The sensor of the bacterial histidine kinase CpxA is a novel dimer of extracytoplasmic Per-ARNT-Sim domains
Bibliographic record
Abstract
Histidine kinases are key bacterial sensors that recognize diverse environmental stimuli. While mechanisms of phosphorylation and phosphotransfer by cytoplasmic kinase domains are relatively well-characterized, the ways in which extracytoplasmic sensor domains regulate activation remain mysterious. The Cpx envelope stress response is a conserved Gram-negative two-component system which is controlled by the sensor kinase CpxA. We report the structure of the Escherichia coli CpxA sensor domain (CpxA-SD) as a globular Per-ARNT-Sim (PAS)-like fold highly similar to that of Vibrio parahaemolyticus CpxA as determined by X-ray crystallography. Because sensor kinase dimerization is important for signaling, we used AlphaFold2 to model CpxA-SD in the context of its connected transmembrane domains, which yielded a novel dimer of PAS domains possessing a distinct dimer organization compared to previously characterized sensor domains. Gain of function cpxA∗ alleles map to the dimer interface, and mutation of other residues in this region also leads to constitutive activation. CpxA activation can be suppressed by mutations that restore inter-monomer interactions, suggesting that inhibitory interactions between CpxA-SD monomers are the major point of control for CpxA activation and signaling. Searching through hundreds of structural homologs revealed the sensor domain of Pseudomonas aeruginosa sensor kinase PfeS as the only PAS structure in the same novel dimer orientation as CpxA, suggesting that our dimer orientation may be utilized by other extracytoplasmic PAS domains. Overall, our findings provide insight into the diversity of the organization of PAS sensory domains and how they regulate sensor kinase activation.
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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".