Alternative splicing of GluN1 gates glycine site–dependent nonionotropic signaling by NMDAR receptors
Bibliographic record
Abstract
-methyl-D-aspartate (NMDA) receptors (NMDARs), a principal subtype of excitatory neurotransmitter receptor, are composed as tetrameric assemblies of two glycine-binding GluN1 subunits and two glutamate-binding GluN2 subunits. NMDARs can signal nonionotropically through binding of glycine alone to its cognate site on GluN1. A consequence of this signaling by glycine is that NMDARs are primed such that subsequent gating, produced by glycine and glutamate, drives receptor internalization. The GluN1 subunit contains eight alternatively spliced isoforms produced by including or excluding the N1 and the C1, C2, or C2' polypeptide cassettes. Whether GluN1 alternative splicing affects nonionotropic signaling by NMDARs is a major outstanding question. Here, we discovered that glycine priming of recombinant NMDARs critically depends on GluN1 isoforms lacking the N1 cassette; glycine priming is blocked in splice variants containing N1. On the other hand, the C-terminal cassettes-C1, C2, or C2'-each permit glycine signaling. In wild-type mice, we found glycine-induced nonionotropic signaling at synaptic NMDARs in CA1 hippocampal pyramidal neurons. This nonionotropic signaling by glycine to synaptic NMDARs was prevented in mice we engineered, such that GluN1 obligatorily contained N1. We discovered in wild-type mice that, in contrast to pyramidal neurons, synaptic NMDARs in CA1 inhibitory interneurons were resistant to glycine priming. But we recapitulated glycine priming in inhibitory interneurons in mice engineered such that GluN1 obligatorily lacked the N1 cassette. Our findings reveal a previously unsuspected molecular function for alternative splicing of GluN1 in controlling nonionotropic signaling of NMDARs by activating the glycine site.
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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".