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Reconstituting T cell receptor selection in-silico

Genes & Immunity volume 22, pages 187–193 (2021)Cite this article

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Abstract

Each T cell receptor (TCR) gene is created without regard for which substances (antigens) the receptor can recognize. T cell selection culls developing T cells when their TCRs (i) fail to recognize major histocompatibility complexes (MHCs) that act as antigen presenting platforms or (ii) recognize with high affinity self-antigens derived from healthy cells and tissue. While T cell selection has been thoroughly studied, little is known about which TCRs are retained or removed by this process. Therefore, we develop an approach using TCR gene sequencing and machine learning to identify patterns in TCR protein sequences influencing the outcome of T cell receptor selection. We verify the trained models classify TCRs from developing T cells as being before selection and TCRs from mature T cells as being after selection. Our approach may provide future avenues for studying the relationship between T cell selection and conditions like autoimmune diseases.

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Fig. 1
Fig. 2: Non-productive TCR genes do not express a functional TCR chain.
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Code availability

All computer code is written in Python3 using NumPy, Tensorflow v1.14, and Keras. Aspects of the computer code can be found at https://github.com/jostmey/dkm. A full copy of the computer source code, detailed instructions for running computer code, and trained models are available upon request under a signed confidentiality agreement. Email the corresponding author if interested.

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Acknowledgements

JO is grateful to the department of Population & Data Sciences and the University of Texas Southwestern Medical Center for the salary support he received for this study.

Funding

JO used his protected time from the department of Population & Data Sciences to conduct this study. LC and Sc may have been supported in part by the US National Institute of Allergy and Infectious Diseases (NIAID) (R01AI097403) and the EU Framework Programme for Research and Innovation (825821).

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Authors and Affiliations

  1. Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, USA

    Jared Ostmeyer, Lindsay Cowell & Scott Christley

  2. Department of Neurology, UT Southwestern Medical Center, Dallas, TX, USA

    Benjamin Greenberg

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  1. Jared Ostmeyer
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  2. Lindsay Cowell
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  3. Benjamin Greenberg
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  4. Scott Christley
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Correspondence to Jared Ostmeyer.

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Ostmeyer, J., Cowell, L., Greenberg, B. et al. Reconstituting T cell receptor selection in-silico. Genes Immun 22, 187–193 (2021). https://doi.org/10.1038/s41435-021-00141-9

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