Proteomic analysis of cap-dependent translation identifies LARP1 as a key regulator of 5′TOP mRNA translation
Bibliographic record
Abstract
The mammalian target of rapamycin (mTOR) promotes cell growth and proliferation by promoting mRNA translation and increasing the protein synthetic capacity of the cell. Although mTOR globally promotes translation by regulating the mRNA 5' cap-binding protein eIF4E (eukaryotic initiation factor 4E), it also preferentially regulates the translation of certain classes of mRNA via unclear mechanisms. To help fill this gap in knowledge, we performed a quantitative proteomic screen to identify proteins that associate with the mRNA 5' cap in an mTOR-dependent manner. Using this approach, we identified many potential regulatory factors, including the putative RNA-binding protein LARP1 (La-related protein 1). Our results indicate that LARP1 associates with actively translating ribosomes via PABP and that LARP1 stimulates the translation of mRNAs containing a 5' terminal oligopyrimidine (TOP) motif, encoding for components of the translational machinery. We found that LARP1 associates with the mTOR complex 1 (mTORC1) and is required for global protein synthesis as well as cell growth and proliferation. Together, these data reveal important molecular mechanisms involved in TOP mRNA translation and implicate LARP1 as an important regulator of cell growth and proliferation.
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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 | 0.001 | 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".