Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses |
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Authors: | Jessica Ann Gaevert,Daniel Luque Duque,Grant Lythe,Carmen Molina-Parí s,Paul Glyndwr Thomas |
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Affiliation: | 1.Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA;2.St. Jude Graduate School of Biomedical Sciences, Memphis, TN 38105, USA;3.Department of Applied Mathematics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK; (D.L.D.); (G.L.);4.T-6, Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA |
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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. |
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Keywords: | cross-reactivity pre-existing immunity heterologous infection mathematical modeling competition process bipartite network |
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