Systems analysis of cell-to-cell variability and signaling-transcription factor motifs regulating macrophage responses to conflicting environmental cues

细胞间变异性和调节巨噬细胞对冲突环境线索反应的信号转录因子基序的系统分析

• 批准号: 10608184
• 负责人: KATHRYN MILLER-JENSEN
• 金额: $ 33.46万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10608184
• 关键词: Adopted; Affect; Anti-Inflammatory Agents; Antiviral Response; Behavior; Biological; Cell Communication; Cells; Chronic; Complex; Cues; Data; Disease; Equilibrium; Flow Cytometry; Future; Genetic Transcription; Heterogeneity; Homeostasis; Immune; Individual; Infection; Inflammatory; Inflammatory Response; Innate Immune System; Interferon Type II; Interferons; Interleukin-4; Knowledge; Link; Macrophage; Macrophage Activation; Malignant Neoplasms; Mammalian Cell; Measurement; Measures; Messenger RNA; Molecular; Natural Immunity; Noise; Paracrine Communication; Physiologic pulse; Population; Population Density; Proteins; Proteome; Public Health; Regulation; Research; Signal Transduction; System; Systems Analysis; Testing; Therapeutic; Tissues; Transcriptional Activation; Variant; Work; cellular targeting; density; extracellular; fighting; in vivo; innovation; live cell imaging; mathematical model; non-genetic; non-healing wounds; pathogen; programs; recruit; response; single-cell RNA sequencing; therapeutic target; transcription factor; transcriptome; translational impact; translational potential; tumor; wound healing

PROJECT SUMMARY Cell-to-cell variability provides a strategy by which cells can explore diverse states; little is known, however, about the regulatory motifs that stabilize particular states into cell subsets that enable diverse functions within a population. Macrophages, cells of the innate immune system, provide an ideal experimental system to study the regulation of cell subsets, because they transiently adopt polarization states (i.e., tailored sets of molecules) to meet changing functional demands in tissues. However, the polarization state adopted to perform one task is often suboptimal for–or even in opposition to–performing other tasks, raising the question of how macrophages respond to conflicting microenvironmental cues. Our recent work suggests that cell-to-cell variation in mutually inhibitory transcription factor (TF) networks increases macrophage functional diversity and enables them to meet functional demands encoded by conflicting cues. The overall objective of this proposal is to define intracellular and extracellular signaling–TF networks that regulate heterogeneous pro-inflammatory (e.g., in response to LPS+IFN-γ) vs. anti-inflammatory (e.g., in response to IL-4) macrophage subsets and ultimately coordinate a coherent functional response. Our central hypothesis is that mutually inhibitory networks establish macrophage pro- vs. anti- inflammatory subsets that are coordinated via context-dependent mechanisms. To test this hypothesis, we will integrate single-cell measurements with mathematical modeling to determine if mutual inhibition and collective sensing are important network motifs for harnessing cell-to-cell variability and organizing appropriate polarization states to meet functional demands in tissues. Achieving the proposed aims would provide an alternative way to describe the macrophage polarization spectrum in innate immunity, by conceptualizing it as a set of functional cell subsets that emerge from multiple competing network motifs. The proposed research is innovative because we will measure single-cell responses after co-stimulation with conflicting environmental cues–specifically, cues that have known mechanisms of regulatory cross talk and cell-cell communication–in order discover new regulatory mechanisms and establish new frameworks describing macrophage functional diversity. The proposed research is significant because it is expected to have broad translational potential to identify therapeutic targets that more specifically alter macrophage functional states in vivo to treat conditions characterized by dysregulation of macrophage functions.

项目摘要 细胞间的变异性提供了一种策略，通过这种策略，细胞可以探索不同的状态;人们对此知之甚少， 然而，关于将特定状态稳定为细胞亚群的调节基序， 在一个群体中的不同功能。巨噬细胞，先天免疫系统的细胞，提供 一个理想的实验系统，研究细胞亚群的调节，因为他们短暂 采用偏振状态（即，定制的分子组），以满足不断变化的功能需求， 组织中然而，执行一项任务所采用的偏振状态对于-或-来说往往是次优的 甚至与执行其他任务相反，这就提出了巨噬细胞如何反应的问题。 相互冲突的微环境线索。我们最近的研究表明，细胞间的变异， 相互抑制转录因子（TF）网络增加巨噬细胞功能多样性 并使它们能够满足由相互冲突的线索编码的功能需求。总体目标 该建议的一个重要方面是定义细胞内和细胞外信号传导-TF网络， 异质促炎性（例如，响应LPS+IFN-γ）与抗炎（例如，在 对IL-4的反应）巨噬细胞亚群，并最终协调一致的功能反应。 我们的中心假设是，相互抑制的网络建立巨噬细胞亲与抗， 炎症亚群通过上下文依赖性机制协调。为了验证这一 假设，我们将整合单细胞测量与数学建模，以确定 如果相互抑制和集体感知是利用细胞到细胞的重要网络模式 可变性和组织适当的偏振状态以满足组织中的功能需求。 实现所提出的目标将提供一种描述巨噬细胞的替代方法。 极化光谱在先天免疫，通过概念化它作为一组功能细胞亚群 从多个相互竞争的网络图案中涌现出来。该研究具有创新性 因为我们将测量单细胞在与冲突环境共刺激后的反应， 线索--具体来说，是具有已知的调节串扰和细胞间串扰机制的线索 沟通-以发现新的监管机制和建立新的框架 描述巨噬细胞功能多样性。这项研究之所以重要，是因为 预期具有广泛的翻译潜力，以鉴定更特异性地 在体内改变巨噬细胞功能状态以治疗以巨噬细胞功能失调为特征的病症， 巨噬细胞功能。