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Transcriptional and functional insights into the host immune response against the emerging fungal pathogen Candida auris

Nature Microbiology volume 5, pages 1516–1531 (2020)Cite this article

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Abstract

Candida auris is among the most important emerging fungal pathogens, yet mechanistic insights into its immune recognition and control are lacking. Here, we integrate transcriptional and functional immune-cell profiling to uncover innate defence mechanisms against C. auris. C. auris induces a specific transcriptome in human mononuclear cells, a stronger cytokine response compared with Candida albicans, but a lower macrophage lysis capacity. C. auris-induced innate immune activation is mediated through the recognition of C-type lectin receptors, mainly elicited by structurally unique C. auris mannoproteins. In in vivo experimental models of disseminated candidiasis, C. auris was less virulent than C. albicans. Collectively, these results demonstrate that C. auris is a strong inducer of innate host defence, and identify possible targets for adjuvant immunotherapy.

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Fig. 1: Comparative analysis between the general and clade-specific C. auris- and C. albicans-induced host response at 24 h.
Fig. 2: Evaluating the dynamics of C. auris phagocytosis by human and murine host immune cells, and the heat sensitivity of the cell wall component that is responsible for C. auris-induced cytokine production.
Fig. 3: Mannans are fundamental for orchestrating the C. auris-induced late host response.
Fig. 4: NMR analysis of C. auris mannans revealed unique structural features.
Fig. 5: Examination of PRR and signalling pathways that are involved in the C. auris-induced host cytokine production.
Fig. 6: C. auris is less virulent than C. albicans in an experimental model of mouse disseminated candidiasis.

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Data availability

Requests for materials should be addressed to the corresponding author. The datasets generated in this study are accessible through GEO Series accession number GSE154911. Source data are provided with this paper.

References

  1. Meis, J. F. & Chowdhary, A. Candida auris: a global fungal public health threat. Lancet Infect. Dis. 18, 1298–1299 (2018).

    PubMed  Google Scholar 

  2. Clancy, C. J. & Nguyen, M. H. Emergence of Candida auris: an international call to arms. Clin. Infect. Dis. 64, 141–143 (2017).

    PubMed  Google Scholar 

  3. de Groot, T., Puts, Y., Berrio, I., Chowdhary, A. & Meis, J. F. Development of Candida auris short tandem repeat typing and its application to a global collection of isolates. mBio 11, e02971-19 (2020).

    PubMed  PubMed Central  Google Scholar 

  4. Lockhart, S. R. et al. Simultaneous emergence of multidrug-resistant Candida auris on 3 continents confirmed by whole-genome sequencing and epidemiological analyses. Clin. Infect. Dis. 64, 134–140 (2017).

    CAS  PubMed  Google Scholar 

  5. Chow, N. A. et al. Potential fifth clade of Candida auris, Iran, 2018. Emerg. Infect. Dis. 25, 1780–1781 (2019).

    PubMed  PubMed Central  Google Scholar 

  6. Welsh, R. M., Sexton, D. J., Forsberg, K., Vallabhaneni, S. & Litvintseva, A. Insights into the unique nature of the East Asian clade of the emerging pathogenic yeast Candida auris. J. Clin. Microbiol. 57, e00007–19 (2019).

    PubMed  PubMed Central  Google Scholar 

  7. Szekely, A., Borman, A. M. & Johnson, E. M. Candida auris isolates of the Southern Asian and South African lineages exhibit different phenotypic and antifungal susceptibility profiles in vitro. J. Clin. Microbiol. 57, e02055-18 (2019).

    PubMed  PubMed Central  Google Scholar 

  8. Borman, A. M., Szekely, A. & Johnson, E. M. Comparative pathogenicity of United Kingdom isolates of the emerging pathogen Candida auris and other key pathogenic Candida species. mSphere 1, e00189-16 (2016).

    PubMed  PubMed Central  Google Scholar 

  9. Kathuria, S. et al. Multidrug-resistant Candida auris misidentified as Candida haemulonii: characterization by matrix-assisted laser desorption ionization-time of flight mass spectrometry and DNA sequencing and its antifungal susceptibility profile variability by vitek 2, CLSI broth microdilution, and Etest method. J. Clin. Microbiol. 53, 1823–1830 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Mizusawa, M. et al. Can multidrug-resistant Candida auris be reliably identified in clinical microbiology laboratories? J. Clin. Microbiol. 55, 638–640 (2017).

