HIV-1 Vpr stimulates NF-κB and AP-1 signaling by activating TAK1
Bibliographic record
Abstract
BACKGROUND: The Vpr protein of human immunodeficiency virus type 1 (HIV-1) plays an important role in viral replication. It has been reported that Vpr stimulates the nuclear factor-κB (NF-κB) and activator protein 1 (AP-1) signaling pathways, and thereby regulates viral and host cell gene expression. However, the molecular mechanism behind this function of Vpr is not fully understood. RESULTS: Here, we have identified transforming growth factor-β-activated kinase 1 (TAK1) as the important upstream signaling molecule that Vpr associates with in order to activate NF-κB and AP-1 signaling. HIV-1 virion-associated Vpr is able to stimulate phosphorylation of TAK1. This activity of Vpr depends on its association with TAK1, since the S79A Vpr mutant lost interaction with TAK1 and was unable to activate TAK1. This association allows Vpr to promote the interaction of TAB3 with TAK1 and increase the polyubiquitination of TAK1, which renders TAK1 phosphorylation. In further support of the key role of TAK1 in this function of Vpr, knockdown of endogenous TAK1 significantly attenuated the ability of Vpr to activate NF-κB and AP-1 as well as the ability to stimulate HIV-1 LTR promoter. CONCLUSIONS: HIV-1 Vpr enhances the phosphorylation and polyubiquitination of TAK1, and as a result, activates NF-κB and AP-1 signaling pathways and stimulates HIV-1 LTR promoter.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.004 | 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".