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

单细胞分辨率下单核细胞和巨噬细胞激活的分子和代谢影响

• 批准号: 10552402
• 负责人: Nikolai Slavov
• 金额: $ 28.71万
• 依托单位: NORTHEASTERN UNIVERSITY
• 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/10552402
• 关键词: Algorithms; Atherosclerosis; Automobile Driving; Biomedical Research; Cells; Data; Data Analyses; Environment; Future; Genetic; Genetic Transcription; Goals; Human; Immune response; Infection; Macrophage; Macrophage Activation; Maintenance; Malignant Neoplasms; Masks; Measurement; Mediating; Metabolic; Metabolism; Methods; Modality; Molecular; Pattern; Physiological; Play; Population; Population Analysis; Positioning Attribute; Process; Property; Proteins; Research; Resolution; Role; Shapes; Signal Transduction; System; Testing; Therapeutic; Tumor-associated macrophages; Variant; aerobic glycolysis; experimental study; human disease; monocyte; pathogen; pharmacologic; public health relevance; response; single cell analysis; tissue regeneration; transcriptomics

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.

项目摘要/摘要 单核细胞和巨噬细胞在潜水过程中起作用，从稳态开始 维持免疫反应和组织再生。这些功能是 通过机制与细胞代谢相协调并受到强烈影响 越来越多地研究巨噬细胞种群。但是，这样 研究掩盖了细胞对细胞变化，这是巨噬细胞的继承特性 多样性。实际上，单细胞转录组学数据证明了巨噬细胞 连续梯度而不是离散状态更好地描述了极化 适合隔离和人口分析。然而，转录测量是 不足以表征塑造单核细胞和蛋白质网络的表征 巨噬细胞多样性。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 （例如关键调节剂的定位，例如NF-κB）在原代人单核细胞中 巨噬细胞应对物理相关的代谢环境。 此外，我们将将这种单细胞分析扩展到这些细胞对 病原体相关的分子模式和损伤相关的分子模式。 这些数据将使我们能够确定驱动单核细胞和 巨噬细胞对代谢状态和分子模式的反应。随后，我们 将通过药物和遗传扰动测试这些网络。我们是独特的 自最近开创了用于量化的方法以来，可以进行这项研究 许多单个细胞中的数千种蛋白质。此外，我们有必要的 分析的代谢系统（包括有氧糖酵解）的专业知识，这通常是 与巨噬细胞激活相关）并为数据开发新算法 分析。该项目将促进我们对巨噬细胞免疫代谢的理解 和极化，将引入更灵敏和准确的单细胞的方法 分析，并将提供识别可能性的原则证明 蛋白质介导的单细胞分辨率的分子机制。我们坚信 实现这些目标将对生物医学研究产生变革性的影响 并将为新的，更好的治疗策略提供信息。