    PubMed  PubMed Central  Google Scholar 

  11. Ruiz-Gaitan, A. et al. An outbreak due to Candida auris with prolonged colonisation and candidaemia in a tertiary care European hospital. Mycoses 61, 498–505 (2018).

    CAS  PubMed  Google Scholar 

  12. Schelenz, S. et al. First hospital outbreak of the globally emerging Candida auris in a European hospital. Antimicrob. Resist. Infect. Control 5, 35 (2016).

    PubMed  PubMed Central  Google Scholar 

  13. Vallabhaneni, S. et al. Investigation of the first seven reported cases of Candida auris, a globally emerging invasive, multidrug-resistant fungus—United States, May 2013–August 2016. Am. J. Transplant. 17, 296–299 (2017).

    CAS  PubMed  Google Scholar 

  14. Lee, W. G. et al. First three reported cases of nosocomial fungemia caused by Candida auris. J. Clin. Microbiol. 49, 3139–3142 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Welsh, R. M. et al. Survival, persistence, and isolation of the emerging multidrug-resistant pathogenic yeast Candida auris on a plastic health care surface. J. Clin. Microbiol. 55, 2996–3005 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Rudramurthy, S. M. et al. Candida auris candidaemia in Indian ICUs: analysis of risk factors. J. Antimicrob. Chemother. 72, 1794–1801 (2017).

    CAS  PubMed  Google Scholar 

  17. Chowdhary, A., Sharma, C. & Meis, J. F. Candida auris: a rapidly emerging cause of hospital-acquired multidrug-resistant fungal infections globally. PLoS Pathog. 13, e1006290 (2017).

    PubMed  PubMed Central  Google Scholar 

  18. Al Maani, A. et al. Ongoing challenges with healthcare-associated Candida auris outbreaks in Oman. J. Fungi 5, 101 (2019).

    CAS  Google Scholar 

  19. Arendrup, M. C., Chowdhary, A., Astvad, K. M. T. & Jorgensen, K. M. APX001A in vitro activity against contemporary blood isolates and Candida auris determined by the EUCAST reference method. Antimicrob. Agents Chemother. 62, e01225-18 (2018).

    PubMed  PubMed Central  Google Scholar 

  20. Hager, C. L. et al. In vitro and in vivo evaluation of the antifungal activity of APX001A/APX001 against Candida auris. Antimicrob. Agents Chemother. 62, e02319-17 (2018).

    PubMed  PubMed Central  Google Scholar 

  21. Arendrup, M. C., Jorgensen, K. M., Hare, R. K. & Chowdhary, A. EUCAST in vitro activity of Ibrexafungerp (SCY-078) against C. auris isolates; comparison with activity against C. albicans and C. glabrata and with that of six comparators. Antimicrob. Agents Chemother. 64, e02136-19 (2019).

    Google Scholar 

  22. Berkow, E. L., Angulo, D. & Lockhart, S. R. In vitro activity of a novel glucan synthase inhibitor, SCY-078, against clinical isolates of Candida auris. Antimicrob. Agents Chemother. 61, e00435-17 (2017).

    PubMed  PubMed Central  Google Scholar 

  23. Larkin, E. et al. The emerging pathogen Candida auris: growth phenotype, virulence factors, activity of antifungals, and effect of SCY-078, a novel glucan synthesis inhibitor, on growth morphology and biofilm formation. Antimicrob. Agents Chemother. 61, e02396-16 (2017).

    PubMed  PubMed Central  Google Scholar 

  24. Hager, C. L., Larkin, E. L., Long, L. A. & Ghannoum, M. A. Evaluation of the efficacy of rezafungin, a novel echinocandin, in the treatment of disseminated Candida auris infection using an immunocompromised mouse model. J. Antimicrob. Chemother. 73, 2085–2088 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Lepak, A. J., Zhao, M. & Andes, D. R. Pharmacodynamic evaluation of rezafungin (CD101) against Candida auris in the neutropenic mouse invasive candidiasis model. Antimicrob. Agents Chemother. 62, e01572-18 (2018).

    PubMed  PubMed Central  Google Scholar 

  26. Richardson, J. P. & Moyes, D. L. Adaptive immune responses to Candida albicans infection. Virulence 6, 327–337 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Erwig, L. P. & Gow, N. A. Interactions of fungal pathogens with phagocytes. Nat. Rev. Microbiol. 14, 163–176 (2016).

