Inducer-independent production of pectinases in Aspergillus niger by overexpression of the D-galacturonic acid-responsive transcription factor gaaR
Bibliographic record
Abstract
The transcription factor GaaR is needed for the expression of genes required for pectin degradation and transport and catabolism of the main degradation product, D-galacturonic acid (GA) in Aspergillus niger. In this study, we used the strong constitutive gpdA promoter of Aspergillus nidulans to overexpress gaaR in A. niger. Overexpression of gaaR resulted in an increased transcription of the genes encoding pectinases, (putative) GA transporters, and catabolic pathway enzymes even under non-inducing conditions, i.e., in the absence of GA. Exoproteome analysis of a strain overexpressing gaaR showed that this strain secretes highly elevated levels of pectinases when grown in fructose. The genes encoding exo-polygalacturonases were found to be subjected to CreA-mediated carbon catabolite repression, even in the presence of fructose. Deletion of creA in the strain overexpressing gaaR resulted in a further increase in pectinase production in fructose. We showed that GaaR localizes mainly in the nucleus regardless of the presence of an inducer, and that overexpression of gaaR leads to an increased concentration of GaaR in the nucleus.
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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 | 0.001 |
| 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".