Optimization of simultaneous production of tyrosinase and laccase by<i>Neurospora crassa</i>
Bibliographic record
Abstract
Increasing demand for efficient and environmentally benign oxidation technologies has resulted in a focus on the use of oxidoreductases. Laccases and tyrosinases, which utilize molecular oxygen and produce water as by-product, are particularly attractive. Simultaneous production of laccase and tyrosinase was studied in Neurospora crassa FGSC #321 as the fungal strain which has the ability to produce tyrosinase intracellularly while producing laccase extracellularly. Using one-variable-at-a-time experiments and a Taguchi orthogonal L9 array demonstrated that a Vogel minimal medium containing 2.5% sucrose at pH 6.5 and 25 °C with no agitation or oxygen purging were the optimum conditions for N. crassa FGSC #321 growth. Conditions were adjusted to obtain the highest laccase and tyrosinase production. Results indicate that the control mechanisms for the production of both enzymes in N. crassa FGSC #321 are similar but not necessarily identical. Results revealed that transferring the harvested cells from the growth medium into the phosphate buffer (pH 6.8, 0.1M) containing cycloheximide (2 μM) and fluorouracil (2 mM) and increasing the temperature to 30 °C were the best conditions for simultaneous production of laccase and tyrosinase (1278 and 410 U/g of biomass, respectively). Nonetheless, starvation at 35 °C is proposed as the most cost-effective means for inducing laccase. The N. crassa laccase was characterized by using its molecular weight, pI value, optimal pH and temperature and stability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".