An efficient recombination system for chromosome engineering in <i>Escherichia coli</i>
Bibliographic record
Abstract
A recombination system has been developed for efficient chromosome engineering in Escherichia coli by using electroporated linear DNA. A defective lambda prophage supplies functions that protect and recombine an electroporated linear DNA substrate in the bacterial cell. The use of recombination eliminates the requirement for standard cloning as all novel joints are engineered by chemical synthesis in vitro and the linear DNA is efficiently recombined into place in vivo. The technology and manipulations required are simple and straightforward. A temperature-dependent repressor tightly controls prophage expression, and, thus, recombination functions can be transiently supplied by shifting cultures to 42 degrees C for 15 min. The efficient prophage recombination system does not require host RecA function and depends primarily on Exo, Beta, and Gam functions expressed from the defective lambda prophage. The defective prophage can be moved to other strains and can be easily removed from any strain. Gene disruptions and modifications of both the bacterial chromosome and bacterial plasmids are possible. This system will be especially useful for the engineering of large bacterial plasmids such as those from bacterial artificial chromosome libraries.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.008 |
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".