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

在单细胞水平追踪巨噬细胞对干扰素γ反应的动态

• 批准号: 10757599
• 负责人: Beverly Naigles
• 金额: $ 4.15万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10757599
• 关键词: Bacteria; Biological Assay; Biological Models; Cell Line; Cells; Chromatin; Communicable Diseases; Complex; Data; Differential Equation; Disease; EP300 gene; Engineering; Environment; Foundations; GBP1 gene; Gene Expression; Gene Expression Profile; Genes; Genetic Engineering; Heterogeneity; Host Defense; Human; IRF1 gene; Image; Immune; Immune response; Individual; Infection; Infection Control; Inflammatory; Inflammatory Response; Innate Immune Response; Interferon Type II; Kinetics; Macrophage; Mediating; Microbe; Microfluidic Microchips; Microfluidics; Modeling; Mycobacterium tuberculosis; NOS2A gene; Nitric Oxide Synthase; Outcome; Patients; Pattern; Phagosomes; Physiologic pulse; Play; Population; Regulation; Reporter; Reporter Genes; Role; Sampling; Signal Transduction; Source; Stimulus; Symptoms; System; Testing; Time; Tissues; Tuberculosis; Visualization; Work; adaptive immune response; cell type; chromatin remodeling; cytokine; cytotoxic; experience; experimental study; genetic variant; global health; immunopathology; improved; in vivo; inhibitor; insight; live cell imaging; mathematical model; network architecture; new therapeutic target; novel; predicting response; predictive modeling; promoter; response; transcription factor USF

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.

项目摘要 需要精确对炎症反应的临时调节以清除感染而不会损害健康 组织。以前阐明该法规所涉及的机制的工作主要集中在单一方面 时间点或大量细胞样品。但是，体内免疫细胞接受了复杂的临时组合 免疫响应期间的刺激，以随着时间变化的基因表达模式响应，并显示 人口中的异质性。干扰素伽玛（IFNγ）是促键的促炎细胞因子 在免疫调查中的作用。巨噬细胞是免疫细胞，是对IFNγ的主要反应者之一。 在感染过程中，巨噬细胞可能会经历多个IFNγ模拟，以及员工信号传导和 基因表达网络将这些变化的刺激解码为基因表达反应和潜水 功能。 GBP1和NOS2是两个IFNγ响应基因，在宿主防御中具有重要作用 微生物，并由不同的网络体系结构和染色质调节机制进行调节。 结核分枝杆菌（MTB）感染是一个紧迫的全球健康问题，也取决于 巨噬细胞对IFNγ的反应。 MTB感染结果在细胞和细胞上都是异质的 有机（人）水平。先前的工作表明，IFNγ信号对于巨噬细胞杀死至关重要 细胞内MTB和这种杀死MTB的能力在细胞之间有所不同。该建议使用一个系统 结合巨噬细胞系中的内源性荧光基因报告基因在A中的长期活细胞成像 微流体装置可轻松跟踪多个基因的表达动力学，以响应动态 随着时间的推移，刺激以及MTB感染的结果。这可以用来获得 对动力学基因表达响应和功能性的机制的定量理解 异质性。在AIM 1中，该系统用于量化和模拟单巨噬细胞基因表达 动态IFNγ刺激后的动力学并阐明了信号解码的机制。这是由 将不同放大器和持续时间的IFNγ刺激应用于巨噬细胞，并同时跟踪 随着时间的推移，GBP1和NOS2网络的三个组件的表达动力学随着时间的流逝。一个 将开发数学模型来描述这些响应，预测对扰动的响应以及 将使用可诱导的启动子和染色质调节剂的抑制剂进行测试以扰动解码。目标2 研究基因表达动力学中细胞与细胞变异性之间的联系与异质MTB 感染结果。这是通过感染的荧光报告基因巨噬细胞系的MTB标记的 生存力记者并在单细胞中分析基因表达动力学和感染结果。这 这些目标的完成将提供对巨噬细胞的机制的定量理解 将动态IFNγ刺激解码为时变化的基因表达模式，以及机械洞察力 MTB感染结果中异质性的来源。