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      Cryptococcus and Beyond—Inositol Utilization and Its Implications for the Emergence of Fungal Virulence

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          Abstract

          There are over one million fungal species in nature, but only a handful of them cause human diseases. A variety of distinct factors aid the virulence of fungi in their transition from environmental reservoirs to mammals. One important factor is their ability to acquire nutrients efficiently so that they can survive and thrive in a nutrient-limiting host environment. The human fungal pathogen Cryptococcus neoformans (C. neoformans) is the most common cause of fungal meningitis, yet the mechanisms of Cryptococcus neurotropism remain poorly understood. Recent studies have revealed that Cryptococcus has evolved sophisticated acquisition systems to utilize the carbohydrate inositol both in plant niches and in human brains, where abundant inositol is available. Inositol utilization in Cryptococcus and its likely contribution to Cryptococcus virulence may represent one example of a common trait for the emergence of pathogens from environmental reservoirs. Cryptococcus Can Undergo Sexual Reproduction by Utilizing Inositol from Plants C. neoformans and its sibling species Cryptococcus gattii (C. gattii) are basidiomycetes that cause systemic fungal infection in animals and humans. These two species have distinct, but also overlapping, environmental niches. C. gattii was traditionally considered to only exist in tropical and subtropical regions and was mostly associated with plants such as the Eucalyptus species [1]. In contrast, C. neoformans has a more global distribution, being isolated mostly in soil contaminated by plant debris and bird droppings. In addition, C. neoformans has been isolated from a variety of plant species [2], including indigenous African trees that have been proposed as the origin of C. neoformans in Africa [3], suggesting that this species also has an arboreal niche. The details as to why Cryptococcus prefers tree or other environmental niches remain unclear. Cryptococcus can complete its sexual cycle by associating with plants, suggesting such association is beneficial for the fungus [4]. Because cryptococcosis is noncommunicable between humans, the initial infection is likely exclusively caused by environmental sources. Basidiospores are thought to be the initial infectious particles inhaled by the human host to cause cryptococcosis, as spores are small enough to lodge into the deep alveoli of the lung and are fully virulent [5], [6]. Hence, mating and recombination of Cryptococcus have to occur in nature, as supported by population studies of environmental isolates [7], [8]. However, neither mating nor basidiospores have yet been observed in the environment. The discovery of Cryptococcus mating on plants sheds light on the whereabouts of Cryptococcus spores in the environment. Recently it was found that inositol secreted from plants stimulates Cryptococcus mating [4]. The importance of inositol in the mating of Schizosaccharomyces pombe [9] and for fertility of plants and humans has also been reported [10], [11], suggesting a conserved contribution of inositol in sexual reproduction. There are two main sources from which fungal cells acquire inositol. For one, intracellular glucose can be used to produce inositol in a multiple-step inositol biosynthetic pathway in which the inositol 3-phosphate synthase (Ino1) is the rate-determining enzyme [12]. Inositol can also be imported from the extracellular environment via inositol transporters (ITRs). Cryptococcus can use inositol both as a carbon source and as a precursor to generate secondary messages that are important for regulating cellular functions and for adapting to environmental signals. Interestingly, in contrast to only one or two inositol transporters present in most fungi, Cryptococcus contains an unusually large inositol transporter gene family with over ten members, derived in part from recent gene duplications, suggesting Cryptococcus has evolved by associating with the tree niches for inositol utilization [13] (Table 1). Among the transporters, Itr1 and Itr1a are two required for fungal mating [13]. The ability to sense and efficiently acquire inositol from plant surfaces could fuel Cryptococcus in its proliferation and sporulation. 10.1371/journal.ppat.1002869.t001 Table 1 Number of inositol transporter (ITR) candidates in fungi. Fungal species Group I* ITRs Group II* ITRs Total ITRs Zygomycota Rhizopus oryzae 3 1 4 Basidiomycota Ustilago maydis 2 1 3 Cryptococcus neoformans var. neoformans JEC21 8 3 11 Cryptococcus neoformans var. grubii H99 7 3 10 Cryptococcus gattii VGI WM276 4 3 7 Cryptococcus gattii VGII R265 3 3 6 Tremella mesenterica 2 1 3 Ascomycota Schizosaccharomyces pombe 2 0 2 Coccidioides immitis 1 1 2 Aspergillus fumigatus 2 3 5 Neurospora crassa 1 1 2 Candida albicans 1 1 2 Ashbya gossypii 1 1 2 Saccharomyces cerevisiae 2 0 2 * ITR candidates can be divided into two distinct groups based on overall amino acid sequence similarity. Group I ITRs are candidates that are highly similar to the known ITRs in Saccharomyces cerevisiae; Group II candidates are less conserved but are closely related to known ITRs in other fungi. Adapting to Trees and Other Niches May Contribute to the Emergence of Cryptococcus Virulence in Humans The progenitor of Cryptococcus existed before humans or other warm-blooded mammals populated the world, and plants or plant materials could well represent the original niches for Cryptococcus, as suggested by a recent report [3]. The successful transmission from an environmental host to a warm-blood mammalian host defines a precondition for the success of a human pathogen. Mammals developed a sophisticated defense system to ward off the attack of deadly microbes, including physical barriers (high body temperature and epithelial surfaces) and immune response (innate and adaptive immunity). In addition, nutrient limitation is an important restricting factor for the growth of those microbes in vivo. Cryptococcus cells grow well at body temperature (37°C), and possess an enlarged polysaccharide capsule and thick melanized cell wall, which enable these cells to resist the hostile host environment. As an intracellular pathogen, the ability of Cryptococcus to survive and replicate in macrophages after phagocytosis has been proposed to be a consequence of adaptations that have evolved for protection against environmental predators in nature, like amoebae [14]. By associating with the plant niche, Cryptococcus may have developed a complex nutrient-acquisition system to acquire limited nutrients, including inositol, to support its growth and sexual reproduction. This efficient nutrient utilization system could also play an important role in using nutrients in mammalian hosts. It has been shown that enzymes involved in inositol metabolism and inositol sphingolipid biosynthesis are required for the pathogenesis of C. neoformans [15]. Inositol Acquisition May Contribute to Cryptococcus CNS Infection The predominant clinical manifestation of cryptococcal infection is the development of fatal meningoencephalitis, especially in people living with AIDS/HIV. The cause of Cryptococcus neurotropism remains unclear. Several factors point to inositol as one of the potential host factors promoting the development of cryptococcal meningitis. First, both human and animal brains contain abundant inositol, which plays a critical role in regulating normal neurological responses and psychological feedback [16]. Inositol is a major osmolyte in the human and animal brains and is present in the human cerebellum (5.1 mM) at over 200-fold higher concentrations than are found in plasma (0.02 mM) [16]. Astrocytes that associate with the blood-brain barrier (BBB) contain over 8 mM inositol that can be rapidly released [16]. HIV-infected persons have increased brain inositol levels due to gliosis or increased cell membrane turnover [17]. Second, Cryptococcus can utilize inositol as a carbon source, which may provide a growth advantage during brain infection since glucose levels are generally low in brain [18], [19]. Third, Cryptococcus can efficiently acquire environmental inositol with its large inositol transporter gene family [4], [13], [20]. Mutants lacking two major fungal inositol transporters, Itr1a and Itr3c, showed attenuated virulence in multiple murine models, indicating that inositol acquisition is required for the Cryptococcus–host interaction, particularly during brain infection [4], [13], [20]. Recently, we found that inositol can directly increase the rate of Cryptococcus transversal across the human brain macrovascular endothelial cell monolayer in an in vitro model of the BBB, and the inositol effect is fungal inositol transporter–dependent (Liu et al., unpublished). This discovery demonstrates that inositol sensing and utilization could be an important virulence factor for the development of cryptococcal meningitis, which provides a direct biological connection between an environmental adaptation strategy and the emergence of its virulence during human infection (Figure 1). 