Effects of Serine 129 Phosphorylation on α-Synuclein Aggregation, Membrane Association, and Internalization
Bibliographic record
Abstract
Although trace levels of phosphorylated α-synuclein (α-syn) are detectable in normal brains, nearly all α-syn accumulated within Lewy bodies in Parkinson disease brains is phosphorylated on serine 129 (Ser-129). The role of the phosphoserine residue and its effects on α-syn structure, function, and intracellular accumulation are poorly understood. Here, co-expression of α-syn and polo-like kinase 2 (PLK2), a kinase that targets Ser-129, was used to generate phosphorylated α-syn for biophysical and biological characterization. Misfolding and fibril formation of phosphorylated α-syn isoforms were detected earlier, although the fibrils remained phosphatase- and protease-sensitive. Membrane binding of α-syn monomers was differentially affected by phosphorylation depending on the Parkinson disease-linked mutation. WT α-syn binding to presynaptic membranes was not affected by phosphorylation, whereas A30P α-syn binding was greatly increased, and A53T α-syn was slightly lower, implicating distal effects of the carboxyl- on amino-terminal membrane binding. Endocytic vesicle-mediated internalization of pre-formed fibrils into non-neuronal cells and dopaminergic neurons matched the efficacy of α-syn membrane binding. Finally, the disruption of internalized vesicle membranes was enhanced by the phosphorylated α-syn isoforms, a potential means for misfolded extracellular or lumenal α-syn to access cytosolic α-syn. Our results suggest that the threshold for vesicle permeabilization is evident even at low levels of α-syn internalization and are relevant to therapeutic strategies to reduce intercellular propagation of α-syn misfolding.
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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".