Regulatory Evolution Drives Evasion of Host Inflammasomes by Salmonella Typhimurium
Bibliographic record
Abstract
Bacterial two-component regulatory systems (TCS) couple the detection of niche-specific cues with adaptive gene expression to optimize fitness. In Salmonella Typhimurium (STM), the SsrA-SsrB TCS regulates virulence genes needed for survival within host cells, yet the impact of this TCS on regulatory evolution in this pathogen remains incompletely understood. Here, we show that SsrB alters a transcriptional network controlling bacterial motility to limit inflammasome activation during host cell infection. Using comparative RNA sequencing between STM and S. bongori (SBG) engineered to express SsrB, we show that SsrB represses flagellar gene expression in STM but activates this pathway in SBG, which has evolved in the absence of SsrB. Motility repression in STM is driven by an SsrB-binding region upstream of flhDC that appears to have evolved in STM following divergence from SBG. These data reveal a divergent regulatory circuit in non-coding DNA that reduces flagellar gene expression to evade host defenses.
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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".