MEK Signaling Is Required for Phosphorylation of eIF2α following Amino Acid Limitation of HepG2 Human Hepatoma Cells
Bibliographic record
Abstract
The mammalian amino acid response (AAR) pathway is up-regulated by protein or amino acid depletion. This pathway involves detection of uncharged tRNA by the GCN2 kinase, phosphorylation of the translation initiation factor eIF2alpha (eukaryotic initiation factor 2alpha), and, through subsequent translational control, enhanced de novo synthesis of the transcription factor ATF4. The present studies demonstrate that inhibition of MEK activation in HepG2 human hepatoma cells by PD98059 or U0126 blocked the increased phosphorylation of eIF2alpha and ATF4 synthesis triggered by amino acid limitation, showing that the AAR requires activation of the MEK-ERK pathway. Inhibitors of the JNK or p38 MAPK pathways were ineffective. Consequently, inhibition of MEK activation blocked transcriptional induction of ATF4 target genes, but the induction was rescued by overexpression of ATF4 protein. Furthermore, the enhanced ERK phosphorylation following amino acid deprivation required GCN2 kinase activity and eIF2alpha phosphorylation. Inhibition of protein phosphatase 1 action on phospho-eIF2alpha by knockdown of GADD34 did not block the sensitivity to PD98059, suggesting that MEK functions to enhance GCN2-dependent eIF2alpha phosphorylation rather than suppressing dephosphorylation. Collectively, these results document a critical interdependence between the MEK-ERK MAPK signaling pathway and the amino acid stress-activated pathway.
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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) | 0.002 | 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".