Tracking the dynamics of the macrophage response to interferon-gamma at a single-cell level

项目摘要 炎症反应的精确时间调节需要清除感染而不损害健康 组织.以前的工作，阐明机制参与这一调节主要集中在单一的 时间点或大量细胞样品。然而，体内的免疫细胞接受免疫调节的复杂时间组合。 在免疫应答过程中的刺激，与随时间变化的基因表达模式反应，并显示 人口中的异质性。干扰素γ（IFNγ）是一种促炎细胞因子， 在免疫反应中的作用。巨噬细胞是免疫细胞，是IFNγ的主要应答者之一。 在感染过程中，巨噬细胞可能经历多个时期的IFNγ刺激，并利用信号传导， 基因表达网络将这些不同的刺激解码成基因表达反应， 功能协调发展的GBP1和NOS2是两个IFNγ应答基因，在宿主防御IFN γ中起重要作用。 微生物和调节不同的网络架构和染色质调控机制。 结核分枝杆菌（Mtb）感染是一个紧迫的全球健康问题，也严重依赖于 巨噬细胞对IFNγ的应答。结核分枝杆菌感染的结果是异质性的细胞以及 生物（人类）水平。先前的工作表明，IFNγ信号对于巨噬细胞的杀伤至关重要 细胞内Mtb，并且这种杀死Mtb的能力在细胞之间变化。该提案使用了一种系统， 将巨噬细胞系中的内源性荧光基因报告与长期活细胞成像相结合， 同时跟踪响应于动力学的多个基因的表达动力学的微流体装置 刺激，以及结核分枝杆菌感染的结果，在相同的单细胞随着时间的推移。这可以用来获得 定量了解动力学基因表达反应和功能的机制， 异质性在目标1中，该系统用于量化和建模单个巨噬细胞基因表达 动态IFNγ刺激后的动力学，并阐明信号解码的机制。这是通过 对巨噬细胞施加不同幅度和持续时间的IFNγ刺激， 在相同的单细胞中，GBP1和NOS2网络的三种组分随时间的表达动力学。一 将建立数学模型来描述这些响应，预测对扰动的响应， 将使用可诱导的启动子和染色质调节剂的抑制剂来干扰解码进行测试。目的2 研究了基因表达动力学中细胞间变异性与异质性结核分枝杆菌之间的联系。 感染结果。这是通过用Mtb感染荧光报告巨噬细胞系来完成的，Mtb由一个 存活力报告基因和测定单细胞中的基因表达动力学和感染结果。的 这些目标的完成将提供对巨噬细胞 将动态IFNγ刺激解码为时变基因表达模式，以及对IFN γ的机制性洞察。 结核分枝杆菌感染结果的异质性来源。

Project Summary Precise temporal regulation of inflammatory responses is required to clear infection without damaging healthy tissue. Previous work elucidating the mechanisms involved in this regulation have focused mainly on single time points or bulk samples of cells. However, immune cells in vivo receive complex temporal combinations of stimuli during an immune response, respond with gene expression patterns that vary over time, and display heterogeneity within the population. Interferon gamma (IFNγ) is a pro-inflammatory cytokine that plays key roles in immune responses. Macrophages are immune cells that are one of the primary responders to IFNγ. During infection, macrophages may experience multiple periods of IFNγ stimulation, and employ signaling and gene expression networks to decode these varying stimuli into gene expression responses and diverse functions. GBP1 and NOS2 are two IFNγ-responsive genes that have important roles in host defense against microbes and are regulated by different network architectures and chromatin regulatory mechanisms. Mycobacterium tuberculosis (Mtb) infection is a pressing global health issue that also depends critically on macrophage responses to IFNγ. Mtb infection outcomes are heterogeneous on the cellular as well as the organismal (human) level. Previous work has shown that IFNγ signaling is essential for macrophages to kill intracellular Mtb and that this ability to kill Mtb varies between cells. This proposal uses a system that combines endogenous fluorescent gene reporters in macrophage cell lines with long-term live-cell imaging in a microfluidic device to simultaneously track expression kinetics of multiple genes in response to dynamic stimuli, as well as the outcomes of Mtb infection, in the same single cells over time. This can be used to obtain a quantitative understanding of the mechanisms underlying kinetic gene expression responses and functional heterogeneity. In Aim 1, this system is used to quantify and model single macrophage gene expression kinetics following dynamic IFNγ stimulus and to elucidate the mechanism of signal decoding. This is done by applying IFNγ stimulus of varying amplitude and duration to the macrophages and simultaneously tracking expression kinetics of three components of the GBP1 and NOS2 networks in the same single cells over time. A mathematical model will be developed to describe these responses, predict the response to perturbation, and will be tested using inducible promoters and inhibitors of chromatin regulators to perturb the decoding. Aim 2 investigates the connection between cell-to-cell variability in gene expression kinetics and heterogeneous Mtb infection outcomes. This is done by infecting fluorescent reporter macrophage cell lines with Mtb marked by a viability reporter and assaying both gene expression kinetics and infection outcomes in single cells. The completion of these aims will provide a quantitative understanding of the mechanisms by which macrophages decode dynamic IFNγ stimuli into time-variant gene expression patterns, as well as mechanistic insight into the sources of heterogeneity in the outcomes of Mtb infection.