Time‐resolved analysis of amino acid deprivation responses reveals dynamic relationship between GCN2 and mTORC1
Bibliographic record
Abstract
In higher eukaryotes, sensing of amino acids by liver is critical for fine tuning of whole body metabolism according to nutrient availability. Amino acid (AA) depletion activates General Control Nonderepressible 2 (GCN2, or eIF2AK4) kinase and consequential phosphorylation of eukaryotic initiation factor 2 (eIF2). Phosphorylated eIF2 allows for preferential translation of specific mRNAs, such as activating transcription factor 4 (ATF4). AA depletion also reduces the activity of another AA sensor, mammalian target of rapamycin complex 1 (mTORC1), a major regulator of cell growth. The GCN2 pathway inhibits mTORC1 activity, but how remains unclear. Our study aimed to define the role of GCN2 in the regulation of mTORC1 activity to AA depletion in vivo . We used the anti‐cancer drug asparaginase (ASNase) as a molecular tool to induce AA depletion in wild type (WT) and Gcn2 −/− mice. Following a single injection of ASNase, hepatic signaling via GCN2 and mTORC1 was analyzed. In this experimental setup we addressed three types of possible regulation: 1) immediate protein‐protein interactions (15–30 min), 2) early translational changes (1–3 h) and 3) long term transcriptional alterations (6–18 h). We found that genetic disruption of GCN2 lead to hyperactivation of hepatic mTORC1 at 15–30 min following ASNase. This indicates that GCN2 modulates hepatic mTORC1 activity via protein‐protein interaction(s). Examination of translational changes via polyribosome profiling revealed enhanced translation of ATF4 in WT, but not Gcn2 −/− livers, at 1h. This suggests that: 1) translational induction of ATF4 by ASNase requires GCN2 and 2) hyperactivation of mTORC1 per se is not enough to induce ATF4 synthesis. Analysis of transcriptional changes induced by ATF4 revealed that Sestrin2, an inhibitor of mTORC1, is induced at a much later time point,12–18 h following ASNase, and is not involved in immediate or early control. Taken together, our data provide a mechanistic framework for dynamic interaction of the GCN2 pathway with mTORC1 during amino acid stress. Support or Funding Information This work was supported by NIH grant RO1HD070487 to T.G.A. and NIH K12 grant IRACDA New Jersey‐New York for Science Partnerships in Research and Education to I.A.N.
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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".