-cell epitope

Acquired thrombotic thrombocytopenic purpura is a rare and severe disease characterized by auto-antibodies directed against “A Disintegrin And Metalloproteinase with Thrombospondin type 1 repeats, 13^th member" (ADAMTS13), a plasma protein involved in hemostasis. Involvement of CD4⁺ T cells in the pathogenesis of the disease is suggested by the IgG isotype of the antibodies. However, the nature of the CD4⁺ T-cell epitopes remains poorly characterized. Here, we determined the HLA-DR-restricted CD4⁺ T-cell epitopes of ADAMTS13. Candidate T-cell epitopes were predicted in silico and binding affinities were confirmed in competitive enzyme-linked immunosorbent assays. ADAMTS13-reactive CD4⁺ T-cell hybridomas were generated following immunization of HLA-DR1 transgenic mice (Sure-L1 strain) and used to screen the candidate epitopes. We identified the ADAMTS13^1239–1253 peptide as the single immunodominant HLA-DR1-restricted CD4⁺ T-cell epitope. This peptide is located in the CUB2 domain of ADAMTS13. It was processed by dendritic cells, stimulated CD4⁺ T cells from Sure-L1 mice and was recognized by CD4⁺ T cells from an HLA-DR1-positive patient with acute thrombotic thrombocytopenic purpura. Interestingly, the ADAMTS13^1239–1253 peptide demonstrated promiscuity towards HLA-DR11 and HLA-DR15. Our work paves the way towards the characterization of the ADAMTS13-specific CD4⁺ T-cell response in patients with thrombotic thrombocytopenic purpura using ADAMTS13^1239–1253-loaded HLA-DR tetramers.

T-cell epitopes predicted from the Nucleocapsid protein of Sin Nombre virus restricted to 30 HLA alleles common to the North American population

Hantavirus cardiopulmonary syndrome in North America is caused by Sin Nombre virus (SNV) and poses a public health problem. We identified T-cell epitopes restricted to HLA alleles commonly seen in the N. American population. Nucleocapsid (N) protein is 428 aminoacid in length and binds to RNA and functions also as a key molecule between virus and host cell processes. The predicted epitopes from N protein that bind to class I MHC were analyzed for human proteasomes cleavage, TAP efficiency, immunogenicity and antigenicity. We identified 8 epitopes through MHC binding prediction, proteasomal cleavage prediction and TAP efficiency. Epitope VMGVIGFSF had highest Vaxijen score and the epitope, TNRAYFITR had highest immunogenicity score. Epitope AAVSALETK and TIACGLFPA had 100% homology to many HCPS causing viruses. Our study focused on T-cell epitope prediction specific to restricted HLA haplotypes of racial groups in North America for the potential vaccine development. Among the candidate epitopes, FLAARCPFL was conserved in SNV, which is suitable for vaccine specific to the virus genotype. Peptide-based vaccines can be designed to include multiple determinants from several hantavirus genotypes, or multiple epitopes from the same genotype. Thereby, immune response will focus solely on relevant epitopes, avoiding non-protective responses or immune evasion. The other advantages include absence of infectious material unlike in live or attenuated vaccines. There is no risk of reversion or formation of adverse reassortants leading to virulence and no risk of genetic integration or recombination forming a rationale for vaccine design including for distinct geographical regions.

DynaDom: structure-based prediction of T cell receptor inter-domain and T cell receptor-peptide-MHC (class I) association angles

Background

T cell receptor (TCR) molecules are involved in the adaptive immune response as they distinguish between self- and foreign-peptides, presented in major histocompatibility complex molecules (pMHC). Former studies showed that the association angles of the TCR variable domains (Vα/Vβ) can differ significantly and change upon binding to the pMHC complex. These changes can be described as a rotation of the domains around a general Center of Rotation, characterized by the interaction of two highly conserved glutamine residues.

Methods

We developed a computational method, DynaDom, for the prediction of TCR Vα/Vβ inter-domain and TCR/pMHC orientations in TCRpMHC complexes, which allows predicting the orientation of multiple protein-domains. In addition, we implemented a new approach to predict the correct orientation of the carboxamide endgroups in glutamine and asparagine residues, which can also be used as an external, independent tool.

