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Candida pathogens induce protective mitochondria-associated type I interferon signalling and a damage-driven response in vaginal epithelial cells

Nature Microbiology volume 6, pages 643–657 (2021)Cite this article

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Abstract

Vaginal candidiasis is an extremely common disease predominantly caused by four phylogenetically diverse species: Candida albicans; Candida glabrata; Candida parapsilosis; and Candida tropicalis. Using a time course infection model of vaginal epithelial cells and dual RNA sequencing, we show that these species exhibit distinct pathogenicity patterns, which are defined by highly species-specific transcriptional profiles during infection of vaginal epithelial cells. In contrast, host cells exhibit a homogeneous response to all species at the early stages of infection, which is characterized by sublethal mitochondrial signalling inducing a protective type I interferon response. At the later stages, the transcriptional response of the host diverges in a species-dependent manner. This divergence is primarily driven by the extent of epithelial damage elicited by species-specific mechanisms, such as secretion of the toxin candidalysin by C. albicans. Our results uncover a dynamic, biphasic response of vaginal epithelial cells to Candida species, which is characterized by protective mitochondria-associated type I interferon signalling and a species-specific damage-driven response.

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Fig. 1: Pathogenicity patterns of four Candida species in the in vitro vaginal epithelial infection model.
Fig. 2: Dynamics of transcriptomic changes of the four Candida species investigated in this study at different time points.
Fig. 3: Transcriptome dynamics of vaginal epithelial cells on exposure to four Candida species.
Fig. 4: Candida species induce mitochondrial responses in vaginal epithelial cells.
Fig. 5: Role of mtDNA in the induction of type I IFN in vaginal epithelial cells.
Fig. 6: Type-I IFN signalling increases epithelial resistance and suppresses innate immune activation.

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Data availability

The data supporting the findings of this study are available within the paper and its Supplementary Information. All relevant data, including further image and processed data are available by request from the corresponding authors, with the restriction of data that would compromise the confidentiality of blood donors. Raw sequencing data have been deposited in the Sequence Read Archive under accession nos. SRR10279972–SRR10280067. Mapped data from the four Candida species can be mined and browsed at Candidamine (http://candidamine.org/candidamine/begin.do); the gene read counts from all samples can be found in our GitHub page https://github.com/Gabaldonlab/Host-pathogen_interactions along with the data analysis scripts for results reproducibility. Publicly available datasets/databases used in the study can be accessed at: Ensembl (https://www.ensembl.org/index.html); RefSeq (https://www.ncbi.nlm.nih.gov/refseq/); CGOB (http://cgob.ucd.ie/); NCBI FTP site (https://www.ncbi.nlm.nih.gov/home/download/); CGD (http://www.candidagenome.org/); and Genome wide annotation for Human (https://bioconductor.org/packages/release/data/annotation/html/org.Hs.eg.db.html). Source data are provided with this paper.

Code availability

All transcriptome data analysis results, including figures, extended data and supplementary materials are fully reproducible using the scripts provided at our GitHub page https://github.com/Gabaldonlab/Host-pathogen_interactions.

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Acknowledgements

M.P., H.H., E.I., J.O.P., T.G., G.B. and B.H. received funding from the European Union Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant no. 642095 (OPATHY). B.H. also received support from the German Research Foundation within the Collaborative Research Centre/Transregio 124 FungiNet (project C1). M.S.G. was supported by the German Research Foundation Emmy Noether Programme (project no. 434385622/GR 5617/1-1). We acknowledge the support of the Spanish Ministry of Science, Innovation and Universities (grant no. PGC2018-099921-B-I00) to the European Molecular Biology Laboratory partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme/Generalitat de Catalunya. We thank C. Kämnitz from the Electron Microscopy Center in Jena for the sample preparation for TEM. The schematic models in Figs. 4–6 were created with images adapted from Servier Medical Art (Servier).

Author information

Author notes

  1. Hrant Hovhannisyan & Toni Gabaldón

    Present address: Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain

  2. Hrant Hovhannisyan & Toni Gabaldón

    Present address: Mechanisms of Disease Department, Institute for Research in Biomedicine, Barcelona, Spain

  3. These authors contributed equally: Marina Pekmezovic, Hrant Hovhannisyan.

  4. These authors jointly supervised this work: Toni Gabaldón, Bernhard Hube.

Authors and Affiliations

  1. Department of Microbial Pathogenicity Mechanisms, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knoell Institute, Jena, Germany

    Marina Pekmezovic, Sofía Siscar-Lewin, Till Kalkreuter, Selene Mogavero, Sascha Brunke & Bernhard Hube

  2. Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain

    Hrant Hovhannisyan & Toni Gabaldón

  3. Universitat Pompeu Fabra, Barcelona, Spain

    Hrant Hovhannisyan & Toni Gabaldón

  4. Junior Research Group Adaptive Pathogenicity Strategies, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knoell Institute, Jena, Germany

