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Pan-drug resistance and hypervirulence in a human fungal pathogen are enabled by mutagenesis induced by mammalian body temperature

Abstract

The continuing emergence of invasive fungal pathogens poses an increasing threat to public health. Here, through the China Hospital Invasive Fungal Surveillance Net programme, we identified two independent cases of human infection with a previously undescribed invasive fungal pathogen, Rhodosporidiobolus fluvialis, from a genus in which many species are highly resistant to fluconazole and caspofungin. We demonstrate that R.fluvialis can undergo yeast-to-pseudohyphal transition and that pseudohyphal growth enhances its virulence, revealed by the development of a mouse model. Furthermore, we show that mouse infection or mammalian body temperature induces its mutagenesis, allowing the emergence of hypervirulent mutants favouring pseudohyphal growth. Temperature-induced mutagenesis can also elicit the development of pan-resistance to three of the most commonly used first-line antifungals (fluconazole, caspofungin and amphotericin B) in different Rhodosporidiobolus species. Furthermore, polymyxin B was found to exhibit potent activity against the pan-resistant Rhodosporidiobolus mutants. Collectively, by identifying and characterizing a fungal pathogen in the drug-resistant genus Rhodosporidiobolus, we provide evidence that temperature-dependent mutagenesis can enable the development of pan-drug resistance and hypervirulence in fungi, and support the idea that global warming can promote the evolution of new fungal pathogens.

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Fig. 1: Identification and phenotypic characterization of two independent cases of human infection with a previously undescribed fungal pathogen, R.fluvialis, based on the CHIF-NET surveillance programme.
Fig. 2: Identification of parallel resistance mechanisms in the Rhodosporidiobolus pathogen.
Fig. 3: Evaluation of the in vivo adaptation of different Rhodosporidiobolus species in an immunocompromised mouse model.
Fig. 4: Pseudohyphal growth promotes the virulence of R.fluvialis and mouse infection induces the emergence of pseudohyphal mutants.
Fig. 5: Heat stress induces the accumulation of intracellular ROS, which is an important factor promoting mutagenesis of R.fluvialis.
Fig. 6: Heat stress induces the emergence of pan-resistance variants in different Rhodosporidiobolus species.

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Data availability

All data needed to evaluate the conclusions in the paper are present in the paper or in Supplementary Information. The sequencing data have been deposited at NCBI under the BioProject PRJNA990320. Source data are provided with this paper.

References

  1. Fisher, M. C. & Denning, D. W. The WHO fungal priority pathogens list as a game-changer. Nat. Rev. Microbiol. 21, 211–212 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Denning, D. W. Global incidence and mortality of severe fungal disease. Lancet Infect. Dis. 24, e268 (2024).

    Article  Google Scholar 

  3. Garcia-Solache, M. A. & Casadevall, A. Global warming will bring new fungal diseases for mammals. mBio 1, e00061-10 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Nnadi, N. E. & Carter, D. A. Climate change and the emergence of fungal pathogens. PLoS Pathog. 17, e1009503 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Casadevall, A., Kontoyiannis, D. P. & Robert, V. On the emergence of Candida auris: climate change, azoles, swamps, and birds. mBio 10, e01397-19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Hawksworth, D. L. & Lucking, R. Fungal diversity revisited: 2.2 to 3.8 million species. Microbiol. Spectr. https://doi.org/10.1128/microbiolspec.funk-0052-2016 (2017).

  7. Kathiravan, M. K. et al. The biology and chemistry of antifungal agents: a review. Bioorg. Med. Chem. 20, 5678–5698 (2012).

    Article  CAS  PubMed  Google Scholar 

  8. Roemer, T. & Krysan, D. J. Antifungal drug development: challenges, unmet clinical needs, and new approaches. Cold Spring Harb. Perspect. Med. 4, a019703 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Szymanski, M., Chmielewska, S., Czyzewska, U., Malinowska, M. & Tylicki, A. Echinocandins - structure, mechanism of action and use in antifungal therapy. J. Enzyme Inhib. Med. Chem. 37, 876–894 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Hamill, R. J. Amphotericin B formulations: a comparative review of efficacy and toxicity. Drugs 73, 919–934 (2013).

