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• W2018093424 abstract "Synapses are highly dynamic structures that mediate cell–cell communication in the central nervous system. Their molecular composition is altered in an activity-dependent fashion, which modulates the efficacy of subsequent synaptic transmission events. Whereas activity-dependent trafficking of individual key synaptic proteins into and out of the synapse has been characterized previously, global activity-dependent changes in the synaptic proteome have not been studied.To test the feasibility of carrying out an unbiased large-scale approach, we investigated alterations in the molecular composition of synaptic spines following mass stimulation of the central nervous system induced by pilocarpine. We observed widespread changes in relative synaptic abundances encompassing essentially all proteins, supporting the view that the molecular composition of the postsynaptic density is tightly regulated. In most cases, we observed that members of gene families displayed coordinate regulation even when they were not known to physically interact.Analysis of correlated synaptic localization revealed a tightly co-regulated cluster of proteins, consisting of mainly glutamate receptors and their adaptors. This cluster constitutes a functional core of the postsynaptic machinery, and changes in its size affect synaptic strength and synaptic size. Our data show that the unbiased investigation of activity-dependent signaling of the postsynaptic density proteome can offer valuable new information on synaptic plasticity. Synapses are highly dynamic structures that mediate cell–cell communication in the central nervous system. Their molecular composition is altered in an activity-dependent fashion, which modulates the efficacy of subsequent synaptic transmission events. Whereas activity-dependent trafficking of individual key synaptic proteins into and out of the synapse has been characterized previously, global activity-dependent changes in the synaptic proteome have not been studied. To test the feasibility of carrying out an unbiased large-scale approach, we investigated alterations in the molecular composition of synaptic spines following mass stimulation of the central nervous system induced by pilocarpine. We observed widespread changes in relative synaptic abundances encompassing essentially all proteins, supporting the view that the molecular composition of the postsynaptic density is tightly regulated. In most cases, we observed that members of gene families displayed coordinate regulation even when they were not known to physically interact. Analysis of correlated synaptic localization revealed a tightly co-regulated cluster of proteins, consisting of mainly glutamate receptors and their adaptors. This cluster constitutes a functional core of the postsynaptic machinery, and changes in its size affect synaptic strength and synaptic size. Our data show that the unbiased investigation of activity-dependent signaling of the postsynaptic density proteome can offer valuable new information on synaptic plasticity. Excitatory synaptic transmission is the primary mode of cell–cell communication in the central nervous system. The efficacy of synaptic transmission is highly regulated, and alterations in the strength of synaptic signaling within networks of neurons provide a mechanism for learning and memory storage, as well as for overall network stability. Modulation of synapse efficacy can occur through alterations in the structure and composition of the postsynaptic spine. The synaptic abundance of several molecules has been shown to be regulated in response to activity (1Sheng M. Kim M.J. Postsynaptic signaling and plasticity mechanisms.Science. 2002; 298: 776-780Crossref PubMed Scopus (596) Google Scholar). The levels of individual proteins at postsynaptic spines are regulated through multiple processes. Active transport mechanisms exist and have been well characterized for AMPA-type glutamate receptors (AMPA-Rs) 1The abbreviations used are:AMPA-RAMPA-type glutamate receptorCamk2calcium-calmodulin dependent kinase IIPCCPearson correlation coefficientNMDA-RNMDA-type glutamate receptorsPSDpostsynaptic densityPSD110a subset of 110 PSD proteinsSCXstrong cation exchange chromatography. 