10.1371/journal.ppat.1002869.g001 Figure 1 A model of how inositol affects the infection cycle of C. neoformans. Cryptococcus cells commonly exist in the environment by associating with several niches, including birds, soil, and plants. Inositol is present on plant surfaces and can stimulate fungal mating (including fruiting) to produce infectious spores. Spores inhaled by humans can enter the lungs to cause lung infection. Fungal cells can also be disseminated to the central nervous system (CNS), where abundant inositol is present, and cause fungal meningitis. Inositol can be used as a precursor for both the energy source and the signaling molecule. Part of the model is adapted from Hull and Heitman [6]. Despite progress in understanding the role of inositol in Cryptococcus pathogenesis, many questions remain unanswered. It remains unclear how inositol promotes fungal cell transversal across the BBB and whether inositol is utilized as a signaling molecule, a carbon source, or both by the fungus during brain infection. It is also unknown whether inositol contributes to the development of capsule structure in Cryptococcus and other neurotropic pathogens, since the capsule is one common feature of those pathogens and contributes to their neurotropism. Addressing these questions could lead to a better understanding of the Cryptococcus CNS infection. Contribution of Inositol to the Virulence of Other Pathogens Inositol is the precursor for making phosphatidylinositol (PI) and is essential for cellular structure and regulation of intracellular signaling in all eukaryotes. The role of inositol acquisition in the development of virulence has been studied in a variety of fungi, protozoa, and certain eubacteria [12]. Similar to Cryptococcus, the yeast pathogens Candida albicans and Candida glabrata (C. glabrata) can acquire inositol through both de novo biosynthesis pathways and import via inositol transporters. Blocking either pathway does not affect fungal infection, but deleting both pathways is lethal, suggesting inositol acquisition is essential for Candida survival and either pathway is sufficient to support fungal growth and full virulence [21]. The inositol regulon is wired differently in C. albicans compared to the one in C. glabrata, suggesting complex inositol regulatory systems in different fungi [22]. Besides fungi, inositol also plays a role in pathogenicity of other parasitic microorganisms [12]. Interestingly, although parasites such as Trypanosoma brucei and Leishmania mexicana and mycobacteria such as Mycobacterium tuberculosis can both synthesize and import inositol, blocking inositol biosynthesis leads to growth defect and virulence attenuation, indicating inositol uptake itself is not sufficient [23], [24]. Inositol synthesized in cells has been suggested to be the source of PI used for GPI anchor assembly, which may explain the importance of inositol biosynthesis despite the ability of pathogens to import inositol. Other Adaption Strategies Associated with Cryptococcus Besides utilizing plants as one niche, Cryptococcus cells often associate with certain amoeba species in which the yeast cells can be taken up but survive inside the amoebae, a phenomenon similar to Cryptococcus–macrophage interactions. The interaction between Cryptococcus and amoebae has been shown to increase the resistance of Cryptococcus to phagocytosis during its infection in lung, suggesting that selective pressures placed by amoebae on Cryptococcus contribute to the maintenance of fungal virulence in animal hosts [14]. In addition, Cryptococcus cells can increase ploidy and significantly enlarge in cell size in vivo as a way of protecting yeast cells from phagocytosis [25]. Nitrogen-rich pigeon guano is another primary ecological niche of C. neoformans. Media made of pigeon guano has been shown to stimulate mating of C. neoformans but not C. gattii [26]. The availability of nitrogen, such as uric acid, has been shown to play a role in Cryptococcus virulence [27]. A recent study demonstrated a nitrogen-metabolite repression process to regulate the nitrogen acquisition [28]. Thus, understanding the environmental niches of a particular human pathogen can be very helpful in understanding its disease mechanism. In addition, the adaption of a pathogen to new environmental niches could result in the emergence of new virulence traits. The perfect example is the outbreak of cryptococcosis in otherwise healthy people caused by C. gattii in western North America where Eucalyptus trees do not exist and it is not a tropical climate. The most common C. gattii strain (VGIIa) showed higher proliferation rates in macrophages than other C. gattii isolates from around the world: an indication of the emergence of virulence since proliferation rate is correlated with fungal virulence [29]. The emergence of disease caused by C. gattii in immunocompetent individuals in temperate Vancouver Island, Canada and its expansion in western North America suggests an evolution of host range, geographic location, and virulence of this pathogen [30].

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          Cryptococcus neoformans interactions with amoebae suggest an explanation for its virulence and intracellular pathogenic strategy in macrophages.

          Cryptococcus neoformans (Cn) is a soil fungus that causes life-threatening meningitis in immunocompromised patients and is a facultative intracellular pathogen capable of replication inside macrophages. The mechanism by which environmental fungi acquire and maintain virulence for mammalian hosts is unknown. We hypothesized that the survival strategies for Cn after ingestion by macrophages and amoebae were similar. Microscopy, fungal and amoebae killing assays, and phagocytosis assays revealed that Cn is phagocytosed by and replicates in Acanthamoeba castellanii, which leads to death of amoebae. An acapsular strain of Cn did not survive when incubated with amoebae, but melanization protected these cells against killing by amoebae. A phospholipase mutant had a decreased replication rate in amoebae compared with isogenic strains. These observations suggest that cryptococcal characteristics that contribute to mammalian virulence also promote fungal survival in amoebae. Intracellular replication was accompanied by the accumulation of polysaccharide containing vesicles similar to those described in Cn-infected macrophages. The results suggest that the virulence of Cn for mammalian cells is a consequence of adaptations that have evolved for protection against environmental predators such as amoebae and provide an explanation for the broad host range of this pathogenic fungus.
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            Expanding fungal pathogenesis: Cryptococcus breaks out of the opportunistic box.

            Cryptococcus neoformans is generally considered to be an opportunistic fungal pathogen because of its tendency to infect immunocompromised individuals, particularly those infected with HIV. However, this view has been challenged by the recent discovery of specialized interactions between the fungus and its mammalian hosts, and by the emergence of the related species Cryptococcus gattii as a primary pathogen of immunocompetent populations. In this Review, we highlight features of cryptococcal pathogens that reveal their adaptation to the mammalian environment. These features include not only remarkably sophisticated interactions with phagocytic cells to promote intracellular survival, dissemination to the central nervous system and escape, but also surprising morphological and genomic adaptations such as the formation of polyploid giant cells in the lung.
