Design of Bacterial Hosts for lac-Based Expression Vectors
Bibliographic record
Abstract
Since introduction of the first pUC plasmids ( 1 ), a great variety of plasmid vectors that use α-complementation and expression from the lac promoter, or its derivatives tac and trc promoters, have been developed (e.g., see refs. 2 – 14 ). In order to maximize utilization of these vectors, various Escherichia coli host strains have been designed which contain the lacZ ΔM15 allele ( 15 ) necessary for α-complementation and the lacI q ( 16 , 17 ) gene, which allows for overproduction of the lac repressor that is required for regulated expression from the lac promoter. The development of F episomes ( 7 , 14 , 18 ) or phages ( 1 , 19 ) containing these components facilitated the construction of various host strains, provided they do not express β-galactosidase (e.g., Δ lac strains). However, these systems suffer from several short-comings that restrict their use: Unless the episomes contain transposon-encoded antibiotic resistance markers (usually kanamycin or tetracycline), which also excludes their use in Tn 5 - or Tn 10 -containing strains, other commonly used F episomes require minimal medium for their maintenance because passage in rich media leads to their frequent loss ( 20 ), Since the episomes and phages have been tailored for use in E. coli , they cannot be exploited for establishment of a lac -based α-complementation and regulated expression system in other bacteria. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 |
| 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) | 0.002 | 0.004 |
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".