Sporulation is vital for the survival of many diverse organisms as a mechanism to survive until suitable conditions for vegetative growth are met ^[1][2][3]. Fungi are particularly efficient at both spore production and dispersal, and fungal geneticists have capitalized on the connection between sexual development and spore formation to carry out classical genetics in many fungal model systems (e.g., Saccharomyces cerevisiae, Neurospora crassa, and Aspergillus nidulans). The manipulable sexual cycles of these organisms coupled with the ability to isolate recombinant spores led to powerful tools for identifying, characterizing, and manipulating genes in these organisms ^[4][5][6]. These developments greatly progressed the understanding of fundamental fungal biology and other eukaryotic processes.

Among the human fungal pathogens, the opportunity to take advantage of classical genetics has been more limited for a variety of reasons; however, the environmental yeast Cryptococcus is a notable exception. Since the discovery of Cryptococcus sexual development in the 1970s, the use of spores to definitively link genotypes to phenotypes has been a mainstay of the system ^[7]. It could be argued that development of Cryptococcus into the model human fungal pathogen that it is today resulted in large part from the fact that basidiospores (known as spores hereafter) could be manipulated for analysis using classical genetic approaches ^[8]. This facilitated the development of other molecular-genetic tools, ultimately creating a system for the study of fungal pathogenesis with broad utility. The production of spores by Cryptococcus occurs via sexual development between either haploid yeast of opposite mating types (a and α) or of a single mating type (α cells alone). Under appropriate conditions, yeast strains fuse with a partner or undergo endoduplication and then initiate filamentous growth. In response to unknown signals, the terminal filament cells form microscopic fruiting bodies (basidia) in which meiosis and repeated mitoses occur. The mixed haploid mitotic products are then packaged, and spores bud onto the surface of each basidium in four chains ^[8][9]. Because Cryptococcus spores are not contained in an ascus, they can be isolated directly from basidia and analyzed on a per chain, per basidium, or population level (random spore analysis) using microdissection of individual spores ^[10]. While microdissection is invaluable as a genetic tool, it is impractical for use in the generation of large numbers of spores for more comprehensive analyses of spore properties. Anecdotally, many attempts were made to isolate Cryptococcus spores in larger numbers over the decades, but methods used successfully in other systems were not adequate to yield large numbers of pure Cryptococcus spores, thus preventing studies to determine their physical, biochemical, molecular, and virulence properties. Therefore, the vast majority of studies of Cryptococcus biology have focused on the yeast form. It was not until over 50 years after the initial report of spores in crosses that sufficient numbers of pure spores were isolated for fundamental studies. This breakthrough facilitated the discoveries that Cryptococcus spores are more resistant to stress conditions than yeast, they are infectious particles in mammalian disease, they are more likely to cause central nervous system disease than yeast, and they are a potential source of new antifungal drug targets ^{[11][12][13][14]}.

2. Quantitative Germination Assays (QGAs)

While spores play critical roles in the dispersal and survival of Cryptococcus, they are a largely dormant cell type that is incapable of actively replicating. To grow vegetatively and survive in new environments, including the mammalian host, spores must differentiate into yeast through the process of germination. Fungal spore germination has been studied to some degree in model systems like Saccharomyces and Aspergillus; however, the process is surprisingly poorly understood relative to other fungal processes. This is due, in part, to a lack of tools to assess germination specifically. Traditionally, germination in most systems has been evaluated through the ability of a spore to form a colony under nutrient-rich growth conditions. This method resulted in a largely binary readout (growth/no-growth) that assessed both germination and subsequent vegetative growth. The purification of Cryptococcus spores en masse, along with the discoveries that germination in Cryptococcus is largely synchronous, follows a reproducible pattern of morphological change, and is independent of spore concentration facilitated the development of quantitative germination assays (QGAs). QGAs are automated, microscopy-based assessments of changes in cell size and shape that correlate with stage of germination that can be made on an individual spore basis across thousands of spores in a population ^[14][15]. The following protocol has been optimized for use with spores from crosses between the JEC20 and JEC21 strains, but it has been used successfully with spores from many strain backgrounds to determine changes in germination rates and/or population dynamics in mutants of interest, variable nutrient conditions, and in the presence of chemical inhibitors ^[14].

Microscopy-Based Quantitative Germination Assay

All imaging is performed on a Ti2 Elements Nikon Microscope (Nikon, Minato City, Tokyo, Japan) with automatic stage and DS-Qi2 Monochrome Microscope Camera. A humidified stage-top incubator is required to prevent evaporation and maintain proper temperature throughout the experiment (Tokai Hit Stage Top Incubator; Model STXG-TIZWX-SET, TOKAI HIT Co., Gendoji-cho, Fujinomiya, Shizuoka, Japan). An additional heating ring should be placed around the objective to be used to prevent thermal drift.