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              Cryptococcal Cell Morphology Affects Host Cell Interactions and Pathogenicity

              Introduction Unicellular organisms exhibit morphological changes under a wide variety of environmental conditions. In many pathogenic fungi, the ability to switch cell morphology is integral to the infection cycle. Dimorphic fungi, such as Blastomyces dermatitidis and Histoplasma capsulatum, grow in the environment in a hyphal form. When a susceptible host inhales spores, these fungi grow as yeasts. This change in morphology is induced by the high mammalian body temperature [1], [2], [3]. Other pathogenic fungi, such as Candida albicans and Coccidioides immitis, change to specific cell morphologies based on environmental cues or stage of infection [4], [5], [6]. Morphological changes in the pathogenic fungus C. albicans affect tissue tropism and dissemination. Hyphal cells are important in the invasion of host tissues, while yeast cells can easily disseminate through the blood and lymph systems to spread the infection [5], [7]. Additionally, phagocytosis of yeast cells induces differentiation into hyphal cells [6]. Cryptococcus neoformans is an opportunistic fungal pathogen that is most commonly associated with disease in immunocompromised patient populations, such as HIV/AIDS patients, transplant recipients, patients with lymphoid disorders, chronic treatment with corticosteroids, or patients undergoing certain types of chemotherapies [8], [9], [10]. C. neoformans presents clinically as skin lesions, pneumonia, or meningitis [11]. Over 30% of the HIV/AIDS population in Sub-Saharan Africa present with cryptococcal meningitis and cryptococcosis is currently the fifth leading cause of fatalities in this region [12]. Infection with C. neoformans begins when desiccated yeast cells or spores are inhaled and lodge in the alveoli of the lungs. Cryptococcosis occurs when yeast cells disseminate to the bloodstream and ultimately penetrate the blood-brain barrier (BBB) [10], [13]. While the exact mechanism for trafficking from the lungs to the central nervous system (CNS) remains unknown, interactions with host phagocytes and the endothelial cells of the BBB have been shown to be important in this process [14], [15], [16], [17], [18], [19], [20], [21], [22]. Morphogenesis in C. neoformans has primarily been observed as a result of pheromone signaling and mating [23], [24]. There are two varieties of C. neoformans: neoformans and grubii. Historically, mating has been studied in vitro in var. neoformans even though the vast majority of human cryptococcosis cases are caused by var. grubii. C. neoformans has two mating types: a and α. Mating is initiated when pheromone (a or α) secreted by one mating type binds to the pheromone receptor, Ste3α or Ste3a respectively, of the other mating type to trigger a mitogen-activated protein kinase (MAPK) signaling cascade [23], [25]. Pheromone signaling results in morphological changes in var. neoformans, including germ tube formation by mating type α cells and enlargement of mating type a cells [23], [24]. Pheromone-induced MAPK signaling ultimately results in fusion of a and α cells followed by dikaryotic filamentation. Dikaryotic hyphae eventually give rise to basidia where nuclear fusion occurs and meiosis produces haploid spores [23], [26]. In var. grubii, no in vitro morphogenesis in wild-type strains has been observed during early pheromone signaling, although hyphal formation and basidium production mimic that seen in var. neoformans [27]. In this study, we show that cell enlargement is observed in vivo in var. grubii, and that this cell enlargement can be regulated by pheromone signaling. Additionally, we show that these morphological changes in cell size affect pathogenicity by altering phagocytosis and dissemination to the central nervous system (CNS). Finally, we characterized DNA content of this novel cell type to reveal that these enlarged cells are polyploid. Results Morphological changes in C. neoformans var. grubii cells in vivo Pheromone signaling in C. neoformans is known to cause morphological changes including formation of conjugation tubes, dikaryotic filaments, and production of basidia and spores [23], [24], [26], [28]. Mating type a cell enlargement has also been observed in confrontation assays [23]. Cell enlargement has been observed in both human and mouse specimens [29], [30], [31], [32]. Thus, we systematically analyzed cellular morphology in various tissues of mice intranasally infected with var. grubii mating type a or α strains or mice coinfected with both mating types to determine the effect of pheromone signaling and mating type on in vivo cell morphology. Histopathologic tissue sections from the lungs, heart, spleen, liver, kidneys, and brain at 1, 2, 3, 7, 14, and 21 days post-infection were examined for changes in cryptococcal cell morphology. Dramatic changes in cryptococcal cell size were observed in the lungs, although a few cells with increased cell size were also observed in the spleen and brain at late time points ( Figure 1A , Figure S1 ). Most fungal cells in the lungs remained small (5–10 µm in diameter) resembling yeast cells grown in rich medium in vitro. However, a proportion of the cryptococcal cells in the lungs were much larger. For ease of reference, we designated this group of enlarged cryptococcal cells as “titan” cells. These titan cells were >10 µm in diameter, with some cell sizes approaching 50 to 100 µm in diameter ( Figure 1A ). Titan cell diameter measurements were based on actual cell body size and excluded capsule changes which were highly variable. Titan cells were observed as early as 1 day post-infection in the lungs, accounted for approximately 20% of the cryptococcal cells in the lungs by 3 days post-infection, and remained relatively constant throughout the rest of the infection ( Figure 1B, 1C ; Figure S1 ). Titan cells were occasionally observed in the spleen and brain but at low levels ( Figure S1 ). In contrast, coinfection with both mating types resulted in an increase in titan cell production to almost 50% of the cells present in the lungs ( Figure 1B, 1C ). 10.1371/journal.ppat.1000953.g001 Figure 1 Titan cells in the lungs of coinfected mice. A) Mice were coinfected with an approximate 1∶1 ratio of a:α intranasally at a final concentration of 5×104 cells. Lung sections were stained with periodic acid Schiff (PAS) 14 days (top) or 3 days (bottom) post-infection. White arrow denotes C. neoformans cells >10 µm in diameter. Black arrow denotes cells ≤10 µm in diameter. Top: bar  = 100 µm, bottom: bar  = 10 µm. B) The number of small cells (≤10 µm) and titan cells (>10 µm) were quantified in single and coinfections at 7 days post-infection. >500 cells were counted per treatment per mouse. Error bars indicate SD from 3 mice per treatment. Asterisk indicates p 80 cells were analyzed per mouse per treatment. Data are representative of three independent experiments with three mice per treatment. Error bars indicate SD. Asterisk indicates p 500 cells were examined per animal. Error bars indicate SD from four mice per treatment. Asterisk indicates p 0.2 were observed for other pair-wise comparisons. Because pheromone signaling induces mating type a cell enlargement during in vitro mating of var. neoformans, we hypothesized that the increase in titan cell formation during coinfection was specific to mating type a cells. To test this hypothesis, we differentially stained a cells with AlexaFluor 488 (green) and α cells with AlexaFluor 594 (red) prior to intranasal inoculation of mice. Mice were sacrificed at 1–3 days post-infection, and unstained histopathological sections were examined for cryptococcal cell fluorescence ( Figure 2 ). At 1 day post-infection, no difference in the proportion of a or α titan cells in individual or coinfections was observed (data not shown). However, at 2–3 days post-infection, the proportion of mating type a titan cells in coinfections increased while the α titan cell proportion remained equivalent to the individual infections ( Figure 1C ). Almost half of the stained mating type a cells in coinfected lungs had converted to titan cells. 