Msn2- and Msn4-Like Transcription Factors Play No Obvious Roles in the Stress Responses of the Fungal Pathogen <i>Candida albicans</i>
Bibliographic record
Abstract
In Saccharomyces cerevisiae, the (C2H2)2 zinc finger transcription factors Msn2 and Msn4 play central roles in responses to a range of stresses by activating gene transcription via the stress response element (STRE; CCCCT). The pathogen Candida albicans displays stress responses that are thought to help it survive adverse environmental conditions encountered within its human host. However, these responses differ from those in S. cerevisiae, and hence we predicted that the roles of Msn2- and Msn4-like proteins might have been functionally reassigned in C. albicans. C. albicans has two such proteins: CaMsn4 and Mnl1 (for Msn2- and Msn4-like). CaMSN4, but not MNL1, weakly complemented the inability of an S. cerevisiae msn2 msn4 mutant to activate a STRE-lacZ reporter. Also, the disruption of CaMsn4 and Mnl1 had no discernible effect upon the resistance of C. albicans to heat, osmotic, ethanol, nutrient, oxidative, or heavy-metal stress or upon the stress-activated transcriptome in C. albicans. Furthermore, although Cap1-dependent activation of a Yap response element-luciferase reporter was observed, a STRE reporter was not activated in response to stresses in C. albicans. Ectopic expression of CaMsn4 or Mnl1 did not affect the cellular or molecular responses of C. albicans to stress. Under the conditions tested, the putative activation and DNA binding domains of CaMsn4 did not appear to be functional. These data suggest that CaMsn4 and Mnl1 do not contribute significantly to stress responses in C. albicans. The data are consistent with the idea that stress signaling in this fungus has diverged significantly from that in budding yeast.
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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) | 0.001 | 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".