Using Reporter Genes and the Escherichia coli ASKA Overexpression Library in Screens for Regulators of the Gram Negative Envelope Stress Response
Bibliographic record
Abstract
We describe methods for screening the E. coliASKA overexpression library for clones that lead to altered expression of reporter genes. First, a promoter of interest is cloned upstream of either the lacZor luxCDABEgenes to yield reporter genes in which transcription is proportional to the levels of β-galactosidase or luminescence produced by strains carrying the reporter. The ASKA library is then condensed into two 96-well plates resulting in mixed preparations of 12 plasmids in each well. The plasmids in each well are transformed into the reporter strain and transformants are screened for either altered β-galactosidase or light production. The genes contained in ASKA clones that result in altered reporter gene expression are amplified and sequenced and the ASKA clone for the gene identified is retransformed into the parent reporter strain to confirm the effect. We have used screens like this one to look for new E. coligenes that, when over-expressed, result in the altered expression of promoters that are regulated by the envelope stress response. The identity of the clones can yield information about the nature of inducing cues and/or additional regulatory molecules. The techniques are broadly applicable to any microbial function of interest.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".