10.1371/journal.ppat.1000953.g002 Figure 2 Fluorescently labeled a (green) and α (red) cells in the lungs during coinfection. C. neoformans a and α strains were combined with AlexaFluor 488 (green) or AlexaFluor 594 (red), respectively, and incubated for 20 minutes. Cells were washed with PBS to remove excess dye. Mice were inoculated with an approximate 1∶1 ratio of a:α cells at a final concentration of 5×107 cells. At 2 days post-infection animals were sacrificed, lungs extracted, fixed in 10% buffered formalin, paraffin-embedded, and 5 µm sections generated. Host tissues are autofluorescent at both wavelengths resulting in a yellow color upon overlay. White arrows denote fluorescent C. neoformans cells. Bar  = 20 µm. To further quantify titan cell formation during coinfection, cells were differentially stained green with AlexaFluor 488 prior to intranasal instillation with the following treatments: a only (green), α only (green), a(green)/α, or a/α(green). At 3 days post-infection, bronchoalveolar lavage (BAL) was performed. The resulting mix of cryptococcal and mouse cells was immediately fixed and the proportion of green titan cells was determined by microscopic examination ( Figure 1D , see below). Similar to the tissue sections, approximately 20% titan cells were observed in the individual infections with no difference in titan cell formation between the two mating types (p = 0.2, Figure 1D ). In the coinfections, mating type α titan cell formation remained at the basal level (p>0.64, Figure 1D ) while mating type a titan cell formation increased (p 0.6, Figure 1D ). Thus, the increase in titan cell formation by mating type a cells during coinfection requires the Ste3a receptor. However, the presence or absence of the Ste3a pheromone receptor has little effect on the basal level of titan cell formation observed in individual infections. Pheromone signaling alters dissemination to the central nervous system To examine the role of titan cell formation in pathogenicity, individual and coinfections with the wild-type and ste3 a Δ mutant strains were compared. The Cryptococcus infectious cycle can be divided into three stages: an initial pulmonary infection (lungs), dissemination (spleen), and penetration of the CNS (brain). Previous studies with C. neoformans var. grubii congenic strains showed no differences in virulence between the a and α mating types [26]. However, coinfection with both mating types simultaneously resulted in reduced a cell penetration of the CNS [33]. Interestingly, while a cell CNS penetration was reduced compared with α cells, both cell types had equivalent accumulation at the first two stages of infection. During coinfection, only mating type a cells displayed an increase in titan cell formation and a subsequent reduction in CNS penetration. Thus we hypothesized that pheromone signaling and the resulting increase in titan cell formation reduces a cell CNS penetration. To determine whether pheromone signaling affected dissemination to the brain during coinfection, we compared wild-type and ste3 a Δ mutant strains for CNS penetration when coinfected with α ( Figure 3 ). In both wild-type and ste3 a Δ coinfections, the number of a and α cells recovered from the spleen and lungs was equivalent to the proportion of the two cell types in the initial inocula (p>0.1). These data show, even at late time points, alterations in titan cell production in response to pheromone signaling do not affect persistence of the cells in the lungs. However, a significant decrease was seen in the proportion of wild-type a cells recovered from the brain (p = 0.001, Figure 3A ). In contrast, coinfections with the ste3 a Δ mutants restored a cell accumulation in the CNS to levels equivalent to the initial inocula (p>0.4, Figure 3B, C ). Both independent ste3 a Δ mutants showed similar results. Together, these data suggest that pheromone signaling during a/α coinfection affects the pathogenicity of a cells by increasing titan cell formation which inhibits the ability of a cells to establish a CNS infection. 10.1371/journal.ppat.1000953.g003 Figure 3 C. neoformans pheromone receptor mutant strains penetrate the CNS during coinfection. Mice were coinfected intranasally with an approximate 1∶1 ratio of A) a:αNAT, B) ste3 a Δ#1:α, or C) ste3 a Δ#2:α at a final concentration of 5×104 cells. The actual proportion of a cells in the infecting inoculum was determined by growth on selective medium and is plotted as a horizontal dashed line. At 21 days post-infection animals were sacrificed, the lungs, brain, and spleen were homogenized and serial dilutions plated. >500 colonies per organ per mouse were isolated and assayed for drug resistance to determine mating type. The proportion of a cells is plotted with open circles denoting values from individual animals and bar height representing the geometric mean. To determine P-values, Wilcoxon rank sum analysis was performed on the measured number of a and α cells compared with the expected number, assuming that both strains remained at the initial inoculum proportions. Coinfection does not affect blood brain barrier penetration upon IV injection An in vivo murine tail vein injection model was employed to determine whether coinfection disrupts CNS penetration by reducing a cell interactions with the endothelial cells of the BBB [34], [35]. In this model, cells bypass the lungs and are injected directly into the bloodstream via the mouse tail vein. The cells then lodge in the small capillaries of the brain and cross the endothelial cell layer of the BBB. To test whether interaction with the BBB was directly affected by mating type or coinfection, a and α cells were fluorescently labeled and examined for their interactions with the BBB. Both cell types were able to traffic to the small capillaries of the brain ( Figure 4A ) and quantification revealed equal proportions of the two mating types in the capillaries (data not shown). During coinfection, the two mating types were observed in close proximity approximately 25% of the time, consistent with random interactions between cells in a mixed population. The finding that cells of opposite mating type are found in close association would enable pheromone signaling to occur between them in the capillaries of the brain ( Figure 4B ). Both mating types could induce phagocytosis by the endothelial cells of the BBB ( Figure 4C ). Capsule structural changes are important for interactions with the endothelial cells of the BBB [35]. These structural changes can be characterized by alterations in anti-capsular antibody binding. The binding patterns to the cryptococcal capsule for two monoclonal antibodies, E1 and CRND-8, recognizing distinct epitopes on the capsular polysaccharide were studied over time and found to be similar for both mating types. Cells observed in the capillaries shortly after inoculation and up to 6 hours post-infection exhibited only E1 antibody binding. In contrast, cells observed in the brain parenchyma were mostly labeled with CRND-8, as described previously for KN99α [35]. No difference in the capsular antigen staining or the kinetics of capsular changes upon crossing of the BBB were observed between the a and α cells during interactions with the endothelial cells of the BBB – either alone or during coinfection (data not shown). These data suggest that the inability of a cells to penetrate the CNS during coinfection is not due to innate differences between the two cell types or their interactions with the BBB itself, but instead may be due to an inability of the a cells to traffic appropriately from the lungs to the brain. 