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Record W4283730852 · doi:10.1101/2022.06.29.498089

Genetic transformation and cell division delay in competent <i>Staphylococcus aureus</i>

2022· preprint· en· W4283730852 on OpenAlexfundno aff
Fedy Morgene, Célia Rizoug Zeghlache, Shi Yuan Feng, Yolande Hauck, Nicolas Mirouze

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersAgence Nationale de la RechercheYork University
KeywordsStaphylococcus aureusTransformation (genetics)BiologyCell divisionGenetic recombinationVirulenceGeneticsGeneDNAHorizontal gene transferCell biologyMicrobiologyCellBacteriaGenomeRecombination

Abstract

fetched live from OpenAlex

Summary Natural competence for genetic transformation, considered as one of the three main mechanisms leading to horizontal gene transfer in bacteria, is able to promote evolution, through genomic plasticity, and foster antibiotic resistance and virulence factors spreading. Conserved machineries and actors required to perform genetic transformation have been shown to accumulate at different cellular localizations depending on the model organism considered. Here, we show in the human pathogen Staphylococcus aureus that DNA binding, uptake and recombination are spatially and temporally coordinated to ensure S. aureus genetic transformation. We also reveal that localization of genetic transformation proteins is dynamic and preferentially occurs in the vicinity of the division septum. We finally propose that S. aureus competent cells would initiate and then block cell division to ensure the success of genetic transformation before the final constriction of the cytokinetic ring.

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 score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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