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Record W2793345208 · doi:10.1007/s00253-018-8753-7

Inducer-independent production of pectinases in Aspergillus niger by overexpression of the D-galacturonic acid-responsive transcription factor gaaR

2018· article· en· W2793345208 on OpenAlexafffund
Ebru Alazi, Tim G J Knetsch, Marcos Di Falco, Ian D. Reid, Mark Arentshorst, Jaap Visser, Adrian Tsang, Arthur F. J. Ram

Bibliographic record

VenueApplied Microbiology and Biotechnology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides and Plant Cell Walls
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaBE-Basic FoundationGenome Canada
KeywordsAspergillus nidulansAspergillus nigerCatabolite repressionInducerTranscription (linguistics)BiochemistryCatabolismGeneChemistryBiologyEnzymeMolecular biologyMutant

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.186
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations44
Published2018
Admission routes2
Has abstractyes

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