Modification of genetic regulation of a heterologous chitosanase gene in Streptomyces lividans TK24 leads to chitosanase production in the absence of chitosan
Bibliographic record
Abstract
BACKGROUND: Chitosanases are enzymes hydrolysing chitosan, a β-1,4 linked D-glucosamine bio-polymer. Chitosan oligosaccharides have numerous emerging applications and chitosanases can be used for industrial enzymatic hydrolysis of chitosan. These extracellular enzymes, produced by many organisms including fungi and bacteria, are well studied at the biochemical and enzymatic level but very few works were dedicated to the regulation of their gene expression. This is the first study on the genetic regulation of a heterologous chitosanase gene (csnN106) in Streptomyces lividans. RESULTS: Two S. lividans strains were used for induction experiments: the wild type strain and its mutant (ΔcsnR), harbouring an in-frame deletion of the csnR gene, encoding a negative transcriptional regulator. Comparison of chitosanase levels in various media indicated that CsnR regulates negatively the expression of the heterologous chitosanase gene csnN106. Using the ΔcsnR host and a mutated csnN106 gene with a modified transcription operator, substantial levels of chitosanase could be produced in the absence of chitosan, using inexpensive medium components. Furthermore, chitosanase production was of higher quality as lower levels of extracellular protease and protein contaminants were observed. CONCLUSIONS: This new chitosanase production system is of interest for biotechnology as only common media components are used and enzyme of high degree of purity is obtained directly in the culture supernatant.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".