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Record W3210452394 · doi:10.1186/s13068-021-02057-y

CRISPR/Cas9-mediated genome editing directed by a 5S rRNA–tRNAGly hybrid promoter in the thermophilic filamentous fungus Humicola insolens

2021· article· en· W3210452394 on OpenAlexaff
Chao Fan, Wei Zhang, Xiaoyun Su, Wangli Ji, Huiying Luo, Yuhong Zhang, Bo Liu, Bin Yao, Huoqing Huang, Xinxin Xu

Bibliographic record

VenueBiotechnology for Biofuels · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsBiotechnology Research Institute
FundersNational Key Research and Development Program of ChinaAgricultural Science and Technology Innovation ProgramChinese Academy of Sciences
KeywordsThermophileBiologyCRISPRGeneticsGenome editingGenomeRibosomal RNAComputational biologyGeneBacteria

Abstract

fetched live from OpenAlex

BACKGROUND: Humicola insolens is a filamentous fungus with high potential of producing neutral and heat- and alkali-resistant cellulase. However, the genetic engineering tools, particularly the genome-editing tool, are scarce, hindering the study of cellulase expression regulation in this organism. RESULTS: promoter. This system is superior to the HDV (hepatitis delta virus) system in genome editing, allowing highly efficient single gene destruction in H. insolens with rates of deletion up to 84.1% (37/44). With this system, a putative pigment synthesis gene pks and the transcription factor xyr1 gene were disrupted with high efficiency. Moreover, the extracellular protein concentration and cellulase activity largely decreased when xyr1 was deleted, demonstrating for the first time that Xyr1 plays an important role in cellulase expression regulation. CONCLUSIONS: The established CRISPR/Cas9 system is a powerful genetic operation tool for H. insolens, which will accelerate studies on the regulation mechanism of cellulase expression and engineering of H. insolens for higher cellulase production.

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 categoriesMeta-epidemiology (narrow)
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 score0.119
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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.

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

Citations14
Published2021
Admission routes1
Has abstractyes

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