The Histone 3′-Terminal Stem-Loop-Binding Protein Enhances Translation through a Functional and Physical Interaction with Eukaryotic Initiation Factor 4G (eIF4G) and eIF3
Bibliographic record
Abstract
Metazoan cell cycle-regulated histone mRNAs are unique cellular mRNAs in that they terminate in a highly conserved stem-loop structure instead of a poly(A) tail. Not only is the stem-loop structure necessary for 3'-end formation but it regulates the stability and translational efficiency of histone mRNAs. The histone stem-loop structure is recognized by the stem-loop-binding protein (SLBP), which is required for the regulation of mRNA processing and turnover. In this study, we show that SLBP is required for the translation of mRNAs containing the histone stem-loop structure. Moreover, we show that the translation of mRNAs ending in the histone stem-loop is stimulated in Saccharomyces cerevisiae cells expressing mammalian SLBP. The translational function of SLBP genetically required eukaryotic initiation factor 4E (eIF4E), eIF4G, and eIF3, and expressed SLBP coisolated with S. cerevisiae initiation factor complexes that bound the 5' cap in a manner dependent on eIF4G and eIF3. Furthermore, eIF4G coimmunoprecipitated with endogenous SLBP in mammalian cell extracts and recombinant SLBP and eIF4G coisolated. These data indicate that SLBP stimulates the translation of histone mRNAs through a functional interaction with both the mRNA stem-loop and the 5' cap that is mediated by eIF4G and eIF3.
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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) | 0.002 | 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".