Membrane cholesterol as regulator of human rhomboid protease RHBDL4
Bibliographic record
Abstract
In the last decade, intramembrane proteases have gained increasing attention because of their many links to various diseases. Nevertheless, our understanding as to how they function or how they are regulated is still limited, especially when it comes to human homologues. In this regard, here we sought to unravel mechanisms of regulation of the protease rhomboid-like protein-4 (RHBDL4), one of five active human serine intramembrane proteases. In view of our recent finding that human RHBDL4 efficiently cleaves the amyloid precursor protein (APP), a key protein in the pathology of Alzheimer's disease, we used established reagents to modulate the cellular cholesterol content and analyzed the effects of this modulation on RHBDL4-mediated processing of endogenous APP. We discovered that lowering membrane cholesterol levels increased the levels of RHBDL4-specific endogenous APP fragments, whereas high cholesterol levels had the opposite effect. Direct binding of cholesterol to APP did not mediate these modulating effects of cholesterol. Instead, using homology modeling, we identified two potential cholesterol-binding motifs in the transmembrane helices 3 and 6 of RHBDL4. Substitution of the essential tyrosine residues of the potential cholesterol-binding motifs to alanine increased the levels of endogenous APP C-terminal fragments, reflecting enhanced RHBDL4 activity. In summary, we provide evidence that the activity of RHBDL4 is regulated by cholesterol likely through a direct binding of cholesterol to the enzyme.
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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".