The strains of the Sporothrix genus used in this study are listed in Table 1. Yeast cells were maintained at 37°C in yeast extract peptone dextrose (YPD) solid medium (2% glucose, 1% peptone, 0.5% yeast extract, and 1.5% agar; pH = 7.8). For the subsequent assay, yeast cells were cultured in YPD liquid medium at 37°C with aeration on a mechanical shaker (150 rpm). Conidia were obtained after incubation in YPD liquid medium at 25°C with mechanical aeration (150 rpm) for 3 days. Conidia were recovered through successive gaze filtration. Aspergillus nidulans A4 and R21/R153 (dos Reis et al., 2018), haploid and diploid strains, respectively, were maintained in YPD solid medium at 30°C. For subsequent analysis, conidia were collected and washed with phosphate buffered saline (PBS) (1×) (8 g NaCl, 0.2 g KCl, 1.44 g Na₂HPO₄, 0.24 g KH₂PO₄ per liter of sterilized water).

The DNA content of isolated cells was determined accordingly to the protocol described in Almeida et al. (2007) with modifications. Exponentially grown yeast cells and conidia were collected, centrifuged (13,000 rpm for 3 min), and washed with PBS (1×). To obtain an uniform single-cell suspension, collected cells were filtered through sterile gauze and fixed overnight with ethanol 70% (vol/vol) at 4°C. Afterwards, cells were harvested, washed, and resuspended in 850 μl of sodium citrate buffer (50 mM; pH = 7.5). Briefly sonicated Sporothrix spp. cells were treated at 50°C for 4 h with RNase A (0.50 mg/ml) (GRiSP, Porto, Portugal) and for 2 h with proteinase K (1 mg/ml) (GRiSP). A. nidulans conidia, after a brief sonication, were treated at 50°C for 2 h with RNase A (0.50 mg/ml) (GRiSP) and for 2 h with proteinase K (1 mg/ml) (GRiSP). A volume of 50 μl of treated cells was stained overnight with SYBR Green I (10,000×) (Invitrogen, CA, USA) at 4°C. For the yeast cells, a concentration of SYBR Green I of 2% (vol/vol) was used from a 10-fold diluted working solution in Tris-EDTA (pH 8.0) (Sigma-Aldrich). For the case of conidia, a final concentration of 12% (vol/vol) of SYBR Green I (10,000×) was used. Prior to flow cytometry (FCM) analysis, 750 μl of sodium citrate buffer (50 mM; pH 7.5) with 0.25% (vol/vol) of Triton X-100 (Sigma-Aldrich) was added to the stained cells.

Stained cells were analyzed in a FACS LSRII flow cytometer (Becton Dickinson, NJ, USA) with a 488 nm excitation laser. Signals from a minimum of 30,000 cells per sample were captured in FITC channel (530 nm ± 30 nm) at low flow rate of about 1,000 cells/s and an acquisition protocol was defined to measure forward scatter (FSC) and side scatter (SSC) on a four-decade logarithmic scale and mean green fluorescence intensity of SYBR Green I (MFI_SGI) on a linear scale. FACS Diva was used as the acquisition software. Results were analyzed with FlowJo (Tree Star, OR, USA) software, version 10, and the coefficients of variation (CV), as well as MFI_SGI, were estimated using Modfit LT software (Verity Software House, ME, USA).

Yeast cells of genome strains, S. schenckii ATCC MYA-4821 and S. brasiliensis ATCC MYA-4823, and S. pallida MUM 17.04 labeled with SYBR Green I were analyzed using a fluorescence microscope (DP71 Olympus). The images (1,036 × 1,024 pixels) were acquired with an oil immersion objective (100×/1.40) and analyzed with cellSens imaging software (Olympus Life Science, Tokyo, Japan).

Raw sequencing data for S. schenckii (SRX342487) and S. pallida (SRX550176) were downloaded, in FASTQ format, from NCBI’s Sequence Read Archive through the SRA-toolkit (Leinonen et al., 2011). The original NGS sequencing files for S. brasiliensis were used (Teixeira et al., 2014). As controls, the raw sequencing data for Aspergillus flavus NRRL 3357 (haploid, SRX2124714) and Candida albicans SC 5314 (diploid, SRX2250255) were also obtained from NCBI-SRA.

