Molecular mapping of the determinants involved in human Staufen–ribosome association
Bibliographic record
Abstract
The human double-stranded (ds) RNA-binding protein Staufen (hStau) is considered to have a role in RNA transport and its localization. By using sedimentation analysis on sucrose gradients, we showed that the Staufen isoform with an apparent molecular mass of 55 kDa (Stau(55)) co-fractionated with ribosomes and associated with both the 40 and 60 S ribosomal subunits, suggesting that the Staufen isoform hStau(55) plays some role in translation. To map the determinant(s) involved in this association, we generated a series of deletion mutants and analysed their subcellular distribution by cell fractionation and fluorescent immunomicroscopy. Our results demonstrated that multiple determinants promote hStau(55)-ribosome association via both an RNA-binding-dependent mechanism and protein-protein interaction. The RNA-binding activity of the ds RNA-binding protein domain 3 (dsRBD3) but not that of dsRBD4 is the first determinant. Although necessary for stable association with ribosomes, dsRBD3 alone is not sufficient and needs other determinants as co-factors. Consistently, when expressed together, dsRBD4 and the tubulin-binding domain constitute the minimal Stau(55)/ribosome protein-protein association domain. This region of Stau(55) is sufficient to associate with ribosomes independently, but requires the RNA-binding activity of dsRBD3 for complete association. Thus the results are consistent with a putative role for Stau(55) in the regulation of translation.
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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 | 0.001 |
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".