MTMR4 Attenuates Transforming Growth Factor β (TGFβ) Signaling by Dephosphorylating R-Smads in Endosomes
Bibliographic record
Abstract
Homeostasis of Smad phosphorylation at its C-terminal SXS motif is essential for transforming growth factor beta (TGFbeta) signaling. Whereas it is known that TGFbeta signaling can be terminated by phosphatases, which dephosphorylate R-Smads in the nucleus, it is unclear whether there are any cytoplasmic phosphatase(s) that can attenuate R-Smad phosphorylation and nuclear translocation. Here we demonstrate that myotubularin-related protein 4 (MTMR4), a FYVE domain-containing dual-specificity protein phosphatase (DSP), attenuates TGFbeta signaling by reducing the phosphorylation level of R-Smads in early endosomes. Co-immunoprecipitation experiments showed that endogenous MTMR4 interacts with phosphorylated R-Smads, and that this interaction is correlated with dephosphorylation of R-Smads. Further analysis showed that overexpression of MTMR4 resulted in the sequestration of activated Smad3 in the early endosomes, thus reducing its nuclear translocation. However, both point mutations at the conserved catalytic site of the phosphatase (MTMR4-C407S) and small interference RNA of endogenous Mtmr4 expression led to sustained Smad3 activation. This work therefore suggests that MTMR4 plays an important role in preventing the overactivation of TGFbeta signaling by dephosphorylating activated R-Smads that have been trafficked to early endosomes.
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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".