Efficient production of isobutanol from glycerol in Klebsiella pneumoniae: Regulation of acetohydroxyacid synthase, a rate-limiting enzyme in isobutanol biosynthesis at gene expression level
Bibliographic record
Abstract
Abstract Background: Glycerol is inexpensive and abundant, and can be used for the industrial production of value-added products. Isobutanol is an important industrial chemical that has many applications, and its biosynthesis from different carbon sources has been studied using various microorganisms. So far, isobutanol production by Klebsiella pneumoniae has been mainly studied using glucose. In this study, we produced isobutanol from glycerol based on the K. pneumoniae ΔldhAΔadcmutant harboring pBR-iBO used in previous study using K. pneumoniae, which has an excellent ability to assimilate glycerol even under limited conditions. Results: We investigated the effect of different acetohydroxyacid synthase (AHAS) isoenzymes (rate-limiting enzymes in isobutanol biosynthesis), plasmid copy number, and different promoters as a method to increase isobutanol production by K. pneumoniae. The K. pneumoniae Cu ΔldhAΔbudA, pUC-tac-BN-ISO strain produced 2.56-fold more isobutanol than previously reported for glycerol-derived isobutanol production. Also, the in vitro enzyme activity of AHAS I (ilvBN) was greater than that of the other two isoenzymes (ilvIHand ilvGM). Evaluation of process factors indicated that an agitation speed of 200 rpm with the culture maintained at pH 6 were favorable conditions for isobutanol production (1.02 g/L). Conclusion: We obtained enhanced isobutanol production from glycerol by metabolic engineering of K. pneumoniae. Our results demonstrated enhanced production of isobutanol from glycerol, and suggest future avenues for research in this area.
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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 | 0.000 |
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".