Identification of long-lived synaptic proteins by proteomic analysis of synaptosome protein turnover
Bibliographic record
Abstract
Memory formation is believed to result from changes in synapse strength and structure. While memories may persist for the lifetime of an organism, the proteins and lipids that make up synapses undergo constant turnover with lifetimes from minutes to days. The molecular basis for memory maintenance may rely on a subset of long-lived proteins (LLPs). While it is known that LLPs exist, whether such proteins are present at synapses is unknown. We performed an unbiased screen using metabolic pulse-chase labeling in vivo in mice and in vitro in cultured neurons combined with quantitative proteomics. We identified synaptic LLPs with half-lives of several months or longer. Proteins in synaptic fractions generally exhibited longer lifetimes than proteins in cytosolic fractions. Protein turnover was sensitive to pharmacological manipulations of activity in neuronal cultures or in mice exposed to an enriched environment. We show that synapses contain LLPs that may underlie stabile long-lasting changes in synaptic structure and function.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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".