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Glutathione-mediated redox regulation in Cryptococcus neoformans impacts virulence

Nature Microbiology (2024)Cite this article

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Abstract

The fungal pathogen Cryptococcus neoformans is well adapted to its host environment. It has several defence mechanisms to evade oxidative and nitrosative agents released by phagocytic host cells during infection. Among them, melanin production is linked to both fungal virulence and defence against harmful free radicals that facilitate host innate immunity. How C. neoformans manipulates its redox environment to facilitate melanin formation and virulence is unclear. Here we show that the antioxidant glutathione is inextricably linked to redox-active processes that facilitate melanin and titan cell production, as well as survival in macrophages and virulence in a murine model of cryptococcosis. Comparative metabolomics revealed that disruption of glutathione biosynthesis leads to accumulation of reducing and acidic compounds in the extracellular environment of mutant cells. Overall, these findings highlight the importance of redox homeostasis and metabolic compensation in pathogen adaptation to the host environment and suggest new avenues for antifungal drug development.

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Fig. 1: Loss of GSH2 impairs melanin and titan cell formation and attenuates virulence.
Fig. 2: Gsh2 is required for growth upon nutrient depletion and WT cells secrete extracellular GSH.
Fig. 3: Deletion of GSH2 reduces susceptibility to H2O2 stress and alters non-GSH antioxidant functions.
Fig. 4: Dysregulation of GSH biosynthesis affects cellular metabolism.
Fig. 5: Extracellular acidity and reducing pontential inhibits melanin formation.
Fig. 6: GSH modulates redox homeostasis to influence melanin production.

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Data availability

The authors declare that all data supporting the findings of this study are available within the main text and Supplementary Information. The complete dataset used for LC-HRMS/MS analysis is publicly available on figshare (https://doi.org/10.6084/m9.figshare.24011169)32 and raw experimental data with their associated metadata are available on MetaboLights (MTBLS9984, https://www.ebi.ac.uk/metabolights/MTBLS9984). Source data are provided with this paper.

Code availability

All analyses were performed using publicly available software as described in the Methods. No custom code was generated for data analyses in this study.

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Acknowledgements

The authors thank T. Huan for useful discussions. Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH) under award number R01AI053721 (to J.W.K.). A.C. was supported in part by NIH grants AI052733, AI15207, AI171093-01 and HL059842. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Additional support came from a University of British Columbia (UBC) Four Year Doctoral Fellowship (to B.B.), and a Natural Sciences and Engineering Research Council of Canada (NSERC) Postgraduate Scholarship – Doctoral (to B.B.). L.C.H. is an NSERC postdoctoral fellow. J.W.K. is a Burroughs Wellcome Fund Scholar in Molecular Pathogenic Mycology, and the Power Corporation Fellow in the Canadian Institute for Advanced Research Program: Fungal Kingdom, Threats and Opportunities. Untargeted metabolomic analysis was performed in the Life Sciences Institute (LSI) Metabolomics Core Facility of the LSI at UBC, supported by the Canada Foundation for Innovation, the BC Knowledge Development Fund, the LSI, and the UBC GREx Biological Resilience Initiative. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. Linda C. Horianopoulos

    Present address: Wisconsin Energy Institute, University of Wisconsin–Madison, Madison, WI, USA

  2. Mélissa Caza

    Present address: Larissa Yarr Medical Microbiology Laboratory, Kelowna General Hospital, Kelowna, British Columbia, Canada

  3. Rodgoun Attarian

    Present address: Pfizer Canada, Kirkland, Quebec, Canada

Authors and Affiliations

  1. The Michael Smith Laboratories, Departments of Microbiology and Immunology, and Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada

    Braydon Black, Leandro Buffoni Roque da Silva, Guanggan Hu, Xianya Qu, Armando Alcázar Magaña, Linda C. Horianopoulos, Mélissa Caza, Rodgoun Attarian, Leonard J. Foster & James W. Kronstad

