Effect of selective interventions on the spatial organization of an inflammation

炎症可以大致分为两个阶段：促炎阶段和炎症消退。在这些阶段的几乎任何给定的时间点，可以观察到亲和亲过程。因此，功能上不同的微环境可以定义的基础上的差异空间定位的亲和亲介质和免疫细胞。免疫细胞对它们从微环境中接收到的信号做出反应，通过调整它们的行动来适应特定的局部情况。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，有必要描述其微环境，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。一种特别适用于描述微环境的技术是多表位配体制图（MELC）。MELC是一种用于连续免疫组织学的成像技术，我们使用它来可视化同一组织切片上的40多种蛋白质。在之前的资助期间，我们采用该系统来研究调节巨噬细胞和肥大细胞促炎功能的信号通路。数据显示了免疫细胞在注射的病原体（酵母聚糖）方面的特定空间分布。这里，可以定义核心区域，其包括病原体、嗜中性粒细胞和促炎性巨噬细胞。该核心区域被巨噬细胞和巨噬细胞介体主导的区域包围。在核心和中间区域之间的区域的特点是树突状细胞和嗜酸性粒细胞。目前的项目的目标是定量评估的空间分布的免疫细胞和信号介质在酵母多糖诱导的炎症。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定位及其相邻细胞。为了研究不同微环境之间的功能关系，将测试区域选择性干预（G2A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，通过FACS验证并与病理生理学影响（例如水肿形成和伤害性行为）进行比较。此外，一个特别的重点将放在识别的细胞在炎症的早期状态和表征他们的作用，在形成的炎症区域的表型。

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.