Ectopic expression of aPKC-mediated phosphorylation in p300 modulates hippocampal neurogenesis, CREB binding and fear memory differently with age
Bibliographic record
Abstract
Epigenetic modifications have become an emerging interface that links extrinsic signals to alterations of gene expression that determine cell identity and function. However, direct signaling that regulates epigenetic modifications is unknown. Our previous work demonstrated that phosphorylation of CBP at Ser 436 by atypical protein kinase C (aPKC) regulates age-dependent hippocampal neurogenesis and memory. p300, a close family member of CBP, lacks the aPKC-mediated phosphorylation found in CBP. Here, we use a phosphorylation-competent p300 (G442S) knock-in (KI) mouse model that ectopically expresses p300 phosphorylation in a homologous site to CBP Ser436, and assess its roles in modulating hippocampal neurogenesis, CREB binding ability, and fear memory. Young adult (3 months) p300G422S-KI mice exhibit enhanced hippocampal neurogenesis due to increased cell survival of newly-generated neurons, without alterations in CREB binding and contextual fear memory. On the other hand, mature adult (6 months) p300G422S-KI mice display reduced CREB binding, associated with impaired contextual fear memory without alterations in hippocampal neurogenesis. Additionally, we show that repulsive interaction between pS133-CREB and pS422-p300G422S may contribute to the reduced CREB binding to p300G422S. Together, these data suggest that a single phosphorylation change in p300 has the capability to modulate hippocampal neurogenesis, CREB binding, and associative fear memory.
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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".