1The abbreviations used are:AMPA-RAMPA-type glutamate receptorCamk2calcium-calmodulin dependent kinase IIPCCPearson correlation coefficientNMDA-RNMDA-type glutamate receptorsPSDpostsynaptic densityPSD110a subset of 110 PSD proteinsSCXstrong cation exchange chromatography. via either insertion into the synapse or tighter association with the postsynaptic density (PSD) following lateral diffusion within the cell membrane (2Henley J.M. Barker E.A. Glebov O.O. Routes, destinations and delays: recent advances in AMPA receptor trafficking.Trends Neurosci. 2011; 34: 258-268Abstract Full Text Full Text PDF PubMed Scopus (131) Google Scholar). In addition to AMPA-Rs, other proteins known to be subject to activity-dependent regulation include calcium calmodulin-dependent protein kinase II alpha and beta, NMDA-type glutamate receptors (NMDA-Rs), and proteosome subunits (3Schulman H. Activity-dependent regulation of calcium/calmodulin-dependent protein kinase II localization.J. Neurosci. 2004; 24: 8399-8403Crossref PubMed Scopus (61) Google Scholar, 4Perez-Otano I. Ehlers M.D. Homeostatic plasticity and NMDA receptor trafficking.Trends Neurosci. 2005; 28: 229-238Abstract Full Text Full Text PDF PubMed Scopus (300) Google Scholar, 5Haas K.F. Broadie K. Roles of ubiquitination at the synapse.Biochim. Biophys. Acta. 2008; 1779: 495-506Crossref PubMed Scopus (47) Google Scholar). Synaptic protein content is dysregulated in a number of neuropsychiatric and neurodegenerative diseases, including Alzheimer's disease and fragile X mental retardation (6Chang R.C. Yu M.S. Lai C.S. Significance of molecular signaling for protein translation control in neurodegenerative diseases.Neurosignals. 2006; 15: 249-258Crossref PubMed Scopus (24) Google Scholar, 7Ronesi J.A. Huber K.M. Metabotropic glutamate receptors and fragile x mental retardation protein: partners in translational regulation at the synapse.Sci. Signal. 2008; 1: 6Crossref Scopus (87) Google Scholar, 8Ramocki M.B. Zoghbi H.Y. Failure of neuronal homeostasis results in common neuropsychiatric phenotypes.Nature. 2008; 455: 912-918Crossref PubMed Scopus (307) Google Scholar). AMPA-type glutamate receptor calcium-calmodulin dependent kinase II Pearson correlation coefficient NMDA-type glutamate receptors postsynaptic density a subset of 110 PSD proteins strong cation exchange chromatography. AMPA-type glutamate receptor calcium-calmodulin dependent kinase II Pearson correlation coefficient NMDA-type glutamate receptors postsynaptic density a subset of 110 PSD proteins strong cation exchange chromatography. Most studies reported thus far have focused on a small number of selected molecules in individual experiments using a subset of synapses. Whereas learning and memory rely on the differential response of individual synapses to their specific input patterns, overall network excitability has to be maintained by homeostatic means. This homeostasis is governed by multiple pathways, and very little is known about the principles that regulate synaptic protein content across large numbers of synapses and neurons. The contributions of individual pathways and the interactions among them are largely unknown. In order to explore synaptic dynamics with a global view, we took advantage of a chemically induced mass stimulation protocol to stimulate synapses broadly throughout the central nervous system. We employed mass spectrometry and isotopically encoded isobaric peptide tagging with the iTRAQ reagent to quantify changes in the abundance of 893 proteins (9Trinidad J.C. Thalhammer A. Specht C.G. Lynn A.J. Baker P.R. Schoepfer R. Burlingame A.L. Quantitative analysis of synaptic phosphorylation and protein expression.Mol. Cell. Proteomics. 2008; 7: 684-696Abstract Full Text Full Text PDF PubMed Scopus (173) Google Scholar). We then analyzed changes in the relative abundance of these proteins at 0, 10, 20, and 60 min after the onset of stimulation. We observed evidence of the coordinated activation of synaptic protein groups, thereby identifying functional core complexes within the PSD. We demonstrate that adopting a quantitative systems biology approach provides insight allowing for a new level of analysis of synaptic function. Mice (strain C57BL/6J; male, 3 to 4 months) were injected intraperitoneally with 140 to 150 μl of a 0.05-mg/μl pilocarpine solution in 0.9% NaCl (7 to 7.5 mg/mouse) (10Cavalheiro E.A. Naffah-Mazzacoratti M.G. Mello L.E. Leite J.P. The pilocarpine model of seizures.in: Pitkanen A. Schwartzkroin P.A. Moshe S.L. Models of Seizures and Epilepsy. Elsevier Academic Press, London, UK2006: 433-448Google Scholar). 