Protein Phosphatase 2A (PP2A) Regulates Low Density Lipoprotein Uptake through Regulating Sterol Response Element-binding Protein-2 (SREBP-2) DNA Binding
Bibliographic record
Abstract
LDL-cholesterol (LDL-C) uptake by Ldlr is regulated at the transcriptional level by the cleavage-dependent activation of membrane-associated sterol response element-binding protein (SREBP-2). Activated SREBP-2 translocates to the nucleus, where it binds to an LDLR promoter sterol response element (SRE), increasing LDLR gene expression and LDL-C uptake. SREBP-2 cleavage and translocation steps are well established. Several SREBP-2 phosphorylation sites have been mapped and functionally characterized. The phosphatases dephosphorylating these sites remain elusive. The phosphatase(s) regulating SREBP-2 represents a novel pharmacological target for treating hypercholesterolemia. Here we show that protein phosphatase 2A (PP2A) promotes SREBP-2 LDLR promoter binding in response to cholesterol depletion. No binding to an LDLR SRE was observed in the presence of the HMG-CoA reductase inhibitor, lovastatin, when PP2A activity was inhibited by okadaic acid or depleted by siRNA methods. SREBP-2 cleavage and nuclear translocation were not affected by loss of PP2A. PP2A activity was required for SREBP-2 DNA binding. In response to cholesterol depletion, PP2A directly interacted with SREBP-2 and altered its phosphorylation state, causing an increase in SREBP-2 binding to an LDLR SRE site. Increased binding resulted in induced LDLR gene expression and increased LDL uptake. We conclude that PP2A activity regulates cholesterol homeostasis and LDL-C uptake.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".