Concomitant reduction of lactate and ammonia accumulation in fed‐batch cultures: Impact on glycoprotein production and quality
Bibliographic record
Abstract
Lactate and ammonia accumulation is a major factor limiting the performance of fed-batch strategies for mammalian cell culture processes. In addition to the detrimental effects of these by-products on production yield, ammonia also contributes to recombinant glycoprotein quality deterioration. In this study, we tackled the accumulation of these two inhibiting metabolic wastes by culturing in glutamine-free fed-batch cultures an engineered HEK293 cell line displaying an improved central carbon metabolism. Batch cultures highlighted the ability of PYC2-overexpressing HEK293 cells to grow and sustain a relatively high viability in absence of glutamine without prior adaptation to the culture medium. In fed-batch cultures designed to maintain glucose at high concentration by daily feeding a glutamine-free concentrated nutrient feed, the maximum lactate and ammonia concentrations did not exceed 5 and 1 mM, respectively. In flask, this resulted in more than a 2.5-fold increase in IFNα2b titer in comparison to the control glutamine-supplied fed-batch. In bioreactor, this strategy led to similar reductions in lactate and ammonia accumulation and an increase in IFNα2b production. Of utmost importance, this strategy did not affect IFNα2b quality with respect to sialylation and glycoform distribution as confirmed by surface plasmon resonance biosensing and LC-MS, respectively. Our strategy thus offers an attractive and simple approach for the development of efficient cell culture processes for the mass production of high-quality therapeutic glycoproteins. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:494-504, 2018.
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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 | 0.000 | 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 | 0.001 |
| 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".