A thermo‐alkaline lipase from a new thermophile <i>Geobacillus thermodenitrificans</i> AV‐5 with potential application in biodiesel production
Bibliographic record
Abstract
Abstract BACKGROUND A thermophilic lipase‐producing Geobacillus thermodenitrificans strain AV‐5 was isolated from the Mushroom Spring of Yellowstone National Park in WY, USA and studied as a source of lipase for transesterification of vegetable oils to biodiesel. RESULTS A maximum activity of 330 U mL−1 was produced on 2% (v/v) waste cooking oil at 50 °C, pH 8, aeration rate of 1 vvm and agitation speed of 400 rpm. However, the higher lipase productivity (14.04 U mL−1 h−1) was found at a volumetric oxygen transfer coefficient (kLa) value of 18.48 h−1. The partially purified lipase had a molecular weight, temperature and pH optimum of 50 kDa, 65 °C and pH 9, respectively, and was thermo‐alkali stable: at 70 °C, it retained 81% activity and 45% stability; at pH 10 it lost only 15% and 2.6% of its maximum activity and stability, respectively. Enzyme kinetic studies with p‐nitrophenyl laurate as substrate revealed high substrate specificity (km of 0.440 mmol L−1) and kinetic activity (vmax of 556 nmol mL min−1) of lipase. CONCLUSIONS The kLa was found to be highly dependent on aeration and agitation rates. Following optimization of fermentation medium and parameters, a 7.5‐fold increase in lipase production by G. thermodenitrificans was attained. The lipase activity and substrate specificity (as km) are among the highest reported in the literature for bacterial lipases. It was demonstrated that the enzyme can produce biodiesel from waste cooking oil with a conversion yields of 76%. © 2015 Society of Chemical Industry
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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 | 0.000 | 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".