    Article  CAS  PubMed  Google Scholar 

  11. Fera, M. T., La Camera, E. & De Sarro, A. New triazoles and echinocandins: mode of action, in vitro activity and mechanisms of resistance. Expert. Rev. Anti Infect. Ther. 7, 981–998 (2009).

    Article  CAS  PubMed  Google Scholar 

  12. Perlin, D. S., Rautemaa-Richardson, R. & Alastruey-Izquierdo, A. The global problem of antifungal resistance: prevalence, mechanisms, and management. Lancet Infect. Dis. 17, e383–e392 (2017).

    Article  PubMed  Google Scholar 

  13. Chowdhary, A., Kathuria, S., Xu, J. & Meis, J. F. Emergence of azole-resistant Aspergillus fumigatus strains due to agricultural azole use creates an increasing threat to human health. PLoS Pathog. 9, e1003633 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Pristov, K. E. & Ghannoum, M. A. Resistance of Candida to azoles and echinocandins worldwide. Clin. Microbiol. Infect. 25, 792–798 (2019).

    Article  CAS  PubMed  Google Scholar 

  15. Fisher, M. C. et al. Tackling the emerging threat of antifungal resistance to human health. Nat. Rev. Microbiol. 20, 557–571 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rhodes, J. & Fisher, M. C. Global epidemiology of emerging Candida auris. Curr. Opin. Microbiol. 52, 84–89 (2019).

    Article  PubMed  Google Scholar 

  17. Pfaller, M. A., Messer, S. A., Woosley, L. N., Jones, R. N. & Castanheira, M. Echinocandin and triazole antifungal susceptibility profiles for clinical opportunistic yeast and mold isolates collected from 2010 to 2011: application of new CLSI clinical breakpoints and epidemiological cutoff values for characterization of geographic and temporal trends of antifungal resistance. J. Clin. Microbiol. 51, 2571–2581 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ostrowsky, B. et al. Candida auris isolates resistant to three classes of antifungal medications - New York, 2019. MMWR Morb. Mortal. Wkly Rep. 69, 6–9 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Scorzetti, G., Fell, J. W., Fonseca, A. & Statzell-Tallman, A. Systematics of basidiomycetous yeasts: a comparison of large subunit D1/D2 and internal transcribed spacer rDNA regions. FEMS Yeast Res. 2, 495–517 (2002).

    Article  CAS  PubMed  Google Scholar 

  20. Schoch, C. L. et al. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc. Natl Acad. Sci. USA 109, 6241–6246 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Fell, J. W., Boekhout, T., Fonseca, A., Scorzetti, G. & Statzell-Tallman, A. Biodiversity and systematics of basidiomycetous yeasts as determined by large-subunit rDNA D1/D2 domain sequence analysis. Int. J. Syst. Evol. Microbiol. 50, 1351–1371 (2000).

    Article  CAS  PubMed  Google Scholar 

  22. Wang, Q. M. et al. Phylogenetic classification of yeasts and related taxa within Pucciniomycotina. Stud. Mycol. 81, 149–189 (2015).

    Article  PubMed  Google Scholar 

  23. Li, A. H. et al. Diversity and phylogeny of basidiomycetous yeasts from plant leaves and soil: proposal of two new orders, three new families, eight new genera and one hundred and seven new species. Stud. Mycol. 96, 17–140 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Sigera, L. S. M. & Denning, D. W. Flucytosine and its clinical usage. Ther. Adv. Infect. Dis. 10, 20499361231161387 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Rhie, A., Walenz, B. P., Koren, S. & Phillippy, A. M. Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies. Genome Biol. 21, 245 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Coelho, M. A., Goncalves, P. & Sampaio, J. P. Evidence for maintenance of sex determinants but not of sexual stages in red yeasts, a group of early diverged basidiomycetes. BMC Evol. Biol. 11, 249 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ji, H. et al. A three-dimensional model of lanosterol 14α-demethylase of Candida albicans and its interaction with azole antifungals. J. Med. Chem. 43, 2493–2505 (2000).

