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.
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 | 0.002 | 0.001 |
| 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 | 0.001 | 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 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".