10.1371/journal.ppat.1000953.g004 Figure 4 KN99a and KN99α cells interact with endothelial cells of the blood-brain barrier during coinfection. a or α were combined with AlexaFluor 350 (blue), AlexaFluor 488 (green) or AlexaFluor 594 (red) and incubated for 20 minutes. Mice were inoculated by tail vein injection with an approximate 1∶1 ratio of a:α at a final concentration of 2×107 cells. At 1 day post-infection, animals were sacrificed and 50 µm frozen brain sections were obtained. A) Sections from mice infected with a (green) and α (blue) were immunostained with anti-collagen IV primary antibody (endothelial cell membrane) with a TRITC (red) labeled secondary antibody. Bar  = 20 µm B) Sections from mice infected with a (green) and α (red) were imaged by confocal microscopy and sections were compiled as a projection. Bar size  = 20 µm C) Frozen sections from mice infected with a (red) and α (green) were treated with Hoechst (host cell nuclei), imaged by confocal microscopy, and sections were compiled as a 3D rendering. The U-shaped nuclei are indicative of endothelial cells containing cryptococcal cells. Bar  = 10 µm. Titan cells are resistant to phagocytosis One of the first lines of defense by the host immune system is phagocytosis and the resultant killing of pathogens by mononuclear macrophages and monocytes in the lungs. These host cells identify pathogens, phagocytose them, and either kill the pathogen outright via oxidative and/or nitrosative bursts or present antigens to T cells for further activation of the host immune response [36]. Recent studies suggest phagocytosis by monocytes or macrophages is important for subsequent CNS penetration [16], [18], [20], [22]. Thus, we examined titan cell interactions with lung host immune cells. Fixed BAL samples were analyzed microscopically for yeast cell interactions with host phagocytic cells. Titan cells were never observed inside host phagocytes, presumably due to their large size. Engulfed small cryptococci were observed inside phagocytic host cells ( Figure 5A, B ). No difference in phagocytosis was observed between mating types (p = 0.82, Figure 5D ). The percentage of intracellular α cells during coinfection was similar to that observed in single mating type infections (p>0.89, Figure 5D ). In contrast, a decrease in the percentage of phagocytosed a cells was seen during coinfection (p 0.53 Figure 5D ). Interestingly, titan cells were often surrounded by one or more host immune cells ( Figure 5C ). Yet complete phagocytosis of titan cells was not observed upon characterization of these cellular interactions by confocal microscopy (data not shown). Taken together, these data indicate titan cell formation was negatively correlated with phagocytosis by host immune cells. 10.1371/journal.ppat.1000953.g005 Figure 5 Titan cell formation and phagocytosis in the lungs of infected mice. Mice were intranasally infected with either a, α, or ste3 a Δ cells labeled with AlexaFluor 488 (green) or coinfected with one labeled and one unlabeled strain (four mice per treatment). Cells obtained by BAL were fixed, stained with DAPI, and examined by microscopy for green fluorescence (cell type) and cell size. >500 cells were examined per animal. Bar  = 10 µm A) C. neoformans a cells (green) ≤10 µm in diameter were visible inside host phagocytes. Host cells were identified by large blue DAPI stained nuclei. B) Several small α (≤10 µm) cells (green) can be seen inside a single host cell. C) Mating type a titan cells (>10 µm) are seen in contact with host phagocytes but are too large to be phagocytosed. D) Cells obtained by bronchoalveolar lavage (BAL) were fixed and examined by microscopy for green fluorescence and percent phagocytosis. >500 cells were examined per animal. Error bars indicate SD from four mice per treatment. Asterisk indicates p 0.4 were observed for other pair-wise comparisons. Both macrophages and neutrophils employ oxidative and nitrosative bursts as a means of killing pathogens (Janeway et al., 2008). Titan cell resistance to these stresses was characterized by comparing the growth of purified titan and small cells isolated by cell sorting of BAL samples. Both cell types showed equivalent growth in the absence of oxidative or nitrosative stress ( Figure 6A ). Treatment with sodium nitrate (NaNO3) slowed the growth of the small cell population compared to the titan cell population ( Figure 6B ). Treatment with tert-butyl hydroperoxide (TBHP) resulted in killing of small cells, represented by a decrease in cell counts relative to the initial time point ( Figure 6C ). In contrast, titan cells exhibited continued growth in the presence of these oxidative stresses ( Figure 6C ). Similar results were observed with stabilized hydrogen peroxide treatment. Thus, titan cells are more resistant than normal cells to both oxidative and nitrosative stresses similar to those employed by cells of the host immune system. 10.1371/journal.ppat.1000953.g006 Figure 6 Titan cells are resistant to oxidative and nitrosative stress. Mice were coinfected intranasally with 4×107 cryptococcal cells. At 3 days post-infection, BALs were performed and cells were sorted by FACS based on size. 2×104 titan cells or small cells were resuspended in 100 µL RMPI. Cryptococcal cells received A) no treatment, B) 10 mM NaNO3, C) 1 mM TBHP. At 0, 6, 16, or 24 hours, aliquots of each treatment were plated on YPD agar and colony forming units (CFU) were determined. Error bars indicate SD from three replicates. Titan cells are polyploid In yeasts, cell enlargement is often associated with either cell cycle arrest or increased DNA content [37], [38], [39]. Pheromone sensing in the model yeasts Schizosaccharomyces pombe and Saccharomyces cerevisiae is known to trigger a cell cycle arrest. We examined titan cells for their progression through the cell cycle by characterizing their ability to bud and produce daughter cells. In addition, we determined the DNA content of titan cells. Titan cells produced in vivo were obtained from BAL of mice with single or coinfections. The cells were immediately fixed and stained with DAPI. Microscopic examination of titan cells revealed a single nucleus ( Figure 7A ). Analysis of titan cell nuclear structure by confocal microscopy and z-stack sectioning showed the nucleus had an elongated tubular shape instead of the classic round shape observed in smaller cells (data not shown). Because of its elongated shape, only a portion of the nucleus was observed in each focal plane. Several stages of the cell cycle were identified. In early bud formation ( Figure 7B ), titan cells had a nucleus in the mother cell while the daughter cell lacked a nucleus. The mother cell nucleus was observed at the bud site and entering the daughter cell ( Figure 7C ). After nuclear division the mother and daughter each contained single nuclei ( Figure 7D ). Finally, after cytokinesis was complete, individual nuclei were visible in the mother and associated daughter cell ( Figure 7E ). Budding of the titan cells was readily observed from in vivo samples suggesting complete cell cycle arrest would not explain the increased titan cell size. 10.1371/journal.ppat.1000953.g007 Figure 7 Titan cells can undergo cell division. Mice were infected with 5×107 cells by inhalation of an approximate 1∶1 ratio of a:α cells. At 3 days post-infection, mice were sacrificed, BALs performed, and the resulting cells were fixed and DAPI stained for nuclear content. A) Titan cell containing a single nucleus. B) Titan cell early bud formation. C) Nuclear transfer from a mother (titan cell) to a daughter cell. D) Titan cell late bud formation. E) Cytokinesis of a daughter cell from a titan cell. Bar  = 10 µm. Increases in cell size in plants, or gigantism, is often correlated with increased ploidy [40]. Because titan cells contain only one nucleus, we quantified their DNA content by flow cytometry and quantitative PCR. Fluorescently labeled cells from individual or coinfections were isolated by BAL and immediately fixed and stained with DAPI. The fixed cell suspensions were then analyzed using an imaging flow cytometer to define cell populations ( Figure S3 ). Two distinct populations of fluorescent cryptococcal cells were identified: cryptococcal cells alone and cryptococcal cells inside host cells. Because phagocytosed cryptococcal cell size cannot be accurately measured with flow cytometry, only single non-phagocytosed yeast cells were examined further. The single non-phagocytosed yeast cells were then divided into three populations based on cell diameter: ≤10 µm, >10 µm but ≤20 µm, and >20 µm. The ≤10 µm cell population was designated as small cells of typical size for Cryptococcus. The group of cells >20 µm were designated as the titan cell population. The intermediate cell population, >10 µm but ≤20 µm, contained a mixture of small and titan cells, thus could not be accurately characterized by flow cytometry. Flow cytometry and cell sorting of 50,000 cells were used to obtain an accurate representation of the DNA content for each population ( Figure 8 ). DNA content determinations were based on DAPI fluorescence in haploid cells grown in vitro in Dulbecco's modified eagle medium (DMEM) at 37°C and 5% CO2 (non-titan-inducing conditions) ( Figure S4 ). The small cell population isolated from coinfected mice showed a prominent peak consistent with a majority of the cells in the population containing two copies (2C) of DNA. These data would suggest that most of the small cell population in vivo were in G2 of the cell cycle ( Figure 8A ). In contrast, the titan cell population showed two peaks consistent with 4C or 8C DNA content ( Figure 8A ). No differences in titan cell DNA content were observed between the two mating types or in individual versus coinfections, indicating that titan cell DNA content was not altered by coinfection ( Figure S4 ). 