Experimental Evolution to Identify Mutations that Compensate for Loss of Xenogeneic Silencing Proteins in Salmonella Typhimurium
Bibliographic record
Abstract
Horizontal Gene Transfer (HGT) is an important process that has driven the evolution of bacteria, and has been particularly important in the development of pathogenic strains. Foreign genes, however, pose a considerable risk to bacteria. The foreign gene silencing proteins H-NS and StpA buffer the fitness costs associated with HGT. To gain insight into how these proteins act as global regulators and to observe the functional consequences of losing these proteins, I employed an in vitro evolution approach with Salmonella strains harbouring deletions in both hns and stpA. I show that passaging over 500 generations partially restores fitness and using whole genome sequencing, identify recurring mutations within chaperones DnaK/DnaJ and the transcription termination factor Rho. My results provide important insights into how H-NS/ StpA likely coordinate with Rho to silence foreign genes and regulate HGT.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".