Adenovirus E1B 55-Kilodalton Oncoprotein Binds to Daxxand Eliminates Enhancement of p53-Dependent Transcription byDaxx
Bibliographic record
Abstract
The adenovirus E1B 55-kDa protein impairs the p53 pathway and enhances transformation, although the underlying mechanisms remain to be defined. We found that Daxx binds to the E1B 55-kDa protein in a yeast two-hybrid screen. The two proteins interact through their C termini. Mutation of three potential phosphorylation sites (S489/490 and T494 to alanine) within the E1B 55-kDa protein did not affect its interaction with Daxx, although such mutations were previously shown to inhibit E1B's ability to repress p53-dependent transcription and to enhance transformation. In addition to their coimmunoprecipitation in 293 extracts, purified Daxx interacted with the E1B 55-kDa protein in vitro, indicating their direct interaction. In 293 cells, Daxx colocalized with the E1B 55-kDa protein within discrete nuclear dots, where p53 was also found. Such structures were distinct from PML (promyelocytic leukemia protein) bodies, and it appeared that Daxx was displaced from PML bodies. Thus, the Daxx concentration was diminished in dots with a prominent presence of PML and vice versa. Indeed, PML overexpression led to dramatic redistribution of Daxx from p53-E1B 55-kDa protein complexes to PML bodies. Additionally, expression of the E1B 55-kDa protein in Saos2 osteosarcoma cells reduced the number of PML bodies. Our data suggest that E1B and PML compete for available Daxx in the cell. Surprisingly, Daxx significantly augmented p53-mediated transcription and the E1B 55-kDa protein eliminated this effect. Thus, it is likely that the E1B 55-kDa protein sequesters Daxx and p53 in specific nuclear locations, where p53 cannot activate transcription. One consequence of the Daxx-E1B interaction might be an alteration of normal interactions of Daxx, PML, and p53, which may contribute to cell transformation.
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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) | 0.002 | 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".