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Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses

Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
St. Jude Graduate School of Biomedical Sciences, Memphis, TN 38105, USA
Department of Applied Mathematics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK
T-6, Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Elizabeth M. Anderson and Sigrid Gouma
Viruses 2021, 13(9), 1786;
Received: 31 July 2021 / Revised: 28 August 2021 / Accepted: 2 September 2021 / Published: 7 September 2021
(This article belongs to the Special Issue Pre-existing Immunity Effects on Viral Infections and Vaccinations)
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. View Full-Text
Keywords: cross-reactivity; pre-existing immunity; heterologous infection; mathematical modeling; competition process; bipartite network cross-reactivity; pre-existing immunity; heterologous infection; mathematical modeling; competition process; bipartite network
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MDPI and ACS Style

Gaevert, J.A.; Luque Duque, D.; Lythe, G.; Molina-París, C.; Thomas, P.G. Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses. Viruses 2021, 13, 1786.

AMA Style

Gaevert JA, Luque Duque D, Lythe G, Molina-París C, Thomas PG. Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses. Viruses. 2021; 13(9):1786.

Chicago/Turabian Style

Gaevert, Jessica Ann, Daniel Luque Duque, Grant Lythe, Carmen Molina-París, and Paul Glyndwr Thomas. 2021. "Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses" Viruses 13, no. 9: 1786.

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