P1‐106: A MULTIPLEX MASS SPECTROMETRY METHOD FOR CHARACTERIZATION AND QUANTIFICATION OF α‐ AND β‐SYNUCLEINS IN BRAIN TISSUE: APPLICATION TO TRANSGENIC MOUSE MODELS OF PARKINSON'S DISEASE
Bibliographic record
Abstract
α-Synuclein deposits are the primary neuropathological finding in dementia with Lewy bodies and are found as a co-pathology in approximately half of Alzheimer's disease cases. Animal models used to study synuclein pathology include those overexpressing α-synuclein and with mutations linked to familial Parkinson's disease (e.g. mutations in SNCA, LRRK2, etc.). Among these are models that display cognitive deficits, and also cortical α-synuclein aggregates as seen in dementia with Lewy bodies. Analysis of α-synuclein in brain tissue from both humans and mouse models by traditional antibody-based methods (e.g. immunoassay, western blot) has helped in the characterization of the models; however, antibody-based methods have their limitations including indirect analyte detection, lack of selectivity and challenges with multiplexing targets. As such, it would be advantageous to develop a new tool using mass spectrometry, which offers improved selectivity and multiplexing ability, for direct detection of synucleins and their modified forms in disease. A multiple reaction monitoring high-resolution liquid chromatography tandem mass spectrometry method was developed to quantify both soluble α- and β-synucleins in brain tissue homogenate. The method monitored six tryptic peptides from the α-synuclein sequence, which included three regions unique to α-synuclein and three regions shared between α- and β-synuclein. Synucleins were enriched from brain homogenate by heat treatment and quantification was achieved by addition of uniformly N-labeled human α-synuclein as an internal standard. The method was then applied to the characterization of brain tissue from wild-type and transgenic mouse models of synucleinopathies. With the multiplex mass spectrometry method, total α-synuclein and combined α- and β-synuclein were quantified in a single measurement. The tool also enabled differentiation of species-specific contributions to α-synclein burden in a transgenic model expressing both mouse and human synuclein. Finally, by monitoring multiple tryptic peptides from synuclein, peptide-specific profile differences were observed that may reflect post-translational modifications along the protein sequence. Mass spectrometry is a selective and cost-effective alternative to antibody-based methods for quantitation and characterization of synucleins. Ongoing applications of this tool include detailed characterization of α-synuclein pathology in experimental mouse models and human tissues.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".