Arabinose-Induction of lac-Derived Promoter Systems for Penicillin Acylase Production in Escherichia coli
Bibliographic record
Abstract
Arabinose was shown to serve as an effective inducer for induction of the lac-derived promoters in Escherichia coli using penicillin acylase (PAC) as a model protein. Upon the induction with a conventional inducer, isopropyl-beta-d-thiogalactopyranoside (IPTG), for pac overexpression, which is regulated by the trc or (DE3)/T7 promoter, the production of PAC was limited by the accumulation of PAC precursors (proPAC) as inclusion bodies. Negative cellular responses, such as growth inhibition and cell lysis, were frequently observed, resulting in a low pac expression level and poor culture performance. Interestingly, these technical hurdles can be overcome simply through the use of arabinose as an inducer. The results indicate that arabinose not only induced the lac-derived promoter systems (i.e., trc and (DE3)/T7) for pac (or LL pac) overexpression but also facilitated the posttranslational processing of proPAC for maturation. However, the arabinose-inducibility appears to be host-dependent and becomes less observable in the strains with a mutation in the ara operon. The arabinose-inducibility was also investigated in the expression system with the coexistence of the trc promoter system regulating pac expression and another arabinose-inducible promoter system of araB regulating degP coexpression.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".