Cell confluence regulates claudin-2 expression: possible role for ZO-1 and Rac
Bibliographic record
Abstract
Claudin-2 (Cldn-2) is a channel-forming tight junction (TJ) protein in the proximal tubules that mediates paracellular Na + transport and has also emerged as a regulator of proliferation and migration. Expression of Cldn-2 is altered by numerous stimuli, but the underlying mechanisms remain incompletely understood. Here we show that Cldn-2 protein and mRNA expression were low in subconfluent tubular cells and increased during junction maturation. Cldn-1 or occludin did not exhibit similar confluence-dependence. Conversely, disruption of TJs by Ca 2+ removal or silencing of zonula occludens-1 (ZO-1) or ZO-2 induced a large drop in Cldn-2 abundance. Immunofluorescent staining revealed a more uneven Cldn-2 staining in nascent, Cldn-1-positive TJs. Subconfluence and ZO-1 silencing augmented Cldn-2 degradation and reduced Cldn-2 promoter activity, suggesting that insertion into the TJs slows Cldn-2 turnover. Indeed, blocking endocytosis or lysosomal degradation increased Cldn-2 abundance. Cell confluence increased expression of the junctional adapters ZO-1 and -2, and the small GTPase Rac, and elevated Rac activity and p21-activated kinase (Pak) phosphorylation, suggesting that they might mediate confluence-dependent Cldn-2 regulation. Indeed, Rac silencing or Pak inhibition strongly reduced Cldn-2 protein abundance, which was likely the combined effect on turnover, as these interventions reduced Cldn-2 promoter activity and augmented Cldn-2 degradation. Taken together, our data suggest that TJ integrity and maturity, ZO-1 expression/TJ localization, and Rac/Pak control Cldn-2 degradation and synthesis. A feedback mechanism connecting Cldn-2 expression with junction remodeling, e.g., during wound healing, epithelial-mesenchymal transition, or tumor metastasis formation, may have important downstream effects on permeability, proliferation, and migration.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".