Bidirectional Control of Postsynaptic Density-95 (PSD-95) Clustering by Huntingtin
Bibliographic record
Abstract
Huntington disease is associated with early alterations in corticostriatal synaptic function that precede cell death, and it is postulated that ameliorating such changes may delay clinical onset and/or prevent neurodegeneration. Although many of these synaptic alterations are thought to be attributable to a toxic gain of function of the mutant huntingtin protein, the role that nonpathogenic huntingtin (HTT) plays in synaptic function is relatively unexplored. Here, we compare the immunocytochemical localization of a major postsynaptic scaffolding protein, PSD-95, in striatal neurons from WT mice and mice overexpressing HTT with 18 glutamine repeats (YAC18, nonpathogenic). We found that HTT overexpression resulted in a palmitoylation- and BDNF-dependent increase in PSD-95 clustering at synaptic sites in striatal spiny projection neurons (SPNs) co-cultured with cortical neurons. Surprisingly, the latter effect was mediated presynaptically, as HTT overexpression in cortical neurons alone was sufficient to increase PSD-95 clustering in the postsynaptic SPNs. In contrast, antisense oligonucleotide knockdown of HTT in WT co-cultures resulted in a significant reduction of PSD-95 clustering in SPNs. Notably, despite these bidirectional changes in PSD-95 clustering, we did not observe an alteration in basal electrophysiological measures of AMPA and NMDA receptors. Thus, unlike in previous studies in the hippocampus, enhanced or decreased PSD-95 clustering alone was insufficient to drive AMPA or NMDA receptors into or out of SPN synapses. In all, our results demonstrate that nonpathogenic HTT can indeed influence synaptic protein localization and uncover a novel role of HTT in PSD-95 distribution.
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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) | 0.000 | 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".