  2. W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Daniel F. Q. Smith & Arturo Casadevall

  3. Metabolomics Core Facility, Life Sciences Institute, Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada

    Armando Alcázar Magaña & Leonard J. Foster

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Contributions

B.B. and J.W.K. conceptualized this project. B.B. developed methodology with guidance from J.W.K., A.C. and D.F.Q.S. and performed all growth experiments, flow cytometry, melanin/ABTS and colorimetric/fluorometric kit assays and data analysis. B.B. wrote the manuscript and J.W.K. provided edits. All authors participated in the review and editing of the manuscript. G.H., L.B.R.d.S., X.Q., B.B., L.C.H. and M.C. performed animal work and X.Q. imaged cells. Macrophage experiments were conducted by L.B.R.d.S., X.Q. and B.B., and L.B.R.d.S. performed all cytokine profiling experiments. G.H., L.C.H. and R.A. designed and constructed the mutant and complemented strains used in this study. A.A.M. conducted all LC-HRMS/MS experiments with guidance from L.J.F. and assisted B.B. with sample preparation and metabolomics data analysis. D.F.Q.S. performed all urease and cell wall laccase experiments and advised on ABTS antioxidant assays. J.W.K. and A.C. acquired funding for the project and L.J.F. funds the LSI Metabolomics Core Facility at UBC.

Corresponding author

Correspondence to James W. Kronstad.

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Extended data

Extended Data Fig. 1 Loss of GSH2 does not affect capsule size but delays virulence and impairs dissemination to the brain.

a, Polysaccharide capsule (left) and cell body diameter (right) of cells grown for 48 h. Measurements represent mean values ± s.d. of n = 50 cells from three independent experiments per strain. Significance was calculated relative to the WT using one-way ANOVA with Dunnett’s correction for multiple comparisons. b, Visualization of polysaccharide capsule with DIC microscopy. Images represent three independent experiments (scale bars = 10 μm). c, Spot assay of growth on solid YPD medium starting at 106 cells ml-1 with 10-fold serial dilutions. Plates were incubated at 30 ˚C, 37 ˚C, 39 ˚C. d, Melanin production of 106 cells on epinephrine (Epi, 0.1 g L-1), dopamine (Dm, 0.1 g L-1), and Niger seed (NS)-containing minimal media at 30 ◦C. NS medium was prepared from 70 g 0.1 g L-1 seed extract supplemented with 0.1 g L-1 glucose, 20 g L-1 Bacto Agar, and 0.05% Tween 20. e, Melanin production of 106 cells per strain retrieved from murine lungs and spotted on solid l-DOPA medium. Agar plates in c, d, and e were grown for 48 h before imaging, and images are representative of three biological replicates. f, Time-course of fungal burden in mice intranasally infected with WT (red), gsh2∆ (light blue), and gsh2∆::GSH2 (dark blue) strains. Significance was calculated using two-way ANOVA with Dunnett’s correction for multiple comparisons. Solid bars indicate mean fungal burden (n = 8 mice per group) and segmented bars represent interquartile range. g, Visualization of fungal cells retrieved from murine lungs with DIC microscopy (top). Images represent fungal cells retrieved from 8 murine lungs per strain (n = 60 cells per sample) per timepoint (bars = 10 μm). Cell body diameter of gsh2∆ mutant cells retrieved from murine lungs (bottom). Lines represent mean values of n = 60 cells from 8 lungs per strain per time point.

Source data

Extended Data Fig. 2 Mutants lacking GSH2 have reduced lung proliferation and cell size in vivo.

a, Representative images of H & E stained lung tissue sections from four mice infected with WT, gsh2∆, or gsh2∆::GSH2 strains at each of the time points indicated (arrows = cryptococcal cells; bars = 10 μm). Segmented squares indicate enhanced zoom sections shown in the lower-right corner of each image. b, Cytokine levels in murine tissue homogenate of lungs infected with the WT (red) or gsh2∆ mutant (blue) strains at the indicated timepoints (n = 8 lungs for each strain at each time point). Uninfected mice (Naïve, gray, inoculated with PBS) were used as a control. Significance was calculated relative to treatment naïve mice using two-way ANOVA with either Tukey’s (7 & 14 dpi) or Šidák’s (21 & 26 dpi) correction for multiple comparisons. Solid bars indicate mean cytokine level and segmented bars represent interquartile range.

