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.

项目摘要/摘要 巨噬细胞是每个组织中存在的第一响应者免疫细胞。他们的回答是由 激活数百个免疫反应基因的信号通路。两个功能标志是特征 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，通常对宿主有害。因此， 它们必须以“仅在需要”的基础上部署。但是，尚不清楚特定巨噬细胞如何 响应是，哪些机制控制响应特异性。量化响应的特异性 需要信号传导或基因表达轨迹的单细胞测量，并开发分析 比较分布，量化信息内容，分类精度和混乱的方法。 （2）与上下文相关的功能状态。巨噬细胞的功能适应组织微环境 组织的细胞因子环境特征以及免疫反应或病原体暴露的先前历史。作为 单核细胞通过组织通过组织循环，它们是损伤或感染的潜在生物传感器。 虽然先前的研究已通过染色质或 转录组，单细胞刺激响应数据可能对实际功能状态更具信息性。 考虑到巨噬细胞的这些功能性标志，这两个假设提出了： 1）单细胞刺激反应的定量测量结果表明巨噬细胞响应特异性是 通过影响特征的分布来调节物理和病理环境 人群的异质反应。 2）量化单个巨噬细胞的响应特异性 允许对其功能状态进行表征，这与单细胞转录组分析不同。 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AIM 1中，我们将确定哪些分子机制驱动细胞到细胞异质性以及为什么 NFκB刺激反应的特异性会因细胞因子极化状态而改变。 在AIM 2中，我们将使用一种新颖的模型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 刺激反应和参数，并将其与传统稳态SCRNA-SEQ数据的地图进行比较。 在AIM 3中，我们将研究单细胞中免疫表达反应的刺激特异性是如何 受极化影响。采用新颖的模型辅助方法，我们能够重建动态轨迹 并确定是否通过mRNA抽象或动态特征更好地评估响应特异性。 在对体外两极化巨噬细胞进行填充后，我们将将它们应用于来自的巨噬细胞 不良健康的鼠标模型。见解可能指导未来的翻译研究以评估先天免疫健康。