Phage‐mediated horizontal transfer of <i>Salmonella enterica</i> virulence genes with regulatory feedback from the host
Bibliographic record
Abstract
Abstract Phage‐mediated horizontal transfer of virulence genes can enhance the transmission and pathogenicity of Salmonella enterica (S. enterica), a process potentially regulated by its regulatory mechanisms. In this study, we explored the global dynamics of phage‐mediated horizontal transfer in S. enterica and investigated the role of its regulatory mechanisms in transduction. A total of 5178 viral sequences encoding 12 S. enterica virulence genes were retrieved from the Integrated Microbial Genomes and Virome (IMG/VR) database, alongside 466,136 S. enterica genomes from EnteroBase. Virulence genes, including iacP (acyl carrier protein), mgtB (P‐type Mg2+ transporter), misL (autotransporter porin), and fliC (flagellar filament protein), were widely distributed in phages and S. enterica across North America, Europe, and Asia. Phylogenetic analysis revealed close genetic affinity between phage‐ and bacterial‐encoded virulence genes, suggesting shared ancestry and historical horizontal gene transfer events. The global regulator carbon storage regulator A (csrA) was highly conserved and ubiquitous in S. enterica. Overexpression of csrA inhibited prophage cyclization and release by upregulating the prophage cI repressor during horizontal gene transfer. Overall, these findings enhance our understanding of phage‐mediated horizontal transfer of virulence genes, explore new areas of bacterial regulators that inhibit gene exchange and evolution by affecting phage life cycles, and offer a novel approach to controlling the transmission of phage‐mediated S. enterica virulence genes.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".