MARK4 Is a Novel Microtubule-associated Proteins/Microtubule Affinity-regulating Kinase That Binds to the Cellular Microtubule Network and to Centrosomes
Bibliographic record
Abstract
The MARK protein kinases were originally identified by their ability to phosphorylate a serine motif in the microtubule-binding domain of tau that is critical for microtubule binding. Here, we report the cloning and expression of a novel human paralog, MARK4, which shares 75% overall homology with MARK1-3 and is predominantly expressed in brain. Homology is most pronounced in the catalytic domain (90%), and MARK4 readily phosphorylates tau and the related microtubule-associated protein 2 (MAP2) and MAP4. In contrast to the three paralogs that all exhibit uniform cytoplasmic localization, MARK4 colocalizes with the centrosome and with microtubules in cultured cells. Overexpression of MARK4 causes thinning out of the microtubule network, concomitant with a reorganization of microtubules into bundles. In line with these findings, we show that a tandem affinity-purified MARK4 protein complex contains alpha-, beta-, and gamma-tubulin. In differentiated neuroblastoma cells, MARK4 is localized prominently at the tips of neurite-like processes. We suggest that although the four MARK/PAR-1 kinases might play multiple cellular roles in concert with different targets, MARK4 is likely to be directly involved in microtubule organization in neuronal cells and may contribute to the pathological phosphorylation of tau 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".