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Record W4280509090 · doi:10.1038/s41467-022-30310-x

A truncated anti-CRISPR protein prevents spacer acquisition but not interference

2022· article· en· W4280509090 on OpenAlexafffund
C. Philippe, Carlee Morency, Pier-Luc Plante, Edwige Zufferey, Rodrigo Achigar, Denise M. Tremblay, Geneviève M. Rousseau, Adeline Goulet, Sylvain Moineau

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité Laval
FundersFrench Infrastructure for Integrated Structural BiologyNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsAgence Nationale de la Recherche
KeywordsCRISPRCas9CRISPR interferenceBiologyGeneDNAAcquired immune systemGeneticsNucleic acidMutantComputational biologyImmune system

Abstract

fetched live from OpenAlex

CRISPR-Cas systems in prokaryotic cells provide an adaptive immunity against invading nucleic acids. For example, phage infection leads to addition of new immunity (spacer acquisition) and DNA cleavage (interference) in the bacterial model species Streptococcus thermophilus, which primarily relies on Cas9-containing CRISPR-Cas systems. Phages can counteract this defense system through mutations in the targeted protospacers or by encoding anti-CRISPR proteins (ACRs) that block Cas9 interference activity. Here, we show that S. thermophilus can block ACR-containing phages when the CRISPR immunity specifically targets the acr gene. This in turn selects for phage mutants carrying a deletion within the acr gene. Remarkably, a truncated acrIIA allele, found in a wild-type virulent streptococcal phage, does not block the interference activity of Cas9 but still prevents the acquisition of new immunities, thereby providing an example of an ACR specifically inhibiting spacer acquisition.

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 score0.193
Threshold uncertainty score0.468

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 science0.0010.001
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 head0.012
GPT teacher head0.317
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

Citations19
Published2022
Admission routes2
Has abstractyes

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