Quantitative modeling of the phenotypic variability of individual T cells and the

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Our long-term goal is to probe theoretically and experimentally how reliable immune responses emerge at the system level from the unreliable responses of individual T cells. Our first project aims at probing how heterogeneity in the expression levels of key signaling proteins generates phenotypic variability in T cells' responsiveness to ligands. We will also probe how such stochasticity of signaling responses translates into functional phenotypic variability. Our second aim tests how multiplexed signals (e.g. T cell ligands and IL15 cytokine) can activate signaling crosstalks that modulate the levels and/or activity of key signaling proteins and make T cells hyperresponsive to self-derived ligands. Our third aim probes how cytokine regulation integrates cell variability in antigen response at the individual cell level towards a regulated collective response. This project focuses on Interleukin-2 as a critical cytokine that controls quorum sensing among effector T cells and suppression by regulatory T cells. Our approach is fundamentally interdisciplinary with concomitant computational modeling and experimental testing. It consists in making and validating theoretical predictions to quantify and control how immune responses emerge as dynamically- and collectively-regulated properties of individual T cells. PUBLIC HEALTH RELEVANCE: Our project focuses on developing experimentally-validated computer models of T cell activation. Our goal is to identify how reliable immune responses emerge dynamically from the unreliable activation of individual T cells. The long-term impact of our research is in a better control of immune responses towards immunotherapies for cancer and auto- immune disorders.