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Record W3154694869 · doi:10.1089/crispr.2020.0145

Functional Study of the Type II-A CRISPR-Cas System of <i>Streptococcus agalactiae</i> Hypervirulent Strains

2021· article· en· W3154694869 on OpenAlexaff
Adeline Pastuszka, Clémence Beauruelle, Émilie Camiade, Geneviève M. Rousseau, Sylvain Moineau, Laurent Méreghetti, Philippe Horvath, Philippe Lanotte

Bibliographic record

VenueThe CRISPR Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCRISPRCRISPR interferenceStreptococcus agalactiaeBiologyGeneTrans-activating crRNAGeneticsTranscription (linguistics)Cas9MicrobiologyStreptococcusBacteria

Abstract

fetched live from OpenAlex

Nearly all strains of Streptococcus agalactiae , the leading cause of invasive infections in neonates, encode a type II-A clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system. Interestingly, S. agalactiae strains belonging to the hypervirulent Sequence Type 17 (ST17) contain significantly fewer spacers in their CRISPR locus than other lineages, which could be the result of a less functional CRISPR-Cas system. Here, we revealed one large deletion in the ST17 cas promoter region and we evaluated its impact on the transcription of cas genes as well as the functionalities of the CRISPR-Cas system. We demonstrated that Cas9 interference is functional and that the CRISPR-Cas system of ST17 strains can still acquire new spacers, despite the absence of a regular cas promoter. We demonstrated that a promoter sequence upstream of srn036, a small RNA partially overlapping the antisense tracrRNA, is responsible for the ST17 CRISPR-Cas adaptation and interference activities.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.034
GPT teacher head0.289
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 source (direct Gemma or distilled Codex), 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

Citations8
Published2021
Admission routes1
Has abstractyes

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