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Record W2217689213 · doi:10.1080/2159256x.2015.1102796

The dualistic nature of integrative and conjugative elements

2015· article· en· W2217689213 on OpenAlexaff
Nicolas Carraro, Vincent Burrus

Bibliographic record

VenueMobile Genetic Elements · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsRepliconPlasmidBiologyMobile genetic elementsAdaptation (eye)Horizontal gene transferGeneGenomeComputational biologyGeneticsEscherichia coli

Abstract

fetched live from OpenAlex

Integrative and conjugative elements (ICEs) are mobile genetic elements that play a key role in bacterial adaptation. Such elements are found in almost every bacterial genera and species, and often code for adaptive traits conferring selective advantages to their host. ICEs maintain by integrating into and replicating along with a replicon of the host genome. ICEs can propagate by conjugative transfer toward a recipient cell following excision from the replicon as a circular covalently-closed molecule. For a long time, the excised form of ICEs was assumed to be non-replicative. This assumption predicts that excised ICEs are sensitive to loss during cell division, unless they carry stabilization systems such as addiction modules or antibiotic resistance genes. Over the past few years, growing evidence have been presented that support conditional replication of the circular intermediate as an intrinsic feature of ICEs. We recently confirmed this feature in the large family of SXT/R391 ICEs, which thrive in several species of Enterobacteriaceae and Vibrionaceae. Furthermore, we demonstrated that SXT/R391 ICEs encode a functional plasmid-like type II partition system that enhances their stability, such systems being probably encoded by other ICEs. The lifecycle of ICEs is therefore much more complex than initially thought as many ICEs may use plasmid-like features to improve their stability and dissemination.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.449

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 head0.270
Teacher spread0.261 · 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

Citations53
Published2015
Admission routes1
Has abstractyes

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