Mathematical modeling of MHC Class II mediated immune responses in tissues

Zhou, Wen
Major Professor
Bo Su
Paul E. Sacks
Committee Member
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In this thesis, we developed a spatial-temporal mathematical model to capture fundamental aspects of MHC Class II mediated immune responses, which plays an essential role in protecting the host from a broad range of pathogens. To capture its essential mechanisms, we have considered terms that broadly describe intercellular communication, cell movement, and effector function (activation or inhibition). By defining the pathogen based on the associated antigens±Pathogen Associated Molecular Patterns (PAMPs), a framework to model phenotypic characteristics of pathogens is introduced. It includes the initial dose, distribution at infection site, secretion rate of associated soluble antigens, replication rate of particulate antigens, resistance of an antigen to be effectively processed by immune agents and capacity of intracellular antigens.

The model can account for antigen recognition, an innate immune response, and an adaptive immune response, and the elimination of antigen and subsequent resolution of the immune response against an acute infection or equilibrium of the immune response to the presence of persistent antigen (chronic infection). The model is robust to variation in pathogen loads and types. We demonstrate, using numerical simulations that the model can successfully respond to broad classes of pathogens. Challenged by the in silicopathogens, our model mimics different immunobiological scenarios: a highly skewed TH1 response is generated against some virtual pathogens (e.g. those modeled after Mycobacterium tuberculosis,Leishmania major etc.) and granuloma formation is observed, other virtual pathogens lead to an unskewed or mixed response (e.g. such asLeishmania mexicana etc.) and some virtual pathogens lead to a TH1 to TH2 switch (modeled afterM. avium paratuberculosis), and a TH2 responses is generated against sole extracellular pathogens (e.g. parasitic worms such asnippostrongylus etc.). Based on the model, we propose testable predictions and hypothesis to explain the critical immunobiological phenomena, such as TH1 and TH2 switch inmycobacterium infections.