The central role of pyruvate metabolism on the epigenetic maturation and transcriptional profile of bovine oocytes
Bibliographic record
Abstract
In brief: Pyruvate metabolism is one of the main metabolic pathways during oocyte maturation. This study demonstrates that pyruvate metabolism also regulates the epigenetic and molecular maturation in bovine oocytes. Abstract: Pyruvate, the final product of glycolysis, undergoes conversion into acetyl-CoA within the mitochondria of oocytes, serving as a primary fuel source for the tricarboxylic acid (TCA) cycle. The citrate generated in the TCA cycle can be transported to the cytoplasm and converted back into acetyl-CoA. This acetyl-CoA can either fuel lipid synthesis or act as a substrate for histone acetylation. This study aimed to investigate how pyruvate metabolism influences lysine 9 histone 3 acetylation (H3K9ac) dynamics and RNA transcription in bovine oocytes during in vitro maturation (IVM). Bovine cumulus-oocyte complexes were cultured in vitro for 24 h, considering three experimental groups: Control (IVM medium only), DCA (IVM supplemented with sodium dichloroacetate, a stimulant of pyruvate oxidation into acetyl-CoA), or IA (IVM supplemented with sodium iodoacetate, a glycolysis inhibitor). The results revealed significant alterations in oocyte metabolism in both treatments, promoting the utilization of lipids as an energy source. These changes during IVM affected the dynamics of H3K9ac, subsequently influencing the oocyte's transcriptional activity. In the DCA and IA groups, a total of 148 and 356 differentially expressed genes were identified, respectively, compared to the control group. These findings suggest that modifications in pyruvate metabolism trigger the activation of metabolic pathways, particularly lipid metabolism, changing acetyl-CoA availability and H3K9ac levels, ultimately impacting the mRNA content of in vitro matured bovine oocytes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".