    Mark S. Gresnigt

  5. School of Biomedical and Biomolecular Science and UCD Conway Institute of Biomolecular and Biomedical Research, Conway Institute, University College Dublin, Dublin, Ireland

    Elise Iracane, João Oliveira-Pacheco & Geraldine Butler

  6. Institute for Biochemistry I, Jena University Hospital-Friedrich Schiller University, Jena, Germany

    Eric Seemann & Britta Qualmann

  7. Institute of Immunology, Universitätsklinikum Jena, Jena, Germany

    Sylvia Müller & Thomas Kamradt

  8. Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain

    Toni Gabaldón

  9. Institute of Microbiology, Friedrich Schiller University, Jena, Germany

    Bernhard Hube

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Contributions

M.P. performed all the laboratory experiments (except for TEM), analysed the data, wrote the manuscript and prepared the figures. H.H. performed all the bioinformatics analyses, wrote the manuscript and prepared the figures. E.I. and J.O.P. performed the infection experiments for RNA-seq and edited the manuscript. S.S.L. performed the growth curve and flow cytometry experiments and helped with the mtDNA depletion set-up, including the data analysis. T. Kalkreuter performed additional RT–qPCR experiments. S. Müller and T. Kamradt contributed to the additional mitochondrial phenotypic assays and data interpretation. E.S. and B.Q. performed the TEM experiments, analysed the data and edited the manuscript. M.S.G., S. Mogavero, S.B. and G.B. designed the experiments and edited the manuscript. B.H. and T.G. conceived and designed the study and wrote the manuscript.

Corresponding authors

Correspondence to Toni Gabaldón or Bernhard Hube.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Microbiology thanks Elaine Bignell, Robert Watson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Overall experimental design of the current study.

a, Schematic representation of the experimental design. Each Candida species was co-cultivated with host cells. Controls included samples at 0 and 24 h for both host and yeasts alone. At the indicated time points of infection, fungal and host RNAs were independently extracted and subsequently combined (pooled) at a 2:3 fungus-to-host ratio into one sample for library preparation and sequencing. Sequencing data were mapped to a concatenated host and fungal reference genome. b, Schematic representation of the entire study including all samples. Each symbol corresponds to a sequenced sample (or technical replicates of the same sample). Host samples are depicted with circles; Candida samples are depicted with squares; the strategy for combining (pooling) human and fungal RNAs in the same sequencing library is shown with ovals surrounding the corresponding samples; technical replicates (that is the same sequencing library sequenced several times) are surrounded with dashed rectangles. Control samples are depicted in yellow; interacting host and fungal samples are depicted in blue; host samples interacting with non-viable fungal cells are depicted in purple. Each row indicates the samples for each human-yeast interaction experiment.

Extended Data Fig. 2 Distinct patterns of transcriptome profiles of the four Candida species upon interaction with human epithelial cells.

a, Distribution of fully shared, partially shared and species-specific differentially expressed (DE) genes across the course of infections. Numbers on bar plots indicate the percentage (%). b, Venn diagrams of DE genes (only 1-to-1 orthologs) in four Candida species at each time point. c, PCA biplot based on expression levels of orthologous genes across Candida species, demonstrating a species-specific stratification of transcriptomic profiles of the four fungal pathogens; Labels of the data points correspond to sample identifiers, where ‘reseq’ indicates that the sample was sequenced more than once (see Supplementary Table 1 for details).

Extended Data Fig. 3 Comparison of orthologous gene content similarities between co-expressed gene modules in different yeast species.

a, Comparison of C. albicans modules against modules of other species. b, Comparison of C. glabrata modules against modules of other species. c Comparison of C. parapsilosis modules against modules of other species. d, Comparison of C. tropicalis modules against modules of other species. Each box represents a module of a given species (reference module); the title of a box represents the reference module name. Each reference module is compared with all modules of other three species, and the modules of other species with the highest similarity to the reference module are plotted with horizontal bars, representing level of similarity (in %). Labels of the horizontal bars indicate <species name > _<module name > . ‘calb’ denotes C. albicans, ‘cglab’ - C. glabrata, ‘cpar’ - C. parapsilosis, ‘ctrop’ - C. tropicalis. The level of similarity refers to the fraction (in %) of shared one-to-one orthologous genes between two given modules, defined as the intersection of gene lists of orthologs of two modules divided by the union of these gene lists.

Extended Data Fig. 4 Infection-specific differentially expressed (DE) genes of Candida species.

a, Venn diagrams indicating similarities and differences of fungal DE* genes in culture medium only (control) and in response to epithelial cells (infection). *To identify infection-specific genes with a higher stringency, we applied filters of |log2 fold change | >0 and padj < 0.01. For the downstream analysis of identified genes, we used a filtering of |log2 fold change | > 1.5 and padj < 0.01 for consistency with other results. Differential expression analysis was done using DESeq2 v. 1.26.0 and comparisons against time point 0 were done using the two-sided Wald test. b, Distribution of infection-specific fungal genes across the studied Candida pathogens. Bar plots demonstrate the distribution of partially shared, fully shared, and species-specific genes. Numbers on bar plots indicate the percentage (%). Venn diagrams depict numbers of fully shared genes (1-to-1 orthologs) across species.