Source data

Extended Data Fig. 3 GSH is required for growth in minimal medium and is not restored with ascorbate or sulfur-containing amino acids.

a, Growth curve analysis of WT (light blue circles), gsh2∆ (blue squares or circles), and gsh2∆::GSH2 (light blue squares) strains grown in rich or minimal medium with and without methionine (Met), cysteine (Cys), or ascorbic acid (AA) supplementation at the indicated concentrations. b, Spot assays on minimal media. Each strain was spotted starting at 106 cells with 10-fold serial dilutions on agar minimal medium with or without Met, Cys, or AA supplementation at the indicated concentrations. Images are representative of three biological replicates. c, Growth of WT, gsh2∆, and gsh2∆::GSH2 strains in minimal medium with or without GSH supplementation at the indicated concentrations. Data points for a and c indicate mean OD600 values ± s.d., and the initial inoculum for each strain was 2 × 104 cells ml-1. Growth was monitored for 72 h with OD600 values measured every 24 h. d–e, Growth of WT, gsh2∆, and gsh2∆::GSH2 cells in 5 ml liquid cultures of l-DOPA medium (with or without GSH supplementation in e). Initial inoculum for each strain was 106 cells ml-1 and CFUs were counted every 24 h for 72 h (d) or at 48 h (e). Points (d) or bars (e) represent mean CFUs ml-1 ± s.d. at each time point or GSH concentration, respectively. f, ABTS antioxidant assay (see Methods) for the proportion of ABTS radical quenched by supernatant isolated from the indicated strains after 72 h incubation in l-asparagine minimal medium (lacking l-DOPA). Pigmentation (blue colouration) indicates presence of the ABTS radical. Images represent three independent experiments. Data are representative of three biological replicates for each experiment.

Source data

Extended Data Fig. 4 Metabolic profiling of the gsh2∆ mutant relative to WT reveals differences in extracellular and intracellular fractions.

a, Volcano plots showing QC-normalized LC-HRMS/MS feature data and differentially abundant metabolites between WT and gsh2∆ mutant cells in supernatant (left) and cell extract (right) fractions. The horizontal axis represents the directional intensity of the metabolite peak abundance fold change (FC) and the vertical axis represents statistical significance. A P-value threshold of P < 0.05 and FC threshold of > 1.5 or < 0.667 (segmented lines) were used to identify differences between the WT and mutant strains, which were determined using an unpaired, two-tailed Student’s t-test with Benjamini-Hochberg FDR correction for multiple comparisons in MetaboAnalyst. b, Heatmap comparing relative intensity of metabolite abundances in the supernatant (sup) and cell extract (ext) of WT and gsh2∆ mutants (KO); n = 3 biological replicates were analyzed for each fragment. Higher and lower intensity values are coloured red and blue, respectively. c, PCA score plot of the first two principal components from WT and gsh2∆ mutant supernatant and cellular extract fractions with QC samples for data normalization. Each data set represents n = 3 biological replicates. Purple = WT; red = gsh2∆ mutant; green = QC.

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Extended Data Fig. 5 Mutants lacking GSH2 show distinct changes in relative abundance of key energy metabolites, antioxidants, and extracellular acids.

Relative abundance of select compounds identified via LC-HRMS/MS between WT (blue) and gsh2∆ mutant (red) strains. Both cell extract (ext) and supernatant (sup) fractions were analyzed for relative peak intensity. Bars represent mean relative abundances ± s.d. for n = 3 biological replicates per strain. Significance was calculated relative to the WT supernatant (sup) fraction using multiple unpaired, two-tailed Student’s t-tests with Benjamini-Hochberg FDR corrections for multiple comparisons.

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Extended Data Fig. 6 Extracellular acidification of gsh2∆ mutants is independent of l-DOPA and GSH pathway metabolites influence melanin formation.

a, pH values of supernatant isolates from WT and gsh2∆ mutant cells grown in l-asparagine minimal medium and normalized to 107 cells ml-1. Statistical significance was calculated using an unpaired, two-tailed Student’s t-test. Bars represent mean pH values ± s.d. b–c, ABTS antioxidant assay indicates the reducing power of compounds tested at the indicated concentrations. Decreased pigmentation (light blue & clear in image) in c indicates increased ABTS• radical scavenging activity. GSH = glutathione; AA = ascorbic acid; Cys = cysteine.

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Black, B., da Silva, L.B.R., Hu, G. et al. Glutathione-mediated redox regulation in Cryptococcus neoformans impacts virulence. Nat Microbiol (2024). https://doi.org/10.1038/s41564-024-01721-x

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