Single nucleotide polymorphisms are associated with strain-specific virulence differences among clinical isolates of Cryptococcus neoformans

Katrina M. Jackson, Thomas J.Y. Kono, Jovany J. Betancourt, Yina Wang, Kisakye D. Kabbale, Minna Ding, Perry Kezh, Grace Ha, J. Marina Yoder, Sophie R. Fulton, Liliane Mukaremera, Peter Tiffin, Asiya Gusa, David B. Meya, R. Blake Billmyre, Chaoyang Xue, Kirsten Nielsen

Research output: Contribution to journalArticlepeer-review

Abstract

Studies across various pathogens highlight the importance of pathogen genetic differences in disease manifestation. In the human fungal pathogen Cryptococcus neoformans, sequence type (ST) associates with patient outcome. We performed a meta-analysis of four genomic studies and identified overlapping gene regions associated with virulence, suggesting the importance of these gene regions in cryptococcal disease in diverse clinical isolates. We explored the relationship between virulence and strain genetic differences using the cryptococcosis mouse model and a closely related library of ST93 clinical isolates. We identified four in vivo virulence phenotypes: hypervirulence, typical virulence with CNS disease, typical virulence with non-CNS disease, and latent disease. Hypervirulent isolates were clade specific and associated with an interferon gamma (IFNγ) dominated immune response. Using a genome wide association study (GWAS), we identified nine genes with polymorphisms associated with IFNγ production, including the inositol sensor ITR4. The itr4Δ mutant recapitulated the hypervirulence phenotype and ITR4 affects expression of two IFNγ associated genes. Finally, we showed that IFNγ production is associated with SNPs that downregulate ITR4 and with SNP accumulation in other IFNγ associated genes. These data highlight the complex role of pathogen genetics in virulence and identify genes associated with hypervirulence and IFNγ in Cryptococcus neoformans.

Original languageEnglish (US)
Article number10491
JournalNature communications
Volume15
Issue number1
DOIs
StatePublished - Dec 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

PubMed: MeSH publication types

  • Journal Article
  • Meta-Analysis

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