2024 mSphere

An approach to analyze spatiotemporal patterns of gene expression at single-cell resolution in Candida albicans-infected mouse tongues.

, ,

mSphere Vol. 9 (9) : e0028224 • Sep 2024

Microbial gene expression measurements derived from infected organs are invaluable to understand pathogenesis. However, current methods are limited to "bulk" analyses that neglect microbial cell heterogeneity and the lesion's spatial architecture. Here, we report the use of hybridization chain reaction RNA fluorescence in situ hybridization (HCR RNA-FISH) to visualize and quantify Candida albicans transcripts at single-cell resolution in tongues of infected mice. The method is compatible with fixed-frozen and formalin-fixed paraffin-embedded tissues. We document cell-to-cell variation and intriguing spatiotemporal expression patterns for C. albicans mRNAs that encode products implicated in oral candidiasis. The approach provides a spatial dimension to gene expression analyses of host-Candida interactions. IMPORTANCE: Candida albicans is a fungal pathobiont inhabiting multiple mucosal surfaces of the human body. Immunosuppression, antibiotic-induced microbial dysbiosis, or implanted medical devices can impair mucosal integrity enabling C. albicans to overgrow and disseminate, causing either mucosal diseases such as oropharyngeal candidiasis or life-threatening systemic infections. Profiling fungal genes that are expressed in the infected mucosa or in any other infected organ is paramount to understand pathogenesis. Ideally, these transcript profiling measurements should reveal the expression of any gene at the single-cell level. The resolution typically achieved with current approaches, however, limits most gene expression measurements to cell population averages. The approach described in this report provides a means to dissect fungal gene expression in infected tissues at single-cell resolution.

No clinical trial protocols linked to this paper

Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.
PICO Elements

No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.

Paper Details
MeSH Terms
Associated Data

No associated datasets or code repositories found for this paper.

Related Papers

Related paper suggestions will be available in future updates.