Ubiquitination regulates the assembly of VLDL in HepG2 cells and is the committing step of the apoB-100 ERAD pathway
Bibliographic record
Abstract
Apolipoprotein B-100 (apoB-100) is degraded by endoplasmic reticulum-associated degradation (ERAD) when lipid availability limits assembly of VLDLs. The ubiquitin ligase gp78 and the AAA-ATPase p97 have been implicated in the proteasomal degradation of apoB-100. To study the relationship between ERAD and VLDL assembly, we used small interfering RNA (siRNA) to reduce gp78 expression in HepG2 cells. Reduction of gp78 decreased apoB-100 ubiquitination and cytosolic apoB-ubiquitin conjugates. Radiolabeling studies revealed that gp78 knockdown increased secretion of newly synthesized apoB-100 and, unexpectedly, enhanced VLDL assembly, as the shift in apoB-100 density in gp78-reduced cells was accompanied by increased triacylglycerol (TG) secretion. To explore the mechanisms by which gp78 reduction might enhance VLDL assembly, we compared the effects of gp78 knockdown with those of U0126, a mitogen-activated protein kinase/ERK kinase1/2 inhibitor that enhances apoB-100 secretion in HepG2 cells. U0126 treatment increased secretion of both apoB100 and TG and decreased the ubiquitination and cellular accumu-lation of apoB-100. Furthermore, p97 knockdown caused apoB-100 to accumulate in the cell, but if gp78 was concomitantly reduced or assembly was enhanced by U0126 treatment, cellular apoB-100 returned toward baseline. This indicates that ubiquitination commits apoB-100 to p97-mediated retrotranslocation during ERAD. Thus, decreasing ubiquitination of apoB-100 enhances VLDL assembly, whereas improving apoB-100 lipidation decreases its ubiquitination, suggesting that ubiquitination has a regulatory role in VLDL assembly.
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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) | 0.002 | 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".