    Article  CAS  PubMed  Google Scholar 

  28. Zhang, Y. et al. The genome of opportunistic fungal pathogen Fusarium oxysporum carries a unique set of lineage-specific chromosomes. Commun Biol 3, 50 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Macedo, D. et al. Molecular confirmation of the linkage between the Rhizopus oryzae CYP51A gene coding region and its intrinsic voriconazole and fluconazole resistance. Antimicrob. Agents Chemother. 62, e00224-18 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Bloom, A. L. M. et al. Thermotolerance in the pathogen Cryptococcus neoformans is linked to antigen masking via mRNA decay-dependent reprogramming. Nat. Commun. 10, 4950 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Nakayama, H., Nakayama, N., Arisawa, M. & Aoki, Y. In vitro and in vivo effects of 14α-demethylase (ERG11) depletion in Candida glabrata. Antimicrob. Agents Chemother. 45, 3037–3045 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Avalos, J. & Carmen Limon, M. Biological roles of fungal carotenoids. Curr. Genet. 61, 309–324 (2015).

    Article  CAS  PubMed  Google Scholar 

  33. Cowen, L. E., Sanglard, D., Howard, S. J., Rogers, P. D. & Perlin, D. S. Mechanisms of antifungal drug resistance. Cold Spring Harb. Perspect. Med. 5, a019752 (2014).

    Article  PubMed  Google Scholar 

  34. Robert, V., Cardinali, G. & Casadevall, A. Distribution and impact of yeast thermal tolerance permissive for mammalian infection. BMC Biol. 13, 18 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Whiteway, M. & Oberholzer, U. Candida morphogenesis and host–pathogen interactions. Curr. Opin. Microbiol. 7, 350–357 (2004).

    Article  CAS  PubMed  Google Scholar 

  36. Gauthier, G. & Klein, B. S. Insights into fungal morphogenesis and immune evasion: Fungal conidia, when situated in mammalian lungs, may switch from mold to pathogenic yeasts or spore-forming spherules. Microbe Wash DC. 3, 416–423 (2008).

    PubMed  PubMed Central  Google Scholar 

  37. Austermeier, S., Kasper, L., Westman, J. & Gresnigt, M. S. I want to break free - macrophage strategies to recognize and kill Candida albicans, and fungal counter-strategies to escape. Curr. Opin. Microbiol. 58, 15–23 (2020).

    Article  CAS  PubMed  Google Scholar 

  38. Kasper, L., Seider, K. & Hube, B. Intracellular survival of Candida glabrata in macrophages: immune evasion and persistence. FEMS Yeast Res. 15, fov042 (2015).

    Article  PubMed  Google Scholar 

  39. Maxson, M. E. et al. Integrin-based diffusion barrier separates membrane domains enabling the formation of microbiostatic frustrated phagosomes. eLife 7, e34798 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  40. King, L. & Butler, G. Ace2p, a regulator of CTS1 (chitinase) expression, affects pseudohyphal production in Saccharomyces cerevisiae. Curr. Genet. 34, 183–191 (1998).

    Article  CAS  PubMed  Google Scholar 

  41. Stead, D. A. et al. Impact of the transcriptional regulator, Ace2, on the Candida glabrata secretome. Proteomics 10, 212–223 (2010).

    Article  CAS  PubMed  Google Scholar 

  42. Boeke, J. D., Trueheart, J., Natsoulis, G. & Fink, G. R. 5-Fluoroorotic acid as a selective agent in yeast molecular genetics. Methods Enzymol. 154, 164–175 (1987).

