Membrane Engineering for Carotenoid Production in Escherichia coli
Bibliographic record
Abstract
Carotenoids are a class of highly hydrophobic compounds synthesized by plants in limited quantities. This study explores the potential for increasing the production yield of lycopene, a typical carotenoid compound, through engineered Escherichia coli. Given that lycopene biosynthesis occurs within microbial hosts and it is subsequently stored within lipid membranes, this study focuses on the impact of inducing membrane vesicles on lycopene yield by expressing monoglycosyldiacylglycerol synthase (MGS) or diglucosyldiacylglycerol synthase (DGS) from Acholeplasma laidlawii and inserting the upstream isopentenol utilization pathway (IUP) into the chromosome. The effect of MGS and DGS on lipid production in the cell was quantified. The results show that inserting the IUP into the chromosome increased the specific lycopene yield by 2.1-fold compared to the plasmid-based system when using a PproD constitutive promoter and by 2.0-fold when using the inducible Ptrc promoter. The expression of MGS and DGS resulted in a small increase of 31% and 33% (w/w) lipid content, respectively. When expressed in lycopene producing strains, the lycopene content decreased in the IUP strains but increased in the negative control strain expressing only the native MEP pathway from undetectable levels to 0.34 ± 0.08 mg/g.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".