DEAD-box RNA helicase Belle posttranscriptionally promotes gene expression in an ATPase activity-dependent manner
Bibliographic record
Abstract
Drosophila Belle (human ortholog DDX3) is a conserved DEAD-box RNA helicase implicated in regulating gene expression. However, the molecular mechanisms by which Belle/DDX3 regulates gene expression are poorly understood. Here we performed systematic mutational analysis to determine the contributions of conserved motifs within Belle to its in vivo function. We found that Belle RNA-binding and RNA-unwinding activities and intrinsically disordered regions (IDRs) are required for Belle in vivo function. Expression of Belle ATPase mutants that cannot bind, hydrolyze, or release ATP resulted in dominant toxic phenotypes. Mechanistically, we discovered that Belle up-regulates reporter protein level when tethered to reporter mRNA, without corresponding changes at the mRNA level, indicating that Belle promotes translation of mRNA that it binds. Belle ATPase activity and amino-terminal IDR were required for this translational promotion activity. We also found that ectopic ovary expression of dominant Belle ATPase mutants decreases levels of cyclin proteins, including Cyclin B, without corresponding changes in their mRNA levels. Finally, we found that Belle binds endogenous cyclin B mRNA. We propose that Belle promotes translation of specific target mRNAs, including cyclin B mRNA, in an ATPase activity-dependent manner.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".