Phosphorylation and Activation of RhoA by ERK in Response to Epidermal Growth Factor Stimulation
Bibliographic record
Abstract
The small GTPase RhoA has been implicated in various cellular activities, including the formation of stress fibers, cell motility, and cytokinesis. In addition to the canonical GTPase cycle, recent findings have suggested that phosphorylation further contributes to the tight regulation of Rho GTPases. Indeed, RhoA is phosphorylated on serine 188 (188S) by a number of protein kinases. We have recently reported that Rac1 is phosphorylated on threonine 108 (108T) by extracellular signal-regulated kinases (ERK) in response to epidermal growth factor (EGF) stimulation. Here, we provide evidence that RhoA is phosphorylated by ERK on 88S and 100T in response to EGF stimulation. We show that ERK interacts with RhoA and that this interaction is dependent on the ERK docking site (D-site) at the C-terminus of RhoA. EGF stimulation enhanced the activation of the endogenous RhoA. The phosphomimetic mutant, GFP-RhoA S88E/T100E, when transiently expressed in COS-7 cells, displayed higher GTP-binding than wild type RhoA. Moreover, the expression of GFP-RhoA S88E/T100E increased actin stress fiber formation in COS-7 cells, which is consistent with its higher activity. In contrast to Rac1, phosphorylation of RhoA by ERK does not target RhoA to the nucleus. Finally, we show that regardless of the phosphorylation status of RhoA and Rac1, substitution of the RhoA PBR with the Rac1 PBR targets RhoA to the nucleus and substitution of Rac1 PBR with RhoA PBR significantly reduces the nuclear localization of Rac1. In conclusion, ERK phosphorylates RhoA on 88S and 100T in response to EGF, which upregulates RhoA activity.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".