2 to 3 min after injection they developed signs of seizures (stage 1 on the Racine scale (11Mares P. Kubova H. Electrical stimulation-induced models of seizures.in: Pitkanen A. Schwartzkroin P.A. Moshe S.L. Models of Seizures and Epilepsy. Elsevier Academic Press, London, UK2006: 153-160Crossref Scopus (43) Google Scholar)), which gradually reached stage 4 or 5 within 5 min. Animals were culled 10, 20, and 60 min after pilocarpine injection according to UK Home Office regulations by dislocation of the neck. The forebrain (without olfactory bulbs) was dissected in less than 2 min after culling and flash frozen in liquid nitrogen. All animals that did not show signs of stage 4 or 5 10 min after pilocarpine injection (4 out of 40) were not considered for the experiment and were culled. Control animals (time point 0) were injected with 150 μl of 0.9% NaCl and culled 10 min later, and their brains were acquired as above. Animal experiments were conducted under licenses of the UK Home Office. Three biological replicates of the pilocarpine stimulation were conducted. For each replicate, PSD samples from the four time points were purified in parallel at 4 °C, as outlined elsewhere (9Trinidad J.C. Thalhammer A. Specht C.G. Lynn A.J. Baker P.R. Schoepfer R. Burlingame A.L. Quantitative analysis of synaptic phosphorylation and protein expression.Mol. Cell. Proteomics. 2008; 7: 684-696Abstract Full Text Full Text PDF PubMed Scopus (173) Google Scholar). The material for each time point was obtained from three animals that were pooled prior to the biochemical purification. The brain tissue was homogenized in a sucrose buffer containing a mixture of phosphatase inhibitors (1 mm Na3VO4, 1 mm NaF, 1 mm Na2MoO4, 4 mm sodium tartrate, 100 nm fenvalerate, 250 nm okadaic acid) and cleared via centrifugation. For each brain region, the ratio of buffer volume to starting brain weight was kept constant (10 ml buffer per gram) to ensure that each PSD preparation was exposed to an equivalent level of inhibitors and buffer. The membranous fraction was layered on a sucrose density and fractionated via centrifugation. Synaptic membranes were collected at the 1.0–1.2 M interface and applied onto a second gradient. The PSD fraction was collected at the 1.4–2.2 M interface and pelleted. During the final pelleting stage, PSD material from a single time point was pelleted into two or more tubes. For each of the three biological replicates, two technical replicates (consisting of one set of tubes) were processed as described below on separate days. The average yield of PSD sample per brain was 0.8 mg. We did not detect alpha-synuclein, a major soluble presynaptic protein (supplemental Tables S1 and S2). For the four time points in a given replicate, 500 μg of each PSD sample was processed in parallel. Each PSD sample was resuspended in 25 mm ammonium bicarbonate containing 6 m guanidine hydrochloride. The mixture was incubated for one hour at 57 °C with 2 mm Tris(2-carboxyethyl)phosphine hydrochloride to reduce cysteine side chains. These side chains were then alkylated with 4.2 mm iodoacetamide in the dark for 45 min at 21 °C. The mixture was diluted 6-fold with 25 mm ammonium bicarbonate, and 5% (w/w) modified trypsin (Promega, Madison, WI) was added. The pH was adjusted to 8.0, and the mixture was digested for 12 h at 37 °C. The digests were desalted using a C18 Sep Pak cartridge (Waters, Milford, MA) and lyophilized to dryness using a SpeedVac concentrator (Thermo Electron, San Jose, CA). The dried peptides were resuspended in 80 μl of iTRAQ dissolution buffer. Each iTRAQ reagent vial was reconstituted using 70 μl of ethanol, and a total of five reagent vials were used to label each 500-μg digest of tryptic peptides. The labeling reaction was allowed to proceed for one hour at 21 °C. An aliquot was then examined using a one-hour LC-MS/MS run and searched allowing iTRAQ as a variable modification to confirm that over 99% of all peptides identified showed complete iTRAQ labeling. A second aliquot containing a 1:1:1:1 mixture of the four labeled samples was then analyzed via LC-MS/MS to determine whether any correction for protein amount needed to be made during the final combination of the four samples. SCX was performed using an ÄKTA Purifier (GE Healthcare, Piscataway, NJ) equipped with a Tricorn 5/200 column (GE Healthcare, Piscataway, NJ) packed in-house with 5 μm 300 Å polysulfoethyl A resin (Western Analytical, Lake Elsinore, CA). The 2.0 mg combined PSD sample was loaded onto the column in 30% acetonitrile, 5 mm KH2PO4, pH 2.7 (buffer A). Buffer B consisted of buffer A with 350 mm KCl. The gradient went from 1% B to 29% B over 19 ml, from 29% B to 75% B over 14 ml, and from 75% B to 100% B