Dissecting the Molecular Pathway Involved in PLK2 Kinase-mediated α-Synuclein-selective Autophagic Degradation
Bibliographic record
Abstract
Increasing lines of evidence support the causal link between α-synuclein (α-syn) accumulation in the brain and Parkinson's disease (PD) pathogenesis. Therefore, lowering α-syn protein levels may represent a viable therapeutic strategy for the treatment of PD and related disorders. We recently described a novel selective α-syn degradation pathway, catalyzed by the activity of the Polo-like kinase 2 (PLK2), capable of reducing α-syn protein expression and suppressing its toxicity in vivo . However, the exact molecular mechanisms underlying this degradation route remain elusive. In the present study we report that among PLK family members, PLK3 is also able to catalyze α-syn phosphorylation and degradation in living cells. Using pharmacological and genetic approaches, we confirmed the implication of the macroautophagy on PLK2-mediated α-syn turnover, and our observations suggest a concomitant co-degradation of these two proteins. Moreover, we showed that the N-terminal region of α-syn is important for PLK2-mediated α-syn phosphorylation and degradation and is implicated in the physical interaction between the two proteins. We also demonstrated that PLK2 polyubiquitination is important for PLK2·α-syn protein complex degradation, and we hypothesize that this post-translational modification may act as a signal for the selective recognition by the macroautophagy machinery. Finally, we observed that the PD-linked mutation E46K enhances PLK2-mediated α-syn degradation, suggesting that this mutated form is a bona fide substrate of this degradation pathway. In conclusion, our study provides a detailed description of the new degradation route of α-syn and offers new opportunities for the development of therapeutic strategies aiming to reduce α-syn protein accumulation and toxicity.
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 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".