Major Histocompatibility Complex Epitopes Research Articles

In Vitro Model of Suppression of the Alloantigen Response by Tolerogenic Dendritic Cells Transfected with Personalized DNA Constructs Encoding HLA Epitopes.

A search for efficient graft rejection modulation techniques for the promotion of durable engraftment remains to be a matter of close study all over the world. Despite the variety of immunosuppressive drugs, the schemes currently used show a lack of selectivity and have a number of side effects. Here we investigated an approach for the induction of antigen-specific tolerance in a human "stimulator-responder" model in vitro, using dendritic cells (DCs) transfected with designed DNA constructs encoding the stimulator's major histocompatibility complex (MHC) epitopes. The object of the study is peripheral blood mononuclear cells (PBMCs) from 10 healthy donors. To induce antigen-specific tolerance, personalized DNA constructs were created for five responder-stimulator pairs, based on the sequences of donors' and recipients' MHCs. DNA sequencing was performed to select epitopes for incorporation into genetic constructs. A mixed lymphocyte culture assay was used (i) to assess the proliferative response in both directions for all possible stimulator-responder pairs (90 reactions) and (ii) to assess the tolerogenic properties of the generated transfected DCs (5 reactions). A significant increase in the amounts of FoxP3+ CD4+CD25+ cells and in IL-10 production was shown in culture of donor mononuclear cells after co-cultivation with the responder's dendritic cells transfected with donor-specific plasmids. The tolerogenic cultures generated using tolerogenic DCs transfected with MHC epitopes had a significantly greater ability to inhibit the proliferation of autologous MNCs in response to an allogeneic MHC stimulus. The produced DCs transfected with DNA constructs against HLA stimulating epitopes exhibited tolerogenic properties and may be used to develop antigen-specific tolerance. Thus, we proposed a perspective approach to the induction of antigen-specific tolerance, which should subsequently be studied for use in clinical practice.

Computational mining of MHC class II epitopes for the development of universal immunogenic proteins.

The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts.

MHCSeqNet: a deep neural network model for universal MHC binding prediction

BackgroundImmunotherapy is an emerging approach in cancer treatment that activates the host immune system to destroy cancer cells expressing unique peptide signatures (neoepitopes). Administrations of cancer-specific neoepitopes in the form of synthetic peptide vaccine have been proven effective in both mouse models and human patients. Because only a tiny fraction of cancer-specific neoepitopes actually elicits immune response, selection of potent, immunogenic neoepitopes remains a challenging step in cancer vaccine development. A basic approach for immunogenicity prediction is based on the premise that effective neoepitope should bind with the Major Histocompatibility Complex (MHC) with high affinity.ResultsIn this study, we developed MHCSeqNet, an open-source deep learning model, which not only outperforms state-of-the-art predictors on both MHC binding affinity and MHC ligand peptidome datasets but also exhibits promising generalization to unseen MHC class I alleles. MHCSeqNet employed neural network architectures developed for natural language processing to model amino acid sequence representations of MHC allele and epitope peptide as sentences with amino acids as individual words. This consideration allows MHCSeqNet to accept new MHC alleles as well as peptides of any length.ConclusionsThe improved performance and the flexibility offered by MHCSeqNet should make it a valuable tool for screening effective neoepitopes in cancer vaccine development.

ACME: pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks.

Prediction of peptide binding to the major histocompatibility complex (MHC) plays a vital role in the development of therapeutic vaccines for the treatment of cancer. Algorithms with improved correlations between predicted and actual binding affinities are needed to increase precision and reduce the number of false positive predictions. We present ACME (Attention-based Convolutional neural networks for MHC Epitope binding prediction), a new pan-specific algorithm to accurately predict the binding affinities between peptides and MHC class I molecules, even for those new alleles that are not seen in the training data. Extensive tests have demonstrated that ACME can significantly outperform other state-of-the-art prediction methods with an increase of the Pearson correlation coefficient between predicted and measured binding affinities by up to 23 percentage points. In addition, its ability to identify strong-binding peptides has been experimentally validated. Moreover, by integrating the convolutional neural network with attention mechanism, ACME is able to extract interpretable patterns that can provide useful and detailed insights into the binding preferences between peptides and their MHC partners. All these results have demonstrated that ACME can provide a powerful and practically useful tool for the studies of peptide-MHC class I interactions. ACME is available as an open source software at https://github.com/HYsxe/ACME. Supplementary data are available at Bioinformatics online.

