Expression of ENaC and other Transport Proteins in <i>Xenopus</i> Oocytes is Modulated by Intracellular Na<sup>+</sup>
Bibliographic record
Abstract
The expression of the epithelial Na+ channel (ENaC) is tissue-specific and dependent on a variety of mediators and interacting proteins. Here we examined the role of intracellular Na+ ([Na+](i)) as a modulator of the expression of rat ENaC in Xenopus laevis oocytes. We manipulated [Na+](i) of ENaC-expressing oocytes in the range of 0-20 mM by incubating in extracellular solutions of different [Na+](o). Electrophysiological, protein biochemical and fluorescence optical methods were used to determine the effects of different [Na+]i on ENaC expression and membrane abundance. In voltage-clamp experiments we found that amiloride-sensitive ENaC current (Iami) and conductance (Gami) peak at a [Na+](i) of approximately 10 mM Na+, but were significantly reduced in 5 mM and 20 mM [Na+](i). Fluorescence intensity of EGFP-ENaC-expressing oocytes also followed a bell-shaped curve with a maximum at approximately 10 mM [Na+](i). In Western blot experiments with specific anti-ENaC antibodies the highest protein expression was found in ENaC-expressing oocytes with [Na+](i) of 10-15 mM. Since ENaC is also highly permeable for Li+, we incubated ENaC-expressing oocytes in different Li+ concentrations and found a peak of Iami and Gami with 5 mM Li+. The influence of [Na+](i) on the expression is not ENaC-specific, since expression of a Cl(-) channel (CFTR) and a Na+/glucose cotransporter (SGLT1) showed the same dependence on [Na+](i). We conclude that specific concentrations of Na+ and Li+ influence the expression and abundance of ENaC and other transport proteins in the plasma membrane in Xenopus laevis oocytes. Furthermore, we suggest the existence of a general mechanism dependent on monovalent cations that optimizes the expression of membrane proteins.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".