Regulation of the heat shock transcription factor Hsf1 in fungi: implications for temperature-dependent virulence traits
Bibliographic record
Abstract
The impact of fungal pathogens on human health is devastating. For fungi and other pathogens, a key determinant of virulence is the capacity to thrive at host temperatures, with elevated temperature in the form of fever as a ubiquitous host response to defend against infection. A prominent feature of cells experiencing heat stress is the increased expression of heat shock proteins (Hsps) that play pivotal roles in the refolding of misfolded proteins in order to restore cellular homeostasis. Transcriptional activation of this heat shock response is orchestrated by the essential heat shock transcription factor, Hsf1. Although the influence of Hsf1 on cellular stress responses has been studied for decades, many aspects of its regulation and function remain largely enigmatic. In this review, we highlight our current understanding of how Hsf1 is regulated and activated in the model yeast Saccharomyces cerevisiae, and highlight exciting recent discoveries related to its diverse functions under both basal and stress conditions. Given that thermal adaption is a fundamental requirement for growth and virulence in fungal pathogens, we also compare and contrast Hsf1 activation and function in other fungal species with an emphasis on its role as a critical regulator of virulence traits.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".