ATG7-mediated autophagy facilitates embryonic stem cell exit from naive pluripotency and marks commitment to differentiation
Bibliographic record
Abstract
Macroautophagy/autophagy is a conserved cellular mechanism to degrade unneeded cytoplasmic proteins and organelles to recycle their components, and it is critical for embryonic stem cell (ESC) self-renewal and somatic cell reprogramming. Whereas autophagy is essential for early development of embryos, no information exists regarding its functions during the transition from naive-to-primed pluripotency. Here, by using an in vitro transition model of ESCs to epiblast-like cells (EpiLCs), we find that dynamic changes in ATG7-dependent autophagy are critical for the naive-to-primed transition, and are also necessary for germline specification. RNA-seq and ATAC-seq profiling reveal that NANOG acts as a barrier to prevent pluripotency transition, and autophagy-dependent NANOG degradation is important for dismantling the naive pluripotency expression program through decommissioning of naive-associated active enhancers. Mechanistically, we found that autophagy receptor protein SQSTM1/p62 translocated into the nucleus during the pluripotency transition period and is preferentially associated with K63 ubiquitinated NANOG for selective protein degradation. In vivo, loss of autophagy by ATG7 depletion disrupts peri-implantation development and causes increased chromatin association of NANOG, which affects neuronal differentiation by competitively binding to OTX2-specific neuroectodermal development-associated regions. Taken together, our findings reveal that autophagy-dependent degradation of NANOG plays a critical role in regulating exit from the naive state and marks distinct cell fate allocation during lineage specification. Abbreviations: 3-MA: 3-methyladenine; EpiLC: epiblast-like cell; ESC: embryonic stem cell; PGC: primordial germ cell
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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 | 0.000 |
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".