Metabolic Engineering of <i>Corynebacterium glutamicum</i> for Highly Efficient Production of Ectoine
Bibliographic record
Abstract
Ectoine is a compatible solute that functions as a cell protector from various stresses, protecting cells and stabilizing biomolecules, and is widely used in medicine, cosmetics, and biotechnology. Microbial fermentation has been widely used for the large-scale production of ectoine, and a number of fermentation strategies have been developed to increase the ectoine yield, reduce production costs, and simplify the production process. Here, Corynebacterium glutamicum was engineered for ectoine production by heterologous expression of the ectoine biosynthesis operon ectBAC gene from Halomonas elongata, and a series of genetic modifications were implemented. This included introducing the de3 gene from Escherichia coli BL21 (DE3) to express the T7 promoter, eliminating the lysine transporter protein lysE to limit lysine production, and performing a targeted mutation lysC S301Y on aspartate kinase to alleviate feedback inhibition of lysine. The new engineered strain Ect10 obtained an ectoine titer of 115.87 g/L in an optimized fed-batch fermentation, representing the highest ectoine production level in C. glutamicum and achieving the efficient production of ectoine in a low-salt environment.
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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 | 0.000 |
| 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".