Moonlighting transcriptional activation function of a fungal sulfur metabolism enzyme
Bibliographic record
Abstract
Moonlighting proteins, including metabolic enzymes acting as transcription factors (TF), are present in a variety of organisms but have not been described in higher fungi so far. In a previous genome-wide analysis of the TF repertoire of the plant-symbiotic fungus Tuber melanosporum, we identified various enzymes, including the sulfur-assimilation enzyme phosphoadenosine-phosphosulfate reductase (PAPS-red), as potential transcriptional activators. A functional analysis performed in the yeast Saccharomyces cerevisiae, now demonstrates that a specific variant of this enzyme, PAPS-red A, localizes to the nucleus and is capable of transcriptional activation. TF moonlighting, which is not present in the other enzyme variant (PAPS-red B) encoded by the T. melanosporum genome, relies on a transplantable C-terminal polypeptide containing an alternating hydrophobic/hydrophilic amino acid motif. A similar moonlighting activity was demonstrated for six additional proteins, suggesting that multitasking is a relatively frequent event. PAPS-red A is sulfur-state-responsive and highly expressed, especially in fruitbodies, and likely acts as a recruiter of transcription components involved in S-metabolism gene network activation. PAPS-red B, instead, is expressed at low levels and localizes to a highly methylated and silenced region of the genome, hinting at an evolutionary mechanism based on gene duplication, followed by epigenetic silencing of this non-moonlighting gene variant.
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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".