An Atlas of Phosphorylation and Proteolytic Processing Events During Excitotoxic Neuronal Death Reveals New Therapeutic Opportunities
Bibliographic record
Abstract
Summary Excitotoxicity, a neuronal death process in neurological disorders, is initiated by over-stimulation of neuronal ionotropic glutamate receptors. The over-stimulated receptors dysregulate proteases, protein kinases and phosphatases, which in turn modify target neuronal proteins to induce cell death. To decipher this cell death mechanism, we used quantitative proteomics, phosphoproteomics and N-terminomics to identify modified proteins in excitotoxic neurons. Data, available in ProteomeXchange (identifiers: PXD019527 and PXD019211), enabled us to identify over one thousand such proteins with calpains, cathepsins and over twenty protein kinases as their major modifiers. These protein modification events can potentially perturb signalling pathways governing cell survival, synaptogenesis, axonal guidance and mRNA processing. Importantly, blocking the modification of Src protein kinase, a signalling hub in excitotoxic neurons, protected against neuronal loss in vivo in a rat model of neurotoxicity. Besides offering new insights into excitotoxic neuronal death mechanism, our findings suggest potential neuroprotective therapeutic targets for treating neurological disorders. Graphical abstract Highlights Multi-dimensional proteomic analysis identified proteins modified by proteolysis and altered phosphorylation in neurons undergoing excitotoxic cell death. Calpains, cathepsins and over twenty protein kinases are major modifiers of these proteins. These protein modification events are predicted to impact cell survival, axonal guidance, synaptogenesis and mRNA processing. Blocking modification of an identified protein Src, which acts as a major signalling hub in neurons, was protective against excitotoxic injury in vivo . In Brief Using multidimensional proteomic approaches, Ameen, et al . mapped the changes of proteome, phosphoproteome and N-terminome of cultured primary neurons during excitotoxicity, a crucial neuronal death process in neurological disorders. These proteomic changes document new excitotoxicity-associated molecular events, and offer insights into how these events are organized to induce neuronal death. Potential therapeutic relevance of these molecular events is illustrated by the demonstration that in vivo blockade of one of these events could protect against excitotoxic neuronal loss.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".