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Computational Modelling of Treg Networks in Experimental Autoimmune Encephalomyelitis

Greaves, Richard (2011) Computational Modelling of Treg Networks in Experimental Autoimmune Encephalomyelitis. MSc by research thesis, University of York.

Available under License Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 UK: England & Wales.

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Recent experiments have demonstrated the value of rigorously validated simulation in furthering our understanding of immunology. We seek to expand on a body of existing work at York in which we simulate the mouse disease, Experimental Autoimmune Encephalomyelitis (EAE) which is a model for Multiple Sclerosis. We use a locally developed EAE simulation which was designed using the CoSMoS (Complex Systems Modelling and Simulation) process. The CoSMoS process was conceived with the aim of promoting the development of rigorous complex system models. In the model of EAE employed herein, there are two populations of regulatory T-cells(Treg), CD4 Treg and CD8 Treg. The CD4 Treg serve to stimulate dendritic cells to express a protein called Qa-1. Qa-1 permits CD8 Treg to bind to dendritic cells and be activated by them, thus facilitating regulation of autoimmunity. Previous experimentation demonstrated a large increase in the population of CD8 Treg upon abrogation of the CD4 Treg from the simulation providing that dendritic cells were made capable of constitutively expressing Qa-1.We use simulation to explore two hypotheses proposed to account for this observation. The hypotheses explored are: i) the timing of Qa-1 expression is influential in determining the population of CD8 Treg. ii) removal of spatial competition between Treg sub-types favours expansion of the CD8 Treg population. We demonstrate that both hypotheses are significant in explaining the observed experimental result. We subsequently investigate addition of a further regulatory mechanism to the existing model. This additional mode of regulation is poorly understood, but has been suggested by an expert immunologist to be an important mechanism of disease regulation. We augmented our model to include this pathway so we could make it more closely resemble the real world murine immune system in EAE. The model implemented proved to cause an overly severe reduction in the activation of T-cells, demonstrating the potential influence of this pathway in disease regulation and that the behaviour of this pathway warrants further investigation.

Item Type: Thesis (MSc by research)
Keywords: in silico modelling; agent-based modelling; Experimental Autoimmune Encephalomyelitis
Academic Units: The University of York > Computer Science (York)
Depositing User: Dr Richard Greaves
Date Deposited: 21 Dec 2011 13:10
Last Modified: 08 Aug 2013 08:47
URI: http://etheses.whiterose.ac.uk/id/eprint/1980

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