The production and characterization of a new active lipase from Acremonium alcalophilum using a plant bioreactor
Bibliographic record
Abstract
BACKGROUND: Microorganisms are the most proficient decomposers in nature, using secreted enzymes in the hydrolysis of lignocellulose. As such, they present the most abundant source for discovery of new enzymes. Acremonium alcalophilum is the only known cellulolytic fungus that thrives in alkaline conditions and can be cultured readily in the laboratory. Its optimal conditions for growth are 30°C and pH 9.0-9.2. The genome sequence of Acremonium alcalophilum has revealed a large number of genes encoding biomass-degrading enzymes. Among these enzymes, lipases are interesting because of several industrial applications including biofuels, detergent, food processing and textile industries. RESULTS: We identified a lipA gene in the genome sequence of Acremonium alcalophilum, encoding a protein with a predicted lipase domain with weak sequence identity to characterized enzymes. Unusually, the predicted lipase displays ≈ 30% amino acid sequence identity to both feruloyl esterase and lipase of Aspergillus niger. LipA, when transiently produced in Nicotiana benthamiana, accumulated to over 9% of total soluble protein. Plant-produced recombinant LipA is active towards p-nitrophenol esters of various carbon chain lengths with peak activity on medium-chain fatty acid (C8). The enzyme is also highly active on xylose tetra-acetate and oat spelt xylan. These results suggests that LipA is a novel lipolytic enzyme that possesses both lipase and acetylxylan esterase activity. We determined that LipA is a glycoprotein with pH and temperature optima at 8.0 and 40°C, respectively. CONCLUSION: Besides being the first heterologous expression and characterization of a gene coding for a lipase from A. alcalophilum, this report shows that LipA is very versatile exhibiting both acetylxylan esterase and lipase activities potentially useful for diverse industry sectors, and that tobacco is a suitable bioreactor for producing fungal proteins.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".