Transcriptional repression of hypoxia-inducible factor-1 (HIF-1) by the protein arginine methyltransferase PRMT1
Bibliographic record
Abstract
Hypoxia-inducible factors (HIF-1 and HIF-2) are essential mediators for the adaptive transcriptional response of cells and tissues to low-oxygen conditions. Under hypoxia or when cells are treated with various nonhypoxic stimuli, the active HIF-α subunits are mainly regulated through increased protein stabilization. For HIF-1α, it is clear that further transcriptional, translational, and posttranslational regulations are important for complete HIF-1 activity. Novel evidence links hypoxia and HIF-1 to arginine methylation, an important protein modification. These studies suggest that arginine methyltransferases may be important for hypoxic responses. Protein arginine methyltransferase 1 (PRMT1), the predominant arginine methyltransferase, can act as a transcriptional activator or repressor by modifying a diverse set of substrates. In this work, we show that PRMT1 is a repressor of both HIF-1 and HIF-2. The cellular depletion of PRMT1 by small interference RNA targeting leads to increased HIF transcriptional activity. This activation is the result of enhanced HIF-α subunit transcription, which allows increased HIF-α subunit availability. We provide evidence that PRMT1-dependent HIF-1α regulation is mediated through the activities of both specificity protein 1 (Sp1) and Sp3, two transcription factors known to control HIF-1α expression. This study therefore identifies PRMT1 as a novel regulator of HIF-1- and HIF-2-mediated responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".