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Record W3134379799 · doi:10.3390/microorganisms9030512

Ectopic Spacer Acquisition in Streptococcus thermophilus CRISPR3 Array

2021· article· en· W3134379799 on OpenAlexafffund
Rodrigo Achigar, Martina Scarrone, Geneviève M. Rousseau, C. Philippe, Felipe Machado, Valentina Duvós, María Pía Campot, Moïra B. Dion, Yuyu Shao, María Julia Pianzzola, Sylvain Moineau

Bibliographic record

VenueMicroorganisms · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsAgencia Nacional de Investigación e Innovación
KeywordsStreptococcus thermophilusBiologyStreptococcus pyogenesBacteriophageGeneticsMicrobiologyBacteriaStaphylococcus aureusGeneEscherichia coli

Abstract

fetched live from OpenAlex

Streptococcus thermophilus relies heavily on two type II-A CRISPR-Cas systems, CRISPR1 and CRISPR3, to resist siphophage infections. One hallmark of these systems is the integration of a new spacer at the 5′ end of the CRISPR arrays following phage infection. However, we have previously shown that ectopic acquisition of spacers can occur within the CRISPR1 array. Here, we present evidence of the acquisition of new spacers within the array of CRISPR3 of S. thermophilus. The analysis of randomly selected bacteriophage-insensitive mutants of the strain Uy01 obtained after phage infection, as well as the comparison with other S. thermophilus strains with similar CRISPR3 content, showed that a specific spacer within the array could be responsible for misguiding the adaptation complex. These results also indicate that while the vast majority of new spacers are added at the 5′ end of the CRISPR array, ectopic spacer acquisition is a common feature of both CRISPR1 and CRISPR3 systems in S. thermophilus, and it can still provide phage resistance. Ectopic spacer acquisition also appears to have occurred naturally in some strains of Streptococcus pyogenes, suggesting that it is a general phenomenon, at least in type II-A systems.

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 score0.027
Threshold uncertainty score0.547

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 head0.004
GPT teacher head0.264
Teacher spread0.260 · 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

Citations14
Published2021
Admission routes2
Has abstractyes

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