Optimization of fermentation parameters in phage production using response surface methodology
Bibliographic record
Abstract
Previously, we used computer-controlled fermentation technology to improve the yield of filamentous phage produced in Escherichia coli by 10-fold (Grieco et al., Bioprocess Biosyst Eng 32:773-779, 2009). In the current study, three major fermentation parameters (temperature, dissolved oxygen [DO], and pH) were investigated using design of experiments (DOE) methodology. Response surface methodology (RSM) was employed to create a process model and determine the optimal conditions for maximal phage production. The experimental data fitted best to a quadratic model (p < 0.0001). Temperature and pH, but not DO, proved to be significant variables. The model predicted a theoretical optimal condition for maximal bacteriophage production at temperature of 28.1 °C and pH 6.9. A validation run resulted in phage production [3.49 × 10(11) transducing units (TU)/mL] comparable to the predicted value (2.86 × 10(11) TU/mL). This represented a 7-fold increase in phage production above that obtained without optimization, resulting in a 70-fold increase above that achieved by shake flask culture alone.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".