Heterologous SUMO-2/3-Ubiquitin Chains Optimize IκBα Degradation and NF-κB Activity
Bibliographic record
Abstract
The NF-κB pathway is regulated by SUMOylation at least at three levels: the inhibitory molecule IκBα, the IKK subunit γ/NEMO and the p52 precursor p100. Here we investigate the role of SUMO-2/3 in the degradation of IκBα and activation of NF-κB mediated by TNFα. We found that under conditions of deficient SUMOylation, an important delay in both TNFα-mediated proteolysis of IκBα and NF-κB dependent transcription occurs. In vitro and ex vivo approaches, including the use of ubiquitin-traps (TUBEs), revealed the formation of chains on IκBα containing SUMO-2/3 and ubiquitin after TNFα stimulation. The integration of SUMO-2/3 appears to promote the formation of ubiquitin chains on IκBα after activation of the TNFα signalling pathway. Furthermore, heterologous chains of SUMO-2/3 and ubiquitin promote a more efficient degradation of IκBα by the 26S proteasome in vitro compared to chains of either SUMO-2/3 or ubiquitin alone. Consistently, Ubc9 silencing reduced the capture of IκBα modified with SUMO-ubiquitin hybrid chains that display a defective proteasome-mediated degradation. Thus, hybrid SUMO-2/3-ubiquitin chains increase the susceptibility of modified IκBα to the action of 26S proteasome, contributing to the optimal control of NF-κB activity after TNFα-stimulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".