Coregulation of extracellular vesicle production and fluconazole susceptibility in Cryptococcus neoformans

Abstract

Resistance to fluconazole (FLC), the most widely used antifungal drug, is typically achieved by altering the azole drug target and/or drug efflux pumps. Recent reports have suggested a link between vesicular trafficking and antifungal resistance. Here, we identified novel Cryptococcus neoformans regulators of extracellular vesicle (EV) biogenesis that impact FLC resistance. In particular, the transcription factor Hap2 does not affect the expression of the drug target or efflux pumps, yet it impacts the cellular sterol profile. Subinhibitory FLC concentrations also downregulate EV production. Moreover, in vitro spontaneous FLC-resistant colonies showed altered EV production, and the acquisition of FLC resistance was associated with decreased EV production in clinical isolates. Finally, the reversion of FLC resistance was associated with increased EV production. These data suggest a model in which fungal cells can regulate EV production in place of regulating the drug target gene expression as a first line of defense against antifungal assault in this fungal pathogen. IMPORTANCE Extracellular vesicles (EVs) are membrane-enveloped particles that are released by cells into the extracellular space. Fungal EVs can mediate community interactions and biofilm formation, but their functions remain poorly understood. Here, we report the identification of the first regulators of EV production in the major fungal pathogen Cryptococcus neoformans. Surprisingly, we uncover a novel role of EVs in modulating antifungal drug resistance. Disruption of EV production was associated with altered lipid composition and changes in fluconazole susceptibility. Spontaneous azole-resistant mutants were deficient in EV production, while loss of resistance restored initial EV production levels. These findings were recapitulated in C. neoformans clinical isolates, indicating that azole resistance and EV production are coregulated in diverse strains. Our study reveals a new mechanism of drug resistance in which cells adapt to azole stress by modulating EV production.

Keywords: Cryptococcus neoformans; antimicrobial resistance; extracellular vesicles; fluconazole; transcription factor.

Fig 1

EV production is regulated by growth conditions and growth phase. Schematic representation of the optimized quick protocol used to obtain EVs from cells grown on solid medium (A). EV production from cells grown on different media: SD, YPD, capsule IM, and SAB at 30°C and 37°C, sterol concentration values are expressed per 10⁹ cells for each condition (B). EV production on SD medium at 30°C during the growth curve was analyzed by the amount of total sterol in cellular supernatants when EVs are isolated using the quick protocol, values are expressed per plate of culture during each timepoint (C). Experiments were done with three or more biological replicates. Error bars show means ± SD. Schematic representation created in BioRender.

Fig 2

Identification of the transcription factors regulating EV production in C. neoformans. The screening of a 155 TF mutant collection identified four major EV production regulators: HAP2, LIV4, BZP2, and GAT5 (A). Confirmation of the EV phenotype using independent knockout strains generated in the KN99α background by measuring the amount of total sterol contained in EV samples. Sterol concentration values are expressed per 10⁹ cells for each condition (B) and single particle counting using nanoFCM (C). Cryo-electron microscopy (Cryo-EM) analysis of EVs obtained from WT and hap2Δ strains (D). Scale bars = 100 nm. Experiments were performed in at least three biological replicates. Error bars show means ± SD.

Fig 3

The HAP2/3/5 complex is involved in EV secretion. Quantification of single EV particles released by WT and HAP complex mutants using nanoFCM (A). Growth analysis by counting the total number of cells obtained from SD plates (B). The experiments were carried out in biological triplicates. Error bars show means ± SD. ns, not significant;. *p < 0.05.

Fig 4

Transcriptomic analysis of the EV-deficient mutants hap2Δ and gat5Δ grown in EV-producing conditions. Venn diagram revealing the number of upregulated genes in both mutants (A). Analysis of the Go-slim categories enriched in the group of genes upregulated in both mutants (B). Venn diagram revealing the number of the downregulated genes in both mutants (C). GO SLIM categories enriched in the group of downregulated genes in both mutants (D). Venn diagram revealing the overlap between genes downregulated in gat5Δ and hap2Δ, and the ones coding for the EV-enriched proteins of C. neoformans, previously identified by proteomics (E). The genes highlighted in gray with an asterisk encode proteins among the 10 most abundant proteins in C. neoformans EVs.

Fig 5

Transcription factors regulating EV release are associated with altered azole susceptibility. Spot assay for FLC, itraconazole (Itraco), and voriconazole (Vorico) susceptibility (A) and FLC diffusion disk diffusion assay (25 µg/disk) for the four EV-defective TF mutants identified in the screening (hap2Δ, gat5Δ, liv4Δ, and bzp2Δ), and for all the members of HAP complex, including hap3Δ, hap5Δ, and hapXΔ, grown for 72 h (B). Average RAD₈₀ values obtained from diskImageR analyses are provided. The results are illustrative of three biological replicates.

