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      Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

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          Abstract

          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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          Most cited references69

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          Dendritic protein synthesis, synaptic plasticity, and memory.

          Considerable evidence suggests that the formation of long-term memories requires a critical period of new protein synthesis. Recently, the notion that some of these newly synthesized proteins originate through local translation in neuronal dendrites has gained some traction. Here, we review the experimental support for this idea and highlight some of the key questions outstanding in this area.
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            The postsynaptic architecture of excitatory synapses: a more quantitative view.

            Excitatory (glutamatergic) synapses in the mammalian brain are usually situated on dendritic spines, a postsynaptic microcompartment that also harbors organelles involved in protein synthesis, membrane trafficking, and calcium metabolism. The postsynaptic membrane contains a high concentration of glutamate receptors, associated signaling proteins, and cytoskeletal elements, all assembled by a variety of scaffold proteins into an organized structure called the postsynaptic density (PSD). A complex machine made of hundreds of distinct proteins, the PSD dynamically changes its structure and composition during development and in response to synaptic activity. The molecular size of the PSD and the stoichiometry of many major constituents have been recently measured. The structures of some intact PSD proteins, as well as the spatial arrangement of several proteins within the PSD, have been determined at low resolution by electron microscopy. On the basis of such studies, a more quantitative and geometrically realistic view of PSD architecture is emerging.
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              A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC).

              Stable isotope labeling by amino acids in cell culture (SILAC) is a simple, robust, yet powerful approach in mass spectrometry (MS)-based quantitative proteomics. SILAC labels cellular proteomes through normal metabolic processes, incorporating non-radioactive, stable isotope-containing amino acids in newly synthesized proteins. Growth medium is prepared where natural ("light") amino acids are replaced by "heavy" SILAC amino acids. Cells grown in this medium incorporate the heavy amino acids after five cell doublings and SILAC amino acids have no effect on cell morphology or growth rates. When light and heavy cell populations are mixed, they remain distinguishable by MS, and protein abundances are determined from the relative MS signal intensities. SILAC provides accurate relative quantification without any chemical derivatization or manipulation and enables development of elegant functional assays in proteomics. In this protocol, we describe how to apply SILAC and the use of nano-scale liquid chromatography coupled to electrospray ionization mass spectrometry for protein identification and quantification. This procedure can be completed in 8 days.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                2 May 2013
                : 8
                : 5
                : e63191
                Affiliations
                [1 ]Technion Faculty of Medicine, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel
                [2 ]Network Biology Research Laboratories, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel
                [3 ]Smoler Proteomics Center, Faculty of Biology, Technion, Haifa, Israel
                [4 ]Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom
                [5 ]Leibniz-Institute for Neurobiology, Magdeburg, Germany
                [6 ]Institute for Pharmacology and Toxicology, Otto-von-Guericke University, Magdeburg, Germany
                University of Michigan, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LDC DCD TZ NEZ. Performed the experiments: LDC RZ AM OS. Analyzed the data: LDC OS AM DCD JDA TZ NEZ. Contributed reagents/materials/analysis tools: TZ NEZ. Wrote the paper: LDC OS DCD JDA TZ NEZ.

                Article
                PONE-D-13-09997
                10.1371/journal.pone.0063191
                3642143
                23658807
                6e7bba3e-3439-497c-bd00-4b87d1ff162e
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 March 2013
                : 29 March 2013
                Page count
                Pages: 20
                Funding
                This work has received funding from the United States Israel Binational Science Foundation (2007425), the European Union Seventh Framework Programme under grant agreement nos. HEALTH-F2–2009–241498 (“EUROSPIN”), and the Deutsch-Israelische-Projektkooperation German-Israeli Project Cooperation foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Metabolism
                Protein Metabolism
                Proteins
                Protein Chemistry
                Model Organisms
                Animal Models
                Rat
                Neuroscience
                Cellular Neuroscience
                Molecular Neuroscience
                Neurochemistry
                Neurophysiology
                Proteomics
                Protein Abundance

                Uncategorized
                Uncategorized

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