(1) The microscope and stage-top incubator need to be preheated to minimize thermal drift during long-term experiments. At least 1 h before starting the experiment, fill the stage-top incubator with dH₂O, place the heating ring on the desired objective (20×) and turn the heating element on to 30 °C.

(2) Prepare a 384-well plate (Thermo Fisher Scientific, Waltham, MA, USA, ref no. 142762) with spores, allow them to settle, then add 2× germination medium just prior to starting the assay as follows:

• Dilute highly pure (>97%) spores to 5000 spores/μL in 1× PBS. Add 20 μL of spores to each well (100,000 spores/well). Be sure not to touch the pipette tip to the bottom of the well as this can lead to scratches that interfere with imaging. Allow spores to settle and adhere to the bottom of the well for ~15 min at 4 °C prior to addition of media. Prepare each sample in triplicate wells.
• Add 20 μL 2× germination medium to each well, pipetting up and down gently 5 times to mix. Synthetic Medium with dextrose (2× Synthetic Minimal Medium, 4% Dextrose) is a defined medium (a.k.a. SD Medium) that promotes synchronous and efficient germination.
• Cover plate with plastic wrap to prevent evaporation during the experiment. Place the plastic plate cover on top of the plastic.
• Place the 384-well plate in the stage-top incubator, ensuring it is pushed fully down and sitting flat on the microscope stage.

(3) Using the 20× objective (Nikon CFI Plan Apochromat Lambda 20XC), maneuver to the location of the first well. Make sure to enable the perfect focus (PFS) on the microscope. Spores are in focus when they are dark ovals without any halo-ed edges. Select X, Y, and Z coordinates for each position. Make sure that there is no overlap between images. Select three images per well for a total of nine images per sample.

(4) Once all image locations have been selected, inspect each image individually, and reset the Z coordinate so that each image is in focus, as thermal drift may occur while the experiment is being set up.

(5) Set up Z-stack imaging ranging from +7.5 μm to −7.5 μm from your selected Z-coordinates with imaging every 1.5 μm for a total of 21 images per position. Z-stacks ensure that in-focus images will be obtained across the time course of germination, regardless of any thermal drift. This step is essential because the PFS is not designed to focus on many small cells, as is done in this assay.

(6) Set the microscope to take images every 2 h for 16 h for a total of 9 timepoints. This is the standard imaging time frame for wild type spore germination in SD medium, although longer time courses and alternative intervals can be used as needed for individual experiments.

(7) Ensure that all desired parameters are set properly for the automated experiment (time loop, each XYZ positions, Z-stack, etc.) before starting the image acquisition. Initiate image acquisition.

(8) Once the image collection is completed, export the images to TIFF files.

(9) Select the image from the Z-stack that is most in-focus for each position and time point. Spores should be dark (black/gray) and free of halo-ed edges.

(10) Place images in corresponding folders with the following progression/experiment/sample/time (0H, 2H, etc.)/Input. Create an “output” and “data” folder under each time point before running ImageJ.

(11) Run each sample folder through the ImageJ program. This program quantifies the area and aspect ratio of each spot in the image and compiles them into a spreadsheet.

(12) Run each sample folder through the MATLAB program. This program determines how many spots fit “spore,” “yeast,” or “other” parameters based on size and aspect ratio. It outputs a 2D histogram with size on the X-axis and aspect ratio on the Y-axis for each time point. Population level changes can be tracked over time.

(13) This program also outputs a data.csv file, which can be used for further data manipulation (creating bar plots and rate curves).

Notes: other microscopes, cameras, and temperature regulators can be used as long as the combination of lens and camera provide sufficient resolution (pixels/μm) to image cells.

It is critical that spores used in this assay are pure (<3% yeast). The presence of even a small number of yeast will result in actively replicating yeast overtaking the well during spore germination, leading to uninterpretable results.

Take care during purification and plate loading to not scrape the sides of microfuge tubes or plates. Doing so may cause debris in the samples or scratches on the plate, which obstruct the images and lead to data loss. When loading 384-well plates, avoid using the outer-most wells around the edges because they are often not as flat as those in the middle, and may create issues during imaging. Starting with well F8 is recommended. Similarly, images should be taken away from the edges of wells (~1/4 of a frame away from the edge) due to curvature that can occur in the wells of 384-well plates.