Molecular and metabolic influences on the activation of monocytes and macrophages at single-cell resolution

项目摘要/摘要 单核细胞和巨噬细胞在不同的过程中发挥作用，从动态平衡 维持免疫反应和组织再生。这些函数是 通过以下机制与细胞新陈代谢协调并受到其强烈影响 在巨噬细胞群体中越来越多地研究和表征。然而，这样的 研究掩盖了巨噬细胞固有的特性--细胞间的变异 多样性。事实上，单细胞转录数据已经证明巨噬细胞 偏振更好地用连续的梯度来描述，而不是离散的状态 易于隔离和种群分析。然而，转录测量是 不足以描述形成单核细胞的代谢和蛋白质网络 巨噬细胞多样性。为了了解这些网络如何控制巨噬细胞 极化和功能，我们建议直接量化蛋白质和调节信号 (例如，关键调节因子，例如，核因子-κB)在原代人类单核细胞中的定位以及 巨噬细胞对生理相关代谢环境的反应。 此外，我们将把这种单细胞分析扩展到这些细胞的反应，以 病原体相关分子模式和损伤相关分子模式。 这些数据将使我们能够确定可能的调控网络驱动单核细胞和 巨噬细胞对代谢状态和分子模式的反应。随后，我们 将通过药理和遗传扰动来测试这些网络。我们独一无二 定位于执行这项研究，因为我们最近率先提出了量化方法 数以千计的蛋白质分布在许多单个细胞中。此外，我们有所需的 分析代谢系统的专业知识(包括有氧糖酵解，这经常是 与巨噬细胞激活相关)，并开发新的数据算法 分析。这个项目将促进我们对巨噬细胞免疫代谢的理解。 和极化，将介绍更灵敏和准确的单细胞方法 分析，并将提供一份原则证明演示，以确定 蛋白质在单细胞分辨率下的分子机制。我们坚信 实现这些目标将对生物医学研究产生革命性的影响 并将为新的更好的治疗策略提供信息。

Project Summary/Abstract Monocytes and macrophages function in diverse processes, from homeostatic maintenance to immune responses and tissue regeneration. These functions are coordinated with and strongly influenced by cellular metabolism via mechanisms that are increasingly studied and characterized in populations of macrophages. However, such studies mask the cell-to-cell variation which is an inherent property of macrophage diversity. Indeed, single-cell transcriptomics data have demonstrated that macrophage polarization is better described by continuous gradients rather than by discrete states amenable to isolation and population analysis. Yet, transcriptional measurements are insufficient to characterize the metabolic and protein networks that shape monocyte and macrophage diversity. To understand how these networks control macrophage polarization and functions, we propose to directly quantify proteins and regulatory signals (such as localization of key regulators, e.g., NF-κB) in primary human monocytes and macrophages responding to physiologically relevant metabolic environments. Furthermore, we will extend this single-cell analysis to the responses of these cells to pathogen-associated molecular patterns and damage-associated molecular patterns. These data will enable us to identify likely regulatory networks driving monocyte and macrophage responses to metabolic states and molecular patterns. Subsequently, we will test these networks via pharmacological and genetic perturbations. We are uniquely positioned to perform this research since we recently pioneered methods for quantifying thousands of proteins across many single cells. Furthermore, we have the required expertise in analyzing metabolic systems (including aerobic glycolysis, which is frequently associated with macrophage activation) and developing new algorithms for data analysis. This project will advance our understanding of macrophage immunometabolism and polarization, will introduce methods for more sensitive and accurate single-cell analysis, and will provide a proof-of-principle demonstration of the possibility to identify protein-mediated molecular mechanisms at single-cell resolution. We strongly believe that attaining these goals will have a transformative impact on biomedical research and will inform new and better therapeutic strategies.