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Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance
Open accessAbstract
Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non-Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2-5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial.
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![Figure 7 Relationships between half-life estimates and protein-protein interaction groups. A) A molecular interaction network of 191 synaptic related proteins (main text and Table 1) generated on the basis of a manually curated public domain protein-protein interaction database (Human Integrated Protein-Protein Interaction Reference, or HIPPIE; [55]; see Materials and Methods for further details). Each circle represents one protein, with the estimated metabolic half-life for that protein color coded according to the legend at the bottom left corner. Proteins in each cluster are listed in clockwise fashion, with the top protein in each list referring to the circle in each cluster encompassed with a thick line. B,C) Differences between metabolic turnover rates are smaller on average for pairs of interacting proteins as compared to pairs of non-interacting proteins. Absolute differences between metabolic half-life estimates for all pairs for which interactions are known to exist were compared to all pairs for which interactions are not known to occur (see main text for details), and the distributions of such differences were plotted for both groups. B) All identified proteins, and C) For the list of synaptic and synaptically related proteins. In both cases, differences between groups were highly significant (p ≪10−10, Kolmogorov-Smirnov test).](/paper-figures/9545d235c5624393b1fa106c2a4265d6/metabolic-turnover-of-synaptic-proteins-kinetics-interdependencies-and-figure-7.jpg)

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“In particular, CaMKII is known to turn over rapidly, with a half-life of 2–4 days (403–405).”
From Synaptic memory and CaMKII (2023) · cites this paper as [403]
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“Although memories can last for the entire span of an animal’s life, most synaptic proteins generally have half-lives of 2–5 days (403, 404).”
From Synaptic memory and CaMKII (2023) · cites this paper as [403]
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Metadata
- Authors
- Cohen, L. D., Zuchman, R., Sorokina, O., Müller, A., Dieterich, D. C., Armstrong, J. D., Ziv, T., & Ziv, N. E.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- University of Edinburgh (GB)
- Otto-von-Guericke-Universität Magdeburg (DE)
- Corresponding author
- Ziv, Noam E.
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-05-02
- Volume
- 8
- Issue
- 5
- Pages
- e63191
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3642143
- OpenAlex
- W2050606229
- Cited by
- 215
- References
- 86
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 16 · 2023: 16 · 2022: 16 · 2021: 18 · 2020: 21 · 2019: 26 · 2018: 20 · 2017: 20 · 2016: 11 · 2015: 15 · 2014: 15 · 2013: 2
- FWCI
- 7.03
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- European Commission (241498)
- University of Haifa
- Technion-Israel Institute of Technology
- Universität Ulm
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- synaptic proteins, protein turnover, protein half-life, presynaptic proteins, postsynaptic proteins, dendritic mRNA, protein degradation, protein synthesis, synapse maintenance, protein complex association
- MeSH terms
- Animals, Cell Compartmentation, Kinetics, Neurons, Proteins, Synapses, Rats, Wistar, Protein Transport, Proteomics, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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