A kainate receptor subunit promotes the recycling of the neuron-specific K+-Cl− co-transporter KCC2 in hippocampal neurons
Bibliographic record
Abstract
Synaptic inhibition depends on a transmembrane gradient of chloride, which is set by the neuron-specific K + -Cl − co-transporter KCC2. Reduced KCC2 levels in the neuronal membrane contribute to the generation of epilepsy, neuropathic pain, and autism spectrum disorders; thus, it is important to characterize the mechanisms regulating KCC2 expression. In the present study, we determined the role of KCC2-protein interactions in regulating total and surface membrane KCC2 expression. Using quantitative immunofluorescence in cultured mouse hippocampal neurons, we discovered that the kainate receptor subunit GluK2 and the auxiliary subunit Neto2 significantly increase the total KCC2 abundance in neurons but that GluK2 exclusively increases the abundance of KCC2 in the surface membrane. Using a live cell imaging assay, we further determined that KCC2 recycling primarily occurs within 1–2 h and that GluK2 produces an ∼40% increase in the amount of KCC2 recycled to the membrane during this time period. This GluK2-mediated increase in surface recycling translated to a significant increase in KCC2 expression in the surface membrane. Moreover, we found that KCC2 recycling is enhanced by protein kinase C-mediated phosphorylation of the GluK2 C-terminal residues Ser-846 and Ser-868. Lastly, using gramicidin-perforated patch clamp recordings, we found that the GluK2-mediated increase in KCC2 recycling to the surface membrane translates to a hyperpolarization of the reversal potential for GABA (E GABA ). In conclusion, our results have revealed a mechanism by which kainate receptors regulate KCC2 expression in the hippocampus.
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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".