Socializing Individualized T-Cell Cancer Immunotherapy.

Tumors typically accumulate hundreds of mutations in “driver” genes critical to transformation as well as in other “passenger” genes.1 These mutations can generate neoantigens—mutated versions of normal proteins that become recognizable by patients’ own T cells.2,3 Such T cells recovered from patients have been used as a source of tumor-hunting T-cell therapies, representing the epitome of individualized medicine as a way to treat tumors.4,5 Unfortunately, at best only a very small handful of potential neoantigens are recognized by a patient’s own T cells,6 probably because of the unrelenting immunosuppressive tactics exerted chronically on the patient’s own T-cell repertoire. Now, Stronen et al. have shown that T cells from normal, healthy donors can recognize many more neoantigens from a given patient than the patient’s own T-cell repertoire allows.7 A situation in which a greater number of neoantigens are recognized by more T cells can only be good news for the treatment of malignant tumors. These results suggest that even individualized cancer immunotherapy might benefit from reaching out into the community for extra T-cell help.

Major histocompatibility complex linked databases and prediction tools for designing vaccines

Presently, the major histocompatibility complex (MHC) is receiving considerable interest owing to its remarkable role in antigen presentation and vaccine design. The specific databases and prediction approaches related to MHC sequences, structures and binding/nonbinding peptides have been aggressively developed in the past two decades with their own benchmarks and standards. Before using these databases and prediction tools, it is important to analyze why and how the tools are constructed along with their strengths and limitations. The current review presents insights into web-based immunological bioinformatics resources that include searchable databases of MHC sequences, epitopes and prediction tools that are linked to MHC based vaccine design, including population coverage analysis. In T cell epitope forecasts, MHC class I binding predictions are very accurate for most of the identified MHC alleles. However, these predictions could be further improved by integrating proteasome cleavage (in conjugation with transporter associated with antigen processing (TAP) binding) prediction, as well as T cell receptor binding prediction. On the other hand, MHC class II restricted epitope predictions display relatively low accuracy compared to MHC class I. To date, pan-specific tools have been developed, which not only deliver significantly improved predictions in terms of accuracy, but also in terms of the coverage of MHC alleles and supertypes. In addition, structural modeling and simulation systems for peptide–MHC complexes enable the molecular-level investigation of immune processes. Finally, epitope prediction tools, and their assessments and guidelines, have been presented to immunologist for the design of novel vaccine and diagnostics.

The human T-cell repertoire grows up.

The human T-cell repertoire grows up.

Prediction of Major Histocompatibility Complex Binding Peptides and Epitopes from Fatty-Acid-Binding Protein of the Human Blood Fluke Schistosoma Japonicum

Schistosoma japonicum are blood flukes of humans that cause chronic, highly debilitating diseases involving extensive liver damage. In the present study, fatty-acid-binding protein of the human blood fluke Schistosoma japonicum is being used to find out highly suitable MHC binding peptides and epitopes. MHC molecules are cell surface proteins, which take active part in host immune reactions and involvement of MHC class in response to almost all antigens and it give effects on specific sites. Predicted MHC binding regions acts like red flags for antigen specific and generate immune response against the parent antigen. So a small fragment of antigen can induce immune response against whole antigen. This theme is implemented in designing subunit and synthetic peptide vaccines. Fragments identified through this approach tend to be high efficiency binders, in which larger percentage of their atoms are directly involved in binding as compared to larger molecules. Binding ability prediction of peptides to major histocompatibility complex (MHC) class I & II molecules is important in vaccine development from fatty-acid-binding protein of the human blood fluke Schistosoma japonicum.

N-Linked Glycosylation Does Not Impair Proteasomal Degradation but Affects Class I Major Histocompatibility Complex Presentation

