Respiratory Syncytial Virus-Mediated NF-κB p65 Phosphorylation at Serine 536 Is Dependent on RIG-I, TRAF6, and IKKβ
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) is the etiological agent of acute respiratory diseases, such as bronchiolitis and pneumonia. The exacerbated production of proinflammatory cytokines and chemokines in the airways in response to RSV is an important pillar in the development of these pathologies. As such, a keen understanding of the mechanisms that modulate the inflammatory response during RSV infection is of pivotal importance to developing effective treatment. The NF-kappaB transcription factor is a major regulator of proinflammatory cytokine and chemokine genes. However, RSV-mediated activation of NF-kappaB is far from characterized. We recently demonstrated that aside from the well-characterized IkappaBalpha phosphorylation and degradation, the phosphorylation of p65 at Ser536 is an essential event regulating the RSV-mediated NF-kappaB-dependent promoter transactivation. In the present study, using small interfering RNA and pharmacological inhibitors, we now demonstrate that RSV sensing by the RIG-I cytoplasmic receptor triggers a signaling cascade involving the MAVS and TRAF6 adaptors that ultimately leads to p65ser536 phosphorylation by the IKKbeta kinase. In a previous study, we highlighted a critical role of the NOX2-containing NADPH oxidase enzyme as an upstream regulator of both the IkappaBalphaSer32 and p65Ser536 in human airway epithelial cells. Here, we demonstrate that inhibition of NOX2 significantly decreases IKKbeta activation. Taken together, our data identify a new RIG-I/MAVS/TRAF6/IKKbeta/p65Ser536 pathway placed under the control of NOX2, thus characterizing a novel regulatory pathway involved in NF-kappaB-driven proinflammatory response in the context of RSV infection.
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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) | 0.002 | 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".