Identification of synaptosomal proteins binding to monomeric and oligomeric α-synuclein

鉴定与单体和寡聚体 α-突触核蛋白结合的突触体蛋白

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作者:Cristine Betzer, A James Movius, Min Shi, Wei-Ping Gai, Jing Zhang, Poul Henning Jensen

Abstract

Monomeric α-synuclein (αSN) species are abundant in nerve terminals where they are hypothesized to play a physiological role related to synaptic vesicle turn-over. In Parkinson's disease (PD) and dementia with Lewy body (DLB), αSN accumulates as aggregated soluble oligomers in terminals, axons and the somatodendritic compartment and insoluble filaments in Lewy inclusions and Lewy neurites. The autosomal dominant heritability associated to mutations in the αSN gene suggest a gain of function associated to aggregated αSN. We have conducted a proteomic screen to identify the αSN interactome in brain synaptosomes. Porcine brain synaptosomes were fractionated, solubilized in non-denaturing detergent and subjected to co-immunoprecipitation using purified recombinant human αSN monomers or oligomers as bait. The isolated αSN binding proteins were identified with LC-LTQ-orbitrap tandem mass spectrometry and quantified by peak area using Windows client application, Skyline Targeted Proteomic Environment. Data are available via ProteomeXchange with identifier PXD001462. To quantify the preferential binding an average fold increase was calculated by comparing binding to monomer and oligomer. We identified 10 proteins preferentially binding monomer, and 76 binding preferentially to oligomer and a group of 92 proteins not displaying any preferred conformation of αSN. The proteomic data were validated by immunoprecipitation in both human and porcine brain extracts using antibodies against monomer αSN interactors: Abl interactor 1, and myelin proteolipid protein, and oligomer interactors: glutamate decarboxylase 2, synapsin 1, glial fibrillary acidic protein, and VAMP-2. We demonstrate the existence of αSN conformation selective ligands and present lists of proteins, whose identity and functions will be useful for modeling normal and pathological αSN dependent processes.

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