over 2.5 ml. Between 90 and 100 fractions were collected and desalted using a MAX-RP reverse phase C18 cartridge (Phenomenex, Torrance, CA) and dried down using a SpeedVac concentrator. Individual SCX fractions were separated using a 75 μm × 15 cm reverse phase C18 column (LC Packings, Sunnyvale, CA) at a flow rate of 350 nl/min, running a 3%–32% acetonitrile gradient in 0.1% formic acid on an Eksigent. Gradient cycle times were between 1.0 and 1.5 h in length, depending on sample complexity. The LC eluent was coupled to a micro-ionspray source attached to a QSTAR Pulsar Elite mass spectrometer (Applied Biosystems, Foster City, CA). MS spectra were acquired for 1 s, and the two most intense multiple charged peaks were selected for the generation of subsequent collision-induced dissociation MS. For precursor ion selection, the quadrupole resolution was set to “high,” which allows for transmission of ions within approximately ±0.5 m/z units of the monoisotopic mass. The collision-induced dissociation energy was automatically adjusted based upon the peptide charge and m/z ratio. A dynamic exclusion window was applied that prevented the same m/z from being selected for 3 min after its initial acquisition. Data were analyzed using Analyst QS software (version 2.0), and MS/MS centroid peak lists were generated using the Mascot.dll script (version 1.6b18). The MS/MS spectra were searched against the entire Uniprot Mus musculus database (downloaded December 2008, with a total of 60,123 entries, to which were appended SHAN1_RAT and SYGP1_RAT). To this database, a randomized version was concatenated to allow for calculations of false discovery rates. Initial peptide tolerances in MS and MS/MS modes were 200 ppm and 0.2 Da, respectively. Trypsin was designated as the protease, and two missed cleavages were allowed. Carbamidomethylation and iTRAQ labeling of lysine residues were searched as fixed modifications. The peptide amino termini were fixed as either iTRAQ modified or protein N-terminal acetylated. Oxidation of methionine was allowed as a variable modification. All high-scoring peptide matches (expectation value < 0.01) from individual LC-MS/MS runs were then used to internally recalibrate MS parent ion m/z values within that run. Recalibrated data files were then searched with a peptide tolerance in MS mode of 50 ppm. Peptide hits were considered if they had peptide scores of ≥15 and expectation values of ≤0.05. Across all six analyses, a total of 720,890 MS/MS spectra were acquired, of which 168,513 matched to peptides (including redundant identifications) using the initial acceptance criteria. For the resulting output, UniGene entries were mapped onto the corresponding UniProt accession numbers, and proteins were condensed to single entries if they matched to the same UniGene entry. Peptides that corresponded to proteins from more than one UniGene entry were not used. UniGene entries were considered identified if they were found with at least two unique peptides. Across all six analyses (two technical replicates each of the three biological replicates), a total of 3321 unique UniGene entries were identified in at least one of the analyses, and 12 proteins were identified from the decoy database false discovery rate (FDR = 0.4%). A total of 911 Unigenes (and no decoy proteins) were identified with at least two peptides per protein in all six of the analyses. The raw MS data in *.wiff format were read directly using Protein Prospector (version 4.24.4). For each peptide MS/MS spectrum, the raw area of the peaks at m/z 114.1, 115.1, 116.1, and 117.1 (±0.1 m/z) was determined. iTRAQ area measurements were adjusted using isotope correction values supplied by the vendor for these batches of the reagent. Only MS/MS spectra in which the most intense iTRAQ peak was ≥25 counts were used. If multiple MS/MS spectra were collected for the same peptide at the same charge state, only the best scoring spectra were used for quantification. To calculate the relative percentage of a given peptide in each of the four samples, the area of that corresponding peak was divided by the average area for all four iTRAQ diagnostic ions in those MS/MS spectra. Relative protein expression values for each UniGene protein entry were the log-averaged value of all peptides matching to that entry. Following the analysis of the expression ratios between the technical replicates, the 18 proteins (2% of 911) that showed the largest variations between any pair of the technical replicates were considered outliers and were