Polycystin-2 Cation Channel Function Is under the Control of Microtubular Structures in Primary Cilia of Renal Epithelial Cells
Bibliographic record
Abstract
Mutations in the gene encoding polycystin-2 (PC2) result in autosomal dominant polycystic kidney disease and defects in left-right asymmetry during embryogenesis. PC2 is a TRP-type Ca2+-permeable non-selective cation channel, which is expressed in kidney and other organs. PC2 is present and functional in microtubule-containing primary cilia of renal epithelial cells. However, no information is yet available as to whether PC2 interacts with microtubules. Here, we assessed the role of microtubular dynamics in regulating PC2 channel function in primary cilia. Isolated ciliary membranes from LLC-PK1 epithelial cells were reconstituted in a lipid bilayer system. The acute addition of the microtubular disrupter colchicine (15 μm) rapidly abolished, whereas the addition of the microtubular stabilizer paclitaxel (taxol, 15 μm) increased ciliary PC2 channel activity. The further addition of α-tubulin plus GTP also stimulated PC2 channel activity in ciliary membranes. However, α-tubulin and GTP had no effect on in vitro translated PC2. Using the yeast two-hybrid assay, we found that PC2 interacts with the microtubule-dependent motor kinesin-2 subunit KIF3A, a protein involved in polycystic kidney disease. The interaction occurred through the carboxyl termini domain of both proteins, which was further confirmed by in vitro glutathione S-transferase pull-down and dot blot overlay assays. Co-immunoprecipitation experiments showed that PC2 and KIF3A are in the same complex in native HEK293, Madin-Darby canine kidney cells (MDCK), and LLC-PK1 cells. Immunofluorescent staining also showed substantial PC2 and KIF3A co-localization in primary cilia of renal epithelial cells. The data indicate that microtubular organization regulates PC2 function, which may explain, among others, the regulatory role of PC2 in the sensory function of primary cilia.
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) | 0.000 | 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".