Proteomic identification of synaptic caspase substrates
Bibliographic record
Abstract
The dismantling and elimination of excess neurons and their connections (pruning) is essential for brain development and may be aberrantly reactivated in some neurodegenerative diseases. Growing evidence implicates caspase-mediated apoptotic and nonapoptotic cascades in the dysfunction and death of neurons in neurodegenerative disorders such as Alzheimer's, Parkinson, and Huntington's diseases. It is the cleaved caspase substrates that are the effectors of synapse elimination. However, their identities, specific cleavage sites, and functional consequences of cleavage are largely unknown. An important gap in our knowledge is a comprehensive catalog of synapse-specific or synapse-enriched caspase targets. Traditional biochemical approaches have revealed only a small number of neuronal caspase targets. Instead, we utilized a gel-based proteomics approach to enable the first global analysis of caspase-mediated cleavage events in mammalian brain synapses, employing both an in vitro system with recombinant activated caspases and an in vivo model of ethanol-induced neuronal apoptosis. Of the more than 70 putative cleavage substrates that were identified, 22 were previously known caspase substrates. Among the novel targets identified and validated by Western blot were the proton pump ATPase subunit ATP6V1B2 and the N-ethylmaleimide-sensitive fusion protein (NSF). Our work represents the first comprehensive, proteome-wide screen for proteolytic targets of caspases in neuronal synapses. Our discoveries will have significance for both furthering basic understanding of roles of caspases in synaptic plasticity and synaptic loss in neurodegeneration, and on a more immediately practical level, may provide candidate biomarkers for measuring synapse loss in human disease states.
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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".