10.1371/journal.ppat.1000953.g008 Figure 8 Titan cells have increased DNA content. Mice were intranasally infected with 5×107 cells with an approximate 1∶1 ratio of a:α cells labeled with AlexaFluor 488 (green). At 3 days post-infection, mice were sacrificed, BALs performed, and the resulting cells were fixed. A) Cells were stained with DAPI to measure nuclear content by flow cytometry. Left panel indicates small (≤10 µm) and titan (>20 µm) cell population gates. Right panel indicates DNA content based on DAPI fluorescence for small (dark gray) and titan (white) populations normalized to cell number (% maximum). Dashed lines indicate predicted 1C, 2C, 4C, and 8C DNA content based on DAPI intensity of the 1C and 2C control cells stained and analyzed in the same experiment. B) Cells were grown in vitro in spent DMEM liquid medium for 7 days at 30°C. Cells were fixed and stained with DAPI. Left panel indicates small (≤10 µm), intermediate (>10, ≤20 µm), and titan (>20 µm) cell population gates. Right panel indicates DNA content based on DAPI fluorescence for small (dark gray), intermediate (light gray), and titan (white) populations normalized to cell number. Dashed lines indicate predicted 1C, 2C, 4C, and 8C DNA content based on DAPI intensity of the 1C and 2C control cells strained and analyzed in the same experiment. C) Fixed BAL samples were sorted into small and titan cell populations by fluorescence activated cell sorting. DNA was purified from the sorted populations, normalized to cell number, and chitin synthase 1 (CHS1) gene copy number was determined by comparison to a log phase control sample with a known ratio of 1C:2C cells with a total gene copy number equivalent to 1.4. Analysis of the in vivo samples suggested that both the small cells and titan cells could be undergoing active cell growth and replication, making characterization of titan cell ploidy difficult in these in vivo samples. To determine the ploidy of titan cells, we identified in vitro conditions that stimulated titan cell production. Titan cell formation was only observed in cryptococcal samples grown in spent media previously used to culture mammalian cells ( Figure S5 ). Differences in titan cell formation were observed based on the media used, the temperature of incubation, and mammalian cell type. Optimal in vitro titan cell production was observed when cryptococcal cells were grown in spent DMEM derived from MH-S alveolar macrophages at 30°C. When grown to stationary phase for 5 days in this medium approximately 4% of the total population was titan cells. On average, titan cells generated in vitro were smaller than those observed in vivo, ranging from 15 µm to 30 µm in diameter. Due to the smaller size of the in vitro titan cells, the intermediate cell population (>10 µm but ≤20 µm) was included in the flow cytometric DNA content analysis ( Figure 8B ). In contrast to the in vivo samples, the DNA content of the in vitro small cell population at 5 days was consistent with 1C cells, suggesting that the cells were in stationary phase ( Figure 8B ). Cells grown to stationary phase in a standard growth medium were also 1C (data not shown). The intermediate cell population had a single peak consistent with 4C cells and the larger titan cell population (>20 µm) had a single peak consistent with 8C cells ( Figure 8B ). Thus, titan cells in stationary phase appeared to be either tetraploid or octoploid based on cell size. Quantitative PCR was used to determine the average copy number per cell of the chitin synthase 1 (CHS1) gene as an additional molecular characterization of DNA content in the in vivo small and titan cell populations. Quantitative PCR was performed on the isolated DNA from three cell populations (small, titan, control). This quantitative PCR analysis confirmed that the titan cells had increased CHS1 DNA content compared with the small cells (p 3 times in sterile PBS to remove unbound dye. The cells were resuspended in PBS at a concentration of 1×108 based on hemocytometer count. Three mice per treatment (a, α, or coinfection) were infected intranasally with 5×106 fungal cells. The concentration of yeast cells in the inoculum was confirmed by plating serial dilutions and enumerating CFU and the proportion of a cells in the coinfection inoculum was determined by mating assay [27]. Infected mice were sacrificed at 1, 2, or 3 days post-infection by CO2 inhalation. Lungs were extracted and fixed as described above and unstained sections were examined for cell size, morphology, and fluorescence. Data presented are representative of three independent experiments with two or three mice per treatment per experiment. ste3aΔ mutant strains Two independent ste3aΔ mutant strains were generated by gene disruption as previously described [73].The nourseothricin transgene (NAT) was used to replace the STE3 a gene coding region. PCR was used to generate the 5′ (KN0035 and KN0036) and 3′ (KN0037 and KN0040) flanking regions containing linkers to a NATr cassette and overlap PCR generated the NAT insertion allele ( Table 1 ). The mutant allele was introduced by biolistic transformation into KN99a to generate ste3 a Δ#1 and into the spontaneous ura- strain JF99a [74] to generate ste3 a Δ#2. Transformed colonies resistant to nourseothricin (100 µg/ml) were identified by PCR amplification and sequencing of PCR products spanning a region upstream of the 5′ flanking region into the NAT cassette (KN0079 and KN0031) and from the NAT cassette to downstream of the 3′ flanking region (KN0032 and KN0109). Gene deletion was further confirmed by mating the mutant strains with KN99α on V8, pH 5 media for >14 days at 25°C in the dark. The mutant strains were sterile. The ste3 a Δ#2 was passaged on SD-ura media to isolate a URA+ revertant for use in virulence tests. 