Short raw reads for each species were aligned to the corresponding assembled genome (S. schenckii 1,099–18 GCF_000961545.1, S. brasiliensis 5110 GCA_000820605.1, S. pallida SPA8 GCA_000710705.2, A. flavus NRRL357 GCF_000006275.2, and C. albicans SC5314 GCF_000182965.3) with Bowtie2 (Leinonen et al., 2011) using the “very-sensitive” option. If raw reads were paired, “no-mixed, no-discordant, no-overlap, no-contain” parameters were also used. For each genome, the resulting SAM files were converted to BAM files and sorted with samtools (Li et al., 2009), and then split by chromosomes/scaffolds using bamtools (Barnett et al., 2011).

Allele frequencies at every position along each chromosome/scaffold for all genomes were calculated using the “ploidyNGS” algorithm (Corrêa dos Santos et al., 2017), with default parameters (max_allele_freq 0.95, max_depth 100). Chromosome/scaffold frequency files for each genome were then merged. Ploidy was estimated by constructing histograms from the frequency files and comparing to the haploid and diploid controls.

Data are reported as the mean ± standard deviation (SD) of at least three independent assays. Data were analyzed using MS Excel 2016 (Office, Microsoft^®, WA, USA) and GraphPad Prism Software, version 7.0 (GraphPad Software Inc., CA, USA). A linear regression was calculated to predict the MFI_SGI based on genome size (Mb).

Measuring the DNA content is a well-established method to monitor cell proliferation, cell cycle, and cell ploidy. Despite the relevance of Sporothrix spp. in human and animal diseases, ploidy determination in species of this genus is scarce. Indeed, the diploid status of S. schenckii has been reported (Torres-Guerrero, 1999). To determine the DNA content of the yeast cells of different species of the Sporothrix genus, a protocol for cell cycle analysis using FCM (Fortuna et al., 2000; Almeida et al., 2007) was applied with modifications to obtain lower coefficients of variation. The CV is a measurement of the peak width of DNA from cells in G₀/G₁ phase of the cell cycle and therefore, low CV values are critical for the accuracy of cellular ploidy determination (Fortuna et al., 2000; Almeida et al., 2007). A minimum of cellular debris and clumps was achieved by using exponentially growing cells and gauze filtration (data not shown). Cell separation and the absence of filamentous forms were confirmed by optical microscopy. The RNase A and proteinase K treatments were optimized to achieve CVs lower than 7, as described elsewhere (Table 2; Rodrigues et al., 2003; Almeida et al., 2007). Additionally, different SYBR Green I concentrations – 0.2, 2, 4, and 10% – were used for DNA staining, ensuring that the dye was not limiting (data not shown). Fluorescence microscopy analysis revealed specific nuclear staining, as expected for SYBR Green I, for the analyzed strains (Figure 1).

FCM allows the establishment of a direct correlation between MFI_SGI and the DNA_C (Rodrigues et al., 2003). As a first approach, the genome size of Sporothrix spp. was estimated using a correlation based in the MFI_SGI and the DNA_C of haploid and diploid strains of Saccharomyces cerevisiae (data not shown). The utilization of this well-established DNA content cell standard would allow the analysis of cell populations with n, 2n, and 4n of DNA content. However, SYBR Green I exhibits a preferential binding to GC-rich sequences (Gudnason et al., 2007), with S. cerevisiae and Sporothrix spp. presenting different GC content. In fact, whereas for S. cerevisiae, the percentage of GC content is around 38%, for S. brasiliensis and S. schenckii, the values are of 62%, being for S. globosa and S. pallida of 54 and 52%, respectively (Teixeira et al., 2014; D’Alessandro et al., 2016; Huang et al., 2016). Thus, for the analysis of the cell DNA content of Sporothrix spp., we took advantage of haploid and diploid strains of A. nidulans as reference, which presents a GC content of 50% (Galagan et al., 2005). As such, from the described haploid genome size of A. nidulans (30.07 Mb) (Galagan et al., 2005) and the MFI_SGI obtained for each cellular DNA content (n and 2n, corresponding to G₀/G₁ phase of the cell cycle of haploid and diploid A. nidulans conidia) (Figure 2A1), a linear regression was established – MFI_SGI = (2,659 ± 141.6)*DNA_C + (21,647 ± 6,726) (Figure 2A2; R ² = 0.9888).

