PKA Reduces the Rat and Human KCa3.1 Current, CaM Binding, and Ca<sup>2+</sup>Signaling, Which Requires Ser332/334 in the CaM-Binding C Terminus
Bibliographic record
Abstract
The Ca2+-dependent K+channel, KCa3.1 (KCNN4/IK/SK4), is widely expressed and contributes to cell functions that include volume regulation, migration, membrane potential, and excitability. KCa3.1 is now considered a therapeutic target for several diseases, including CNS disorders involving microglial activation; thus, we need to understand how KCa3.1 function is regulated. KCa3.1 gating and trafficking require calmodulin binding to the two ends of the CaM-binding domain (CaMBD), which also contains three conserved sites for Ser/Thr kinases. Although cAMP protein kinase (PKA) signaling is important in many cells that use KCa3.1, reports of channel regulation by PKA are inconsistent. We first compared regulation by PKA of native rat KCa3.1 channels in microglia (and the microglia cell line, MLS-9) with human KCa3.1 expressed in HEK293 cells. In all three cells, PKA activation with Sp-8-Br-cAMPS decreased the current, and this was prevented by the PKA inhibitor, PKI14–22. Inhibiting PKA with Rp-8-Br-cAMPS increased the current in microglia. Mutating the single PKA site (S334A) in human KCa3.1 abolished the PKA-dependent regulation. CaM-affinity chromatography showed that CaM binding to KCa3.1 was decreased by PKA-dependent phosphorylation of S334, and this regulation was absent in the S334A mutant. Single-channel analysis showed that PKA decreased the open probability in wild-type but not S334A mutant channels. The same decrease in current for native and wild-type expressed KCa3.1 channels (but not S334A) occurred when PKA was activated through the adenosine A2a receptor. Finally, by decreasing the KCa3.1 current, PKA activation reduced Ca2+-release-activated Ca2+entry following activation of metabotropic purinergic receptors in microglia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.004 | 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".