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Record W1500856445 · doi:10.1093/nar/gkv546

The Cas6e ribonuclease is not required for interference and adaptation by the<i>E. coli</i>type I-E CRISPR-Cas system

2015· article· en· W1500856445 on OpenAlexaff
Ekaterina Semenova, Konstantin Kuznedelov, Kirill A. Datsenko, Pierre Boudry, Ekaterina Savitskaya, Sofia Medvedeva, Natalia Beloglazova, Maria D. Logacheva, Alexander F. Yakunin, Konstantin Severinov

Bibliographic record

VenueNucleic Acids Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesAgence Nationale de la Recherche
KeywordsTrans-activating crRNACRISPRBiologyCRISPR interferenceRNAGeneticsDNACas9Transcription (linguistics)NucleaseEndoribonucleaseComputational biologyGeneRNase P

Abstract

fetched live from OpenAlex

CRISPR-Cas are small RNA-based adaptive prokaryotic immunity systems protecting cells from foreign DNA or RNA. Type I CRISPR-Cas systems are composed of a multiprotein complex (Cascade) that, when bound to CRISPR RNA (crRNA), can recognize double-stranded DNA targets and recruit the Cas3 nuclease to destroy target-containing DNA. In the Escherichia coli type I-E CRISPR-Cas system, crRNAs are generated upon transcription of CRISPR arrays consisting of multiple palindromic repeats and intervening spacers through the function of Cas6e endoribonuclease, which cleaves at specific positions of repeat sequences of the CRISPR array transcript. Cas6e is also a component of Cascade. Here, we show that when mature unit-sized crRNAs are provided in a Cas6e-independent manner by transcription termination, the CRISPR-Cas system can function without Cas6e. The results should allow facile interrogation of various targets by type I-E CRISPR-Cas system in E. coli using unit-sized crRNAs generated by transcription.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.076
GPT teacher head0.381
Teacher spread0.305 · 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

Citations26
Published2015
Admission routes1
Has abstractyes

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