Production of itaconic acid using metabolically engineered Escherichia coli
Why this work is in the frame
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Bibliographic record
Abstract
An Escherichia coli system was engineered for the heterologous production of itaconic acid via the expression of cis-aconitate decarboxylase gene (cad), and then maximal itaconic acid levels produced by engineered E. coli were evaluated. Expression of cad in E. coli grown in Luria-Bertani (LB) medium without glucose in a test tube resulted in 0.07 g/L itaconic acid production after 78 h at 20°C. To increase itaconic acid production, E. coli recombinants were constructed by inactivating the isocitrate dehydrogenase gene (icd) and/or the isocitrate lyase gene (aceA). Expression of cad and inactivation of icd resulted in 0.35 g/L itaconic acid production after 78 h, whereas aceA inactivation had no effect on itaconic acid production. The intracellular itaconate concentration in the Δicd strain was higher than that in the cad-expressing strain without icd inactivation, which suggests that the extracellular secretion of itaconate in E. coli is the rate-determining step during itaconic acid production. pH-stat cultivation using the cad-expressing Δicd strain in LB medium with 3% glucose in a jar fermenter resulted in 1.71 g/L itaconic acid production after 97 h at 28°C. To further increase itaconic acid production, the aconitase B gene (acnB) was overexpressed in the cad-expressing Δicd strain. Simultaneous overexpression of acnB with the expression of cad in the Δicd strain led to 4.34 g/L itaconic acid production after 105 h. Our findings indicate that icd inactivation and acnB overexpression considerably enhance itaconic acid production in cad-expressing E. coli.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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 it