2018 Fiscal Year Annual Research Report
Identification of epitopes targeted by TCR-MHC pairs
| Project/Area Number |
18H02430
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| Research Institution | Osaka University |
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Principal Investigator |
Standley Daron 大阪大学, 微生物病研究所, 教授 (00448028)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Keywords | Adaptive immunity / T cell / epitope / machine learning / structural modeling |
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| Outline of Annual Research Achievements |
We have carried out a proof-of-concept study of the overall prediction methodology using a model pathogen, Yellow Fever Virus. First, we built Repertoire Builder models of 170 TCRs with known MHC and epitope, including 60 that target a single Yellow Fever epitope that is presented by the MHC allele HLA-A*02. We next clustered the models using InterClone and showed that the TCRs the Yellow Fever Virus epitope formed a single, well-defined, cluster. Next, we computed 53 possible epitopes predicted by NetMHCpan for the antigen and MHC. We then estimated the probability of TCRs in the cluster binding to each epitope. In this test, the correct epitope was selected from among the 53 possible epitopes based only on the ImmuneScape binding energy (NetMHCpan score was not used). We have carried out large-scale single T cell sequencing ourselves in collaboration with several immunology labs. First, we collaborated with Dr. Shuhei Sakakibara in the Kikutani Lab (IFReC) to analyze B and T cells in patients with chronic rhinosinusitis with nasal polyposis. This disease is widespread, characterized by IgE antibodies (typical of an allergic response) and shows a high co-incidence with asthma. Dr. Sakakibara found that in spite of these traits, all of the IgE B cells in the patients exhibited strong immune responses to residential bacteria, not known allergens (Takeda, et al. J Allergy Clin Immunol, 2019). This implicates a role of T cells in mediating the proliferation of the anti-bacterial B cells, although the epitopes stimulating such T cells have not yet been identified.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
We have carried out a proof-of-concept study of the overall prediction methodology using a model pathogen, Yellow Fever Virus. First, we built Repertoire Builder models of 170 TCRs with known MHC and epitope, including 60 that target a single Yellow Fever epitope that is presented by the MHC allele HLA-A*02. We next clustered the models using InterClone and showed that the TCRs the Yellow Fever Virus epitope formed a single, well-defined, cluster. Next, we computed 53 possible epitopes predicted by NetMHCpan for the antigen and MHC. We then estimated the probability of TCRs in the cluster binding to each epitope. In this test, the correct epitope was selected from among the 53 possible epitopes based only on the ImmuneScape binding energy (NetMHCpan score was not used). We have carried out large-scale single T cell sequencing ourselves in collaboration with several immunology labs. First, we collaborated with Dr. Shuhei Sakakibara in the Kikutani Lab (IFReC) to analyze B and T cells in patients with chronic rhinosinusitis with nasal polyposis. This disease is widespread, characterized by IgE antibodies (typical of an allergic response) and shows a high co-incidence with asthma. Dr. Sakakibara found that in spite of these traits, all of the IgE B cells in the patients exhibited strong immune responses to residential bacteria, not known allergens (Takeda, et al. J Allergy Clin Immunol, 2019). This implicates a role of T cells in mediating the proliferation of the anti-bacterial B cells, although the epitopes stimulating such T cells have not yet been identified.
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| Strategy for Future Research Activity |
The primary focus for future work will be on validating the prediction methodology experimentally. There are two levels of prediction that we can easily validate: clustering accuracy and epitope prediction accuracy. Both types of experiments will involve cloning TCRs of interest, preparation of peptide libraries and screening peptides against TCRs in reporter cells. We will collaborate with Prof. Hisashi Arase to carry the screening using his NFAT-GFP-reporter cells. The original reporter cells are from T cell hybridoma (Arase et al. Science. 2002 296:1323; Ohtsuka, Arase et al. PNAS. 2004 101:8126; Saito et al Nature 2017 552:101; Deng et al. Nature 2018 562:605). So, to exclude the effect of intrinsic TCR, he has recently deleted intrinsic TCR alpha and beta genes from the reporter cells and now exogenous TCRs can easily be expressed on the reporter cells to analyze the function of TCR (unpublished). We have recently begun developing a new measure of binding affinity that showed promise for antibody-antigen docking and we intend to develop it further in the near future for TCR-epitope-MHC docking. One of the more exciting developments is the ability to observe TCR and RNAseq data in a single cell. We will use this technology to study the role that TCR signaling plays in the development of regulatory T cells and conventional T cells.
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