Dynamics of the SetCD-Regulated Integration and Excision of Genomic Islands Mobilized by Integrating Conjugative Elements of the SXT/R391 Family
Bibliographic record
Abstract
Mobilizable genomic islands (MGIs) are small genomic islands that are mobilizable by SXT/R391 integrating conjugative elements (ICEs) due to similar origins of transfer. Their site-specific integration and excision are catalyzed by the integrase that they encode, but their conjugative transfer entirely depends upon the conjugative machinery of SXT/R391 ICEs. In this study, we report the mechanisms that control the excision and integration processes of MGIs. We found that while the MGI-encoded integrase Int(MGI) is sufficient to promote MGI integration, efficient excision from the host chromosome requires the combined action of Int(MGI) and of a novel recombination directionality factor, RdfM. We determined that the genes encoding these proteins are activated by SetCD, the main transcriptional activators of SXT/R391 ICEs. Although they share the same regulators, we found that unlike rdfM, int(MGI) has a basal level of expression in the absence of SetCD. These findings explain how an MGI can integrate into the chromosome of a new host in the absence of a coresident ICE and shed new light on the cross talk that can occur between mobilizable and mobilizing elements that mobilize them, helping us to understand part of the rules that dictate horizontal transfer mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".