Gaevert, JA, Luque Duque, D, Lythe, G orcid.org/0000-0001-7966-5571 et al. (2 more authors) (2021) Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses. Viruses, 13 (9). 1786. ISSN 1999-4915
Abstract
If viral strains are sufficiently similar in their immunodominant epitopes, then populations of cross-reactive T cells may be boosted by exposure to one strain and provide protection against infection by another at a later date. This type of pre-existing immunity may be important in the adaptive immune response to influenza and to coronaviruses. Patterns of recognition of epitopes by T cell clonotypes (a set of cells sharing the same T cell receptor) are represented as edges on a bipartite network. We describe different methods of constructing bipartite networks that exhibit cross-reactivity, and the dynamics of the T cell repertoire in conditions of homeostasis, infection and re-infection. Cross-reactivity may arise simply by chance, or because immunodominant epitopes of different strains are structurally similar. We introduce a circular space of epitopes, so that T cell cross-reactivity is a quantitative measure of the overlap between clonotypes that recognize similar (that is, close in epitope space) epitopes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | cross-reactivity; pre-existing immunity; heterologous infection; mathematical modeling; competition process; bipartite network |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Sep 2021 10:23 |
Last Modified: | 25 Jun 2023 22:45 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/v13091786 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177789 |