Modulation of PKM1/2 Levels by Steric Blocking Morpholinos Alters the Metabolic and Pluripotent State of Murine Pluripotent Stem Cells
Bibliographic record
Abstract
Cellular metabolism plays both an active and passive role in embryonic development, pluripotency, and cell-fate decisions. However, little is known regarding the role of metabolism in regulating the recently described "formative" pluripotent state. The pluripotent developmental continuum features a metabolic switch from a bivalent metabolism (both glycolysis and oxidative phosphorylation) in naive cells, to predominantly glycolysis in primed cells. We investigated the role of pyruvate kinase muscle isoforms 1/2 (PKM1/2) in naive, formative, and primed mouse embryonic stem cells through modulation of PKM1/2 messenger RNA transcripts using steric blocking morpholinos that downregulate PKM2 and upregulate PKM1. We have examined these effects in naive, formative, and primed cells by quantifying the effects of PKM1/2 modulation on pluripotent and metabolic transcripts and by measuring shifts in the population frequencies of cells expressing naive and primed cell surface markers by flow cytometry. Our results demonstrate that modulating PKM1 and PKM2 levels alters the transition from the naive state into a primed pluripotent state by enhancing the proportion of the affected cells seen in the "formative" state. Therefore, we conclude that PKM1/2 actively contributes to mechanisms that oversee early stem pluripotency and their progression toward a primed pluripotent state.
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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".