removed, leaving 893 proteins for bioinformatic analysis, for which the two technical replicates for each protein where averaged into one value per time point. This was followed, separately for each biological replicate, by 10 rounds of iterative normalization for each protein, so that the sum of the time points equaled 4, and total protein amount per time point, so that the sum of all proteins equaled 893. In two sets of biological replicates, four proteins were spiked into the PSD pellets prior to resuspension to estimate the magnitude of iTRAQ compression as a function of the isolation window. Bovine albumin and human transferrin were each spiked in at a 1:2:4:8 ratio. Human hemoglobin and bovine casein were each spiked in at a 1:3:9:27 ratio, allowing a series of 1:2 and 1:3 ratio comparisons. The subset of peptides from these proteins that were identical to mus musculus were excluded from quantification. For those biological replicates with these internal standards, all SCX fractions were analyzed twice using different Q1 isolation settings. The first setting corresponded to the “high” setting on the QSTAR (isolation setting values 0.1 higher than “low”), and the other represented a narrower “custom” isolation (isolation setting value 0.45 higher than “low”). The median observed protein ratio for expected 2- and 3-fold changes were 1.4 and 1.6 using the “high” setting and 1.8 and 1.8 using the “custom” setting. Therefore, all PSD quantification data were acquired using the narrow “custom” setting. Whereas changes in protein expression 3-fold and greater showed substantial compression at these settings, changes 2-fold (and less) were less affected. For all proteins, we have used the non-italicized version of the gene name as the protein name in all tables and figures. In the text, a protein may additionally be referred to by its common protein name. Expression profiles and histograms were calculated and displayed in IGOR 6.x. (Wavemetrics, Portland, OR). Pearson correlation coefficients (PCCs) were calculated via the Pearson correlation. Correlation networks were displayed using Cytoscape (version 2.7.0) (12Cline M.S. Smoot M. Cerami E. Kuchinsky A. Landys N. Workman C. Christmas R. Avila-Campilo I. Creech M. Gross B. Hanspers K. Isserlin R. Kelley R. Killcoyne S. Lotia S. Maere S. Morris J. Ono K. Pavlovic V. Pico A.R. Vailaya A. Wang P.L. Adler A. Conklin B.R. Hood L. Kuiper M. Sander C. Schmulevich I. Schwikowski B. Warner G.J. Ideker T. Bader G.D. Integration of biological networks and gene expression data using Cytoscape.Nat. Protoc. 2007; 2: 2366-2382Crossref PubMed Scopus (1824) Google Scholar). Details are given in the respective figure legends. Statistical calculations were performed using R (version 2.11.1). Weighted expression network analysis (13Zhang B. Horvath S. A general framework for weighted gene co-expression network analysis.Stat. Appl. Genet. Mol. Biol. 2005; 4 (Article 17)Crossref PubMed Scopus (3361) Google Scholar, 14Horvath S. Dong J. Geometric interpretation of gene coexpression network analysis.PLoS Comput. Biol. 2008; 4: e1000117Crossref PubMed Scopus (573) Google Scholar) was conducted to group proteins based upon their temporal patterns using R (version 2.11.1). Custom libraries used for the analysis included dynamicTreeCut, moduleColor, and WGCNA (15Langfelder P. Horvath S. WGCNA: an R package for weighted correlation network analysis.BMC Bioinformatics. 2008; 9: 559Crossref PubMed Scopus (10410) Google Scholar) using the following parameters: power = 9; minconnections = 0.01; hclust method = “average”; cutHeight = 0.99, minClusterSiz = 20, method: “tree”; deepSplit = TRUE. To reduce the influence of co-purified proteins on the correlation analysis, we defined a subset of 110 proteins (PSD110) representing generally accepted components of PSDs, and we refer to this group as the biochemical core of PSDs. The starting point of this list is the analysis of an affinity-purified PSD preparation (16Fernandez E. Collins M.O. Uren R.T. Kopanitsa M.V. Komiyama N.H. Croning M.D. Zografos L. Armstrong J.D. Choudhary J.S. Grant S.G. Targeted tandem affinity purification of PSD-95 recovers core postsynaptic complexes and schizophrenia susceptibility proteins.Mol. Syst. Biol. 2009; 5: 269Crossref PubMed Scopus (203) Google Scholar), which was analyzed by a less deep-reaching MS strategy than we employed here. Our analysis had 97 proteins overlapping with the biochemical PSD core complex from Fernandez et al. (16Fernandez E. Collins M.O. Uren R.T. Kopanitsa M.V. Komiyama