Results

The approach was evaluated for the remodeling of 75 and 53 experimental structures of TCR and TCRpMHC (class I) complexes, respectively. We show that the DynaDom method predicts the correct orientation of the TCR Vα/Vβ angles in 96 and 89% of the cases, for the poses with the best RMSD and best interaction energy, respectively. For the concurrent prediction of the TCR Vα/Vβ and pMHC orientations, the respective rates reached 74 and 72%. Through an exhaustive analysis, we could show that the pMHC placement can be further improved by a straightforward, yet very time intensive extension of the current approach.

Conclusions

The results obtained in the present remodeling study prove the suitability of our approach for interdomain-angle optimization. In addition, the high prediction rate obtained specifically for the energetically highest ranked poses further demonstrates that our method is a powerful candidate for blind prediction. Therefore it should be well suited as part of any accurate atomistic modeling pipeline for TCRpMHC complexes and potentially other large molecular assemblies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12900-016-0071-7) contains supplementary material, which is available to authorized users.

Integrated computational prediction and experimental validation identifies promiscuous T cell epitopes in the proteome of Mycobacterium bovis

The discovery of novel antigens is an essential requirement in devising new diagnostics or vaccines for use in control programmes against human tuberculosis (TB) and bovine tuberculosis (bTB). Identification of potential epitopes recognised by CD4⁺ T cells requires prediction of peptide binding to MHC class-II, an obligatory prerequisite for T cell recognition. To comprehensively prioritise potential MHC-II-binding epitopes from Mycobacterium bovis, the agent of bTB and zoonotic TB in humans, we integrated three binding prediction methods with the M. bovisproteome using a subset of human HLA alleles to approximate the binding of epitope-containing peptides to the bovine MHC class II molecule BoLA-DRB3. Two parallel strategies were then applied to filter the resulting set of binders: identification of the top-scoring binders or clusters of binders. Our approach was tested experimentally by assessing the capacity of predicted promiscuous peptides to drive interferon-γ secretion from T cells of M. bovis infected cattle. Thus, 376 20-mer peptides, were synthesised (270 predicted epitopes, 94 random peptides with low predictive scores and 12 positive controls of known epitopes). The results of this validation demonstrated significant enrichment (>24 %) of promiscuously recognised peptides predicted in our selection strategies, compared with randomly selected peptides with low prediction scores. Our strategy offers a general approach to the identification of promiscuous epitopes tailored to target populations where there is limited knowledge of MHC allelic diversity.

Human Leukocyte Antigen (HLA) Peptides Derived from Tumor Antigens Induced by Inhibition of DNA Methylation for Development of Drug-facilitated Immunotherapy

Treatment of cancer cells with anticancer drugs often fails to achieve complete remission. Yet, such drug treatments may induce alteration in the tumor's gene expression patterns, including those of Cancer/Testis Antigens (CTA). The degradation products of such antigens can be presented as HLA peptides on the surface of the tumor cells and be developed into anticancer immunotherapeutics. For example, the DNA methyl transferase inhibitor, 5-aza-2'-deoxycytidine (Decitabine) has limited antitumor efficacy, yet it induces the expression of many genes, including CTAs that are normally silenced in the healthy adult tissues. In this study, the presentation of many new HLA peptides derived from CTAs and induced by Decitabine was demonstrated in three human Glioblastoma cell lines. Such presentation of CTA-derived HLA peptides can be exploited for development of new treatment modalities, combining drug treatment with anti-CTA targeted immunotherapy. The Decitabine-induced HLA peptidomes include many CTAs that are not normally detected in healthy tissues or in cancer cells, unless treated with the drug. In addition, the study included large-scale analyses of the simultaneous effects of Decitabine on the transcriptomes, proteomes and HLA peptidomes of the human Glioblastoma cells. It demonstrates the poor correlations between these three levels of gene expression, both in their total levels and in their response to the drug. The proteomics and HLA peptidomics data are available via ProteomeXchange with identifier PXD003790 and the transcriptomics data are available via GEO with identifier GSE80137.

In silico and in vivo analysis of Toxoplasma gondii epitopes by correlating survival data with peptide-MHC-I binding affinities

BACKGROUND

Protein antigens comprising peptide motifs with high binding affinity to major histocompatibility complex class I (MHC-I) molecules are expected to induce a stronger cytotoxic T-lymphocyte response and thus provide better protection against infection with microorganisms where cytotoxic T-cells are the main effector arm of the immune system.

