2020 Fiscal Year Research-status Report
Identification of potentially self-reactive T cell receptors and their candidate epitopes in a mouse model of rheumatoid arthritis
| Project/Area Number |
20K16286
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | Autoimmunity / T Cell Receptor / Rheumatoid Arthritis |
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| Outline of Annual Research Achievements |
Autoimmune diseases, such as rheumatoid arthritis (RA), are believed to be caused, in part, by a defect in the selection of T cells. Developing T cells undergo a process known as “negative selection” where self-derived proteins are presented to the cells; those that react to the self-peptides are either eliminated, or develop into regulatory T cells (Tregs), which suppress immune responses by conventional T cells (Tconvs). In order to study self-reactive T cell receptors (TCRs), and their likely target antigens, we performed single cell repertoire analysis n ZAC mice with impaired TCR signaling. We sequenced TCR and transcriptomes of Treg and Tconv single cells from spleen (n=2), draining lymph nodes (LN) (n=4) and joints (n=4) from arthritic ZAC mice. We discovered a cluster of pro-inflammatory Th17 Tconv cells in ZAC spleens that was absent in WT mice. This was similar to our previous observation in the non-arthritic but signaling-impaired SKG mice. ZAC Th17 TCRs showed clonal expansion and the same Tconv TCR sequences were found in the joints and LN of the same mouse. Dfferent mice had different TCR sequences, which is expected. Next, we will select the top candidate TCR clones and produce T cell hybridomas in order to test their self reactivity at the tissue level.
Currently, one paper regarding ZAC mice findings is under preparation in collaboration with Dr. Atsushi Tanaka and Prof. Shimon Sakaguchi.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We have successfully performed TCR and transcriptome sequencing of Tconv single cells from Spleen, LN and joints from ZAC arthritic mice.
Because we were able to perform gene expression sequencing, we could identify clusters of Th17 cells in arthritic mice. We are thus currently focusing on TCR sequences from these candidate self-reactive cells for further analysis. We have made a couple of adjustments to our original plan: 1) we used ZAC arthritic mice instead of SKG arthritic mice, because disease presentation is more severe in the ZAC mice. Therefore, it was easier to capture T cells of interest. We note, however, that the SKG and ZAC results were consistent; 2) We included spleen and joint tissue, in order to increase the chance of observing self-reactive TCRs; 3) We identified a Th17 cluster in Tconv cells so we will focus our TCR clustering (using the in-house software InterClone) on these cells.
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| Strategy for Future Research Activity |
Next, we will select the best TCR candidates, and a set of negative controls. From these cells, we will produce T cell NFAT-GFP reporter hybridomas that will be screened for tissue self-reactivity with tissue lysates. A positive result will strongly support the hypothesis that weakened TCR signaling leads to self-reactive Tconv cells, which, in turn, causes RA-like autoimmunity.
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| Causes of Carryover |
The budget for miscellaneous use was slightly higher than planned, but the article costs could be adjusted. Nevertheless, a small amount is still available to be used next year and it is planned to be used for laboratory reagents for the production of hybridomas and antigen challenges (Article costs).
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Research Products
(1 results)
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[Journal Article] Methods for sequence and structural analysis of B and T cell receptor repertoires2020
Author(s)
Teraguchi Shunsuke、Saputri Dianita S.、Llamas-Covarrubias Mara Anais、Davila Ana、Diez Diego、Nazlica Sedat Aybars、Rozewicki John、Ismanto Hendra S.、Wilamowski Jan、Xie Jiaqi、Xu Zichang、Loza-Lopez Martin de Jesus、van Eerden Floris J.、Li Songling、Standley Daron M.
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Journal Title
Computational and Structural Biotechnology Journal
Volume: 18
Pages: 2000～2011
DOI
Peer Reviewed / Open Access / Int'l Joint Research