    Article  CAS  PubMed  Google Scholar 

  43. Gusa, A. et al. Transposon mobilization in the human fungal pathogen Cryptococcus is mutagenic during infection and promotes drug resistance in vitro. Proc. Natl Acad. Sci. USA 117, 9973–9980 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Lee, H. J., Kim, J. M., Kang, W. K., Yang, H. & Kim, J. Y. The NDR kinase Cbk1 downregulates the transcriptional repressor Nrg1 through the mRNA-binding protein Ssd1 in Candida albicans. Eukaryot. Cell 14, 671–683 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Nelson, B. et al. RAM: a conserved signaling network that regulates Ace2p transcriptional activity and polarized morphogenesis. Mol. Biol. Cell 14, 3782–3803 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Kreutzer, D. A. & Essigmann, J. M. Oxidized, deaminated cytosines are a source of C→T transitions in vivo. Proc. Natl Acad. Sci. USA 95, 3578–3582 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Jeon, J., Choi, J., Lee, G. W., Dean, R. A. & Lee, Y. H. Experimental evolution reveals genome-wide spectrum and dynamics of mutations in the rice blast fungus, Magnaporthe oryzae. PLoS One 8, e65416 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Liu, R. et al. Heat stress-induced reactive oxygen species participate in the regulation of HSP expression, hyphal branching and ganoderic acid biosynthesis in Ganoderma lucidum. Microbiol. Res. 209, 43–54 (2018).

    Article  CAS  PubMed  Google Scholar 

  49. Moraitis, C. & Curran, B. P. Reactive oxygen species may influence the heat shock response and stress tolerance in the yeast Saccharomyces cerevisiae. Yeast 21, 313–323 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. Zhang, H., Zhu, J., Gong, Z. & Zhu, J. K. Abiotic stress responses in plants. Nat. Rev. Genet. 23, 104–119 (2022).

    Article  PubMed  Google Scholar 

  51. Yousfi, H., Ranque, S., Rolain, J. M. & Bittar, F. In vitro polymyxin activity against clinical multidrug-resistant fungi. Antimicrob. Resist. Infect. Control 8, 66 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Hazen, K. C. Fungicidal versus fungistatic activity of terbinafine and itraconazole: an in vitro comparison. J. Am. Acad. Dermatol. 38, S37–S41 (1998).

    Article  CAS  PubMed  Google Scholar 

  53. Kelesidis, T. & Falagas, M. E. The safety of polymyxin antibiotics. Expert Opin. Drug Saf. 14, 1687–1701 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Casadevall, A. Global warming could drive the emergence of new fungal pathogens. Nat. Microbiol. 8, 2217–2219 (2023).

    Article  CAS  PubMed  Google Scholar 

  55. Jung, K. W. et al. Systematic functional profiling of transcription factor networks in Cryptococcus neoformans. Nat. Commun. 6, 6757 (2015).

    Article  CAS  PubMed  Google Scholar 

  56. Vaser, R., Sovic, I., Nagarajan, N. & Sikic, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 27, 737–746 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9, e112963 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Palmer, J. & Stajich, J. Funannotate v1.8.1: Eukaryotic genome annotation (v1.8.1). Zenodo. https://doi.org/10.5281/zenodo.4054262 (2020).

  61. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Nguyen, L. T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).

    Article  CAS  PubMed  Google Scholar 

  64. Criscuolo, A. A fast alignment-free bioinformatics procedure to infer accurate distance-based phylogenetic trees from genome assemblies. Res. Ideas Outcomes 5, e36178 (2019).

  65. Tian, X. et al. Cryptococcus neoformans sexual reproduction is controlled by a quorum sensing peptide. Nat. Microbiol. 3, 698–707 (2018).

    Article  CAS  PubMed  Google Scholar 

  66. Lin, X., Chacko, N., Wang, L. & Pavuluri, Y. Generation of stable mutants and targeted gene deletion strains in Cryptococcus neoformans through electroporation. Med. Mycol. 53, 225–234 (2015).