    CAS  PubMed  Google Scholar 

  28. Gow, N. A., van de Veerdonk, F. L., Brown, A. J. & Netea, M. G. Candida albicans morphogenesis and host defence: discriminating invasion from colonization. Nat. Rev. Microbiol. 10, 112–122 (2011).

    PubMed  PubMed Central  Google Scholar 

  29. Pathirana, R. U. et al. Fluconazole-resistant Candida auris is susceptible to salivary histatin 5 killing and to intrinsic host defenses. Antimicrob. Agents Chemother. 62, e01872-17 (2018).

    PubMed  PubMed Central  Google Scholar 

  30. Johnson, C. J., Davis, J. M., Huttenlocher, A., Kernien, J. F. & Nett, J. E. Emerging fungal pathogen Candida auris evades neutrophil attack. mBio 9, e01403-18 (2018).

    PubMed  PubMed Central  Google Scholar 

  31. Navarro-Arias, M. J. et al. Differential recognition of Candida tropicalis, Candida guilliermondii, Candida krusei, and Candida auris by human innate immune cells. Infect. Drug Resist. 12, 783–794 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Munoz, J. F. et al. Genomic insights into multidrug-resistance, mating and virulence in Candida auris and related emerging species. Nat. Commun. 9, 5346 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Brown, G. D. et al. Hidden killers: human fungal infections. Sci. Transl. Med. 4, 165rv113 (2012).

    Google Scholar 

  34. Hall, R. A. & Gow, N. A. Mannosylation in Candida albicans: role in cell wall function and immune recognition. Mol. Microbiol. 90, 1147–1161 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Gow, N. A. et al. Immune recognition of Candida albicans β-glucan by dectin-1. J. Infect. Dis. 196, 1565–1571 (2007).

    CAS  PubMed  Google Scholar 

  36. Netea, M. G. et al. Immune sensing of Candida albicans requires cooperative recognition of mannans and glucans by lectin and Toll-like receptors. J. Clin. Invest. 116, 1642–1650 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Klebanoff, S. J. Myeloperoxidase: friend and foe. J. Leukoc. Biol. 77, 598–625 (2005).

    CAS  PubMed  Google Scholar 

  38. Kerrigan, A. M. & Brown, G. D. Syk-coupled C-type lectin receptors that mediate cellular activation via single tyrosine based activation motifs. Immunol. Rev. 234, 335–352 (2010).

    CAS  PubMed  Google Scholar 

  39. Gringhuis, S. I. et al. Dectin-1 directs T helper cell differentiation by controlling noncanonical NF-κB activation through Raf-1 and Syk. Nat. Immunol. 10, 203–213 (2009).

    CAS  PubMed  Google Scholar 

  40. Yan, L. et al. Unique cell surface mannan of yeast pathogen Candida auris with selective binding to IgG. ACS Infect. Dis. 6, 1018–1031 (2020).

    CAS  PubMed  Google Scholar 

  41. Marakalala, M. J. et al. Differential adaptation of Candida albicans in vivo modulates immune recognition by dectin-1. PLoS Pathog. 9, e1003315 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Keppler-Ross, S., Douglas, L., Konopka, J. B. & Dean, N. Recognition of yeast by murine macrophages requires mannan but not glucan. Eukaryot. Cell 9, 1776–1787 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. McKenzie, C. G. J. et al. Contribution of Candida albicans cell wall components to recognition by and escape from murine macrophages. Infect. Immun. 78, 1650–1658 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Tucey, T. M. et al. Glucose homeostasis is important for immune cell viability during Candida challenge and host survival of systemic fungal infection. Cell Metab. 27, 988–1006 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Fakhim, H. et al. Comparative virulence of Candida auris with Candida haemulonii, Candida glabrata and Candida albicans in a murine model. Mycoses 61, 377–382 (2018).

    PubMed  Google Scholar 

  46. Ben-Ami, R. et al. Multidrug-resistant Candida haemulonii and C. auris, Tel Aviv, Israel. Emerg. Infect. Dis. 23, 195–203 (2017).

    CAS  PubMed Central  Google Scholar 

  47. Urban, C. F. & Nett, J. E. Neutrophil extracellular traps in fungal infection. Semin. Cell Dev. Biol. 89, 47–57 (2019).

