Interaction of Nck1 and PERK phosphorylated at Y<sup>561</sup>negatively modulates PERK activity and PERK regulation of pancreatic β-cell proinsulin content
Bibliographic record
Abstract
PERK, the PKR-like endoplasmic reticulum (ER) kinase, is an ER transmembrane serine/threonine protein kinase activated during ER stress. In this study, we provide evidence that the Src-homology domain-containing adaptor Nck1 negatively regulates PERK. We show that Nck directly binds to phosphorylated Y(561) in the PERK juxtamembrane domain through its SH2 domain. We demonstrate that mutation of Y(561) to a nonphosphorylatable residue (Y561F) promotes PERK activity, suggesting that PERK phosphorylation at Y(561) (pY(561)PERK) negatively regulates PERK. In agreement, we show that pY(561)PERK delays PERK activation and signaling during ER stress. Compatible with a role for PERK in pancreatic β-cells, we provide strong evidence that Nck1 contributes to PERK regulation of pancreatic β-cell proteostasis. In fact, we demonstrated that down-regulation of Nck1 in mouse insulinoma MIN6 cells results in faster dephosphorylation of pY(561)PERK, which correlates with enhanced PERK activation, increased insulin biosynthesis, and PERK-dependent increase in proinsulin content. Furthermore, we report that pancreatic islets in whole-body Nck1-knockout mice contain more insulin than control littermates. Together our data strongly suggest that Nck1 negatively regulates PERK by interacting with PERK and protecting PERK from being dephosphorylated at its inhibitory site pY(561) and in this way affects pancreatic β-cell proinsulin biogenesis.
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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 | 0.000 |
| 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".