Models of self-peptide sampling by developing T cells identify candidate mechanisms of thymic selection

Bains, I., van Santen, H. M., Seddon, B. and Yates, A. J. (2013) Models of self-peptide sampling by developing T cells identify candidate mechanisms of thymic selection. PLoS Computational Biology, 9(7), e1003102. (doi: 10.1371/journal.pcbi.1003102)

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Conventional and regulatory T cells develop in the thymus where they are exposed to samples of self-peptide MHC (pMHC) ligands. This probabilistic process selects for cells within a range of responsiveness that allows the detection of foreign antigen without excessive responses to self. Regulatory T cells are thought to lie at the higher end of the spectrum of acceptable self-reactivity and play a crucial role in the control of autoimmunity and tolerance to innocuous antigens. While many studies have elucidated key elements influencing lineage commitment, we still lack a full understanding of how thymocytes integrate signals obtained by sampling self-peptides to make fate decisions. To address this problem, we apply stochastic models of signal integration by T cells to data from a study quantifying the development of the two lineages using controllable levels of agonist peptide in the thymus. We find two models are able to explain the observations; one in which T cells continually re-assess fate decisions on the basis of multiple summed proximal signals from TCR-pMHC interactions; and another in which TCR sensitivity is modulated over time, such that contact with the same pMHC ligand may lead to divergent outcomes at different stages of development. Neither model requires that T and T are differentially susceptible to deletion or that the two lineages need qualitatively different signals for development, as have been proposed. We find additional support for the variable-sensitivity model, which is able to explain apparently paradoxical observations regarding the effect of partial and strong agonists on T and T development.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Yates, Professor Andrew
Authors: Bains, I., van Santen, H. M., Seddon, B., and Yates, A. J.
College/School:College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:PLoS Computational Biology
Publisher:Public Library of Science
ISSN (Online):1553-7358
Copyright Holders:Copyright © 2013 The Authors
First Published:First published in PLoS Computational Biology 9(7):e1003102
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
673361Modeling the development and maintenance of peripheral naive T cell populationsAndrew YatesNational Institute of Health (USA) (NIH(US))R01AI093870III -IMMUNOLOGY