Preventing pyruvate kinase muscle expression in <scp>Chinese</scp> hamster ovary cells curbs lactogenic behavior by altering glycolysis, gating pyruvate generation, and increasing pyruvate flux into the <scp>TCA</scp> cycle
Bibliographic record
Abstract
Deletion of the pyruvate kinase muscle (PKM) gene, which is involved in conversion of phosphoenolpyruvate to pyruvate, has been shown to curb lactogenic behavior in Chinese hamster ovary (CHO) cells. This study describes the generation of pyruvate kinase muscle isoforms 1 and 2 knockout (PKM-KO) and pyruvate kinase muscle isoform-1 knockout (PKM1-KO) CHO host cells to understand metabolic shifts that reduce lactate secretion in these cells. Glucose and amino acids uptake levels in wild-type (WT), PKM-KO, and PKM1-KO stable cell lines, expressing two different antibodies, were analyzed in 14-day fed-batch production assays using different vessels. PKM-KO and PKM1-KO cells consumed more glucose per cell, altered amino acids metabolism, had higher flux of pyruvate into the tricarboxylic acid (TCA) cycle, and as previously shown reduced lactate secretion levels compared with the WT cells. Additionally, both PKM-KO and PKM1-KO cells had higher specific productivity and lower cell growth rates compared with the WT cells. Our findings suggest that rewiring the flux of pyruvate to the TCA cycle by deletion of PKM or PKM1 reduced cell growth and increased specific productivity in CHO cells. Overall, PKM1-KO cells had similar product quality and comparable or better titers relative to the WT cells, hence, targeted deletion of this isoform for curbing lactogenic behavior in CHO cells is suggested.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".