Stimulatory and inhibitory protein kinase C consensus sequences regulate the cystic fibrosis transmembrane conductance regulator
Bibliographic record
Abstract
Protein kinase C (PKC) phosphorylation stimulates the cystic fibrosis transmembrane conductance regulator (CFTR) channel and enhances its activation by protein kinase A (PKA) through mechanisms that remain poorly understood. We have examined the effects of mutating consensus sequences for PKC phosphorylation and report here evidence for both stimulatory and inhibitory sites. Sequences were mutated in subsets and the mutants characterized by patch clamping. Activation of a 4CA mutant (S707A/S790A/T791A/S809A) by PKA was similar to that of wild-type CFTR and was enhanced by PKC, whereas responses of 3CA (T582A/T604A/S641A) and 2CA (T682A/S686A) channels to PKA were both drastically reduced (>90%). When each mutation in the 3CA and 2CA constructs was studied individually in a wild-type background, T582, T604, and S686 were found to be essential for PKA activation. Responses were restored when these three residues were reintroduced simultaneously into a 9CA mutant lacking all nine PKC consensus sequences (R6CA revertant); however, PKC phosphorylation was not required for this rescue. Nevertheless, two of the sites (T604 and S686) were phosphorylated in vitro, and PKC alone partially activated wild-type CFTR, the 4CA mutant, and the point mutants T582A and T604A, but not S686A channels, indicating that PKC does act at S686. The region encompassing S641 and T682 is inhibitory, because S641A enhanced activation by PKA, and T682A channels had 4-fold larger responses to PKC compared to wild-type channels. These results identify functionally important PKC consensus sequences on CFTR and will facilitate studies of its convergent regulation by PKC and PKA.
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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) | 0.002 | 0.001 |
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".