Protein Kinase C-dependent Phosphorylation of Transient Receptor Potential Canonical 6 (TRPC6) on Serine 448 Causes Channel Inhibition
Bibliographic record
Abstract
TRPC6 is a cation channel in the plasma membrane that plays a role in Ca(2+) entry following the stimulation of a G(q)-protein coupled or tyrosine kinase receptor. A dysregulation of TRPC6 activity causes abnormal proliferation of smooth muscle cells and glomerulosclerosis. In the present study, we investigated the regulation of TRPC6 activity by protein kinase C (PKC). We showed that inhibiting PKC with GF1 or activating it with phorbol 12-myristate 13-acetate potentiated and inhibited agonist-induced Ca(2+) entry, respectively, into cells expressing TRPC6. Similar results were obtained when TRPC6 was directly activated with 1-oleyl-2-acetyl-sn-glycerol. Activation of the cells with carbachol increased the phosphorylation of TRPC6, an effect that was prevented by the inhibition of PKC. The target residue of PKC was identified by an alanine screen of all canonical PKC sites on TRPC6. Unexpectedly, all the mutants, including TRPC6(S768A) (a residue previously proposed to be a target for PKC), displayed PKC-dependent inhibition of channel activity. Phosphorylation prediction software suggested that Ser(448), in a non-canonical PKC consensus sequence, was a potential target for PKCδ. Ba(2+) and Ca(2+) entry experiments revealed that GF1 did not potentiate TRPC6(S448A) activity. Moreover, activation of PKC did not enhance the phosphorylation state of TRPC6(S448A). Using A7r5 vascular smooth muscle cells, which endogenously express TRPC6, we observed that a novel PKC isoform is involved in the inhibition of the vasopressin-induced Ca(2+) entry. Furthermore, knocking down PKCδ in A7r5 cells potentiated vasopressin-induced Ca(2+) entry. In summary, we provide evidence that PKCδ exerts a negative feedback effect on TRPC6 through the phosphorylation of Ser(448).
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".