The cAMP/Protein Kinase A Pathway Regulates Virulence and Adaptation to Host Conditions in Cryptococcus neoformans
Bibliographic record
Abstract
Nutrient sensing is critical for adaptation of fungi to environmental and host conditions. The conserved cAMP/PKA signalling pathway contributes to adaptation by sensing the availability of key nutrients such as glucose and directing changes in gene expression and metabolism. Interestingly, the cAMP/PKA pathway in fungal pathogens also influences the expression of virulence determinants in response to nutritional and host signals. For instance, protein kinase A (PKA) in the human pathogen Cryptococcus neoformans plays a central role in orchestrating phenotypic changes, such as capsule elaboration and melanin production, that directly impact disease development. In this review, we focus first on insights into the role of the cAMP/PKA pathway in nutrient sensing for the model yeast Saccharomyces cerevisiae to provide a foundation for understanding the pathway in C. neoformans. We then discuss key features of cAMP/PKA signaling in C. neoformans including new insights emerging from the analysis of transcriptional and proteomic changes in strains with altered PKA activity and expression. Finally, we highlight recent studies that connect the cAMP/PKA pathway to cell surface remodelling and the formation of titan cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".