A decrease in eukaryotic elongation factor 2 phosphorylation is required for local translation of sensorin and long‐term facilitation in Aplysia
Bibliographic record
Abstract
Mechanistic target of rapamycin complex 1 (mTORC1)-dependent protein synthesis is required for many forms of synaptic plasticity and memory, but the downstream pathways important for synaptic plasticity are poorly understood. Long-term facilitation (LTF) in Aplysia is a form of synaptic plasticity that is closely linked to behavioral memory and an attractive model system for examining the important downstream targets for mTORC1 in regulating synaptic plasticity. Although mTORC1-regulated protein synthesis has been strongly linked to translation initiation, translation elongation is also regulated by mTORC1 and LTF leads to an mTORC1-dependent decrease in eukaryotic elongation factor 2 (eEF2) phosphorylation. The purpose of this study is to test the hypothesis that the decrease in eEF2 phosphorylation is required for mTORC1-dependent translation and plasticity. We show that the LTF-induced decrease in eEF2 phosphorylation is blocked by expression of an eEF2 kinase (eEF2K) modified to be resistant to mTORC1 regulation. We found that expression of this modified kinase blocked LTF. LTF requires local protein synthesis of the neuropeptide sensorin and importantly, local sensorin synthesis can be measured using a dendra fluorescent protein containing the 5' and 3' untranslated regions (UTRs) of sensorin. Using this construct, we show that blocking eEF2 dephosphorylation also blocks the increase in local sensorin synthesis. These results identify decreases in eEF2 phosphorylation as a critical downstream effector of mTOR required for long-term plasticity and identify an important translational target regulated by decreases in eEF2 phosphorylation.
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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 | 0.001 |
| 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".