Regulation of TRIB1 abundance in hepatocyte models in response to proteasome inhibition
Bibliographic record
Abstract
Tribbles related homolog 1 (TRIB1) contributes to lipid and glucose homeostasis by facilitating the degradation of cognate cargos by the proteasome. In view of the key metabolic role of TRIB1 and the impact of proteasome inhibition on hepatic function, we continue our exploration of TRIB1 regulation in two commonly used human hepatocyte models, transformed cell lines HuH-7 and HepG2. In both models, proteasome inhibitors potently upregulated both endogenous and recombinant TRIB1 mRNA and protein levels. Increased transcript abundance was unaffected by MAPK inhibitors while ER stress was a weaker inducer. Suppressing proteasome function via PSMB3 silencing was sufficient to increase TRIB1 mRNA expression. ATF3 was required to sustain basal TRIB1 expression and support maximal induction. Despite increasing TRIB1 protein abundance and stabilizing bulk ubiquitylation, proteasome inhibition delayed but did not prevent TRIB1 loss upon translation block. Immunoprecipitation experiments indicated that TRIB1 was not ubiquitylated in response to proteasome inhibition. A control bona fide proteasome substrate revealed that high doses of proteasome inhibitors resulted in incomplete proteasome inhibition. Cytoplasm retained TRIB1 was unstable, suggesting that TRIB1 lability is regulated prior to its nuclear import. N-terminal deletion and substitutions were insufficient to stabilize TRIB1. These findings identify transcriptional regulation as a prominent mechanism increasing TRIB1 abundance in transformed hepatocyte cell lines in response to proteasome inhibition and provide evidence of an inhibitor resistant proteasome activity responsible for TRIB1 degradation.
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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 | 0.001 |
| 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".