The addition of N-linked glycans to nascent polypeptides occurs cotranslationally in the endoplasmic reticulum (ER). For many proteins the state of the glycans serves as an indicator, which allows the ER quality control system to monitor the conformation of polypeptides upon folding. Proteins that fail to fold in the ER are often dislocated to the cytoplasm, where they are subjected to proteasomal degradation. Although the addition of N-linked glycans occurs within the ER, non-lysosomal removal of the glycans occurs in the cytosol by the action of peptide N-glycanase (PNGase). In this study, we investigated the interplay between PNGase action and proteasomal degradation of ER misfolded proteins (i.e. whether PNGase acts prior to or following proteasomal degradation). Interestingly, we found that glycan removal from N-terminally extended peptides modulates the presentation of class I major histocompatibility complex-restricted epitopes. Our findings provide direct evidence that the proteasome is capable of degrading glycoproteins without prior removal of their glycans. This degradation is independent of either the identity of the glycosylated protein or the type and number of N-linked glycans it harbors. We also captured and characterized glycopeptides generated following proteasomal degradation of RNaseB. Although the carbohydrate moiety reduced the variability of the degradation products that include the glycosylated residue (local effect), the overall global digestion pattern of RNaseB was unaffected. Together with earlier findings by others, our data support a model in which PNGase may act both upstream and downstream to proteasomal degradation and demonstrates its important role in class I major histocompatibility complex antigen presentation.

Omega-3 fatty acid modification of membrane structure and function. I. Dietary manipulation of tumor cell susceptibility to cell- and complement-mediated lysis.

Omega-3 fatty acids, abundant in fish oil, are reported to alter membrane properties when incorporated into membrane phospholipids. We report that dietary omega-3 fatty acids, incorporated into tumor cell membranes, alter tumor recognition and cytolysis by the immune system. Mice were fed diets rich in corn oil, hydrogenated coconut oil, or menhaden (fish) oil. T27A leukemia cells were grown as an ascites tumor in these mice and harvested for biochemical and immunologic assays. The incorporation of the long-chain omega-3 fatty acid docosahexaenoic acid (22:6) into tumor plasma membranes correlated with an increased susceptibility to tumor cytolysis by alloreactive cytotoxic T lymphocytes and decreased expression of a class I major histocompatibility complex epitope, monitored by complement-mediated lysis and radioimmunoassay. Thus the immunologic phenotype of this ascites tumor reflected the source of oil present in the diet during tumor growth.

Major histocompatibility complex conformational epitopes are peptide specific.

Serologically distinct forms of H-2Kb are stabilized by loading cells expressing "empty" class I major histocompatibility complex (MHC) molecules with different H-2Kb binding peptides. The H-2Kb epitope recognized by monoclonal antibody (mAb) 28.8.6 was stabilized by ovalbumin (OVA) (257-264) and murine cytomegalovirus (MCMV) pp89 (168-176) peptides, but not by vesicular stomatic virus nucleoprotein (VSV NP) (52-59) and influenza NP (Y345-360) peptides. The H-2Kb epitope recognized by mAb 34.4.20 was stabilized by VSV NP (52-59) peptide but not by OVA (257-264), MCMV pp89 (168-176), or influenza NP (Y345-360) peptides. Immunoprecipitation of H-2Kb molecules from normal cells showed that 28.8.6 and 34.4.20 epitopes were only present on a subset of all conformationally reactive H-2Kb molecules. Using alanine-substituted derivatives of the VSV peptide, the 28.8.6 epitope was completely stabilized by substitution of the first residue and partially stabilized by substitution of the third or the fifth residues in the peptides. These results indicate that distinct conformational MHC epitopes are dependent on the specific peptide that occupies the antigenic peptide binding groove on individual MHC molecules. The changes in MHC epitopes observed may also be important in understanding the diversity of T cell receptors used in an immune response and the influence of peptides on development of the T cell repertoire.

Analysis of cross-reactive antigen-specific T cell clones. Specific recognition of two major histocompatibility complex (MHC) and two non-MHC antigens by a single clone.

Two T cell clones, one specific for I-Es/d plus myelin basic protein (BP) and another specific for I-Ak plus influenza virus have been demonstrated to cross-react with DBA/2 cells. Genetic and serological analyses have shown that each clone recognizes its respective priming antigen in association with self-major histocompatibility complex (MHC) determinants and each recognizes DBA/2 minor H antigens in association with allo I-Ad MHC antigens. Further analysis of these clones suggests (a) that the allo I-Ad MHC epitopes recognized by these clones are not shared with self-I-A epitopes, (b) that the virus or BP antigens do not cross-react with DBA/2 minor H antigens, (c) that these clones recognize different determinants on the DBA/2 minor H antigens, and (d) that there is a requirement for a specific association between the different MHC antigens and the non-MHC antigens to stimulate these clones. This specific associative recognition argues strongly for the "altered self" hypothesis.