N-end Rule–Mediated Proteasomal Degradation of ATGL Promotes Lipid Storage
Bibliographic record
Abstract
Cellular lipid storage is regulated by the balance of lipogenesis and lipolysis. The rate-limiting triglyceride hydrolase ATGL (desnutrin/PNPLA2) is critical for lipolysis. The control of ATGL transcription, localization, and activation has been intensively studied, while regulation of the protein stability of ATGL is much less explored. In this study, we showed that the protein stability of ATGL is regulated by the N-end rule in cultured cells and in mice. The N-end rule E3 ligases UBR1 and UBR2 reduce the level of ATGL and affect lipid storage. The N-end rule-resistant ATGL(F2A) mutant, in which the N-terminal phenylalanine (F) of ATGL is substituted by alanine (A), has increased protein stability and enhanced lipolysis activity. ATGLF2A/F2A knock-in mice are protected against high-fat diet (HFD)-induced obesity, hepatic steatosis, and insulin resistance. Hepatic knockdown of Ubr1 attenuates HFD-induced hepatic steatosis by enhancing the ATGL level. Finally, the protein levels of UBR1 and ATGL are negatively correlated in the adipose tissue of obese mice. Our study reveals N-end rule-mediated proteasomal regulation of ATGL, a finding that may potentially be beneficial for treatment of obesity.
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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".