Fig 6

Complementation of the hap2Δ and gat5Δ mutant strains restores the phenotypes of EV production and FLC susceptibility. Total sterol contents in EVs produced by WT, mutants, and complemented cells. Sterol concentration values are expressed per 10⁹ cells for each condition (A). Quantification of EV particles using nanoFCM in WT, mutants, and complemented strains (B). FLC susceptibility by disk diffusion assay (25 µg/disk) and RAD₈₀ values obtained by diskImageR (C). FLC susceptibility analysis by spot assay (D). Growth analysis in the presence of cell wall and plasma membrane disturbing agents (CFW, H₂O₂, and SDS) (E). The experiments were carried out in biological triplicates. Error bars show means ± SD.

Fig 7

Gene expression analysis of known FLC resistance regulators in C. neoformans. ERG11 (A), AFR1 (B), AFR2 (C), and AFR3 (D) gene expression profile as generated by RT-qPCR. The experiments were carried out in at least biological triplicates. Error bars show means ± SD.

Fig 8

Fluconazole treatment affects EV production and cellular sterol homeostasis. WT cells were grown in different concentrations of FLC on SD agar medium, and the total number of cells was counted (A). Levels of ERG11 expression in the presence of a subinhibitory concentration of FLC (0.6 µg/mL) (B). Analysis of EV production by nanoFCM in the presence of FLC (0.6 µg/mL) (C). Analysis of lanosterol and ergosterol lipid profile by TLC in cells (D). Analysis of TLC bands by densitometry units and ratio between lanosterol- and ergosterol-specific signals for cells (E). The experiments were carried out in at least two biological duplicates, and representative results were shown. Error bars show means ± SD. ns, not significant. *p < 0.05.

Fig 9

Analysis of FLC susceptibility and EV production in FLC-resistant isolates obtained in vitro. Illustrative scheme of the experimental strategy used to explore the association between FLC resistance and EV production in spontaneous drug-resistant strains obtained in vitro (A). Cells at passage 0: quantitative analysis of the growth inhibition halo from the FLC-disk diffusion assays by diskImageR, RAD₈₀(B), EV production analysis by nanoFCM (C), and qualitative analysis of the inhibition halo of the FLC-disk diffusion assays (D). Cells after six successive passages in the absence of FLC: quantitative analysis of growth inhibition halo from the FLC-disk diffusion assays by diskImageR, RAD₈₀ (E), EV production analysis by nanoFCM (F), and qualitative analysis of the growth inhibition halo (G). Schematic representation created in BioRender.

Fig 10

qPCR assays evaluating the monosomic or disomic status of chromosome 1 in the FLC-sensitive and FLC-resistant strains obtained in vitro. Parental strains (A, D), FLC-resistant passage 0 strains (B, E), and passage 6 strains (C, F) were tested using primers specific for genes located on chromosome 1 right (A–C) and left arms (D–F). Primers specific to chromosome 2 were used as control.

Fig 11

Chromosome duplications revealed after aligning DNA sequencing reads obtained from the A series of strains to the C. neoformans reference genome (A). *, chromosome duplication. Analysis of AFR1 (B) and ERG11 (C) gene expression in A0, A2, and A4 strains by RT-qPCR. ns, not significant. *p < 0.05.

Fig 12

EV production and FLC resistance are linked in clinical isolates. Analysis of EV production by nanoFCM and size of FLC-disk inhibition halo in clinical isolates by linear regression (A, radius of inhibition=RAD₈₀ values by diskImageR). EV production as measured by nanoFCM in the recurrent isolates CNRMA17.247 and CNRMA20.738 (top) and FLC-disk diffusion assays (bottom) from patient A (B). EV production as measured by nanoFCM in the recurrent isolates CNRMA4.1291 and CNRMA4.1293 (top) and FLC-disk diffusion assays (bottom) from patient B (C). FLC-disk diffusion assay in passaged clinical isolates. The CNRMA20.738 and CNRMA4.1293 passage 0 pictures are details of the ones presented in panels B and C, respectively (D). Analysis of EV production of passaged clinical isolates by nanoFCM (E). Alignment of DNA-Seq reads obtained from P0 and P8 CNRMA5.114 passaged clinical isolates (F). EV and FLC-disk analyses were carried out in at least biological triplicates, and representative results were shown. ns, not significant. *p < 0.05.

Fig 13

Model of EV biogenesis regulation and FLC susceptibility in C. neoformans. Specific gene mutations and FLC exposure can trigger diverse cellular responses, including changes in the expressions of drug efflux-associated genes, of the azole target gene, and in EVs biogenesis. Gat5 inhibits the expression of AFR1 and AFR3, which can affect the intracellular FLC levels, while subinhibitory concentration of FLC can inhibit EV production. Hap2/3/5 and Gat5 regulate EV production, and cellular lipid homeostasis. The differential regulation of these cellular processes may determine FLC resistance phenotypes in this fungal pathogen. Schematic model created in BioRender.