Extracellular signal-regulated kinase and GEF-H1 mediate depolarization-induced Rho activation and paracellular permeability increase
Bibliographic record
Abstract
Plasma membrane depolarization activates the Rho/Rho kinase (ROK) pathway and thereby enhances myosin light chain (MLC) phosphorylation, which in turn is thought to be a key regulator of paracellular permeability. However, the upstream mechanisms that couple depolarization to Rho activation and permeability changes are unknown. Here we show that three different depolarizing stimuli (high extracellular K(+) concentration, the lipophilic cation tetraphenylphosphonium, or l-alanine, which is taken up by electrogenic Na(+) cotransport) all provoke robust phosphorylation of ERK in LLC-PK1 and Madin-Darby canine kidney (MDCK) cells. Importantly, inhibition of ERK prevented the depolarization-induced activation of Rho. Searching for the underlying mechanism, we have identified the GTP/GDP exchange factor GEF-H1 as the ERK-regulated critical exchange factor responsible for the depolarization-induced Rho activation. This conclusion is based on our findings that 1) depolarization activated GEF-H1 but not p115RhoGEF, 2) short interfering RNA-mediated GEF-H1 silencing eliminated the activation of the Rho pathway, and 3) ERK inhibition prevented the activation of GEF-H1. Moreover, we found that the Na(+)-K(+) pump inhibitor ouabain also caused ERK, GEF-H1, and Rho activation, partially due to its depolarizing effect. Regarding the functional consequences of this newly identified pathway, we found that depolarization increased paracellular permeability in LLC-PK1 and MDCK cells and that this effect was mitigated by inhibiting myosin using blebbistatin or a dominant negative (phosphorylation incompetent) MLC. Taken together, we propose that the ERK/GEF-H1/Rho/ROK/pMLC pathway could be a central mechanism whereby electrogenic transmembrane transport processes control myosin phosphorylation and regulate paracellular transport in the tubular epithelium.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".