QUANTIFICATION OF THE SYNAPTOSOMAL PROTEOME OF THE RAT CEREBELLUM DURING POST-NA
QUANTIFICATION OF THE SYNAPTOSOMAL PROTEOME OF THE RAT CEREBELLUM DURING POST-NA
批准号:
7723624
负责人:
John R Yates III
金额:
$0.08万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-01 至 2009-08-31
关键词:
Animal ModelBrainCerebellumComputer Retrieval of Information on Scientific Projects DatabaseDevelopmentFundingGrantInstitutionLabelMammalsMass Spectrum AnalysisNeurological ModelsProteinsProteomeProteomicsRattusReportingResearchResearch PersonnelResourcesSourceStable Isotope LabelingStandards of Weights and MeasuresStatistically SignificantSynapsesTechniquesTechnologyTimeUnited States National Institutes of Healthnervous system disorderneurodevelopmentnovelprotein expression
中文摘要
点击翻译按钮获取中文摘要
英文摘要
This subproject is one of many research subprojects utilizing the
resources provided by a Center grant funded by NIH/NCRR. The subproject and
investigator (PI) may have received primary funding from another NIH source,
and thus could be represented in other CRISP entries. The institution listed is
for the Center, which is not necessarily the institution for the investigator.
Large-scale proteomic analysis of the mammalian brain has been successfully performed with mass spectrometry techniques, such as Multidimensional Protein Identification Technology (MudPIT), to identify hundreds to thousands of proteins. Strategies to efficiently quantify protein expression levels in the brain in a large-scale fashion, however, are lacking. Here, we demonstrate a novel quantification strategy for brain proteomics called SILAM (Stable Isotope Labeling in Mammals). We utilized a (15)N metabolically labeled rat brain as an internal standard to perform quantitative MudPIT analysis on the synaptosomal fraction of the cerebellum during post-natal development. We quantified the protein expression level of 1138 proteins in four developmental time points, and 196 protein alterations were determined to be statistically significant. Over 50% of the developmental changes observed have been previously reported using other protein quantification techniques, and we also identified proteins as potential novel regulators of neurodevelopment. We report the first large-scale proteomic analysis of synaptic development in the cerebellum, and we demonstrate a useful quantitative strategy for studying animal models of neurological disease.
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