PKCγ-induced trafficking of AMPA receptors in embryonic zebrafish depends on NSF and PICK1
Bibliographic record
Abstract
The trafficking of AMPA receptors (Rs) to and from synaptic membranes is a key component underlying synaptic plasticity mechanisms such as long-term potentiation (LTP) and long-term depression (LTD), and is likely important for synaptic development in embryonic organisms. However, some of the key biochemical components required for receptor trafficking in embryos are still unknown. Here, we report that in embryonic zebrafish, the activation of PKCgamma by phorbol 12-myristate 13-acetate, strongly potentiates the amplitude of AMPAR-mediated miniature excitatory postsynaptic currents (AMPA-mEPSCs) via a N-ethylmaleimide-sensitive fusion (NSF) and protein interacting with C-kinase-1 (PICK1)-dependent process. We found that the mEPSC potentiation is DAG- and Ca(2+)-dependent, and occurs on application of active PKCgamma. Peptides that prevent the association of NSF and PICK1 with the GluR2 subunit, and the actin-polymerization blocker, latrunculin B, prevented the increase in mEPSC amplitude. Also, application of tetanus toxin (TeTx), which cleaves SNARE proteins, also blocked the increase in mEPSC amplitude. Last, application of a 5 mM K(+) medium led to an enhancement in mEPSC amplitude that was prevented by addition of the PKCgamma and NSF-blocking peptides, and the NMDA receptor blocker, 2-amino-5-phosphonovaleric acid (APV). Thus, activation of PKCgamma is necessary for the activity-dependent trafficking of AMPARs in embryonic zebrafish. This process is NMDA and SNARE-dependent and requires AMPARs to associate with both NSF and PICK1. The present data further our understanding of AMPAR trafficking, and have important implications for synaptic development and synaptic plasticity.
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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".