N.H. Croning M.D. Zografos L. Armstrong J.D. Choudhary J.S. Grant S.G. Targeted tandem affinity purification of PSD-95 recovers core postsynaptic complexes and schizophrenia susceptibility proteins.Mol. Syst. Biol. 2009; 5: 269Crossref PubMed Scopus (203) Google Scholar). We further added the 13 proteins Lrrc7 (Densin-180), Actn1 (Actinin 1), Actn2 (Actinin 2), Ank3 (Ankyrin 3), Camk2d, Cask, Cdh2 (Cadherin 2), Ctnnb1 (Catenin β1), Ctnnd2 (Catenin δ2), Nlgn1 (Neuroligin 1), Shank2, Shank3, and Synpo (Synaptopodin), which (a) were part of the Gene Ontology term “synapse” and generally accepted PSD components (17Sheng M. Hoogenraad C.C. The postsynaptic architecture of excitatory synapses: a more quantitative view.Annu. Rev. Biochem. 2007; 76: 823-847Crossref PubMed Scopus (729) Google Scholar), (b) were localized neither exclusively pre-synaptically nor at inhibitory synapses, and (c) had at least 10% sequence coverage in our MS analysis (supplemental Table S1). The PSD110 components are listed in supplemental Table S3. In this study, we addressed the question of how pharmacologically induced synaptic activity affects the relative amounts of synaptic proteins in preparations of murine PSDs. We investigated changes occurring during the first 60 min following the onset of stimulation. Changes observed during that period primarily reflect a redistribution of proteins between the purified synaptic compartment and the remaining extrasynaptic cellular volume, plus possibly some induced protein degradation and limited induced synthesis of new proteins, if any. In order to induce acute massive synaptic stimulation, mice were treated with interperitoneal injection of pilocarpine (10Cavalheiro E.A. Naffah-Mazzacoratti M.G. Mello L.E. Leite J.P. The pilocarpine model of seizures.in: Pitkanen A. Schwartzkroin P.A. Moshe S.L. Models of Seizures and Epilepsy. Elsevier Academic Press, London, UK2006: 433-448Google Scholar). PSD preparations were obtained for three biological replicates and were each pelleted into multiple identical aliquots. This allowed us to conduct two technical replicates on each biological replicate, for a total of six independently conducted analyses of the synapse. An outline of the workflow is shown in Fig. 1. The two technical replicates provided very similar measurements, consistent with a high degree of accuracy for protein level quantification. For the 893 proteins that passed our stringency criteria (see “Experimental Procedures”), the median difference between protein measurements across technical replicates was 5.1% for individual time point measurements. For subsequent analyses, the mean of each technical replicate pair was used throughout. To assess the biological reproducibility, we examined a subset of 12 individual key synaptic protein values in detail (supplemental Fig. S1). For the 12 proteins shown, the median coefficient of variation of protein time point values was 3.8%, whereas for the entire dataset this value was 6.6%. For the profiling of individual protein levels, we averaged the three biological replicates. For correlation analysis, the time points from each of the three biological replicates were kept as unique datapoints. We first determined the overall changes in protein levels. 95% of all changes are within a ±15% range (Fig. 2A). The variations within the biochemical core proteins (PSD110; see “Experimental Procedures” and below) were of comparable magnitude (Fig. 2C). Ratios between the minimum and maximum levels of individual proteins had a median of 1.115 (Fig. 2B). Taken together, massive synaptic stimulation induced relatively modest overall changes in protein levels within the complete population of forebrain synapses. We next analyzed members of protein families that shared a high degree of sequence similarity. The subunits of AMPA-Rs (18Greger I.H. Ziff E.B. Penn A.C. Molecular determinants of AMPA receptor subunit assembly.Trends Neurosci. 2007; 30: 407-416Abstract Full Text Full Text PDF PubMed Scopus (152) Google Scholar), which are the main determinants of synaptic strength, were strikingly correlated in the response to mass stimulation. In particular, Gria1, Gria2, and Gria3 (GluA1, GluA2, and GluA3, respectively) displayed nearly identical dynamics (Fig. 2D). NMDA-Rs (19Cull-Candy S.G. Leszkiewicz D.N. Role of distinct NMDA receptor subtypes at central synapses.Sci. STKE. 2004; 2004: re16Crossref PubMed Scopus (605) Google Scholar) are the primary mediators of coincident neuronal stimulation and are involved in input pattern recognition. It is clear that levels of Grin1, Grin2a, and Grin2b (GluN1, GluN2A, and GluN2B) protein behave nearly identically, with Grin2d (GluN2D) showing less correlation (Fig. 2E). Both NMDA-R and AMPA-R subunits showed a profile of about ±10% change, with an initial increase peaking at 20 min and a return to near-baseline values after 60 min. Within the Dlg family (20Kim E. Sheng M. PDZ domain proteins of synapses.Nat. Rev. Neurosci. 