METHODS

Data on cyst formation and survival were extracted from past studies on the DNA immunization of mice with plasmids coding for Toxoplasma gondii antigens. From in silico analyses of the vaccine antigens, the correlation was tested between the predicted affinity for MHC-I molecules of the vaccine peptides and the survival of immunized mice after challenge with T. gondii. ELISPOT analysis was used for the experimental testing of peptide immunogenicity.

RESULTS

Predictions for the Db MHC-I molecule produced a strong, negative correlation between survival and the dissociation constant of vaccine-derived peptides. The in silico analyses of nine T. gondii antigens identified peptides with a predicted dissociation constant in the interval from 10nM to 40μM. ELISPOT assays with splenocytes from T. gondii-infected mice further supported the importance of the peptide affinity for MHC-I.

CONCLUSIONS

In silico analysis clearly helped the search for protective vaccine antigens. The ELISPOT analysis confirmed that the predicted T-cell epitopes were immunogenic by their ability to release interferon gamma in spleen cells.

T Cell Epitope Peptide Therapy for Allergic Diseases

Careful selection of dominant T cell epitope peptides of major allergens that display degeneracy for binding to a wide array of MHC class II molecules allows induction of clinical and immunological tolerance to allergen in a refined treatment strategy. From the original concept of peptide-induced T cell anergy arising from in vitro studies, proof-of-concept murine models and flourishing human trials followed. Current randomized, double-blind, placebo-controlled clinical trials of mixtures of T cell-reactive short allergen peptides or long contiguous overlapping peptides are encouraging with intradermal administration into non-inflamed skin a preferred delivery. Definitive immunological mechanisms are yet to be resolved but specific anergy, Th2 cell deletion, immune deviation, and Treg induction seem implicated. Significant efficacy, particularly with short treatment courses, in a range of aeroallergen therapies (cat, house dust mite, grass pollen) with inconsequential non-systemic adverse events likely heralds a new class of therapeutic for allergy, Synthetic Peptide Immuno-Regulatory Epitopes (SPIRE).

Sequence conservation analysis and in silico human leukocyte antigen-peptide binding predictions for the Mtb72F and M72 tuberculosis candidate vaccine antigens

Background

Requisites for an efficacious tuberculosis (TB) vaccine are a minimal genomic diversity among infectious Mycobacterium tuberculosis strains for the selected antigen, and the capability to induce robust T-cell responses in the majority of human populations. A tool in the identification of putative T-cell epitopes is in silico prediction of major histocompatibility complex (MHC)-peptide binding. Candidate TB vaccine antigen Mtb72F and its successor M72 are recombinant fusion proteins derived from Mtb32A and Mtb39A (encoded by Rv0125 and Rv1196, respectively). Adjuvanted Mtb72F and M72 candidate vaccines were shown to induce CD4⁺ T-cell responses in European, US, African and Asian populations.

Methods

Sequence conservation of Mtb32A, Mtb39A, Mtb72F and M72 among 46 strains (prevalent Mycobacterium strains causing human TB disease, and H37Ra) was assessed by multiple alignments using ClustalX. For Mtb32A, Mtb39A and Mtb72F, 15-mer human leukocyte antigen (HLA)-class II-binding peptides were predicted for 158 DRB1 alleles prevailing in populations with high TB burden, 6 DRB3/4/5, 8 DQ and 6 DP alleles, using NetMHCII-pan-3.0. Results for 3 DRB1 alleles were compared with previously published allele-matched in vitro binding data. Additional analyses were done for M72. Nonameric MHC class I-binding peptides in Mtb72F were predicted for three alleles representative of class I supertypes A02, A03 and B07, using seven prediction algorithms.

Results

Sequence identity among strains was ≥98 % for each protein. Residue changes in Mtb39A comprised primarily single residue or nucleotide insertions and/or deletions in repeat regions, and were observed in 67 % of strains. For Mtb72F, 156 DRB1, 6 DRB3/4/5, 7 DQ and 5 DP alleles were predicted to contain at least one MHC class II-binding peptide, and class I-binding peptides were predicted for each HLA-A/B allele. Comparison of predicted MHC-II-binding peptides with experimental data indicated that the algorithm’s sensitivity and specificity were variable among alleles.

Conclusions

The sequences from which Mtb72F and M72 are derived are highly conserved among representative Mycobacterium strains. Predicted putative T-cell epitopes in M72 and/or Mtb72F covered a wide array of HLA alleles. In silico binding predictions for class I- and II-binding putative epitopes can be complemented with biochemical verification of HLA binding capacity, processing and immunogenicity of the predicted peptides.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-015-0119-7) contains supplementary material, which is available to authorized users.

