Tau hyperphosphorylation impairs cooperative binding to microtubules and perturbs organelle trafficking in neurons
Bibliographic record
Abstract
Abstract Tau, a neuronal microtubule-associated protein (MAP), organizes the axonal cytoskeleton and regulates intracellular transport. Tau hyperphosphorylation is linked to neurodegeneration in tauopathies including Alzheimer’s disease. Tau binds microtubules cooperatively to form cohesive envelopes, which are thought to control access to the microtubule lattice and regulate the activity of motor proteins and other microtubule-associated proteins. However, how disease-related perturbations affect tau dynamics and its function as a selective barrier to intracellular transport remains unclear. Using tau phospho-variants in vitro and in live neurons, we show that tau hyperphosphorylation disrupts cooperative microtubule binding and dysregulates lysosome transport. Hyperphosphorylated tau does not form envelopes, distributes more uniformly along the axon, and dissociates faster from microtubules. Tau weakly inhibits KIF5C motility, but strongly inhibits KIF1A. Hyperphosphorylation reduces KIF5C inhibition but increases KIF1A inhibition by decreasing processivity and accelerating detachment. Consistent with these effects, hyperphosphorylated tau alters lysosome transport in neurons. While phospho-resistant tau inhibits processive lysosome motility, hyperphosphorylated tau weakens tau-mediated regulation of lysosome transport, mimicking tau knockout neurons that exhibit enhanced processivity. Altogether, these findings show that hyperphosphorylation disrupts tau envelopes and impairs lysosome trafficking, likely contributing to early defects in degradative pathways that drive neurodegeneration.
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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) | 0.002 | 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".