Familial FTDP-17 Missense Mutations Inhibit Microtubule Assembly-promoting Activity of Tau by Increasing Phosphorylation at Ser202 in Vitro
Bibliographic record
Abstract
In Alzheimer disease (AD), frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17) and other tauopathies, tau accumulates and forms paired helical filaments (PHFs) in the brain. Tau isolated from PHFs is phosphorylated at a number of sites, migrates as approximately 60-, 64-, and 68-kDa bands on SDS-gel, and does not promote microtubule assembly. Upon dephosphorylation, the PHF-tau migrates as approximately 50-60-kDa bands on SDS-gels in a manner similar to tau that is isolated from normal brain and promotes microtubule assembly. The site(s) that inhibits microtubule assembly-promoting activity when phosphorylated in the diseased brain is not known. In this study, when tau was phosphorylated by Cdk5 in vitro, its mobility shifted from approximately 60-kDa bands to approximately 64- and 68-kDa bands in a time-dependent manner. This mobility shift correlated with phosphorylation at Ser(202), and Ser(202) phosphorylation inhibited tau microtubule-assembly promoting activity. When several tau point mutants were analyzed, G272V, P301L, V337M, and R406W mutations associated with FTDP-17, but not nonspecific mutations S214A and S262A, promoted Ser(202) phosphorylation and mobility shift to a approximately 68-kDa band. Furthermore, Ser(202) phosphorylation inhibited the microtubule assembly-promoting activity of FTDP-17 mutants more than of WT. Our data indicate that FTDP-17 missense mutations, by promoting phosphorylation at Ser(202), inhibit the microtubule assembly-promoting activity of tau in vitro, suggesting that Ser(202) phosphorylation plays a major role in the development of NFT pathology in AD and related tauopathies.
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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".