Computational Analysis of CD8 T Cells Using Single Cell Sequencing

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PROJECT SUMMARY Autoimmunity is a complex disorder affecting over 20 million Americans. Unveiling the multi-step process leading to autoimmunity and ultimately the ability to effectively treat disease requires an in-depth understanding of the self-reactive lymphocytes and the mechanisms by which they evade tolerance and promote destruction of self-tissue. Although there has been a large accumulation of quantitative data on the dynamics of CD8 T cell responses following infection, much less is known about how naive CD8 T cells differentiate into various effector pathways, nor about global CD8 T cell gene expression changes during autoimmune disease. Our proposal seeks to combine experimental, computational and mathematical approaches to understand the initiation and development of autoimmune disease by analysis of CD8 T cells. Using well-characterized, tractable experimental models of autoimmune disease, we will test, refine and validate previously published CD4 T cell differentiation mathematical models to develop a model of CD8 T cell differentiation and dysregulation during the autoimmune disease process. Aim 1 will quantitatively define the gene expression kinetics in spontaneous autoimmune models with multiple disease manifestations. In Aim 2 we will expand this evaluation to several autoimmune models with some overlapping and distinct autoimmune disease outcomes to systematically define the genes and pathways that underlie immune abnormalities critical to the development of individual diseases and those that underlie multiple diseases. We will further compare these data to published patient data to focus on clinically relevant genes. In Aim 3 we will combine the results of Aim 1 and 2 to mathematically model CD8 T cell gene expression kinetics, and validate this model using mouse in vivo disease studies. This mathematical model will enable us to predict the gene signatures driving CD8 T cell fate choices and triggering autoimmunity.