Improving Glucose and Glutamine Metabolism of Human HEK 293 and <i>Trichoplusia</i> <i>ni</i> Insect Cells Engineered To Express a Cytosolic Pyruvate Carboxylase Enzyme
Bibliographic record
Abstract
Metabolic engineering has been defined as a directed improvement of product formation or cellular properties by modification of specific biochemical pathways or introduction of new enzymatic reactions by recombinant DNA technology. The use of metabolic flux analysis (MFA) has helped in the understanding of the key limitation in the metabolic pathways of cultured animal cells. The MFA of the major nutrients glucose and glutamine showed that the flux of glucose to the TCA cycle and its subsequent utilization is limited as a result of the lack of certain key enzymes in the pathway. One of the key enzymes controlling this flux is pyruvate carboxylase. Introduction of this enzyme into mammalian cells has been shown to improve the utilization of glucose and limit the production of lactate and ammonia, which are deleterious to cell growth. In the present work a yeast pyruvate carboxylase gene has been introduced into mammalian (HEK 293) and insect (Trichoplusia ni High-Five) cells, resulting in the cytosolic expression of the enzyme. In both cases the resulting transfected cells were able to utilize glucose and glutamine more efficiently and produce lower amounts of lactate and ammonia. Differences in the amino acid utilization pattern were also observed, indicating changes in the basic metabolism of the cells. The performance of the transfected cells as expression systems for adenovirus and baculovirus vectors, respectively, has also been examined. The results obtained and their impact on the process development for protein and viral vector production are discussed.
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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".