JNK3 Couples the Neuronal Stress Response to Inhibition of Secretory Trafficking
Bibliographic record
Abstract
Secretory trafficking through the Golgi complex is critical for neuronal development, function, and stress response. Altered secretion is associated with the pathogenesis of various neurological diseases. We found that c-Jun amino-terminal kinase 3 (JNK3) inhibited secretory trafficking by promoting the depletion of phosphatidylinositol 4-phosphate (PI4P) in the Golgi complex of COS7 cells and primary rat neurons. Exposure of cultured primary rat neurons to excitotoxic concentrations of NMDA (N-methyl-d-aspartate), an agonist of a class of ionotropic glutamate receptors, or overexpression of zD17 (a palmitoyl transferase) resulted in JNK3 palmitoylation and association with the Golgi complex. Analysis of mutant constructs of JNK3 indicated that Golgi association was independent of its kinase activity but depended on its palmitoylation. The association of JNK3 with the Golgi in cultured neurons decreased the secretory trafficking of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor subunit GluR1 (glutamate receptor subunit 1), a component of ionotropic glutamate receptors found at glutamatergic synapses. Palmitoylated JNK3 bound to the phosphatase Sac1, increasing its abundance at the Golgi and thereby decreasing the abundance of PI4P, a lipid necessary for post-Golgi trafficking. Disrupting the JNK3-Sac1 interaction with two synthetic peptides prevented the loss of surface GluR1 and preserved synaptic integrity in cultured neurons exposed to NMDA. Together, our results suggest that JNK3 participates in an adaptive response to neuronal hyperexcitation by impeding secretory trafficking at the Golgi complex.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
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".