Representative histograms for S. brasiliensis, S. schenckii, S. globosa, and S. pallida obtained by FCM are shown in Figures 2B–H, respectively. This figure includes the histograms obtained for the fully sequenced strains: S. brasiliensis ATCC MYA-4823 and S. schenckii ATCC MYA-4821 (Figures 2B,F, respectively) (Teixeira et al., 2014). The average of the DNA_C estimated according to the cells in G₀/G₁ phase of the cell cycle for the different strains of S. brasiliensis analyzed ranged between 25.32 and 29.89 Mb, and was of 24.13, 28.40, and 33.12 Mb for S. schenckii, S. globosa, and S. pallida, respectively (Table 2). Moreover, S. brasiliensis ATCC MYA-4823 and S. schenckii ATCC MYA-4821 conidia presented identical values of MFI_SGI to those presented for the yeast form (Figure 3). Overall, these data suggest that there are no variations in ploidy in the morphological transition from conidia to yeast cells of these Sporothrix spp.

To determine the ploidy of the analyzed organisms, a comparison was performed between the DNA_C of cells in G₀/G₁ phase of the cell cycle, determined by FCM (Table 2), and the genome length reported for each organism from the full sequence analysis. The ploidy state of the studied organisms was inferred by the ratio obtained from these two parameters (designed as ploidy ratio) (Almeida et al., 2007). S. schenckii presented a ploidy ratio of 0.7, suggestive of a haploid profile, although aneuploidy cannot be excluded (Table 2). In what regards S. brasiliensis, the ploidy ratio ranged from 0.9, for the sequenced strain, to 0.8 in other isolates (Table 2). These data point for a haploid profile in these strains. For the analyzed strains of S. globosa and S. pallida, a ploidy ratio of 0.9 was obtained, suggestive also of a haploid profile. Additionally, a DNA_C for S. mexicana MUM 17.07 identical to the other isolates tested was obtained suggesting a haploid status, considering a genome length similar to the other Sporothrix spp. (data not shown).

Ploidy can be determined indirectly – without measuring cellular DNA_C – from the analysis of the short-read sequencing data generated by NGS experiments. Therefore, to strengthen our data, this methodology was also applied to determine the ploidy of Sporothrix spp. Briefly, a typical NGS run produce millions of reads coming from every piece of DNA present on the original sample. After mapping, the NGS reads to an assembled genome, the frequency of variations at every position along the genome can be interpreted to be supporting different alleles at each position and used to infer the ploidy level. In the case of a haploid organism, a single allele for the vast majority of reads it is expected (monomorphic positions), whereas for diploids, polymorphic positions are expected where half of the readings support one allele and the other half support an alternative allele. As controls, we analyzed the allele frequency of NGS data from haploid and diploid fungus, A. flavus and C. albicans, respectively (Figures 4A,B).

As expected, for A. flavus the most abundant allele is close to 95% (monomorphic positions). Conversely, for C. albicans, the histogram displays monomorphic positions, with a frequency close to 95%, and heterozygous positions, with frequencies close to 50% for the first and second more frequent base. The allele frequency plots for S. schenckii, S. brasiliensis, and S. pallida (Figures 4C–E, respectively) present a single peak for both the most abundant allele (close to 95%) and the second most abundant one (close to 5%), supporting the hypothesis that these three strains of Sporothrix spp. are haploid organisms. For S. globosa, a low heterozygosity was also previously described (Huang et al., 2016). The differences on the densities of the histograms can be accounted due to the difference on depth coverage and NGS sequencing technology used in each case (S. schenckii Illumina HiSeq 2000, S. brasiliensis 454 GS FLX, and S. pallida Ion Torrent PGM).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.