2004; 5: 771-781Crossref PubMed Scopus (1233) Google Scholar) of adaptor proteins, Dlg4 (PSD95) and Dlg2 (PSD93/Chapsyn110) show very similar patterns, with maximum synaptic localization at 20 min. In contrast, the average levels of Dlg1 (SAP97) protein are minimally changed in response to stimulation (Fig. 2F). A markedly distinctive pattern was observed for all four isoforms of calcium-calmodulin dependent kinase II (Camk2) (21Hudmon A. Schulman H. Structure-function of the multifunctional Ca2+/calmodulin-dependent protein kinase II.Biochem. J. 2002; 364: 593-611Crossref PubMed Scopus (468) Google Scholar), a major kinase involved in synaptic plasticity, which showed a sustained decrease across the time-course of the experiment (Fig. 2G). Sixty minutes post-pilocarpine injection, there was a 10% to 20% decrease in the average Camk2 content at the synapse. The AP2 components of the adaptor protein complex 2 (22Owen D.J. Collins B.M. Evans P.R. Adaptors for clathrin coats: structure and function.Annu. Rev. Cell Dev. Biol. 2004; 20: 153-191Crossref PubMed Scopus (359) Google Scholar) were strongly co-regulated with a small increase in synaptic protein levels during the time course of the experiment (Fig. 2H). A group of filament-forming GTPases, the septins, are necessary for organization of the actin cytoskeleton and localize to the neck of synaptic spines (23Tada T. Simonetta A. Batterton M. Kinoshita M. Edbauer D. Sheng M. Role of Septin cytoskeleton in spine morphogenesis and dendrite development in neurons.Curr. Biol. 2007; 17: 1752-1758Abstract Full Text Full Text PDF PubMed Scopus (220) Google Scholar, 24Xie Y. Vessey J.P. Konecna A. Dahm R. Macchi P. Kiebler M.A. The GTP-binding protein Septin 7 is critical for dendrite branching and dendritic-spine morphology.Curr. Biol. 2007; 17: 1746-1751Abstract Full Text Full Text PDF PubMed Scopus (199) Google Scholar). They display concerted regulation in synaptic protein levels with a minimum at 20 min after stimulation (Fig. 2I). In these examples, members of gene families often, but not always, show a coordinated pattern. Direct interaction within some members of a gene family are expected and well established, su" @default.
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• W2018093424 date "2013-01-01" @default.
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• W2018093424 title "Activity-dependent Protein Dynamics Define Interconnected Cores of Co-regulated Postsynaptic Proteins" @default.
• W2018093424 cites W1966327575 @default.
• W2018093424 cites W1969651353 @default.
• W2018093424 cites W1975786395 @default.
• W2018093424 cites W1989119979 @default.
• W2018093424 cites W1994815778 @default.
• W2018093424 cites W1999556153 @default.
• W2018093424 cites W2005800358 @default.
• W2018093424 cites W2016425872 @default.
• W2018093424 cites W2020939800 @default.
• W2018093424 cites W2031195859 @default.
• W2018093424 cites W2033844584 @default.
• W2018093424 cites W2045085957 @default.
• W2018093424 cites W2056145172 @default.
• W2018093424 cites W2056655737 @default.
• W2018093424 cites W2060705109 @default.
• W2018093424 cites W2071318481 @default.
• W2018093424 cites W2078167209 @default.
• W2018093424 cites W2081551641 @default.
• W2018093424 cites W2082411508 @default.
• W2018093424 cites W2087776586 @default.
• W2018093424 cites W2088239473 @default.
• W2018093424 cites W2093573816 @default.
• W2018093424 cites W2095352645 @default.
• W2018093424 cites W2117333689 @default.
• W2018093424 cites W2120016041 @default.
• W2018093424 cites W2133465414 @default.
• W2018093424 cites W2137531873 @default.
• W2018093424 cites W2137689860 @default.
• W2018093424 cites W2141114982 @default.
• W2018093424 cites W2143935409 @default.
• W2018093424 cites W2145310318 @default.
• W2018093424 cites W2146033515 @default.
• W2018093424 cites W2150710263 @default.
• W2018093424 cites W2152994191 @default.
• W2018093424 cites W2158217645 @default.
• W2018093424 cites W2917375902 @default.
• W2018093424 doi "https://doi.org/10.1074/mcp.m112.019976" @default.
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