Characterizing functional states of macrophages via their stimulus-responses

项目摘要/摘要 巨噬细胞是存在于每个组织中的第一反应免疫细胞。他们的反应是通过 激活数百个免疫反应基因的信号通路。有两个功能特征 所有巨噬细胞功能的部署： (1)刺激反应特异性。免疫反应很强大，而且往往对宿主有害。因此， 它们必须在“仅在需要时”的基础上部署。然而，目前尚不清楚巨噬细胞的特异性。 反应是什么，以及控制反应特异性的机制是什么。量化回答的特异性 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、量化信息量、分类精确度和混淆程度。 (2)依赖于上下文的功能状态。巨噬细胞的功能通过 组织的细胞因子环境特征和免疫反应或病原体暴露的既往病史。AS 单核细胞在体内循环，通过组织，它们是潜在的损伤或感染的生物传感器。 虽然先前的研究已经通过染色质或 转录组、单细胞刺激反应数据可能更能反映实际的功能状态。 考虑到巨噬细胞的这些功能特征，导致了本提案涉及的两个假设： 1)单细胞刺激反应的定量测量表明，巨噬细胞反应的特异性是 由生理和病理背景调节的，通过影响以下特征的分布 人群中的异质反应。2)量化单个巨噬细胞的反应特异性 允许对它们的功能状态进行表征，这与单细胞转录图谱不同。 我们将反复使用实验、数学建模和计算分析来解决这些假设。 在目标1中，我们将确定驱动细胞间异质性的分子机制，以及为什么 细胞因子极化状态改变了核因子κB刺激反应的特异性。 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条件绘制巨噬细胞状态的地图 刺激反应和参数，并将其与传统的稳态scRNA-seq数据图进行比较。 在目标3中，我们将研究免疫基因表达反应的刺激特异性如何在单细胞中 受两极分化影响。通过一种新的模型辅助方法，我们能够重建动态轨迹 并确定通过mRNA丰度或动态特征来更好地评估反应的特异性。 在体外极化的巨噬细胞上对这些方法进行微调后，我们将把它们应用于来自 健康不佳的小鼠模型。洞察力可能会指导未来的翻译研究，以评估先天免疫健康。

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.