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

Abstract

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.

Keywords: Aspergillus fumigatus; alveolar macrophages; automated image analysis; host-pathogen interaction; phagocytosis assay.

Figure 1

Example of image data from the phagocytosis assay. (A) Green layer (FITC staining) with all conidia. (B) Blue layer (Calcoflour white staining) overlaid with the FITC layer revealing the difference between phagocytosed and non-phagocytoced conidia as only the latter were stained with Calcoflour white (differential staining). (C) Red layer (anti-CD9 antibody) with macrophages and (D) overlay of all layers.

Figure 2

Schematic representation of the automated image analysis algorithm with boxes showing input and output of image analysis processes. Circled numbers indicate split points where the different processes were performed, e.g., thresholding or object classification. For the details of each split point we refer the reader to the text.

Figure 3

Pre-processing and segmentation of conidia. (A) Original scene showing a cluster of conidia and an isolated conidium. (B) Scene after pre-processing with a Gaussian filter. (C) Scene after thresholding into background and foreground indicated by magenta borders. (D) Distinguishing the foreground between clusters (cyan) and single conidia (magenta). Segmentation of the cluster into smaller clusters and finally single conidia after (E) the first and (F) the third iteration.

Figure 4

Preprocessing and segmentation of macrophages. (A) Original scene showing macrophages. (B) Scene after pre-processing with a Gaussian filter. (C) Scene after thresholding into background and foreground indicated by yellow borders. (D) Scene after merging the background enclosed by foreground into foreground. (E) Scene after edge detection and application of a Gaussian filter. Scene after (F) application of watershed segmentation and (G) merging of surrounding border foreground into background. (H) Scene after region growing enabling classification into individual macrophages.

Figure 5

Final image analysis result of the scene in Figure 1. (A) All conidia and (B) conidia after classification as being phagocytosed (green border) or non-phagocytosed (magenta border). (C) Segmented macrophages. (D) Overlay of all image layers showing the final result of image analysis.

Figure 6

Two-dimensional probability distributions of adherent and phagocytosed conidia over macrophages for the two A. fumiatus strains ATCC and CEA10.

Figure 7

One-dimensional probability distributions for a macrophage to have a certain number of (A) adherent and (B) phagocytosed conidia.

Figure 8

Comparison of phagocytosis measures between the two A. fumiatus strains ATCC and CEA10. (A) Phagocytosis ratio φ_c. (B) Uptake ratio φ_m. (C) Phagocytic index φ_i. (D) Symmetrized phagocytic index φ^sym_i. See the text for details.

Figure 9

Comparison of aggregation ratio, γ_r, of non-phagocytosed conidia between the two A. fumiatus strains ATCC and CEA10. Aggregation ratio relative to (A) all non-phagocytosed conidia, (B) adherent conidia, and (C) non-adherent conidia.