Phosphorylation of tau regulates its axonal transport by controlling its binding to kinesin
Bibliographic record
Abstract
Defective axonal transport has been proposed as an underlying mechanism that may give rise to neurodegeneration. We investigated the effect of phosphorylation on the axonal transport of tau, a neuronal protein that stabilizes microtubules and is hyperphosphorylated and mislocalized in Alzheimer's disease. We report here that specific inhibition of glycogen synthase kinase-3 (GSK-3) reduces tau phosphorylation and significantly decreases the overall rate of axonal transport of tau in rat cortical neurons. Tau mutants, with serine/threonine targets of GSK-3 mutated to glutamate to mimic a permanent state of phosphorylation, were transported at a significantly increased rate compared to wild-type tau. Conversely, tau mutants, in which alanine replaced serine/threonine to mimic permanent dephosphorylation, were transported at a decreased rate compared to wild-type tau. We also found that tau interacts with the light chain of kinesin-1 and that this is dependent on the phosphorylation state of tau. Tau phosphorylation by GSK-3 increased binding, and dephosphorylated tau exhibited a reduced association with kinesin-1. We conclude that GSK-3 phosphorylation of tau modulates its axonal transport by regulating binding to kinesin-1. Hyperphosphorylated tau in Alzheimer's disease appearing first in distal portions of axons may result from aberrant axonal transport of phosphorylated tau reported here.
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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) | 0.001 | 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".