Generation of an Artificial Double Promoter for Protein Expression in Bacillus subtilis through a Promoter Trap System
Bibliographic record
Abstract
Bacillus subtilis is an attractive host for production of recombinant proteins. Promoters and expression plasmid backbones have direct impacts on the efficiency of gene expression. To screen and isolate strong promoters, a promoter trap vector pShuttleF was developed in this study. Using the vector, approximately 1000 colonies containing likely promoters from Bacillus licheniformis genomic DNA were obtained. Amongst them, pShuttle-09 exhibited the highest β-Gal activities in both Escherichia coli and B. subtilis. The activity of pShuttle-09 in B. subtilis was eight times of that of the P43 promoter, a commonly used strong promoter for B. subtilis. A sequence analysis showed that pShuttle-09 contained P(luxS) and truncated luxS in-frame fused with the reporter gene as well as another fragment upstream of P(luxS) containing a putative promoter. This putative promoter was a hybrid promoter and its β-Gal activity was higher than P(luxS). Reconstructing the hybrid promoter from pShuttle-09 to P(lapS) further improved the β-Gal production by 60%. The usefulness of our promoter trap system is likely due to random shuffling and recombination of DNA fragments and adoption of a rapid and high-throughput screening. Thus, our data provide additional evidence to support the concept of using a promoter trap system to create new promoters.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".