A Coumermycin/Novobiocin-Regulated Gene Expression System
Bibliographic record
Abstract
Regulated expression of transgenes in mammals is an important technique in both functional genomic studies and clinical applications. Here we describe a regulated gene expression system for mammals, based on coumarin-switched dimerization of the bacterial DNA gyrase B subunit (GyrB). The transactivator was constructed by fusing the GyrB activator to the bacterial lambda repressor-binding domain. The antibiotic coumermycin in nanomolar concentrations activated the transgene through binding of the homodimerized chimeric transactivator to the lambda operator located upstream of a minipromoter. More significantly, addition of novobiocin, an antagonist of coumermycin, promptly switched off expression of the gene by abolishing coumermycin-induced dimerization of the transactivator. Site-directed mutagenesis of the lambda repressor-binding domain resulted in significant reduction of basal expression levels and an induction reaching four orders of magnitude in stably transfected 293A cells in response to coumermycin. The capability of this inducible system for tightly regulated gene expression was demonstrated by the ready generation of stable cell lines inducibly expressing the proapoptotic bax gene in mammalian cells. Hence, this novel coumarin switch-on/switch-off system should broaden the utility of regulated gene expression, particularly when rapid on/off interchange is required.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".