A galactose-based auto-expression system improves T7-inducible protein production in Escherichia coli
Bibliographic record
Abstract
Protein production using Escherichia coli is a cornerstone of modern biotechnology. In this study, we developed a novel auto-expression medium to maximize protein production. Each E. coli strain tested was capable of auto-expression in response to galactose, including strains in which the endogenous lacZ had been disrupted. This provides key evidence that galactose can regulate the lac operon independent of known lac operon-regulated metabolism. The enhanced capabilities of the novel auto-expression medium were documented across protein production systems including (1) increased yields for routinely expressed proteins (e.g. eGFP), (2) improved expression of human cytochrome c within a dual expression system, (3) robust auto-expression in lacZ-deficient strains producing proteins with challenging disulfide bonds, and (4) reproducible 8-fold increase in SpCas9 yields, at ≥ 95% purity. This novel medium can streamline production and improve yields for routine as well as challenging proteins, accelerating recombinant protein production and creating new opportunities in biotechnology and structural biology.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".