14-3-3ζ Mediates Tau Aggregation in Human Neuroblastoma M17 Cells
Bibliographic record
Abstract
Microtubule-associated protein tau is the major component of paired helical filaments (PHFs) associated with the neuropathology of Alzheimer's disease (AD). Tau in the normal brain binds and stabilizes microtubules. Tau isolated from PHFs is hyperphosphorylated, which prevents it from binding to microtubules. Tau phosphorylation has been suggested to be involved in the development of NFT pathology in the AD brain. Recently, we showed that 14-3-3ζ is bound to tau in the PHFs and when incubated in vitro with 14-3-3ζ, tau formed amorphous aggregates, single-stranded straight filaments, double stranded ribbon-like filaments and PHF-like filaments that displayed close resemblance with corresponding ultrastructures of AD brain. Surprisingly however, phosphorylated and non-phosphorylated tau aggregated in a similar manner, indicating that tau phosphorylation does not affect in vitro tau aggregation (Qureshi et al (2013) Biochemistry 52, 6445-6455). In this study, we have examined the role of tau phosphorylation in tau aggregation in cellular level. We have found that in human M17 neuroblastoma cells, tau phosphorylation by GSK3β or PKA does not cause tau aggregation, but promotes 14-3-3ζ-induced tau aggregation by destabilizing microtubules. Microtubule disrupting drugs also promoted 14-3-3ζ-induced tau aggregation without changing tau phosphorylation in M17 cell. In vitro, when incubated with 14-3-3ζ and microtubules, nonphosphorylated tau bound to microtubules and did not aggregate. Phosphorylated tau on the other hand did not bind to microtubules and aggregated. Our data indicate that microtubule-bound tau is resistant to 14-3-3ζ-induced tau aggregation and suggest that tau phosphorylation promotes tau aggregation in the brain by detaching tau from microtubules and thus making it accessible to 14-3-3ζ.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".