Analysis of SARS-CoV-2 specific T-cell receptors in ImmuneCode reveals cross-reactivity to immunodominant Influenza M1 epitope
Adaptive Biotechnologies and Microsoft have recently partnered to release ImmuneCode, a database containing SARS-CoV-2 specific T-cell receptors derived through MIRA, a T-cell receptor (TCR) sequencing based sequencing approach to identify antigen-specific TCRs. Herein, we query the extent of cross reactivity between these derived SARS-CoV-2 specific TCRs and other known antigens present in McPas-TCR, a manually curated catalogue of pathology-associated TCRs. We reveal cross reactivity between SARS-CoV-2 specific TCRs and the immunodominant Influenza GILGFVFTL M1 epitope, suggesting the importance of further work in characterizing the implications of prior Influenza exposure or co-exposure to the pathology of SARS-CoV-2 illness.
In this github repository, all data and code are present to replicate the results illustrated in the manuscript. Data collected from Adaptive and McPas-TCR can be found under the Data directory. All code required to recreate the main figure in the manuscript can be found under scripts in Reproduce_Results.py or in the jupyter notebook Reproduce_Results.ipynb with results in the Results directory.
For full description of analysis and approach, refer to the following manuscript:
Sidhom, J. W. & Baras, A. S. (2020). Analysis of SARS-CoV-2 specific T-cell receptors in ImmuneCode reveals cross-reactivity to immunodominant Influenza M1 epitope. bioRxiv, 160499.
https://www.biorxiv.org/content/10.1101/2020.06.20.160499v1
See requirements.txt for all dependencies to run the analysis.
We would love feedback and critique of the analysis and ways to improve it! Thanks! For questions or help, email: jsidhom1@jhmi.edu