MODELING NATURAL KILLER CELL REPERTOIRE DEVELOPMENT AND ACTIVATION DYNAMICS

摘要

Natural killer (NK) cells are immune system cells that play a key role in several clinical conditions, such as cancer, transplantations and pregnancies. Their activation is determined by the integration of opposing signals received through a set of activating and inhibitory receptors. Self tolerance of NK cells is ensured during a process termed "education", which acts by adjusting the expression frequency of the inhibitory receptors and by tuning the responsiveness of the cell, according to the strength of inhibitory signals it receives. As a result, the NK cell repertoire is comprised of a heterogeneous population of cells that vary in their receptor composition as well as in their functionality. The high complexity of the NK cell repertoire calls for the use of computational methods to elucidate the rules governing its formation and function. Our group investigates several aspects concerning the development and activation of NK cells, at different levels. At the population level, we study the dynamics of developing NK cells using labeling data and overall differential equations. At the repertoire level, we investigate the forces shaping the repertoire composition, in terms of the expression frequencies of each receptor. At the single cell level, it has been shown that the NK cell population is very heterogenic, as each NK cell will behave differently once encountering a target cell. We wish to use computer simulation to understand which characteristics distinguish one NK cell from the other. Finally, we investigate the internal mechanisms that control the activation of the NK cell.