    Article  CAS  PubMed  Google Scholar 

  67. Dixon, D. M., Polak, A. & Walsh, T. J. Fungus dose-dependent primary pulmonary aspergillosis in immunosuppressed mice. Infect. Immun. 57, 1452–1456 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank S. Gao and S. Hu for important advice on R.fluvialis NJ103 and TZ579 genome assembly. We are grateful to all participants in the CHIF-NET programme. This study was financially supported by the National Key Research and Development Program of China (2022YFC2303000, L.W.); the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2021-I2M-1-038, Y. Xu); the National High Level Hospital Clinical Research Funding (2022-PUMCH-C-052, M.X.); the CAS Interdisciplinary Innovation Team (L.W.), and the Scientific Research Program of the Affiliated Huai’an No. 1 People’s Hospital of Nanjing Medical University (YCT202302 and CG202305, J.H.).

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Contributions

All authors contributed to the data analysis. J.H., P.H., L.Y., Z.S., X.C., F.L., Y. Xie, J.Y., X.F., M.X., C.K.M.T., L.C., G.Z., F.B., Y. Xu and L.W. designed the experiments. J.H., P.H., L.Y. and Z.S. conducted most of the studies. J.H. and P.H. constructed most of the strains and conducted the phenotypic assays. Z.S. conducted most of the bioinformatics assays. J.H. and P.H. performed the SEM experiments. J.H., P.H. and L.Y. performed the animal experiments. L.Y. conducted the macrophage phagocytosis assays. L.W., Y. Xu, F.B., L.C., K.H.W., W.W. and Y.L. contributed reagents, materials or analysis tools. L.W., K.H.W. and P.H. wrote the paper with contributions from all other authors.

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Correspondence to Yingchun Xu or Linqi Wang.

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Extended data

Extended Data Fig. 1 Phylogenetic and phenotypic analysis of Rhodosporidiobolus species NJ103 and TZ579.

a. Comparison of the ITS and D1/D2 sequences of NJ103, TZ579 and their closest relatives. b. Phylogenetic analysis of NJ103, TZ59 and R. fluvialis strains based on ITS and D1/D2 sequences. The ITS and D1/D2 sequences of nine isolates of R. fluvialis species were obtained from the GenBank database. c. Colony and cellular morphology of strains from eight Rhodosporidiobolus species. Colonies and cells were photographed after 10 days of growth on YPD plate. Scale bars, 200 μm (upper panel), 10 μm (bottom panel). Images are representative of three independent experiments conducted with similar results.

Extended Data Fig. 2 Phenotypic assays of nine strains from Rhodosporidiobolus species.

Strains of Rhodosporidiobolus species were cultured for 12 h in YPD liquid medium at 25 °C. Cells were washed with distilled water and 5-fold serially diluted and then spotted (3 μl of each dilution) onto YPD containing the indicated stress inducing reagents. Sorbitol to induce osmotic stress; NaCl, KCl, CaCl2, CdSO4 or Cr2(SO4)3 to induce salt stress or heavy-metal stress; hydrogen peroxide, tert-butyl hydroperoxide, paraquat or diamide to induce oxidative stress; CoCl2 to induce hypoxic stress; SDS, DMSO, calcofluor white or Congo red to induce cell membrane/cell wall stress; dithiothreitol to induce endoplasmic reticulum stress; methyl methanesulfonate, hydroxyurea and cisplatin to induce genotoxic stress; cycloheximide or brefeldin A to inhibit protein biosynthesis or transport; or antifungal agents (amphotericin B, fluconazole, caspofungin, nystatin, monesin, cyclosporine A or rapamycin). The abbreviations used are the same as those in the phenome heat map in Fig. 1d. Images are representative of three independent experiments conducted with similar results.

Extended Data Fig. 3 R. fluvialis could rapidly generate 5-fluorocytosine-resistant mutants.

a. 5-flucytosine resistance rate for R. fluvialis NJ103. Approximately 5 × 105 cells of R. fluvialis NJ103 or the control strain C. neoformans H99 were plated on RPMI medium containing 500 μg/mL 5-flucytosine and incubated at 25 °C for 1 week. Data are presented as the mean ± SD of three independent experiments, two-tailed, unpaired Student’s t-test. b. The R. fluvialis NJ103 MIC values for 5-flucytosine with test results read at different time points.

Source data

Extended Data Fig. 4 Genome-wide comparison of high-quality genome assemblies of two R. fluvialis strains.

