Characterizing functional states of macrophages via their stimulus-responses

通过刺激反应表征巨噬细胞的功能状态

• 批准号: 10737449
• 负责人: Alexander Hoffmann
• 金额: $ 71万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10737449
• 关键词: Address; Affect; Autoimmune Diseases; Biological; Biosensor; Cells; Characteristics; Chromatin; Classification; Computer Analysis; Confusion; DNA; Data; Data Set; Development; Disease; Future; Gene Expression; Gene Targeting; Genes; Health; Heterogeneity; Hyperactivity; Immune; Immune Response Genes; Immune response; In Vitro; Individual; Infection; Inflammatory; Injury; Kinetics; Knowledge; Lead; Ligands; Machine Learning; Macrophage; Maps; Measurement; Measures; Mediating; Messenger RNA; Methods; Modeling; Molecular; Molecular Profiling; Mus; Noise; Obesity; Pathologic; Pathology; Physiological; Population; Population Heterogeneity; Reaction Time; Recording of previous events; Reporter; Research; Response to stimulus physiology; Sentinel; Signal Pathway; Signal Transduction; Source; Specificity; Stimulus; Testing; Tissues; aged; cell behavior; cytokine; data integration; epigenomic profiling; epigenomics; experimental study; first responder; immune health; individual response; insight; live cell microscopy; machine learning classifier; mathematical model; monocyte; mouse model; network models; novel; pathogen; pathogen exposure; predictive modeling; receptor; reconstruction; response; single-cell RNA sequencing; tool; transcription factor; transcriptome; transcriptome sequencing; transcriptomics; translational study

Project Summary/Abstract Macrophages are first responder immune cells present in every tissue. Their responses are mediated by signaling pathways that activate hundreds of immune response genes. Two functional hallmarks characterize the deployment of all macrophage functions: (1) Stimulus-Response Specificity. Immune responses are powerful, and often detrimental for the host. Hence, they must be deployed on an “only-as-needed” basis. However, it remains unknown how specific macrophage responses are, and what mechanisms control Response Specificity. Quantifying the specificity of responses requires single-cell measurements of signaling or gene expression trajectories, and the development of analysis methods to compare distributions, quantify information content, precision of classification and confusion. (2) Context-Dependent Functional States. Macrophage functions adapt to the tissue microenvironment via the cytokine milieu characteristic of the tissue and the prior history of immune responses or pathogen exposure. As monocytes circulate through the body passing through tissues, they are potential biosensors of injury or infection. While prior studies have characterized these states via steady-state molecular profiling of chromatin or transcriptome, single-cell stimulus response data may be more informative of actual functional states. Considering these functional hallmarks of macrophages lead to two hypotheses that this proposal addresses: 1) Quantitative measurements of single cell stimulus responses reveal that macrophage Response Specificity is modulated by physiological and pathological context by affecting the distributions that characterize heterogeneous responses in the population. 2) Quantifying the Response Specificity of individual macrophages allows for a characterization of their Functional States, that is distinct from single-cell transcriptomic profiling. We will address these hypotheses using experimental, math modeling, and computational analysis iteratively. In Aim 1, we will determine which molecular mechanisms that drive cell-to-cell heterogeneity and why the specificity of NFκB stimulus-responses is altered by cytokine polarization states. In Aim 2, we will use a novel model-aided data integration approach to quantify for the first time the Response Specificity of individual macrophages. This will allow us to map the landscape of macrophage states based on stimulus-responses and parameters, and compare it to maps of traditional steady-state scRNA-seq data. In Aim 3, we will study how the stimulus-specificity of immune gene expression responses in single-cells are affected by polarization. With a novel model-aided approach, we are able to reconstruct dynamic trajectories and determine whether Response Specificity is better assessed by mRNA abundances or dynamical features. After finetuning these approaches on in vitro polarized macrophages, we will apply them to macrophages from mouse models of ill-health. Insights may guide future translational studies to assess Innate immune Health.

项目总结/摘要 巨噬细胞是存在于每个组织中的第一反应免疫细胞。它们的反应是由 激活数百个免疫反应基因的信号通路。两个功能性特征 所有巨噬细胞功能的部署： (1)刺激-反应特异性。免疫反应是强大的，往往对宿主有害。因此，我们认为， 它们必须“只在需要时”部署。然而，目前尚不清楚巨噬细胞 反应是什么，以及什么机制控制反应特异性。量化反应的特异性 需要信号或基因表达轨迹的单细胞测量，以及分析的发展 方法比较分布，量化信息内容，分类精度和混淆。 (2)上下文相关功能状态。巨噬细胞功能通过免疫调节适应组织微环境。 组织的细胞因子环境特征和免疫应答或病原体暴露的先前历史。作为 单核细胞通过组织在体内循环，它们是损伤或感染的潜在生物传感器。 虽然先前的研究已经通过染色质或DNA的稳态分子谱表征了这些状态， 转录组，单细胞刺激反应数据可能是更多的实际功能状态的信息。 考虑到巨噬细胞的这些功能特征，本提案提出了两个假设： 1)单细胞刺激反应的定量测量揭示巨噬细胞反应特异性是 由生理和病理背景通过影响表征 人群中的异质反应。2)量化单个巨噬细胞的反应特异性 允许表征其功能状态，这与单细胞转录组学分析不同。 我们将使用实验，数学建模和计算分析迭代地解决这些假设。 在目标1中，我们将确定哪些分子机制驱动细胞间异质性，以及为什么 NFκB刺激反应的特异性被细胞因子极化状态改变。 在目标2中，我们将使用一种新的模型辅助数据集成方法来首次量化响应 单个巨噬细胞的特异性。这将使我们能够根据以下信息绘制巨噬细胞状态的地图： 刺激响应和参数，并将其与传统稳态scRNA-seq数据的图谱进行比较。 在目标3中，我们将研究单细胞中免疫基因表达反应的刺激特异性如何 受两极分化的影响。通过一种新的模型辅助方法，我们能够重建动态轨迹 并确定是否响应特异性更好地评估mRNA丰度或动态特征。 在体外极化巨噬细胞上微调这些方法后，我们将把它们应用于巨噬细胞， 健康状况不佳的小鼠模型。这些见解可以指导未来的转化研究，以评估先天免疫健康。