Tuning Hsf1 levels drives distinct fungal morphogenetic programs with depletion impairing Hsp90 function and overexpression expanding the target space
Bibliographic record
Abstract
The capacity to respond to temperature fluctuations is critical for microorganisms to survive within mammalian hosts, and temperature modulates virulence traits of diverse pathogens. One key temperature-dependent virulence trait of the fungal pathogen Candida albicans is its ability to transition from yeast to filamentous growth, which is induced by environmental cues at host physiological temperature. A key regulator of temperature-dependent morphogenesis is the molecular chaperone Hsp90, which has complex functional relationships with the transcription factor Hsf1. Although Hsf1 controls global transcriptional remodeling in response to heat shock, its impact on morphogenesis remains unknown. Here, we establish an intriguing paradigm whereby overexpression or depletion of C. albicans HSF1 induces morphogenesis in the absence of external cues. HSF1 depletion compromises Hsp90 function, thereby driving filamentation. HSF1 overexpression does not impact Hsp90 function, but rather induces a dose-dependent expansion of Hsf1 direct targets that drives overexpression of positive regulators of filamentation, including Brg1 and Ume6, thereby bypassing the requirement for elevated temperature during morphogenesis. This work provides new insight into Hsf1-mediated environmentally contingent transcriptional control, implicates Hsf1 in regulation of a key virulence trait, and highlights fascinating biology whereby either overexpression or depletion of a single cellular regulator induces a profound developmental transition.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".