Mathematical modeling in cellular immunology: T cell activation and parameter estimation

A critical step in mounting an immune response is antigen recognition by T cells. This step proceeds by productive interactions between T cell receptors (TCR) on the surface of T cells and foreign antigen, in the form of peptide-major-histocompatibility-complexes (pMHC), on the surface of antigen-p...

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Main Author: Dushek, Omer
Format: Others
Language:English
Published: University of British Columbia 2008
Subjects:
Online Access:http://hdl.handle.net/2429/2894
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-BVAU.-28942013-06-05T04:17:18ZMathematical modeling in cellular immunology: T cell activation and parameter estimationDushek, OmerT cell receptorMathematical modelingA critical step in mounting an immune response is antigen recognition by T cells. This step proceeds by productive interactions between T cell receptors (TCR) on the surface of T cells and foreign antigen, in the form of peptide-major-histocompatibility-complexes (pMHC), on the surface of antigen-presenting-cells (APC). Antigen recognition is exceedingly difficult to understand because the vast majority of pMHC on APCs are derived from self-proteins. Nevertheless, T cells have been shown to be exquisitely sensitive, responding to as few as 10 antigenic pMHC in an ocean of tens of thousands of self pMHC. In addition, T cells are extremely specific and respond only to a small subset of pMHC by virtue of their specific TCR. To explain the sensitivity of T cells to pMHC it has been proposed that a single pMHC may serially bind multiple TCRs. Integrating present knowledge on the spatial-temporal dynamics of TCR/pMHC in the T cell-APC contact interface, we have constructed mathematical models to investigate the degree of TCR serial engagements by pMHC. In addition to reactions within clusters, the models capture the formation and mobility of TCR clusters. We find that a single pMHC serially binds a substantial number of TCRs in a TCR cluster only if the TCR/pMHC bond is stabilized by coreceptors and/or pMHC dimerization. In a separate study we propose that serial engagements can explain T cell specificity. Using Monte Carlo simulations, we show that the stochastic nature of TCR/pMHC interactions means that multiple binding events are needed for accurate detection of foreign pMHC. Critical to our studies are estimates of TCR/pMHC reaction rates and mobilities. In the second half of the thesis, we show that Fluorescence Recovery After Photobleaching (FRAP) experiments can reveal effective diffusion coefficients. We then show, using asymptotic analysis and model fitting, that FRAP experiments can be used to estimate reaction rates between cell surface proteins, like TCR/pMHC. Lastly, we use FRAP experiments to investigate how the actin cytoskeleton modulates TCR mobility and report effective reaction rates between TCR and the cytoskeleton.University of British Columbia2008-12-15T22:05:56Z2008-12-15T22:05:56Z20082008-12-15T22:05:56Z2009-05Electronic Thesis or Dissertation3507557 bytesapplication/pdfhttp://hdl.handle.net/2429/2894eng
collection NDLTD
language English
format Others
sources NDLTD
topic T cell receptor
Mathematical modeling
spellingShingle T cell receptor
Mathematical modeling
Dushek, Omer
Mathematical modeling in cellular immunology: T cell activation and parameter estimation
description A critical step in mounting an immune response is antigen recognition by T cells. This step proceeds by productive interactions between T cell receptors (TCR) on the surface of T cells and foreign antigen, in the form of peptide-major-histocompatibility-complexes (pMHC), on the surface of antigen-presenting-cells (APC). Antigen recognition is exceedingly difficult to understand because the vast majority of pMHC on APCs are derived from self-proteins. Nevertheless, T cells have been shown to be exquisitely sensitive, responding to as few as 10 antigenic pMHC in an ocean of tens of thousands of self pMHC. In addition, T cells are extremely specific and respond only to a small subset of pMHC by virtue of their specific TCR. To explain the sensitivity of T cells to pMHC it has been proposed that a single pMHC may serially bind multiple TCRs. Integrating present knowledge on the spatial-temporal dynamics of TCR/pMHC in the T cell-APC contact interface, we have constructed mathematical models to investigate the degree of TCR serial engagements by pMHC. In addition to reactions within clusters, the models capture the formation and mobility of TCR clusters. We find that a single pMHC serially binds a substantial number of TCRs in a TCR cluster only if the TCR/pMHC bond is stabilized by coreceptors and/or pMHC dimerization. In a separate study we propose that serial engagements can explain T cell specificity. Using Monte Carlo simulations, we show that the stochastic nature of TCR/pMHC interactions means that multiple binding events are needed for accurate detection of foreign pMHC. Critical to our studies are estimates of TCR/pMHC reaction rates and mobilities. In the second half of the thesis, we show that Fluorescence Recovery After Photobleaching (FRAP) experiments can reveal effective diffusion coefficients. We then show, using asymptotic analysis and model fitting, that FRAP experiments can be used to estimate reaction rates between cell surface proteins, like TCR/pMHC. Lastly, we use FRAP experiments to investigate how the actin cytoskeleton modulates TCR mobility and report effective reaction rates between TCR and the cytoskeleton.
author Dushek, Omer
author_facet Dushek, Omer
author_sort Dushek, Omer
title Mathematical modeling in cellular immunology: T cell activation and parameter estimation
title_short Mathematical modeling in cellular immunology: T cell activation and parameter estimation
title_full Mathematical modeling in cellular immunology: T cell activation and parameter estimation
title_fullStr Mathematical modeling in cellular immunology: T cell activation and parameter estimation
title_full_unstemmed Mathematical modeling in cellular immunology: T cell activation and parameter estimation
title_sort mathematical modeling in cellular immunology: t cell activation and parameter estimation
publisher University of British Columbia
publishDate 2008
url http://hdl.handle.net/2429/2894
work_keys_str_mv AT dushekomer mathematicalmodelingincellularimmunologytcellactivationandparameterestimation
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