    CAS  PubMed  Google Scholar 

  48. Urban, C. F., Reichard, U., Brinkmann, V. & Zychlinsky, A. Neutrophil extracellular traps capture and kill Candida albicans yeast and hyphal forms. Cell Microbiol. 8, 668–676 (2006).

    CAS  PubMed  Google Scholar 

  49. Wiederhold, N. P. et al. Efficacy of delayed therapy with fosmanogepix (APX001) in a murine model of Candida auris invasive candidiasis. Antimicrob. Agents Chemother. 63, e01120-19 (2019).

    PubMed  PubMed Central  Google Scholar 

  50. Oosting, M. et al. Borrelia-induced cytokine production is mediated by spleen tyrosine kinase (Syk) but is dectin-1 and dectin-2 independent. Cytokine 76, 465–472 (2015).

    CAS  PubMed  Google Scholar 

  51. Gaus, H., Miller, C. M., Seth, P. P. & Harris, E. N. Structural determinants for the interactions of chemically modified nucleic acids with the stabilin-2 clearance receptor. Biochemistry 57, 2061–2064 (2018).

    CAS  PubMed  Google Scholar 

  52. Sherrington, S. L. et al. Adaptation of Candida albicans to environmental pH induces cell wall remodelling and enhances innate immune recognition. PLoS Pathog. 13, e1006403 (2017).

    PubMed  PubMed Central  Google Scholar 

  53. Kruppa, M., Greene, R. R., Noss, I., Lowman, D. W. & Williams, D. L. C. albicans increases cell wall mannoprotein, but not mannan, in response to blood, serum and cultivation at physiological temperature. Glycobiology 21, 1173–1180 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12 (2016).

    Google Scholar 

  55. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  PubMed  Google Scholar 

  56. Anders, S., Pyl, P. T. & Huber, W. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    CAS  PubMed  Google Scholar 

  57. Zhu, A., Ibrahim, J. G. & Love, M. I. Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Bioinformatics 35, 2084–2092 (2018).

    PubMed Central  Google Scholar 

  58. Kamburov, A., Wierling, C., Lehrach, H. & Herwig, R. ConsensusPathDB—a database for integrating human functional interaction networks. Nucleic Acids Res. 37, D623–D628 (2009).

    CAS  PubMed  Google Scholar 

  59. Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Fabregat, A. et al. The reactome pathway knowledgebase. Nucleic Acids Res. 46, D649–D655 (2018).

    CAS  PubMed  Google Scholar 

  61. Lowman, D. W. et al. Mannan structural complexity is decreased when Candida albicans is cultivated in blood or serum at physiological temperature. Carbohydr. Res. 346, 2752–2759 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Graus, M. S. et al. Mannan molecular substructures control nanoscale glucan exposure in Candida. Cell Rep. 24, e2435 (2018).

    Google Scholar 

  63. Smith, A. J. et al. Immunoregulatory activity of the natural product laminarin varies widely as a result of its physical properties. J. Immunol. 200, 788–799 (2018).

    CAS  PubMed  Google Scholar 

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Acknowledgements

We thank T. Jansen for performing the initial pilot experiments and I. Curfs-Breuker and D. Faro for their support at the CWZ hospital; C. Kaffa for her technical assistance; V. Kumar for his input during the transcriptomic data analysis; M. Gresnigt for in vitro experimental suggestions; and A. Becker for help during the revision experiments. A.J.P.B. and N.A.R.G. thank the Medical Research Council (MRC) (MR/M026663/1) and Wellcome for support and the MRC Centre for Medical Mycology at the University of Aberdeen (MR/N006364/1). A.H. and S.K. were supported by the Radboud Institute for Molecular Life Sciences. Part of the study was supported by the Hellenic Institute for the Study of Sepsis. D.L.W. was supported by National Institutes of Health grant nos NIH GM083016, GM119197 and C06RR0306551. M.G.N. was supported by an ERC Advanced Grant (no. 833247) and a Spinoza Grant from the Netherlands Organization for Scientific Research.

