The Dual Nature of Nek9 in Adenovirus Replication
Bibliographic record
Abstract
UNLABELLED: To successfully replicate in an infected host cell, a virus must overcome sophisticated host defense mechanisms. Viruses, therefore, have evolved a multitude of devices designed to circumvent cellular defenses that would lead to abortive infection. Previous studies have identified Nek9, a cellular kinase, as a binding partner of adenovirus E1A, but the biology behind this association remains a mystery. Here we show that Nek9 is a transcriptional repressor that functions together with E1A to silence the expression of p53-inducible GADD45A gene in the infected cell. Depletion of Nek9 in infected cells reduces virus growth but unexpectedly enhances viral gene expression from the E2 transcription unit, whereas the opposite occurs when Nek9 is overexpressed. Nek9 localizes with viral replication centers, and its depletion reduces viral genome replication, while overexpression enhances viral genome numbers in infected cells. Additionally, Nek9 was found to colocalize with the viral E4 orf3 protein, a repressor of cellular stress response. Significantly, Nek9 was also shown to associate with viral and cellular promoters and appears to function as a transcriptional repressor, representing the first instance of Nek9 playing a role in gene regulation. Overall, these results highlight the complexity of virus-host interactions and identify a new role for the cellular protein Nek9 during infection, suggesting a role for Nek9 in regulating p53 target gene expression. IMPORTANCE: In the arms race that exists between a pathogen and its host, each has continually evolved mechanisms to either promote or prevent infection. In order to successfully replicate and spread, a virus must overcome every mechanism that a cell can assemble to block infection. On the other hand, to counter viral spread, cells must have multiple mechanisms to stifle viral replication. In the present study, we add to our understanding of how the human adenovirus is able to circumvent cellular roadblocks to replication. We show that the virus uses a cellular protein, Nek9, in order to block activation of p53-regulated gene GADD45A, which is an important player in stress response and p53-mediated cell cycle arrest. Importantly, our study also identifies Nek9 as a transcriptional repressor.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".