Automated Image Analysis of the Host-Pathogen Interaction between Phagocytes and Aspergillus fumigatus

Aspergillus fumigatus is a ubiquitous airborne fungus and opportunistic human pathogen. In immunocompromised hosts, the fungus can cause life-threatening diseases like invasive pulmonary aspergillosis. Since the incidence of fungal systemic infections drastically increased over the last years, it is a major goal to investigate the pathobiology of A. fumigatus and in particular the interactions of A. fumigatus conidia with immune cells. Many of these studies include the activity of immune effector cells, in particular of macrophages, when they are confronted with conidia of A. fumigus wild-type and mutant strains. Here, we report the development of an automated analysis of confocal laser scanning microscopy images from macrophages coincubated with different A. fumigatus strains. At present, microscopy images are often analysed manually, including cell counting and determination of interrelations between cells, which is very time consuming and error-prone. Automation of this process overcomes these disadvantages and standardises the analysis, which is a prerequisite for further systems biological studies including mathematical modeling of the infection process. For this purpose, the cells in our experimental setup were differentially stained and monitored by confocal laser scanning microscopy. To perform the image analysis in an automatic fashion, we developed a ruleset that is generally applicable to phagocytosis assays and in the present case was processed by the software Definiens Developer XD. As a result of a complete image analysis we obtained features such as size, shape, number of cells and cell-cell contacts. The analysis reported here, reveals that different mutants of A. fumigatus have a major influence on the ability of macrophages to adhere and to phagocytose the respective conidia. In particular, we observe that the phagocytosis ratio and the aggregation behaviour of pksP mutant compared to wild-type conidia are both significantly increased.烟曲霉（Aspergillus fumigatus）是一种广泛分布的空气传播真菌，同时也是机会致病性人类病原体。在免疫功能低下的宿主中，该真菌可引发侵袭性肺曲霉病等致命性感染。近年来真菌性全身感染的发病率大幅攀升，因此探究烟曲霉的致病机制，尤其是其分生孢子（conidia）与免疫细胞的相互作用，已成为本领域的重要研究目标。 此类研究多会考察免疫效应细胞（immune effector cells，尤其是巨噬细胞（macrophages））在接触烟曲霉野生型及突变菌株分生孢子时的活性变化。 本研究报道了一种针对与不同烟曲霉菌株共孵育的巨噬细胞的激光共聚焦扫描显微镜（confocal laser scanning microscopy）图像自动化分析方法的开发流程。 目前，显微镜图像的分析多依赖人工完成，包括细胞计数及细胞间相互关系的判定，该过程不仅耗时冗长，且极易引入系统误差。 将该分析流程自动化可有效克服上述弊端，并实现分析操作的标准化，这是开展包括感染过程数学建模在内的后续系统生物学研究的必要前提。 为实现上述研究目标，本实验对细胞进行了差异化染色，并通过激光共聚焦扫描显微镜进行成像监测。 为完成图像的自动化分析，我们开发了一套通用适用于吞噬作用（phagocytosis）实验的分析规则集，本研究中该规则集通过Definiens Developer XD软件进行处理。 通过完整的图像分析流程，我们可获取细胞大小、形态、数量及细胞间接触情况等多维度特征参数。 本研究的分析结果显示，不同烟曲霉突变菌株对巨噬细胞黏附及吞噬对应分生孢子的能力具有显著影响。 具体而言，相较于野生型分生孢子，pksP突变株的巨噬细胞吞噬率与细胞聚集行为均显著升高。