Amino acid limitation regulates the expression of genes involved in several specific biological processes through GCN2‐dependent and GCN2‐independent pathways
Bibliographic record
Abstract
Evidence has accumulated that amino acids play an important role in controlling gene expression. Nevertheless, two components of the amino acid control of gene expression are not yet completely understood in mammals: (a) the target genes and biological processes regulated by amino acid availability, and (b) the signaling pathways that mediate the amino acid response. Using large-scale analysis of gene expression, the objective of this study was to gain a better understanding of the control of gene expression by amino acid limitation. We found that a 6 h period of leucine starvation regulated the expression of a specific set of genes: 420 genes were up-regulated by more than 1.8-fold and 311 genes were down-regulated. These genes were involved in the control of several biological processes, such as amino acid metabolism, lipid metabolism and signal regulation. Using GCN2-/- cells and rapamycin treatment, we checked for the role of mGCN2 and mTORC1 kinases in this regulation. We found that (a) the GCN2 pathway was the major, but not unique, signaling pathway involved in the up- and down-regulation of gene expression in response to amino acid starvation, and (b) that rapamycin regulates the expression of a set of genes that only partially overlaps with the set of genes regulated by leucine starvation.
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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) | 0.001 | 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".