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Record W2887070160 · doi:10.1080/15476286.2018.1502589

<i>Lactococcus lactis</i> type III-A CRISPR-Cas system cleaves bacteriophage RNA

2018· article· en· W2887070160 on OpenAlexafffund
Anne M. Millen, Julie Samson, Denise M. Tremblay, Alfonso H. Magadán, Geneviève M. Rousseau, Sylvain Moineau, Dennis Romero

Bibliographic record

VenueRNA Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBiologyCRISPRLactococcus lactisBacteriophageRNAPlasmidDNANucleic acidTranscription (linguistics)Molecular biologyPhagemidSiphoviridaeGeneticsGeneBacteriaEscherichia coli

Abstract

fetched live from OpenAlex

CRISPR-Cas defends microbial cells against invading nucleic acids including viral genomes. Recent studies have shown that type III-A CRISPR-Cas systems target both RNA and DNA in a transcription-dependent manner. We previously found a type III-A system on a conjugative plasmid in Lactococcus lactis which provided resistance against virulent phages of the Siphoviridae family. Its naturally occurring spacers are oriented to generate crRNAs complementary to target phage mRNA, suggesting transcription-dependent targeting. Here, we show that only constructs whose spacers produce crRNAs complementary to the phage mRNA confer phage resistance in L. lactis. In vivo nucleic acid cleavage assays showed that cleavage of phage dsDNA genome was not detected within phage-infected L. lactis cells. On the other hand, Northern blots indicated that the lactococcal CRISPR-Cas cleaves phage mRNA in vivo. These results cannot exclude that single-stranded phage DNA is not being targeted, but phage DNA replication has been shown to be impaired.

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 score0.124
Threshold uncertainty score0.856

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 integrity0.0000.000
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 head0.009
GPT teacher head0.315
Teacher spread0.306 · 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

Citations27
Published2018
Admission routes2
Has abstractyes

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