Author information

Author notes

  1. These authors contributed equally: Mariolina Bruno, Simone Kersten.

  2. These authors jointly supervised this work: Jacques F. Meis, David L. Williams, Mihai G. Netea.

Authors and Affiliations

  1. Department of Internal Medicine, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands

    Mariolina Bruno, Simone Kersten, Martin Jaeger, Diletta Rosati, Frank L. van de Veerdonk, Bart-Jan Kullberg, Alexander Hoischen & Mihai G. Netea

  2. Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands

    Simone Kersten & Alexander Hoischen

  3. Medical Research Council Centre for Medical Mycology, University of Aberdeen, Aberdeen, UK

    Judith M. Bain, Neil A. R. Gow & Alistair J. P. Brown

  4. Departments of Surgery, Biomedical Sciences and Center of Excellence in Inflammation, Infectious Disease and Immunity, Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA

    Michael D. Kruppa, Douglas W. Lowman, Bridget Graves, Zuchao Ma, Yue Ning Jiao & David L. Williams

  5. Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO, USA

    Peter J. Rice

  6. Department of Medical Mycology, Vallabhbhai Patel Chest Institute, University of Delhi, New Delhi, India

    Anuradha Chowdhary

  7. 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece

    George Renieris & Evangelos J. Giamarellos-Bourboulis

  8. Center of Expertise in Mycology, Radboud University Medical Center and Canisius Wilhelmina Hospital, Nijmegen, the Netherlands

    Frank L. van de Veerdonk, Bart-Jan Kullberg & Jacques F. Meis

  9. MRC Centre for Medical Mycology, University of Exeter, Exeter, UK

    Neil A. R. Gow & Alistair J. P. Brown

  10. Bioprocess Engineering and Biotechnology Graduate Program, Federal University of Paraná, Curitiba, Brazil

    Jacques F. Meis

  11. Department of Medical Microbiology and Infectious Diseases, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands

    Jacques F. Meis

  12. Department for Genomics & Immunoregulation, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany

    Mihai G. Netea

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  1. Mariolina Bruno
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  2. Simone Kersten
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Contributions

Conceptualization: J.F.M., D.L.W. and M.G.N.; methodology: M.B., S.K., J.M.B., M.J., D.R., M.D.K., D.W.L., Z.M., Y.N.J., A.C., A.H., N.A.R.G., A.J.P.B., J.F.M., D.L.W. and M.G.N.; investigation: M.B., S.K., J.M.B., M.J, D.R., D.W.L., P.J.R., B.G., F.L.v.d.V., B.-J.K., E.J.G.-B., G.R., A.H., N.A.R.G., A.J.P.B., D.L.W. and M.G.N.; writing the original draft: M.B., S.K. and M.G.N.; review and editing the manuscript: M.B., S.K., J.M.B., M.J., M.D.K., D.W.L., Z.M., Y.N.J., A.C., F.L.v.d.V., E.J.G.-B., A.H., N.A.R.G., A.J.P.B., J.F.M., D.L.W. and M.G.N.; supervision: M.J., F.L.v.d.V., A.H., N.A.R.G., A.J.P.B. and M.G.N.

Corresponding authors

Correspondence to Mariolina Bruno or Mihai G. Netea.

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Extended data

Extended Data Fig. 1 Transcriptomic profiling PBMCs stimulated with live C. albicans or C. auris and respective cell wall components β-glucans and mannans for 4 and 24 hours.

a, Principal component analysis (PCA) performed on normalized count data (normTransform, DESeq2) demonstrates the main component introducing variance in the dataset is time (40%), as indicated by a clear split between the early 4-hour host induced response (left, triangle) and the late 24-hour response (right, circle). To a lower extent (15%), the second component introducing variance appears to be inherent to the stimulus (color). b, At 4 h, PCA reveals a clear donor clustering (shape) irrespective of stimulus (color), indicating the main variance in the early host response reflects inter-individual differences (left). PCA on the late response, 24 h, is predominantly influenced by the respective stimulus (38%, color), and to a lower extent by the donors (19%, shape), indicated by the scattering of stimuli together with a rough clustering amongst donors. c, Pathway enrichment plot displaying the top 20 enriched pathways for both C. albicans live and C. auris live (color) at 24 h. Enrichment determined using Consensus PathDB, including pathways as defined by KEGG and Reactome (shape), considering a p-adjusted value < 0.01 (indicated as ‘q-value’) significant. Size of the geometric points indicates the amount of DEG in relation to the pathways’ size. The exact q values and the data used to make this figure can be found in Source Data Extended Data Fig. 1.

