Regulation of PKD2 channel function by TACAN
Bibliographic record
Abstract
Autosomal dominant polycystic kidney disease is caused by mutations in the membrane receptor PKD1 or the cation channel PKD2. TACAN (also termed TMEM120A), recently reported as an ion channel in neurons for mechanosensing and pain sensing, is also distributed in diverse non-neuronal tissues, such as kidney, heart and intestine, suggesting its involvement in other functions. In this study, we found that TACAN is in a complex with PKD2 in native renal cell lines. Using the two-electrode voltage clamp in Xenopus oocytes, we found that TACAN inhibits the channel activity of PKD2 gain-of-function mutant F604P. TACAN fragments containing the first and last transmembrane domains interacted with the PKD2 C- and N-terminal fragments, respectively. The TACAN N-terminus acted as a blocking peptide, and TACAN inhibited the function of PKD2 by the binding of PKD2 with TACAN. By patch clamping in mammalian cells, we found that TACAN inhibits both the single-channel conductance and the open probability of PKD2 and mutant F604P. PKD2 co-expressed with TACAN, but not PKD2 alone, exhibited pressure sensitivity. Furthermore, we found that TACAN aggravates PKD2-dependent tail curvature and pronephric cysts in larval zebrafish. In summary, this study revealed that TACAN acts as a PKD2 inhibitor and mediates mechanosensitivity of the PKD2-TACAN channel complex. KEY POINTS: TACAN inhibits the function of PKD2 in vitro and in vivo. TACAN N-terminal S1-containing fragment T160X interacts with the PKD2 C-terminal fragment N580-L700, and its C-terminal S6-containing fragment L296-D343 interacts with the PKD2 N-terminal A594X. TACAN inhibits the function of the PKD2 channel by physical interaction. The complex of PKD2 with TACAN, but not PKD2 alone, confers mechanosensitivity.
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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) | 0.001 | 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".