Immunoregulatory T cell epitope peptides: the new frontier in allergy therapy

Allergen immunotherapy (AIT) has been practised since 1911 and remains the only therapy proven to modify the natural history of allergic diseases. Although efficacious in carefully selected individuals, the currently licensed whole allergen extracts retain the risk of IgE-mediated adverse events, including anaphylaxis and occasionally death. This together with the need for prolonged treatment regimens results in poor patient adherence. The central role of the T cell in orchestrating the immune response to allergen informs the choice of T cell targeted therapies for down-regulation of aberrant allergic responses. Carefully mapped short synthetic peptides that contain the dominant T cell epitopes of major allergens and bind to a diverse array of HLA class II alleles, can be delivered intradermally into non-inflamed skin to induce sustained clinical and immunological tolerance. The short peptides from allergenic proteins are unable to cross-link IgE and possess minimal inflammatory potential. Systematic progress has been made from in vitro human models of allergen T cell epitope-based peptide anergy in the early 1990s, through proof-of-concept murine allergy models and early human trials with longer peptides, to the current randomized, double-blind, placebo-controlled clinical trials with the potential new class of synthetic short immune-regulatory T cell epitope peptide therapies. Sustained efficacy with few adverse events is being reported for cat, house dust mite and grass pollen allergy after only a short course of treatment. Underlying immunological mechanisms remain to be fully delineated but anergy, deletion, immune deviation and Treg induction all seem contributory to successful outcomes, with changes in IgG4 apparently less important compared to conventional AIT. T cell epitope peptide therapy is promising a safe and effective new class of specific treatment for allergy, enabling wider application even for more severe allergic diseases.

Databases for T-cell epitopes

Modem immunology and vaccinology incorporate immunoinformatics techniques to give insights into immune systems and accelerate vaccine design. Databases managing epitope data in a structured form with immune-related annotations including sequences, alleles, source organisms, structures, and diseases could be the most crucial part of immunoinformatics offering data sources for the analysis of immune systems and development of prediction methods. This chapter provides an overview of publicly available databases of T-cell epitopes including general databases, pathogen- and tumor-specific databases, and 3D structure databases.

Varicella-zoster virus-derived major histocompatibility complex class I-restricted peptide affinity is a determining factor in the HLA risk profile for the development of postherpetic neuralgia

Postherpetic neuralgia (PHN) is the most common complication of herpes zoster and is typified by a lingering pain that can last months or years after the characteristic herpes zoster rash disappears. It is well known that there are risk factors for the development of PHN, such as its association with certain HLA alleles. In this study, previous HLA genotyping results were collected and subjected to a meta-analysis with increased statistical power. This work shows that the alleles HLA-A*33 and HLA-B*44 are significantly enriched in PHN patients, while HLA-A*02 and HLA-B*40 are significantly depleted. Prediction of the varicella-zoster virus (VZV) peptide affinity for these four HLA variants by using one in-house-developed and two existing state-of-the-art major histocompatibility complex (MHC) class I ligand prediction methods reveals that there is a great difference in their absolute and relative peptide binding repertoires. It was observed that HLA-A*02 displays a high affinity for an ∼7-fold-higher number of VZV peptides than HLA-B*44. Furthermore, after correction for HLA allele-specific limitations, the relative affinity of HLA-A*33 and HLA-B*44 for VZV peptides was found to be significantly lower than those of HLA-A*02 and HLA-B*40. In addition, HLA peptide affinity calculations indicate strong trends for VZV to avoid high-affinity peptides in some of its proteins, independent of the studied HLA allele.

IMPORTANCE

Varicella-zoster virus can cause two distinct diseases: chickenpox (varicella) and shingles (herpes zoster). Varicella is a common disease in young children, while herpes zoster is more frequent in older individuals. A common complication of herpes zoster is postherpetic neuralgia, a persistent and debilitating pain that can remain months up to years after the resolution of the rash. In this study, we show that the relative affinity of HLA variants associated with higher postherpetic neuralgia risk for varicella-zoster virus peptides is lower than that of variants with a lower risk. These results provide new insight into the development of postherpetic neuralgia and strongly support the hypothesis that one of its possible underlying causes is a suboptimal anti-VZV immune response due to weak HLA binding peptide affinity.

