Back

Spores of the fungal pathogen Cryptococcus exhibit cell type-specific carbon source utilization during germination

Ortiz, S. C.; McKeon, M. C.; Botts, M. R.; Gage, H.; Frerichs, A.; Hull, C. M.

2023-10-01 microbiology
10.1101/2023.10.01.560341 bioRxiv
Show abstract

Spores are critical morphotypes required for long-term survival of most fungi. Under the right environmental conditions, spores can escape dormancy and differentiate into vegetatively growing cells through the process of germination. For fatal human fungal pathogens like Cryptococcus, germination is the key differentiation process required for spores to initiate vegetative growth and ultimately cause disease; however, relatively little is known about the molecular mechanisms that control germination. To this end, we performed an extensive characterization of Cryptococcus spore germination through the morphological assessment of germinating spores, the inhibition of key eukaryotic processes, and the detailed quantification of fungal spore germination kinetics under numerous nutrient conditions. We identified temporal associations between molecular and morphological events and determined that carbon metabolism pathways (both glycolysis and oxidative phosphorylation) were required from the beginning of germination. We further determined that carbon sources are primarily used as fuel rather than as simply triggers of germination commitment, and identified spore-specific carbon source utilization that is absent in yeast. Finally, we discovered the first spore-specific enzyme, Nth2, a trehalase that is required for germination when trehalose is the primary available carbon source. Together this work provides an extensive characterization of Cryptococcus spore germination and suggests that germination is more than simply a modified cell cycle but is rather a highly adapted differentiation process.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.