Combining light-induced aggregation and biotin proximity labeling implicates endolysosomal proteins in early α-synuclein oligomerization
Bibliographic record
Abstract
Alpha-synuclein (α-syn) aggregation is a defining feature of Parkinson's disease (PD) and related synucleinopathies. Despite significant research efforts focused on understanding α-syn aggregation mechanisms, the early stages of this process remain elusive, largely due to limitations in experimental tools that lack the temporal resolution to capture these dynamic events. Here, we introduce UltraID-LIPA, an innovative platform that combines the light-inducible protein aggregation (LIPA) system with the UltraID proximity-dependent biotinylation assay to identify α-syn-interacting proteins and uncover key mechanisms driving its oligomerization. UltraID-LIPA successfully identified 38 α-syn-interacting proteins, including both established and previously unreported candidates, highlighting the accuracy and robustness of the approach. Notably, a strong interaction with endolysosomal and membrane-associated proteins was observed, supporting the hypothesis that interactions with membrane-bound organelles are pivotal in the early stages of α-syn aggregation. This powerful platform provides new insights into dynamic protein aggregation events, enhancing our understanding of synucleinopathies and other proteinopathies.
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".