PKR and PKR-like Endoplasmic Reticulum Kinase Induce the Proteasome-dependent Degradation of Cyclin D1 via a Mechanism Requiring Eukaryotic Initiation Factor 2α Phosphorylation
Bibliographic record
Abstract
Cyclin D1 plays a critical role in controlling the G(1)/S transition via the regulation of cyclin-dependent kinase activity. Several studies have indicated that cyclin D1 translation is decreased upon activation of the eukaryotic initiation factor 2alpha (eIF2alpha) kinases. We examined the effect of activation of the eIF2alpha kinases PKR and PKR-like endoplasmic reticulum kinase (PERK) on cyclin D1 protein levels and translation and determined that cyclin D1 protein levels decrease upon the induction of PKR and PERK catalytic activity but that this decrease is not due to translation. Inhibition of the 26 S proteasome with MG132 rescued cyclin D1 protein levels, indicating that rather than inhibiting translation, PKR and PERK act to increase cyclin D1 degradation. Interestingly, this effect still requires eIF2alpha phosphorylation at serine 51, as cyclin D1 remains unaffected in cells containing a non-phosphorylatable form of the protein. This proteasome-dependent degradation of cyclin D1 requires an intact ubiquitination pathway, although the ubiquitination of cyclin D1 is not itself affected. Furthermore, this degradation is independent of phosphorylation of cyclin D1 at threonine 286, which is mediated by the glycogen synthase kinase 3beta and mitogen-activated protein kinase pathways as described in previous studies. Our study reveals a novel functional cross-talk between eIF2alpha phosphorylation and the proteasomal degradation of cyclin D1 and that this degradation is dependent upon eIF2alpha phosphorylation during short, but not prolonged, periods of stress.
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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 | 0.001 |
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".