Signaling by the heavy‐metal sensor CusS involves rearranged helical interactions in specific transmembrane regions
Bibliographic record
Abstract
Two-component systems (TCSs) play important roles in the adaptation of bacteria to stress. Despite their increasingly well understood mechanistic features, it remains poorly understood how TCSs transduce signals across membranes. Here, we use the E. coli Cu/Ag-responsive CusSR TCS as a model to investigate the roles of CusS transmembrane (TM) residues. Proline scanning of TM1 domain led to identification of the T17P, F18P, and S21P variants, which display higher kinase activities relative to wild type. A single point mutation, V202G, in the adjacent TM2 domain specifically suppresses the hyperactivities of these mutants. Disulfide crosslinking analysis demonstrated that T17 and V202 are situated in close proximity, and Cys residues substituted at those two positions form exclusive intramolecular crosslinks when CusS is in the signaling-inactive state. In the signaling-active variant of CusS, however, only intermolecular crosslinking between the two Cys residues could be observed, suggesting that destabilization of an intramolecular constraint and a subsequent rearrangement of helical interactions in this TM region is involved in the activation of CusS. An analogous TM helical interface in the P. aeruginosa heavy metal sensor kinase CzcS is also observed. Together, these results suggested a conserved transmembrane signal transduction mechanism in the heavy metal sensing TCSs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".