10.1371/journal.ppat.1000953.t001 Table 1 PCR Primers. Primer Designation Sequence STE3a Knockout construct KN0035 GCCCTAGCAATGTCGATACCC KN0036 AGCTCACATCCTCGCAGC GCACGTCCGGAGTACACG KN0032 GCTGCGAGGATGTGAGCT KN0031 GGTTTATCTGTATTAACACGG KN0037 CCGTGTTAATACAGATAAACCCTGTATGGCGCTCCTTGGAAG KN0040 CACAGCAAAGGCACATTCGCAAG Outside PCR Checks KN0079 GGAGTTGACGCACGTTTATGGCAA KN0109 CACTGGTGGAGCATTCATGTCG qPCR with primers for CHS1 KN104 GTCCCAGGAGGACTCCTTTC KN105 TGTCGTTCAGGTCGAGTGAG In vivo analysis of ste3aΔ strains Groups of 5–10 mice were infected with 5×104 cells in an approximate 1∶1 ratio of ste3 a Δ#1:KN99α, ste3 a Δ#2:KN99α, or KN99a:KN99αNAT. The actual proportion of a cells in the infecting inoculum was determined by growth on selective media. At 21 days post-infection, animals were sacrificed. The lungs, spleen, and brain from each animal were homogenized in 2–4 ml PBS and serial dilutions were plated on YPD for CFU enumeration. >500 colonies per organ were isolated and assayed for antibiotic resistance on YPD containing 100 µg/ml nourseothricin to determine mating type. Interactions with the blood-brain barrier (BBB) KN99a and KN99α cells were fluorescently labeled as described above. Three mice per treatment were inoculated by tail vein injection with KN99a, KN99α, or an approximate 1∶1 ratio of KN99a:KN99α at a final concentration of 2×107 cells. At 1 day post-infection animals were sacrificed, perfused with 20 ml PBS then 20 ml 4% paraformaldehyde (PFA). Brains were harvested, placed in 4% PFA then 40% w/v sucrose solution in PBS, frozen in isopentane and liquid nitrogen, stored at −80°C, and 50 µm sections were generated. For immunohybridizations, slides were washed in PBS for 15 min followed by incubation with 100 µl trypsin-EDTA (Invitrogen) at 37°C for 10 minutes. Slides were then washed in PBS containing 20% fetal calf serum (Invitrogen) for 10 minutes, blocked with PBS containing 20% FCS, 0.1% bovine serum albumin (BSA) and 0.1% triton X-100 (Sigma, St. Louis, MO) for 20 minutes, then washed with PBS containing 0.1% triton X-100. Anti-collagen IV antibody (Santa Cruz Biotechnology, Santa Cruz, CA) was diluted to a 1/50 concentration in PBS with 0.1% BSA and 0.1% Triton X-100. Antibody-treated slides were incubated overnight at 4°C followed by washing in PBS. Cy3 labeled goat anti-rabbit antibody was diluted to a 1/200 concentration and added to the slides. After 5 hours of incubation at 37°C, slides were washed three times in PBS for 15 minutes. Hoechst medium was diluted to a 1/500 concentration and added to the slides for 30 seconds. Slides were washed for 5 minutes in PBS and mounted in Vectashield mounting medium. Capsule antigen staining was as described in Charlier et al., 2005 using the CRND-8 and E1 antibodies. Slides were imaged by fluorescence microscopy (Zeiss Axioplan) or by 2-photon confocal microscopy (Zeiss LSM 510 equipped with a Coherent Mira 900 tunable laser) with sections compiled as a projection or as a 3D rendering. Bronchoalveolar lavage (BAL) Four mice per treatment were infected as described above with 5×106 AlexaFluor 488 labeled KN99a, KN99α, and ste3 a Δ#1, or an approximate 1∶1 ratio of one stained and one unstained strain. Infected mice were sacrificed at 3 days post-infection by CO2 inhalation. Lungs were lavaged with 1.5 mL sterile PBS three times using a 20 gauge needle placed in the trachea. For flow cytometry, cells in the lavage fluid were pelleted at 16,000 g, resuspended in 3.7% formaldehyde, and incubated at room temperature for 30 minutes. Cells were then washed once with PBS, resuspended in PBS containing 300 ng/ml 4′,6-diamidino-2-phenylindole (DAPI) (Invitrogen), incubated at room temperature for 10 minutes, washed with PBS, and resuspended in PBS. >500 cells per animal were analyzed for size and fluorescence by microscopy (AxioImager, Carl Zeiss, Inc). Confocal microscopy (LSM710, Carl Zeiss, Inc) and z-stack imaging (AxioImager with Apotome, Carl Zeiss, Inc) were used to examine interactions with host mononuclear cells. Images were analyzed using Axiovision and Zen software (Carl Zeiss, Inc). Crescent shaped and other fluorescently-labeled cryptococcal cell fragments (i.e. not round cells) were observed within host mononuclear cells. These cell fragments were not included in the analysis. Nitrosative and oxidative stress assays Twelve mice were intranasally infected with 2×107 cells in 50 µL PBS of an approximately 1∶1 ratio of KN99a and KN99α cells. At 3 days post-infection, mice were sacrificed by CO2 inhalation and BALs were performed. Cells were sorted by FACS using an iCyt Reflection cell sorter (iCyt, Champaign, IL). Cells were sorted based on size using forward scatter (FSC) into small cell and titan cell populations. Purity of samples was checked by flow cytometry and microscopy. Samples were resuspended in Roswell Park Memorial Institute (RPMI) medium 1640 (Invitrogen) supplemented with 10% fetal bovine serum (FBS) (ATCC, Manassas, VA), 4.5 g glucose/L (BD), 1 mM sodium pyruvate (Invitrogen), 0.01 M HEPES (MP Biomedicals, Solon, OH), 5% penicillin/streptomycin (Invitrogen) and 0.05 mM β-mercaptoethanol (Chemicon) to a concentration of 2×104 cells per 100 µL. Samples were then treated with 10 mM NaNO3 (Sigma-Aldrich, St Louis, MO), 3 mM H2O2 (Walgreens Co., Deerfield, IL), or 1 mM tert-butyl hydroperoxide (TBHP) (Sigma-Aldrich). At 0, 6, 16 or 24 hours post treatment, 10 µL aliquots of each sample were plated onto YPD agar for CFU enumeration. Flow cytometry Fixed BAL samples from 4 mice per treatment were generated as described above and analyzed using an ImageStream imaging flow cytometer and INSPIRE software (Amnis Corporation, Seattle Washington). Briefly, images for 5000 cells per sample were collected and analyzed for single cells (R1), doublets (R0), or aggregates of cells ( Figure S3A ). Only single cells (R1) were used in our analyses because cell aggregates would misrepresent cell sizes. Single cells were further analyzed for AlexaFluor 488 fluorescence and DAPI staining ( Figure S3B ). Due to the high nuclear content of mammalian cells, these cells had extremely high DAPI staining (R2 and R3). Non-phagocytosed yeast cells (R5) we identified based on their low DAPI staining. Visual confirmation of cell size in the flow cytometry images was used to identify small and titan cell populations (R6 and R7), that each gate contained only the target cells, and that no contamination between the populations was observed ( Figure S3C ). Data analysis and gating was performed using IDEAS software (Amnis Corporation). Cryptococcal cells grown in vitro in YPD or DMEM to log or stationary phase were used as controls to identify haploid cells (1C) and actively dividing cells (1C + 2C). To examine titan cell ploidy, fixed BAL samples from 4 mice per treatment were generated as described above. In vitro control samples were grown in YPD or Dulbecco's modified eagle medium (DMEM, 37°C, supplemented with 10% fetal bovine serum (FBS) (ATCC), 4.5 g glucose/L (BD), 1 M sodium pyruvate (Invitrogen), 0.01 M HEPES (MP Biomedicals, Solon, OH), 5% penicillin/streptomycin (Invitrogen) and 0.05 mM β-mercaptoethanol (Chemicon) for 6 hours (log phase) or 5 days (stationary phase). Spent DMEM or RPMI was collected from MH-S macrophages after 3–5 days culture at 37°C and 5% CO2. Spent endothelial cell (EC) media (complete EGM medium, Clonetics, San Diego, CA, USA) was collected from human umbilical vein endothelial cells (HUVEC) after 3–5 day culture at 37°C and 5% CO2. In vitro titan cells were grown in filter sterilized spent media at 30°C or 37°C for 7 days. In vitro and in vivo samples were fixed in 3.7% formaldehyde and stained with 300 ng/ml DAPI in PBS. Autofluorescence of non-DAPI stained fixed titan cells was measured and used to set the baseline for ploidy measurements. Cells were examined for cell size by forward scatter (FCS) and nuclear content by DAPI using an LSRII flow cytometer with FACSDiva software (BD) using gating defined by imaging flow cytometry. FCS cell sizes in each gate were verified by microscopy (Zeiss Axioplan). Data presented are representative of three independent experiments with four mice per treatment. 50,000 cells per treatment were analyzed to determine titan cell formation in vitro. In vitro titan cell formation was variable from experiment to experiment but trends between treatments remained constant. Data presented are representative of five independent experiments. Because the absolute number of cells in each population and in each mouse differed, the DAPI fluorescence for each population was normalized to the number of cells in that population in order to clearly visualize peaks on a histogram representation of the data ( Figure 8 , Figure S4 ). Cells were examined for cell size by forward scatter (FCS) and nuclear content by DAPI using an LSRII flow cytometer with FACSDiva software (BD) using the gating defined by imaging flow cytometry. FCS cell sizes in each gate were verified by microscopy to identify the ≤10 µm, >10 µm but ≤20 µm, and >20 µm cell populations (Zeiss AxioImager). Data presented are representative of three independent experiments with four mice per treatment. 