Activation-pathway transitions in human voltage-gated proton channels revealed by a non-canonical fluorescent amino acid
Bibliographic record
Abstract
Abstract Voltage-dependent gating of the voltage-gated proton channels (H V 1) remains poorly understood, partly because of the difficulty of obtaining direct measurements of voltage sensor movement in the form of gating currents. To circumvent this problem, we have implemented patch-clamp fluorometry in combination with the incorporation of the fluorescent non-canonical amino acid Anap to monitor channel opening and movement of the S4 segment. Simultaneous recording of currents and fluorescence signals allows for direct correlation of these parameters and investigation of their dependence on voltage and the pH gradient (ΔpH). We present data that indicate that Anap incorporated in the S4 helix is quenched by an aromatic residue located in the S2 helix, and that motion of the S4 relative to this quencher is responsible for fluorescence increases upon depolarization. The kinetics of the fluorescence signal reveals the existence of a very slow transition in the deactivation pathway, which seems to be singularly regulated by ΔpH. Our experiments also suggest that the voltage sensor can move after channel opening and that the absolute value of the pH can influence the channel opening step. These results shed light on the complexities of voltage-dependent opening of human H V 1 channels. Significance statement The activation mechanisms of voltage-gated proton channels (H V 1) are not well understood. Here we have combined patch-clamp fluorometry and a fluorescent non-canonical amino acid to uncover transitions in the activation pathway of human H V 1 that are modulated by voltage and the pH gradient.
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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) | 0.000 | 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 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".