Identification and HLA-tetramer-validation of human CD4+ and CD8+ T cell responses against HCMV proteins IE1 and IE2

Human cytomegalovirus (HCMV) is an important human pathogen. It is a leading cause of congenital infection and a leading infectious threat to recipients of solid organ transplants as well as of allogeneic hematopoietic cell transplants. Moreover, it has recently been suggested that HCMV may promote tumor development. Both CD4+ and CD8+ T cell responses are important for long-term control of the virus, and adoptive transfer of HCMV-specific T cells has led to protection from reactivation and HCMV disease. Identification of HCMV-specific T cell epitopes has primarily focused on CD8+ T cell responses against the pp65 phosphoprotein. In this study, we have focused on CD4+ and CD8+ T cell responses against the immediate early 1 and 2 proteins (IE1 and IE2). Using overlapping peptides spanning the entire IE1 and IE2 sequences, peripheral blood mononuclear cells from 16 healthy, HLA-typed, donors were screened by ex vivo IFN-γ ELISpot and in vitro intracellular cytokine secretion assays. The specificities of CD4+ and CD8+ T cell responses were identified and validated by HLA class II and I tetramers, respectively. Eighty-one CD4+ and 44 CD8+ T cell responses were identified representing at least seven different CD4 epitopes and 14 CD8 epitopes restricted by seven and 11 different HLA class II and I molecules, respectively, in total covering 91 and 98% of the Caucasian population, respectively. Presented in the context of several different HLA class II molecules, two epitope areas in IE1 and IE2 were recognized in about half of the analyzed donors. These data may be used to design a versatile anti-HCMV vaccine and/or immunotherapy strategy.

NetMHCstab - predicting stability of peptide-MHC-I complexes; impacts for cytotoxic T lymphocyte epitope discovery

Major histocompatibility complex class I (MHC-I) molecules play an essential role in the cellular immune response, presenting peptides to cytotoxic T lymphocytes (CTLs) allowing the immune system to scrutinize ongoing intracellular production of proteins. In the early 1990s, immunogenicity and stability of the peptide-MHC-I (pMHC-I) complex were shown to be correlated. At that time, measuring stability was cumbersome and time consuming and only small data sets were analysed. Here, we investigate this fairly unexplored area on a large scale compared with earlier studies. A recent small-scale study demonstrated that pMHC-I complex stability was a better correlate of CTL immunogenicity than peptide-MHC-I affinity. We here extended this study and analysed a total of 5509 distinct peptide stability measurements covering 10 different HLA class I molecules. Artificial neural networks were used to construct stability predictors capable of predicting the half-life of the pMHC-I complex. These predictors were shown to predict T-cell epitopes and MHC ligands from SYFPEITHI and IEDB to form significantly more stable MHC-I complexes compared with affinity-matched non-epitopes. Combining the stability predictions with a state-of-the-art affinity predictions NetMHCcons significantly improved the performance for identification of T-cell epitopes and ligands. For the HLA alleles included in the study, we could identify distinct sub-motifs that differentiate between stable and unstable peptide binders and demonstrate that anchor positions in the N-terminal of the binding motif (primarily P2 and P3) play a critical role for the formation of stable pMHC-I complexes. A webserver implementing the method is available at www.cbs.dtu.dk/services/NetMHCstab.

Novel approaches in polyepitope T-cell vaccine development against HIV-1

RV144 clinical trial was modestly effective in preventing HIV infection. New alternative approaches are needed to design improved HIV-1 vaccines and their delivery strategies. One of these approaches is construction of synthetic polyepitope HIV-1 immunogen using protective T- and B-cell epitopes that can induce broadly neutralizing antibodies and responses of cytotoxic (CD8(+) CTL) and helpers (CD4(+) Th) T-lymphocytes. This approach seems to be promising for designing of new generation of vaccines against HIV-1, enables in theory to cope with HIV-1 antigenic variability, focuses immune responses on protective determinants and enables to exclude from the vaccine compound that can induce autoantibodies or antibodies enhancing HIV-1 infectivity. Herein, the authors will focus on construction and rational design of polyepitope T-cell HIV-1 immunogens and their delivery, including: advantages and disadvantages of existing T-cell epitope prediction methods; features of organization of polyepitope immunogens, which can generate high-level CD8(+) and CD4(+) T-lymphocyte responses; the strategies to optimize efficient processing, presentation and immunogenicity of polyepitope constructs; original software to design polyepitope immunogens; and delivery vectors as well as mucosal strategies of vaccination. This new knowledge may bring us a one step closer to developing an effective T-cell vaccine against HIV-1, other chronic viral infections and cancer.

