Spatial coupling of endogenous Tau translation and degradation by neuroproteasomes in dendrites revealed by STARFISH
Bibliographic record
Abstract
Cells regulate protein synthesis, folding, and degradation to maintain proteostasis, and disruptions in these processes have been linked to neurodegenerative diseases. In Alzheimer’s disease (AD), the protein Tau mislocalizes from axons to the somatodendritic compartment and aggregates into pathological filaments. Although Tau aggregation is a hallmark of AD, the subcellular dynamics of its synthesis and degradation are not well characterized. Because nascent polypeptides are particularly susceptible to misfolding, local control of Tau synthesis and degradation may be essential to prevent aggregation. Here, we develop STARFISH, a method for visualizing the subcellular site of endogenous mRNA translation in primary neurons and in vivo with single-molecule sensitivity and near-codon resolution, without modifying the nascent polypeptide. Using STARFISH, we show that despite the broad distribution of Mapt mRNA, Tau is translated almost exclusively in neuronal dendrites, revealing an unexpected level of spatial regulation. We further identify that one-third of newly synthesized Tau is co- or peri-translationally degraded in dendrites by a neuronal-specific plasma membrane-associated proteasome, the neuroproteasome. Failure of neuroproteasome-mediated degradation leads to the protein synthesis-dependent accumulation of somatodendritically mislocalized Tau aggregates. These findings define a previously unrecognized proteostasis mechanism that counterbalances the constitutive physiological overproduction of Tau. We speculate that failure of this proteostasis system contributes directly to Tau aggregation in dendrites, defining a new pathomechanism in Alzheimer’s disease.
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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".