mTORC1 Signaling Is Palmitoylation-Dependent in Hippocampal Neurons and Non-neuronal Cells and Involves Dynamic Palmitoylation of LAMTOR1 and mTOR
Bibliographic record
Abstract
The mechanistic target of rapamycin (mTOR) Complex 1 (mTORC1) controls growth and proliferation of non-neuronal cells, while during neuronal development mTORC1 responds to glutamate and neurotrophins to promote neuronal migration and dendritic arborization. Recent studies reveal that mTORC1 signaling complexes are assembled on lysosomal membranes, but how mTORC1 membrane targeting is regulated is not fully clear. Our examination of palmitoyl-proteomic databases and additional bioinformatic analyses revealed that several mTORC1 proteins are predicted to undergo covalent modification with the lipid palmitate. This process, palmitoylation, can dynamically target proteins to specific membranes but its roles in mTORC1 signaling are not well described. Strikingly, we found that acute pharmacological inhibition of palmitoylation prevents amino acid-dependent mTORC1 activation in HEK293T cells and brain-derived neurotrophic factor (BDNF)-dependent mTORC1 activation in hippocampal neurons. We sought to define the molecular basis for this finding and found that the mTORC1 proteins LAMTOR1 and mTOR itself are directly palmitoylated, while several other mTORC1 proteins are not palmitoylated, despite strong bioinformatic prediction. Interestingly, palmitoylation of LAMTOR1, whose anchoring on lysosomal membranes is important for mTORC1 signaling, was rapidly increased prior to mTORC1 activation. In contrast, mTOR palmitoylation was decreased by stimuli that activate mTORC1. These findings reveal that specific key components of the mTOR pathway are dynamically palmitoylated, suggesting that palmitoylation is not merely permissive for mTOR activation but is instead actively involved in mTORC1-dependent signaling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".