Phosphorylation of Tet3 by cdk5 is critical for robust activation of BRN2 during neuronal differentiation
Bibliographic record
Abstract
Tet3 regulates the dynamic balance between 5-methylcyotsine (5mC) and 5-hydroxymethylcytosine (5hmC) in DNA during brain development and homeostasis. However, it remains unclear how its functions are modulated in a context-dependent manner during neuronal differentiation. Here, we show that cyclin-dependent kinase 5 (cdk5) phosphorylates Tet3 at the highly conserved serine 1310 and 1379 residues within its catalytic domain, changing its in vitro dioxygenase activity. Interestingly, when stably expressed in Tet1, 2, 3 triple-knockout mouse embryonic stem cells (ESCs), wild-type Tet3 induces higher level of 5hmC and concomitant expression of genes associated with neurogenesis whereas phosphor-mutant (S1310A/S1379A) Tet3 causes elevated 5hmC and expression of genes that are linked to metabolic processes. Consistent with this observation, Tet3-knockout mouse ESCs rescued with wild-type Tet3 have higher level of 5hmC at the promoter of neuron-specific gene BRN2 when compared to cells that expressed phosphor-mutant Tet3. Wild-type and phosphor-mutant Tet3 also exhibit differential binding affinity to histone variant H2A.Z. The differential 5hmC enrichment and H2A.Z occupancy at BRN2 promoter is correlated with higher gene expression and more efficient neuronal differentiation of ESCs that expressed wild-type Tet3. Taken together, our results suggest that cdk5-mediated phosphorylation of Tet3 is required for robust activation of neuronal differentiation program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".