Krüppel-like Factor 11 Differentially Couples to Histone Acetyltransferase and Histone Methyltransferase Chromatin Remodeling Pathways to Transcriptionally Regulate Dopamine D2 Receptor in Neuronal Cells
Bibliographic record
Abstract
The importance of Krüppel-like factor (KLF)-mediated transcriptional pathways in the biochemistry of neuronal differentiation has been recognized relatively recently. Elegant studies have revealed that KLF proteins are important regulators of two major molecular and cellular processes critical for neuronal cell differentiation: neurite formation and the expression of neurotransmitter-related genes. However, whether KLF proteins mediate these key processes in a separate or coordinated fashion remains unknown. Moreover, knowledge on the contribution of chromatin dynamics to the biochemical mechanisms utilized by these proteins to perform their function is absent. Here we report the characterization of two antagonistic, chromatin-mediated mechanisms by which KLF11, also known as TIEG2 (transforming growth factor-β-inducible early gene 2) and MODY VII (maturity onset diabetes of the young VII), regulates transcription of the fopamine D2 receptor (Drd2) gene. First, KLF11 activates transcription by binding to a distinct Sp-KLF site within the Drd2 promoter (-98 to -94) and recruiting the p300 histone acetyltransferase. Second, Drd2 transcriptional activation is partially antagonized by heterochromatin protein 1 (HP1), the code reader for histone H3 lysine 9 methylation. Interestingly, KLF11 regulates neurotransmitter receptor gene expression in differentiating neuronal cell populations without affecting neurite formation. Overall, these studies highlight histone methylation and acetylation as key biochemical mechanisms modulating KLF-mediated neurotransmitter gene transcription. These data extend our knowledge of chromatin-mediated biochemical events that maintain key phenotypic features of differentiated neuronal cells.
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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".