Source data

Extended Data Fig. 2 Comparative LDH secretion, LDH cytokine gene expression and phagocytosis dynamics between C. albicans and C. auris.

a, Assessment of Candida induced cell death of PBMCs after 24 h stimulation without (RPMI; negative control) or with C. albicans, several C. auris strains originating from all five geographical clades or a positive control (dead cells). Lactate dehydrogenase (LDH) was detected as measure of cell death (Mean ± SEM, n = 6, pooled from two independent experiments). b, Log2Fold Change (Log2FC) of IL-6, IL-1β, and IL-1RN (encoding for IL-1Ra) gene expression in PBMCs from 3 donors stimulated for 24 h with C. albicans (1006110) and C. auris (KCTC17810, clade II) and their respective cell wall components, β-glucans (left) and mannans (right). Graphs represent Log2FC from DEG analysis. * p < 0.05, ** p < 0.01, *** p < 0.001, 1-way ANOVA with correction for multiple comparison. c, The BMDM phagocytic capacity of Thimerosal-fixed C. albicans or C. auris strains in the course of 3-hours. BMDM engulfment depicted as the percentage of macrophages having phagocytosed at least one fungal cell (left), and the phagocytic index, here considered as the number of fungal cells engulfed per 100 macrophages (right); graphs represent mean, n = 9, pooled from at least two independent experiments. d, BMDM phagocytic capacity of Thimerosal-fixed C. albicans or C. auris strains after 1 h. Engulfment is depicted as the percentage of macrophages having phagocytosed at least one fungal cell; graphs represent mean ± SEM, n = 9, pooled from at least two independent experiments. e, BMDM phagocytic capacity of live C. albicans or C. auris strains after 1 h. Engulfment is depicted as the percentage of macrophages having phagocytosed at least one fungal cell. Graphs represent mean ± SEM, n = 9 (n = 7 for C. auris 10051893), pooled from at least two independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, d 1-way ANOVA with a Holm-Sidak’s multiple comparison test, e Kruskal Wallis test with two-sided Dunn’s multiple comparison. f, Distribution of phagocytosed Thimerosal-fixed fungal cells per macrophage in a 3-hour period, n ≥ 100 observations per condition. Data used to make this figure can be found in Source Data Extended Data Fig. 2.

Source data

Extended Data Fig. 3 Relative C. auris induced ROS production and heat-sensitivity of the cell wall components responsible for the C. auris induced cytokine production.

a, Neutrophil ROS release after 1-hour stimulation without (RPMI; negative control) or with heat-killed C. albicans, C. auris strains or zymosan (positive control), depicted in relative light units (RLU) either as time-course (left) or as area under the curve (AUC, right), n = 9. b, PBMC ROS release after 1-hour stimulation without (RPMI; negative control) or with heat-killed C. albicans, C. auris strains or zymosan (positive control), depicted in RLU either as time-course (left) or as AUC (right), n = 6. c, TNF-α, IL-6, IL-1β, and IL-1Ra levels in the supernatant of PBMCs after stimulation without (RPMI; negative control) or with heat-killed C. albicans and C. auris from all five geographical clades for 24 h, n = 8. d, PBMC production of cytokines IFN-γ (n = 10; n = 7 for C. auris 10051895), IL-10 (n = 6), IL-17 (n = 6), and IL-22 (n = 14; n = 6 for C. auris 10051893; n = 11 for C. auris 10051895) after stimulation without (RPMI; negative control) or with heat-killed C. albicans and C. auris for 7 days. Graphs represent mean ± SEM, data are pooled from at least two independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p = 0.001, a, b Time curves (left panels) were assessed for statistical differences between C. auris strains and C. albicans by a two-way ANOVA, Area Under curve (AUC) means (right panels) were compared using the two-sided Wilcoxon signed rank test, c, d two-sided Wilcoxon matched pairs signed-rank test comparing respective C. auris strains with C. albicans as control or reference species. Data used to make this figure can be found in Source Data Extended Data Fig. 3.

Source data

Extended Data Fig. 4 Transcriptional changes induced by purified cell wall components and their respective exposure on C. albicans and C. auris surface.

a, Heatmap displaying the Log2Fold change (color scale) of the top 50 DEG of C. albicans live, for both Candida species and their cell wall components, β-glucan and mannan, at 4 h (left panel) and 24 h (right panel). b, Flow cytometry plot based on forward scatter component (FSC) and side scatter component (SSC), demonstrating C. auris strains are slightly smaller and of higher complexity than C. albicans. c, Flow cytometry-based comparison of cell wall components of C. albicans and C. auris strains. Mean fluorescent intensity (MFI) of thimerosal-fixed Candida cells stained for Fc-Dectin-1, a marker for β-glucan (left), and ConA, a marker for mannans (right). Graphs represent mean ± SEM of the 3 means, each performed with three replicates in three independent measurements, * p < 0.05, Kruskall Wallis test with two-sided Dunn’s multiple comparison test was performed comparing the respective C. auris strains with the two C. albicans reference strains. Data used to make this figure can be found in Source Data Extended Data Fig. 4.