50,000 cells per treatment were analyzed to determine titan cell formation in vitro. In vitro titan cell formation was variable from experiment to experiment but trends between treatments remained constant. Data presented are representative of five independent experiments. Cell sorting and qPCR Ten to fourteen mice were infected with 5×106 AlexaFluor 488-stained cells at an approximate 1∶1 ratio of KN99a:KN99α, as described above. Infected mice were sacrificed at 3 days post-infection and BALs were performed. BALs were pelleted and resuspended in 0.05% SDS in sterile water for 1 minute to promote host cell lysis. Cells were then fixed in 1 ml PBS containing 1% formaldehyde and incubated for 30 minutes at room temperature with mixing. Samples were incubated in 125 mM glycine for 5 minutes, centrifuged at 1500 g for 10 minutes, and the pellets were resuspended in ice cold TBS (20 mM Tris, pH 7.6, 150 mM NaCl) containing 125 mM glycine. Cells were washed once in TBS, resuspended in 1 ml PBS and the cell concentration was determined by hemocytometer count. Cell numbers were adjusted to 106 cells/ml, and 1% BSA was added to the fixed cell suspension. Cells were sorted using a FACSAria fluorescence activated cell sorter (FACS) using FACSDiva software (BD). Small and titan cell populations were isolated by FACS using gating as described above. DNA was isolated from 106 cells from small, titan, and 37°C DMEM (control) cell populations. A portion of the control cell population was DAPI stained and the number of haploid and diploid cells in the population was determined by flow cytometry ( Figure S3 ). Small cells were classified as ≤10 µm and titan cells were >10 µm. After sorting, the two cell populations were pelleted and resuspended in lysis buffer (50 mM HEPES, 140 mM NaCl, 1% Triton X-100, 0.1% Sodium deoxycholate, 1 mM EDTA). The cell suspensions were transferred to tubes containing 0.3 mm glass beads and vortexed for six 5 minute cycles at 4°C. The bottoms of the tubes were then pierced with a hot 21-gauge needle. The tubes were placed into 15 ml conical tubes and centrifuged at 1500 g for 5 minutes at 4°C. The pellets and supernatants were combined and transferred to new tubes. These mixtures were centrifuged for 10 minutes at 10,000 g at 4°C and the supernatants transferred to clean tubes. After a further 5 minute centrifugation, the DNA crosslinks were reversed by adding 200 µl TE (10 mM Tris, pH 7.5, 1 mM EDTA) containing 1% SDS to the clarified supernatants and incubating for 6 hours at 65°C. Samples were then incubated 2 hours at 37°C with 250 µl TE containing 0.4 mg/ml proteinase K. After adding 55 µl 4 M LiCl, the DNA was extracted with 0.5 ml phenol and the DNA was precipitated with 100% ethanol. The DNA pellets were washed with 70% ethanol, dried, and resuspended in TE containing 1.5 µl RNase (Ambion AM22886). Samples were stored at −20°C until analyzed by qPCR with primers KN104 and KN105 for chitin synthase (CHS1) ( Table 1 ). Gene copy number in the control sample was calculated based on the known number of 1C and 2C cells present in that sample (1.4C) based on flow cytometry. The small and titan cell gene copy numbers were normalized to the control sample. Statistical analysis All analyses were performed using Analyse-It (Analyse-it Ltd., Leeds, England). Wilcoxon rank sum analysis was used to analyze differences in coinfection data and P-values 10 µm in diameter) was determined by microscopic examination of >500 cells per sample per mouse. Sufficient cell numbers were unavailable in tissue sections from 1 dpi lungs and 1, 3, 7, and 14 dpi spleen and brain for quantification. Error bars indicate SD from six mice per time point. (2.29 MB TIF) Click here for additional data file. Figure S2 ste3aΔ survival assays. Mice were inoculated with 5×104 cells of either wild-type a, ste3aΔ#1 (left) or ste3aΔ#2 (right) cells and progression to morbidity was monitored. (2.43 MB TIF) Click here for additional data file. Figure S3 Imaging Flow Cytometry. C. neoformans a and α strains were combined with AlexaFluor 488 (green) and incubated at 25°C for 20 minutes. Cells were washed with sterile PBS to remove excess dye. Mice were inoculated with an approximate 1∶1 ratio of a:α cells. At 3 days post-infection animals were sacrificed and BALs were performed. The resulting cells were fixed, DAPI stained, and analyzed using an ImageStream flow cytometer using IDEAS software (Amnis Corporation). A) Cells were first examined for single cells (R1). Aggregates and doublets were excluded from further analysis. B) The R1 population was analyzed for DAPI intensity (X-axis) and AlexaFluor 488 intensity (Y-axis). DAPIhi host cells and phagocytosed cryptococcal cells (R2 and R3) as well as unstained yeast cells (R4) were excluded from further analysis. C) Diameter was used to divide the remaining population, R5, into cells 10 µm (R7). Samples from four mice per treatment were analyzed and gates determined by consensus among the samples. (8.29 MB TIF) Click here for additional data file. Figure S4 C. neoformans titan cells are polyploid. a and α strains were combined with AlexaFluor 488 (green) and incubated at 25°C for 20 minutes. Cells were washed with sterile PBS to remove excess dye. Mice were inoculated with an approximate 1∶1 ratio of a:α cells. At 3 days post-infection animals were sacrificed and BALs were performed. The resulting cells were fixed, DAPI stained and analyzed using an LSRII flow cytometer using FACSDiva software (BD). Fluorescently labeled yeast cells were first identified as 488hi and DAPIlow (left). Forward scatter (FSC) was used to identify small (≤10 µm) and titan (>20 µm) cells. Small (blue line) and titan (red line) cell populations were analyzed for DNA content (DAPI) and normalized for cell number (right). A–D coinfections E–G individual infections H) C. neoformans cells were grown for 5 days at 37°C and 5% CO2 in DMEM, fixed and DAPI stained. Both 1C and 2C peaks can be seen in this cell population. Absolute levels of DAPI intensity in these control cells varied from experiment to experiment thus were included as internal controls for every experiment. (2.31 MB TIF) Click here for additional data file. Figure S5 In vitro titan cell production. Cryptococcal cells were grown in spent DMEM (MH-S alveolar macrophages), RPMI (MH-S alveolar macrophages), or endothelial cell media (human umbilical vein endothelial cells, HUVEC) at 30°C or 37°C. Samples were fixed in 3.7% formaldehyde and 50,000 cells per sample were analyzed for cell size (forward scatter). Data presented are representative of five independent experiments. (2.12 MB TIF) Click here for additional data file.
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                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                September 2012
                September 2012
                13 September 2012
                : 8
                : 9
                : e1002869
                Affiliations
                [1 ]Public Health Research Institute, University of Medicine and Dentistry of New Jersey, Newark, New Jersey, United States of America
                [2 ]Department of Microbiology and Molecular Genetics, University of Medicine and Dentistry of New Jersey, Newark, New Jersey, United States of America
                Duke University Medical Center, United States of America
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                The author has declared that no competing interests exist.

                Article
                PPATHOGENS-D-12-00981
                10.1371/journal.ppat.1002869
                3441655
                23028304
                9fd42b63-04eb-4190-a162-630b0c712f8d
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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                Pages: 4
                Funding
                This study is supported by the American Heart Association grant 12SDG9110034 and UMDNJ institutional startup fund to C.X. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Pearls
                Biology
                Evolutionary Biology
                Microbiology
                Medicine
                Infectious Diseases
                Fungal Diseases
                Cryptococcosis

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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