Ppp1r15 gene knockout reveals an essential role for translation initiation factor 2 alpha (eIF2α) dephosphorylation in mammalian development
Bibliographic record
Abstract
Diverse cellular stress responses are linked to phosphorylation of serine 51 on the alpha subunit of translation initiation factor 2. The resultant attenuation of protein synthesis and activation of gene expression figure heavily in the adaptive response to stress, but dephosphorylation of eIF2(alphaP), which terminates signaling in this pathway, is less well understood. GADD34 and CReP, the products of the related mammalian genes Ppp1r15a and Ppp1r15b, can recruit phosphatase catalytic subunits of the PPP1 class to eIF2(alphaP), but the significance of their contribution to its dephosphorylation has not been explored systematically. Here we report that unlike Ppp1r15a mutant mice, which are superficially indistinguishable from wild type, Ppp1r15b(-/-) mouse embryos survive gestation but exhibit severe growth retardation and impaired erythropoiesis, and loss of both Ppp1r15 genes leads to early embryonic lethality. These loss-of-function phenotypes are rescued by a mutation, Eif2a(S51A), that prevents regulated phosphorylation of eIF2alpha. These findings reveal that the essential process of eIF2(alphaP) dephosphorylation is the predominant role of PPP1R15 proteins in mammalian development.
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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 | 0.001 |
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".