Computational Resources for MHC Ligand Identification

Advances in the high-throughput determination of functional modulators of major histocompatibility complex (MHC) and improved computational predictions of MHC ligands have rendered the rational design of immunomodulatory peptides feasible. Proteome-derived peptides and 'reverse vaccinology' by computational means will play a driving role in future vaccine design. Here we review the molecular mechanisms of the MHC mediated immune response, present the computational approaches that have emerged in this area of biotechnology, and provide an overview of publicly available computational resources for predicting and designing new peptidic MHC ligands.

Vaccine design: emerging concepts and renewed optimism

Arguably, vaccination represents the single most effective medical intervention ever developed. Yet, vaccines have failed to provide any or adequate protection against some of the most significant global diseases. The pathogens responsible for these vaccine-recalcitrant diseases have properties that allow them to evade immune surveillance and misdirect or eliminate the immune response. However, genomic and systems biology tools, novel adjuvants and delivery systems, and refined molecular insight into protective immunity have started to redefine the landscape, and results from recent efficacy trials of HIV and malaria vaccines have instilled hope that another golden age of vaccines may be on the horizon.

Systemic immunization with an epitope-based vaccine elicits a Th1-biased response and provides protection against Helicobacter pylori in mice

Vaccine-mediated Th1-biased CD4+ T cell responses have been shown to be crucial for protection against Helicobacter pylori (H. pylori). In this study, we investigated whether a vaccine composed of CD4+ T cell epitopes together with Th1 adjuvants could confer protection against H. pylori in a mouse model. We constructed an epitope-based vaccine, designated Epivac, which was composed of predicted immunodominant CD4+ T cell epitopes from H. pylori adhesin A (HpaA), urease B (UreB) and cytotoxin-associated gene A product (CagA). Together with four different Th1 adjuvants, Epivac was administered subcutaneously and the prophylactic potential was examined. Compared to non-immunized mice, immunization with Epivac alone or with a Th1 adjuvant significantly reduced H. pylori colonization, and better protection was observed when an adjuvant was used. Immunized mice exhibited a strong local and systemic Th1-biased immune response, which may contribute to the inhibition of H. pylori colonization. Though a significant specific antibody response was induced by the vaccine, no correlation was found between the intensity of the humoral response and the protective effect. Our results suggest that a vaccine containing CD4+ T cell epitopes is a promising candidate for protection against H. pylori infection.

Clusters versus affinity-based approaches in F. tularensis whole genome search of CTL epitopes

Deciphering the cellular immunome of a bacterial pathogen is challenging due to the enormous number of putative peptidic determinants. State-of-the-art prediction methods developed in recent years enable to significantly reduce the number of peptides to be screened, yet the number of remaining candidates for experimental evaluation is still in the range of ten-thousands, even for a limited coverage of MHC alleles. We have recently established a resource-efficient approach for down selection of candidates and enrichment of true positives, based on selection of predicted MHC binders located in high density “hotspots" of putative epitopes. This cluster-based approach was applied to an unbiased, whole genome search of Francisella tularensis CTL epitopes and was shown to yield a 17–25 fold higher level of responders as compared to randomly selected predicted epitopes tested in Kb/Db C57BL/6 mice. In the present study, we further evaluate the cluster-based approach (down to a lower density range) and compare this approach to the classical affinity-based approach by testing putative CTL epitopes with predicted IC₅₀ values of <10 nM. We demonstrate that while the percent of responders achieved by both approaches is similar, the profile of responders is different, and the predicted binding affinity of most responders in the cluster-based approach is relatively low (geometric mean of 170 nM), rendering the two approaches complimentary. The cluster-based approach is further validated in BALB/c F. tularensis immunized mice belonging to another allelic restriction (Kd/Dd) group. To date, the cluster-based approach yielded over 200 novel F. tularensis peptides eliciting a cellular response, all were verified as MHC class I binders, thereby substantially increasing the F. tularensis dataset of known CTL epitopes. The generality and power of the high density cluster-based approach suggest that it can be a valuable tool for identification of novel CTLs in proteomes of other bacterial pathogens.