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Here, we demonstrate how image cytometry can be used for quantification of pathogenic fungi in association with host cells in culture. This technique can be used as an alternative to CFU enumeration.
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.
Studies of pathogenic fungi in association with their hosts and/or host cells often require quantification of viable fungal cells over a time course or under different infection conditions. Enumeration of colony forming units (CFU) is the standard method by which the number of viable fungal cells has been measured, however, this technique has several drawbacks and limitations. First, many fungal species are slow-growing. Growth of visible colonies on solid media can take 1-2 weeks, significantly slowing the pace of research. Second, manipulation of samples during CFU plating is a laborious process, since several dilutions must be plated to ensure a countable number of colonies. Third, the number of CFU is typically lower than the number of viable organisms plated because the plating efficiency is well below 100%. For example, plating efficiencies for the dimorphic fungal pathogen Histoplasma capsulatum can be as high as 90%, but are routinely as low as 30% and are even lower (10%) for the related fungal dimorph Paracoccidioides brasiliensis 1, 2. Plating efficiency for Candida albicans is also subject to variability 3. Finally, CFU analysis accounts for only live and actively dividing cells capable of establishing growth on solid media, whereas in many situations, it would be useful to determine the presence and concentration of dead and/or metabolically inactive cells.
Previously, flow cytometric methods for quantification of several pathogenic fungal species has been described 4-6. However, due to biosafety containment issues involved with using biosafety level 2 (BSL2) or BSL3-level pathogens on shared flow cytometers, adoption of this technique has been limited. Like flow cytometry, image cytometry is a sensitive and rapid method of cell quantification. However, image cytometry can be performed at a fraction of the cost with comparable results 7-11. Here, we describe methods for performing image cytometry of pathogenic fungi in association with host cells. We demonstrate our methods using two human fungal pathogens: Histoplasma capsulatum and Candida albicans. H. capsulatum is a dimorphic fungal pathogen that causes respiratory disease; in humans, it grows as budding yeast and replicates within alveolar macrophages. Candida albicans is a human commensal species that occasionally causes candidiasis. We show that image cytometry allows rapid quantification of these yeasts, together with visualization capability.
1. Infection of Macrophages with H. capsulatum, C. albicans
2. Macrophage Lysis
3. CFU Plating
4. Visualization of Fungi within Live Macrophages
5. Sample Preparation for Image Cytometric Analysis
6. Cellometer Instrument Setup
7. Cellometer Software Setup
8. Image Acquisition Procedure
9. Image Data Analysis
We used the Cellometer Vision image cytometer to monitor growth of H. capsulatum in macrophage cells. RAW 264.7 cells were infected with H. capsulatum yeast cells and at various time points, samples were subjected to AO/PI staining followed by image-based cytometric analysis. In parallel, samples were analyzed by traditional CFU enumeration. At each time point, samples were incubated in water to lyse macrophages, and the liberated yeast cells were identified by the Cellometer Vision software (F...
Image cytometry allows the user to capture high quality images and, using specialized software, perform rapid quantification of cells. One potential challenge to the adoption of image cytometry in the field of microbial pathogenesis is that the microbes to be counted are present in a mixed population of cells, including mammalian host cells. Here, we demonstrate that image cytometry can be used for the quantification of viable pathogenic yeasts during in vitro macrophage infection. Our methodology not only faith...
The authors Leo Li-Ying Chan and Benjamin Paradis are employees of Nexcelom Bioscience LLC.
Name | Company | Catalog Number | Comments |
REAGENTS | |||
DMEM | Life Technologies | 11965-084 | |
Fetal Bovine Serum | Life Technologies | 16000044 | |
AO/PI Solution | Nexcelom Bioscience | CSK-0102 | |
Disposable Counting Chamber | Nexcelom Bioscience | CHT4-SD100 | |
EQUIPMENT | |||
Cellometer Vision | Nexcelom Bioscience | ||
Cellometer Vision Software | Nexcelom Bioscience |
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