Extended Data Fig. 5 Candida species induce type I interferon signalling independently of apoptosis.

The proportion of healthy, necrotic, and apoptotic vaginal epithelial cells (ECs) 3 and 24 hours post-infection (hpi) with Candida in (a) A431 vaginal ECs used throughout this study and (b) primary vaginal ECs. Treatment with 1.2 µM staurosporine was used as a positive control. c, Mitochondrial membrane potential change of primary vaginal ECs at 1 hpi, positive control CCCP 100 μM. d, Relative expression (RT-qPCR) of selected Interferon-Stimulated Genes (ISGs) in C. albicans-infected ECs where apoptosis was induced with 1.2 µM staurosporine at 3 hpi. All values are presented as mean ± SD of n = 3 independent experiments. Statistical significance is indicated as: *, p ≤ 0.05; ***, p ≤ 0.001; ***, p ≤ 0.0001 (one-way ANOVA with Dunnett’s multiple comparisons test (c-d).; ‘calb’ denotes C. albicans, ‘cglab’ - C. glabrata, ‘cpar’ - C. parapsilosis, ‘ctrop’ - C. tropicalis.

Source data

Extended Data Fig. 6 Human transcriptome profiles response to fungal damage.

a, Levels of LDH release by epithelial cells upon the damage by four fungal pathogens 24 hpi. All values are presented as mean ± SD of n = 3 independent experiments. b, PCA plot of human samples interacting with non-viable and viable fungal species, including C. albicans ece1Δ/Δ. The plot is obtained using the RUVg function of RUVseq with k = 1 (see Extended Data Fig. 7 for plots with alternative k values). Labels of the data points correspond to sample identifiers, where ‘reseq’ indicates that the sample was sequenced more than once (see Supplementary Table 1 for details). ‘non-viable’ indicates host samples interacting with non-viable fungal cells; ‘ece1Δ/Δ’ indicates host samples interacting with C. albicans ece1Δ/Δ.

Source data

Extended Data Fig. 7 Human transcriptome response assessed with different parameters of batch effect correction.

PCA plots of human samples interacting with fungal cells obtained using k = 0, 1, 2, 3 values of RUVseq package for batch effect correction. Labels of the data points correspond to sample identifiers, where ‘reseq’ indicates that the sample was sequenced more than once (see Supplementary Table 1 for details). ‘non-viable’ indicates host samples interacting with non-viable fungal cells; ‘ece1Δ/Δ’ indicates host samples interacting with C. albicans ece1Δ/Δ.

Extended Data Fig. 8 Applied gating strategies across flow cytometry experiments for epithelial cells.

a, A431 cells (linked to Fig. 4e) and (b) primary vaginal cells (linked to Extended Data Fig. 6c). First, 104 events were analyzed based on their side scatter area (SSC-A) vs. forward scatter area (FSC-A). For further analysis, single cells were selected based on forward scatter height (FSC-H) vs. forward scatter area (FSC-A). MitoTracker® Deep Red FM signal was measured using detection channel Alexa 647-A. The unstained population was taken as a reference to determine the median fluoresce intensity of all samples (depicted as histogram Alexa 647-A- and Alexa 647-A+). The ratio from the median intensity of the stained/uninfected cells and unstained/uninfected cells was used as a reference to obtain the results of the infected samples shown in the manuscript figures.

Supplementary information

Reporting Summary

Peer Review File

Supplementary Tables

Supplementary Table 1. Study design, general information, sequencing and read mapping statistics of all analysed samples. Supplementary Table 2. Primers used in this study.

Supplementary Files 1–4

Supplementary File 1. Output of Crossmapper software for C. albicans and the host. Supplementary File 2. Output of Crossmapper software for C. glabrata and the host. Supplementary File 3. Output of Crossmapper software for C. parapsilosis and the host. Supplementary File 4. Output of Crossmapper software for C. tropicalis and the host.

Supplementary File 5

Differential gene expression analysis of C. albicans and the host.

Supplementary File 6

Differential gene expression analysis of C. glabrata and the host.

Supplementary File 7

Differential gene expression analysis of C. parapsilosis and the host.

Supplementary File 8

Differential gene expression analysis of C. tropicalis and the host.

Supplementary File 9

Gene Ontology enrichment analysis for all the data.

Supplementary File 10

Information on coexpressed modules between the host and the studied Candida species.

Source data

Source Data Fig. 1

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Source Data Extended Data Fig. 5

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Source Data Extended Data Fig. 6

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Pekmezovic, M., Hovhannisyan, H., Gresnigt, M.S. et al. Candida pathogens induce protective mitochondria-associated type I interferon signalling and a damage-driven response in vaginal epithelial cells. Nat Microbiol 6, 643–657 (2021). https://doi.org/10.1038/s41564-021-00875-2

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