MINK and TNIK Differentially Act on Rap2-Mediated Signal Transduction to Regulate Neuronal Structure and AMPA Receptor Function
Bibliographic record
Abstract
Misshapen/NIKs (Nck-interacting kinases)-related kinase (MINK) and closely related TRAF2/Nck-interacting kinase (TNIK) are proteins that specifically bind to activated Rap2 and are thus hypothesized to relay its downstream signal transduction. Activated Rap2 has been found to stimulate dendritic pruning, reduce synaptic density and cause removal of synaptic AMPA receptors (AMPA-Rs) (Zhu et al., 2005; Fu et al., 2007). Here we report that MINK and TNIK are postsynaptically enriched proteins whose clustering within dendrites is bidirectionally regulated by the activation state of Rap2. Expression of MINK and TNIK in neurons is required for normal dendritic arborization and surface expression of AMPA receptors. Overexpression of a truncated MINK mutant unable to interact with Rap2 leads to reduced dendritic branching and this MINK-mediated effect on neuronal morphology is dependent upon Rap2 activation. While similarly truncated TNIK also reduces neuronal complexity, its effect does not require Rap2 activity. Furthermore, Rap2-mediated removal of surface AMPA-Rs from spines is entirely abrogated by coexpression of MINK, but not TNIK. Thus, although both MINK and TNIK bind GTP-bound Rap2, these kinases employ distinct mechanisms to modulate Rap2-mediated signaling. MINK appears to antagonize Rap2 signal transduction by binding to activated Rap2. We suggest that MINK interaction with Rap2 plays a critical role in maintaining the morphological integrity of dendrites and synaptic transmission.
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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) | 0.001 | 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".