Functional consequences of the over-expression of TRPC6 channels in HEK cells: impact on the homeostasis of zinc
Bibliographic record
Abstract
The canonical transient receptor potential 6 (TRPC6) protein is a non-selective cation channel able to transport essential trace elements like iron (Fe) and zinc (Zn) through the plasma membrane. Its over-expression in HEK-293 cells causes an intracellular accumulation of Zn, indicating that it could be involved in Zn transport. This finding prompted us to better understand the role played by TRPC6 in Zn homeostasis. Experiments done using the fluorescent probe FluoZin-3 showed that HEK cells possess an intracellular pool of mobilisable Zn present in compartments sensitive to the vesicular proton pump inhibitor Baf-A, which affects endo/lysosomes. TRPC6 over-expression facilitates the basal uptake of Zn and enhances the size of the pool of Zn sensitive to Baf-A. Quantitative RT-PCR experiments showed that TRPC6 over-expression does not affect the mRNA expression of Zn transporters (ZnT-1, ZnT-5, ZnT-6, ZnT-7, ZnT-9, Zip1, Zip6, Zip7, and Zip14); however it up-regulates the mRNA expression of metallothionein-I and -II. This alters the Zn buffering capacities of the cells as illustrated by the experiments done using the Zn ionophore Na pyrithione. In addition, HEK cells over-expressing TRPC6 grow slower than their parental HEK cells. This feature can be mimicked by growing HEK cells in a culture medium supplemented with 5 μM of Zn acetate. Finally, a proteomic analysis revealed that TRPC6 up-regulates the expression of the actin-associated proteins ezrin and cofilin-1, and changes the organisation of the actin cytoskeleton without changing the cellular actin content. Altogether, these data indicate that TRPC6 is participating in the transport of Zn and influences the Zn storage and buffering capacities of the cells.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".