LARP1 is a major phosphorylation substrate of mTORC1
Bibliographic record
Abstract
Abstract The mammalian target of rapamycin complex 1 (mTORC1) controls critical cellular functions such as protein synthesis, lipid metabolism, protein turnover and ribosome biogenesis through the phosphorylation of multiple substrates. In this study, we examined the phosphorylation of a recently identified target of mTORC1: La-related protein 1 (LARP1), a member of the LARP superfamily. Previously, we and others have shown that LARP1 plays an important role in repressing TOP mRNA translation downstream of mTORC1. LARP1 binds the 7-methylguanosine triphosphate (m 7 Gppp) cap moiety and the adjacent 5’terminal oligopyrimidine (5’TOP) motif of TOP mRNAs, thus impeding the assembly of the eIF4F complex on these transcripts. mTORC1 plays a critical role in the control of TOP mRNA translation via LARP1 but the precise mechanism by which this occurs is incompletely understood. The data described herein help to elucidate this process. Specifically, it show that: (i) mTORC1 interacts with LARP1, but not other LARP superfamily members, via the C-terminal region that comprises the DM15 domain, (ii) mTORC1 pathway controls the phosphorylation of multiple (up to 26) serine and threonine residues on LARP1 in vivo , (iii) mTORC1 regulates the binding of LARP1 to TOP mRNAs and (iv) phosphorylation of S689 by mTORC1 is particularly important for the association of the DM15 domain of LARP1 with the 5’UTR of RPS6 TOP mRNA. These data reveal LARP1 as a major substrate of mTORC1.
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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) | 0.003 | 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".