Crucial role of <i>Salmonella</i> genomic island 1 master activator in the parasitism of IncC plasmids
Bibliographic record
Abstract
IncC conjugative plasmids and the multiple variants of Salmonella Genomic Island 1 (SGI1) are two functionally interacting families of mobile genetic elements commonly associated with multidrug resistance in the Gammaproteobacteria. SGI1 and its siblings are specifically mobilised in trans by IncC conjugative plasmids. Conjugative transfer of IncC plasmids is activated by the plasmid-encoded master activator AcaCD. SGI1 carries five AcaCD-responsive promoters that drive the expression of genes involved in its excision, replication, and mobilisation. SGI1 encodes an AcaCD homologue, the transcriptional activator complex SgaCD (also known as FlhDCSGI1) that seems to recognise and activate the same SGI1 promoters. Here, we investigated the relevance of SgaCD in SGI1's lifecycle. Mating assays revealed the requirement for SgaCD and its IncC-encoded counterpart AcaCD in the mobilisation of SGI1. An integrative approach combining ChIP-exo, Cappable-seq, and RNA-seq confirmed that SgaCD activates each of the 18 AcaCD-responsive promoters driving the expression of the plasmid transfer functions. A comprehensive analysis of the activity of the complete set of AcaCD-responsive promoters of SGI1 and the helper IncC plasmid was performed through reporter assays. qPCR and flow cytometry assays revealed that SgaCD is essential to elicit the excision and replication of SGI1 and destabilise the helper IncC plasmid.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".