Hessian-based quantitative image analysis of host-pathogen confrontation assays.

Host-fungus interactions have gained a lot of interest in the past few decades, mainly due to an increasing number of fungal infections that are often associated with a high mortality rate in the absence of effective therapies. These interactions can be studied at the genetic level or at the functional level via imaging. Here, we introduce a new image processing method that quantifies the interaction between host cells and fungal invaders, for example, alveolar macrophages and the conidia of Aspergillus fumigatus. The new technique relies on the information content of transmitted light bright field microscopy images, utilizing the Hessian matrix eigenvalues to distinguish between unstained macrophages and the background, as well as between macrophages and fungal conidia. The performance of the new algorithm was measured by comparing the results of our method with that of an alternative approach that was based on fluorescence images from the same dataset. The comparison shows that the new algorithm performs very similarly to the fluorescence-based version. Consequently, the new algorithm is able to segment and characterize unlabeled cells, thus reducing the time and expense that would be spent on the fluorescent labeling in preparation for phagocytosis assays. By extending the proposed method to the label-free segmentation of fungal conidia, we will be able to reduce the need for fluorescence-based imaging even further. Our approach should thus help to minimize the possible side effects of fluorescence labeling on biological functions. © 2017 International Society for Advancement of Cytometry.

Identification of the antiphagocytic trypacidin gene cluster in the human-pathogenic fungus Aspergillus fumigatus.

The opportunistic human pathogen Aspergillus fumigatus produces numerous different natural products. The genetic basis for the biosynthesis of a number of known metabolites has remained unknown. The gene cluster encoding for the biosynthesis of the conidia-bound metabolite trypacidin is of particular interest because of its antiprotozoal activity and possible role in the infection process. Here, we show that the genes encoding the biosynthesis enzymes of trypacidin reside within an orphan gene cluster in A. fumigatus. Genome mining identified tynC as an uncharacterized polyketide synthase with high similarity to known enzymes, whose products are structurally related to trypacidin including endocrocin and fumicycline. Gene deletion of tynC resulted in the complete absence of trypacidin production, which was fully restored when the mutant strain was complemented with the wild-type gene. When confronted with macrophages, the tynC deletion mutant conidia were more frequently phagocytosed than those of the parental wild-type strain. This was also found for phagocytic amoebae of the species Dictyostelium discoideum, which showed increased phagocytosis of ΔtynC conidia. Both macrophages and amoebae were also sensitive to trypacidin. Therefore, our results suggest that the conidium-bound trypacidin could have a protective function against phagocytes both in the environment and during the infection process.

Automated quantification of the phagocytosis of Aspergillus fumigatus conidia by a novel image analysis algorithm.

Studying the pathobiology of the fungus Aspergillus fumigatus has gained a lot of attention in recent years. This is due to the fact that this fungus is a human pathogen that can cause severe diseases, like invasive pulmonary aspergillosis in immunocompromised patients. Because alveolar macrophages belong to the first line of defense against the fungus, here, we conduct an image-based study on the host-pathogen interaction between murine alveolar macrophages and A. fumigatus. This is achieved by an automated image analysis approach that uses a combination of thresholding, watershed segmentation and feature-based object classification. In contrast to previous approaches, our algorithm allows for the segmentation of individual macrophages in the images and this enables us to compute the distribution of phagocytosed and macrophage-adherent conidia over all macrophages. The novel automated image-based analysis provides access to all cell-cell interactions in the assay and thereby represents a framework that enables comprehensive computation of diverse characteristic parameters and comparative investigation for different strains. We here apply automated image analysis to confocal laser scanning microscopy images of the two wild-type strains ATCC 46645 and CEA10 of A. fumigatus and investigate the ability of macrophages to phagocytose the respective conidia. It is found that the CEA10 strain triggers a stronger response of the macrophages as revealed by a higher phagocytosis ratio and a larger portion of the macrophages being active in the phagocytosis process.

Virulent strain of Lichtheimia corymbifera shows increased phagocytosis by macrophages as revealed by automated microscopy image analysis.

Lichtheimia corymbifera is a ubiquitous soilborne zygomycete fungus, which is an opportunistic human pathogen in immunocompromised patients. The fungus can cause life-threatening diseases by attacking the lung during early stages of invasion and by disseminating during later phases causing systemic infection. Since infections have drastically increased during the last decades, it is a major goal to investigate the mechanisms underlying pathogenicity of L. corymbifera. One of the first barriers, which the fungus needs to cope with in the lung tissue, is phagocytosis by alveolar macrophages. Here, we report on phagocytosis assays for murine alveolar macrophages co-incubated with resting, swollen and opsonised spores of a virulent and an attenuated L. corymbifera strain. A major finding of this study is the significantly increased phagocytosis ratio of the virulent strain if compared to the attenuated strain. We quantify the phagocytosis by performing automated analysis of fluorescence microscopy images and by computing ratios for (i) fungal phagocytosis, (ii) fungal adhesion to phagocytes and (iii) fungal aggregation and spore cluster distribution in space. Automation of the image analysis yields objective results that overcome the disadvantages of manual analyses being time consuming, error-prone and subjective. Therefore, it can be expected that automated image analysis of confrontation assays will play a crucial role in future investigations of host-pathogen interactions.