Multiple histidines in the periplasmic domain of the <scp><i>S</i></scp><i>almonella enterica</i> sensor kinase <scp>SsrA</scp> enhance signaling in response to extracellular acidification
Bibliographic record
Abstract
The two-component regulatory system SsrA-SsrB in Salmonella enterica controls expression of a virulence gene program required for intracellular survival in host cells. SsrA signaling is induced within the acidic host vacuole in which the bacteria reside; however, the mechanism by which SsrA senses this intracellular environment is unknown. Here, we show that the periplasmic sensor domain of SsrA is enriched in histidine residues that increase SsrA signaling below external pH of 6. While no single histidine accounted for the full acid-responsiveness of SsrA, we localized the acid-responsiveness principally to five histidines in the C-terminal end of the periplasmic sensor domain, with input from additional histidines in the N-terminal end of the senor. A sensor mutant lacking critical pH-responsive histidines was defective for acid-promoted activity, yet retained basal activity similar to wild type at neutral pH, indicating that the role of these histidines is to enhance signaling in response to acidification. In support of this, a pH-blind mutant was insensitive to the vacuole acidification blocking activity of bafilomycin, and was attenuated for competitive fitness during infection of mice. Our data demonstrate that SsrA contains a histidine-rich periplasmic sensor that enhances signaling in response to the innate host defense of vacuolar acidification.
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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".