Effect of selective interventions on the spatial organization of an inflammation

炎症大致可分为两个阶段：前炎症阶段和炎症消退阶段。在这些阶段中几乎任何给定的时间点，都可以观察到促炎和抗炎过程。因此，基于促炎和抗炎介质和免疫细胞的不同空间定位，可以定义不同的功能微环境。免疫细胞对它们从微环境接收到的信号做出反应，根据特定局部情况的需要调整自己的行动。因此，为了了解炎症背景下免疫细胞表型和功能的调节机制，有必要表征它们的微环境，特别是形成这些微环境的不同免疫细胞群体之间的空间关系。多表位配基图谱(MALC)是一种特别有助于表征微环境的技术。MELC是一种序列免疫组织学成像技术，我们使用它在同一组织切片上可视化40多种蛋白质。在之前的资助期间，我们使用这个系统来研究信号通路，它调节巨噬细胞和肥大细胞的促炎功能。数据显示了关于注射的病原体(酵母多糖)的免疫细胞的特定空间分布。在这里，可以定义一个核心区域，它包括病原体、中性粒细胞和促炎巨噬细胞。这一核心区域被抗炎巨噬细胞和抗炎介质主导的区域所包围。核心和抗炎区之间的中间区域以树突状细胞和嗜酸性粒细胞为特征。本项目的目标是定量评估酵母多糖诱导炎症过程中免疫细胞和信号介质的空间分布。目标是识别和定义炎症过程中出现的不同微环境。在这方面，将使用机器学习方法分析MELC数据，以描述免疫细胞及其邻近细胞的定位。为了研究不同微环境之间的功能关系，将测试和验证区域选择性干预(G2A基因敲除小鼠、嗜酸性粒细胞耗竭和药物干预)对炎症结构的影响，并将其与诸如水肿形成和伤害性行为等病理生理效应进行比较。此外，还将特别关注炎症早期具有抗炎表型的细胞的鉴定，以及它们在抗炎区形成中的作用。

An inflammation can be roughly divided in two phases: the proinflammatory phase and the resolution of inflammation. At nearly any given time point during these phases, pro- as well as antiinflammatory processes can be observed. Thus, functionally different microenvironments can be defined based on the differential spatial localization of pro- and antiinflammatory mediators and immune cells. Immune cells respond to signals they receive from their microenvironment by adjusting their actions to the needs of the specific local situation. Therefore, to understand the mechanisms, which regulate immune cell phenotypes and functions, in the context of an inflammation, it is necessary to characterize their microenvironment and specifically the spatial relations between the different immune cell populations forming these microenvironments.One technology, which is especially useful to characterize microenvironments, is the Multi-Epitope-Ligand-Cartography (MELC). MELC is an imaging technology for sequential immunohistology, which we use to visualize over 40 proteins on the same tissue slice. In the previous funding period we employed this system to investigate signaling pathways, which regulate the proinflammatory functions of macrophages and mast cells. The data showed a specific spatial distribution of the immune cells in regard to the injected pathogen (zymosan). Here, a core region can be defined, which comprises the pathogen, neutrophils and proinflammatory macrophages. This core region is surrounded by a region dominated by antiinflammatory macrophages and antiinflammatory mediators. The intermediary area between the core and the antiinflammatory region is characterized by dendritic cells and eosinophils.The objective of the current project is the quantitative assessment of the spatial distribution of immune cells and signaling mediators during a zymosan-induced inflammation. The goal is to identify and define the different microenvironments, which arise during the course of an inflammation. In this regard, the MELC data will be analyzed to describe immune cell localization and their neighboring cells using a machine learning approach. To investigate the functional relationships between the different microenvironments, the effect of region-selective interventions (G2A knockout mice, eosinophil depletion and pharmacological intervention) on the inflammatory architecture will be tested, validated by FACS and compared to pathophysiological effects, such as edema formation and nociceptive behavior. Also, a special focus will be put on the identification of cells with an antiinflammatory phenotype in early states of the inflammation and the characterization of their role in the formation of the antiinflammatory region.