Use of Image Cytometry for Quantification of Pathogenic Fungi in Association with Host Cells

白色念珠菌 生物 微生物学 新生隐球菌 流式细胞术 碘化丙啶 酵母 病原真菌 吖啶橙 白色体 菌落形成单位 染色 真菌 分子生物学 细菌 程序性细胞死亡 细胞凋亡 植物 生物化学 遗传学
作者
Charlotte Berkes,Leo Li‐Ying Chan,Alisha R. Wilkinson,Benjamin Paradis
出处
期刊:Journal of Visualized Experiments [MyJOVE]
卷期号: (76) 被引量:1
标识
DOI:10.3791/50599
摘要

Studies of the cellular pathogenesis mechanisms of pathogenic yeasts such as Candida albicans, Histoplasma capsulatum, and Cryptococcus neoformans commonly employ infection of mammalian hosts or host cells (i.e. macrophages) followed by yeast quantification using colony forming unit analysis or flow cytometry. While colony forming unit enumeration has been the most commonly used method in the field, this technique has disadvantages and limitations, including slow growth of some fungal species on solid media and low and/or variable plating efficiencies, which is of particular concern when comparing growth of wild-type and mutant strains. Flow cytometry can provide rapid quantitative information regarding yeast viability, however, adoption of flow cytometric detection for pathogenic yeasts has been limited for a number of practical reasons including its high cost and biosafety considerations. Here, we demonstrate an image-based cytometric methodology using the Cellometer Vision (Nexcelom Bioscience, LLC) for the quantification of viable pathogenic yeasts in co-culture with macrophages. Our studies focus on detection of two human fungal pathogens: Histoplasma capsulatum and Candida albicans. H. capsulatum colonizes alveolar macrophages by replicating within the macrophage phagosome, and here, we quantitatively assess the growth of H. capsulatum yeasts in RAW 264.7 macrophages using acridine orange/propidium iodide staining in combination with image cytometry. Our method faithfully recapitulates growth trends as measured by traditional colony forming unit enumeration, but with significantly increased sensitivity. Additionally, we directly assess infection of live macrophages with a GFP-expressing strain of C. albicans. Our methodology offers a rapid, accurate, and economical means for detection and quantification of important human fungal pathogens in association with host cells.
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