Transcriptional Regulation by Protein Kinase A in Cryptococcus neoformans
Bibliographic record
Abstract
A defect in the PKA1 gene encoding the catalytic subunit of cyclic adenosine 5'-monophosphate (cAMP)-dependent protein kinase A (PKA) is known to reduce capsule size and attenuate virulence in the fungal pathogen Cryptococcus neoformans. Conversely, loss of the PKA regulatory subunit encoded by pkr1 results in overproduction of capsule and hypervirulence. We compared the transcriptomes between the pka1 and pkr1 mutants and a wild-type strain, and found that PKA influences transcript levels for genes involved in cell wall synthesis, transport functions such as iron uptake, the tricarboxylic acid cycle, and glycolysis. Among the myriad of transcriptional changes in the mutants, we also identified differential expression of ribosomal protein genes, genes encoding stress and chaperone functions, and genes for secretory pathway components and phospholipid synthesis. The transcriptional influence of PKA on these functions was reminiscent of the linkage between transcription, endoplasmic reticulum stress, and the unfolded protein response in Saccharomyces cerevisiae. Functional analyses confirmed that the PKA mutants have a differential response to temperature stress, caffeine, and lithium, and that secretion inhibitors block capsule production. Importantly, we also found that lithium treatment limits capsule size, thus reinforcing potential connections between this virulence trait and inositol and phospholipid metabolism. In addition, deletion of a PKA-regulated gene, OVA1, revealed an epistatic relationship with pka1 in the control of capsule size and melanin formation. OVA1 encodes a putative phosphatidylethanolamine-binding protein that appears to negatively influence capsule production and melanin accumulation. Overall, these findings support a role for PKA in regulating the delivery of virulence factors such as the capsular polysaccharide to the cell surface and serve to highlight the importance of secretion and phospholipid metabolism as potential targets for anti-cryptococcal therapy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".