Circos maps of the whole genomes of R. fluvialis NJ103 (a) and TZ579 (b). The outer ring represents the karyotype. A = GC content, B = gene density, C = repeat density. All statistics are calculated for windows of 100-Kb. Inter-scaffold interactions are displayed in the inner-most ring. c. Gene collinearity between the R. fluvialis TZ579 subgenomes. Each line connects one pair of homologous genes. d. Gene collinearity between the R. fluvialis NJ103 and TZ579 genomes. Each line connects one pair of homologous genes. e. K-mer distribution and contig frequency analyses. Seventeen k-mer depth distribution of whole-genome Illumina reads. f. R. fluvialis NJ103 and TZ579 cells were cultured on YPD plate for 1 day and FACS analysis was performed using cells stained with propidium iodide. Histogram was plotted representing 10,000 cell events.

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Extended Data Fig. 5 The two subgenomes of R. fluvialis TZ579 share a high degree of sequence identity.

Distribution of amino acid sequence identity level between homologous genes from the two subgenomes of R. fluvialis TZ579.

Source data

Extended Data Fig. 6 Synteny maps of the MAT loci in R. fluvialis NJ103 and TZ579.

The mating pheromone (RHA) and receptor (STE3) genes are shown in green and orange, respectively. Additional genes that are present in the MAT locus are shown in blue.

Source data

Extended Data Fig. 7 Duplication of ERG11 gene is not the cause of the high fluconazole resistance observed in the R. fluvialis.

a. Gene deletion experiments on the ERG11-1 gene in R. fluvialis NJ103. The wild type showed a 492 bp band when amplified with internal primers (PCR1) and a 6,088 bp band that could not be digested by EcoR V when amplified with external primers (PCR2). erg11-1Δ showed no bands when amplified with internal primers, and showed a 5,854 bp band that could be digested by EcoR V to produce two bands of 4,178 bp and 1,786 bp when amplified with external primers. b. Gene deletion experiments on the ERG11-2 gene in R. fluvialis NJ103. The wild type showed a 434 bp band when amplified with internal primers (PCR1) and a 5,973bp band that could not be digested by EcoR V when amplified with external primers (PCR2). erg11-2Δ showed no bands when amplified with internal primers, and showed a 5,971 bp band that could be digested by EcoR V to produce two bands of 3,996 bp and 1,975 bp when amplified with external primers. c. MIC (left) and spotting susceptibility (right) assays of WT, erg11-1Δ, and erg11-2Δ stains. MIC values were tested as described in Materials and Methods. For spotting susceptibility assays, cells of different strains were spotted onto RPMI agar containing 100 μg/mL fluconazole (FLC). C. neoformans H99 was used as a control. Images are representative of three independent experiments conducted with similar results.

Source data

Extended Data Fig. 8 Phenotypic assays of R. fluvialis NJ103 WT and crtYBΔ mutant strains.

Cells of different strains were cultured for 12 h in YPD liquid medium at 25 °C. Cells were washed with distilled water and 5-fold serially diluted and then spotted (3 μl of each dilution) onto YPD containing the indicated stress inducing reagents. Images are representative of three independent experiments conducted with similar results.

Extended Data Fig. 9 Incubation at 37 °C is a key factor in inducing the formation of pseudohyphal variants.

R. fluvialis cells were pre-cultured in RPMI medium at 25 °C or 37 °C in the presence or absence of CO2 for 2 days and the cells were then plated on YPD agar at 25 °C until colonies were formed. Data are presented as the mean ± SD of six independent experiments, two-tailed, unpaired Student’s t-test.

Source data

Extended Data Table 1 Antifungal susceptibility profiles of nine strains from Rhodosporidiobolus species

Supplementary information

Supplementary Information

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Reporting Summary

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Huang, J., Hu, P., Ye, L. et al. Pan-drug resistance and hypervirulence in a human fungal pathogen are enabled by mutagenesis induced by mammalian body temperature. Nat Microbiol 9, 1686–1699 (2024). https://doi.org/10.1038/s41564-024-01720-y

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