Manipulating the Mediator complex to induce naïve pluripotency
Bibliographic record
Abstract
Human naïve pluripotent stem cells (PSCs) represent an optimal homogenous starting point for molecular interventions and differentiation strategies. This is in contrast to the standard primed PSCs which fluctuate in identity and are transcriptionally heterogeneous. However, despite many efforts, the maintenance and expansion of human naïve PSCs remains a challenge. Here, we discuss our recent strategy for the stabilization of human PSC in the naïve state based on the use of a single chemical inhibitor of the related kinases CDK8 and CDK19. These kinases phosphorylate and negatively regulate the multiprotein Mediator complex, which is critical for enhancer-driven recruitment of RNA Pol II. The net effect of CDK8/19 inhibition is a global stimulation of enhancers, which in turn reinforces transcriptional programs including those related to cellular identity. In the case of pluripotent cells, the presence of CDK8/19i efficiently stabilizes the naïve state. Importantly, in contrast to previous chemical methods to induced the naïve state based on the inhibition of the FGF-MEK-ERK pathway, CDK8/19i-naïve human PSCs are chromosomally stable and retain developmental potential after long-term expansion. We suggest this could be related to the fact that CDK8/19 inhibition does not induce DNA demethylation. These principles may apply to other fate decisions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".