Source data

Extended Data Fig. 5 Evaluation of cytokine production upon C. albicans and C. auris mannan stimulation.

a, PBMC production of cytokines TNF-α, IL-6, IL-1β, and IL-1Ra after 24 h stimulation without (RPMI; negative control) or with purified mannans from C. albicans and C. auris strains in the presence of 10% heat-inactivated human serum, n = 7. b, PBMC production of cytokines IFN-γ (n = 6), IL-17 (n = 9), and IL-22 (n = 9) after 7 days hours stimulation without (RPMI; negative control) or with purified mannans from C. albicans and C. auris strains in the presence of 10% human serum. Graphs represent mean ± SEM, data pooled from at least two independent experiments. * p < 0.05, two-sided Wilcoxon matched pairs signed-rank test, comparing respective C. auris strains with C. albicans as control or reference species. Data used to make this figure can be found in Source Data Extended Data Fig. 5.

Source data

Extended Data Fig. 6 Cytokine levels in plasma and organ homogenates from C.albicans and C. auris-infected mice.

a, IL-6 production in plasma and supernatants from liver homogenates. b, IFN-γ production in supernatants from kidney and spleen homogenates. c–e, IL-1β (c), IL-17 (d), and IL-10 (e) production in plasma and supernatants from liver, kidney, and spleen homogenates. Mice have been infected i.v. with 1×106 c.f.u. of C. albicans or C. auris. Graphs represent mean ± SEM, n = 6 per group per time-point pooled from two independent experiments. Data used to make this figure can be found in Source Data Extended Data Fig. 6.

Source data

Extended Data Fig. 7 Applied gating strategies across flow cytometry experiments.

a, Gating strategy for FITC-labelled Candida in PBMCs (linked to Fig. 2b). All events were plotted based on forward scatter (FS) and side scatter (SS) characteristics. In the upper plot (2.1) the region of cells positive for FITC-Candida was highlighted (green gate) while in the bottom plot (2.2) CD14 positive cells are represented (red gate) gated within the total PBMCs population (1). Within the CD14 + cells selection, the amount of phagocytosed FITC positive Candida was examined by plotting (3) the FITC signal against the CD14-PB450 signal (blue gate) and the percentage of cells and mean fluorescent intensity (MFI) were used for analysis. b, Gating strategy for Thimerosal-fixed Candida cells stained for either β-glucan using Fc-Dectin-1 or ConA as marker for mannans (Extended Data Fig. 4c).

Supplementary information

Supplementary Information

Supplementary Tables 1–8.

Reporting Summary

Supplementary Video 1

C. auris is able to multiply within phagosomes.

Supplementary Video 2

C. auris accumulates in high numbers within macrophages and does not induce macrophage lysis.

Supplementary Video 3

C. auriscells are taken up extensively into a subpopulation of macrophages.

Supplementary Video 4

Phagocytosis of C. albicans SC5314 and macrophage lysis after 3 h.

Source data

Source Data Fig. 1

Supporting data for Fig. 1.

Source Data Fig. 2

Supporting data for Fig. 2.

Source Data Fig. 3

Supporting data for Fig. 3.

Source Data Fig. 5

Supporting data for Fig. 5.

Source Data Fig. 6

Supporting data for Fig. 6.

Source Data Extended Data Fig. 1

Supporting data for Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Supporting data for Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Supporting data for Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Supporting data for Extended Data Fig. 4.

Source Data Extended Data Fig. 5

Supporting data for Extended Data Fig. 5.

Source Data Extended Data Fig. 6

Supporting data for Extended Data Fig. 6.

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Bruno, M., Kersten, S., Bain, J.M. et al. Transcriptional and functional insights into the host immune response against the emerging fungal pathogen Candida auris. Nat Microbiol 5, 1516–1531 (2020). https://doi.org/10.1038/s41564-020-0780-3

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