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

项目总结 细胞间的可变性提供了一种策略，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成细胞子集的调控基序， 不同的功能在一个群体中。巨噬细胞，先天免疫系统的细胞，提供 研究细胞亚群调节的理想实验系统，因为它们是瞬时的 采用极化状态(即，量身定做的分子集)以满足不断变化的功能需求 纸巾。然而，执行一项任务所采用的偏振状态对于-或 即使在与执行其他任务相反的情况下，也引发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冲突提示编码的功能需求。总体目标 这一建议的目的是定义细胞内和细胞外信号传递网络，这些网络调节 异质促炎(例如，对脂多糖+干扰素-γ的反应)与抗炎(例如，在 对IL-4)巨噬细胞亚群的反应，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了巨噬细胞亲与抗 通过上下文相关机制协调的炎症性亚集。为了测试这一点 假设，我们将把单细胞测量与数学建模相结合来确定 如果相互抑制和集体感知是利用细胞到细胞的重要网络主题 可变性和组织适当的极化状态，以满足组织的功能需求。 达到提议的目标将提供另一种描述巨噬细胞的方式。 先天免疫中的极化光谱，通过将其概念化为一组功能细胞亚集 从多个相互竞争的网络主题中涌现出来。建议的研究具有创新性。 因为我们将测量在与相互冲突的环境共同刺激后的单细胞反应 信号-具体地说，具有已知的调节串扰和细胞-细胞机制的信号 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。这项拟议的研究具有重要意义，因为它 预计将具有广泛的翻译潜力，以确定更具体的治疗目标 改变体内巨噬细胞的功能状态以治疗以 巨噬细胞的功能。

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.