Proteomic Characterization of the Alzheimer's Disease Risk Factor BIN1 Interactome.

IF 5.5 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Molecular & Cellular Proteomics Pub Date : 2025-09-01 Epub Date: 2025-08-18 DOI:10.1016/j.mcpro.2025.101055
Joseph D McMillan, Shuai Wang, Jessica Wohlfahrt, Jennifer Guergues, Stanley M Stevens, Gopal Thinakaran
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引用次数: 0

Abstract

The gene BIN1 is the second-largest genetic risk factor for late-onset Alzheimer's disease (LOAD). It is expressed in neurons and glia in the brain as cell-type-specific and ubiquitous isoforms. BIN1 is an adaptor protein that regulates membrane dynamics in many cell types. Previously, we reported that BIN1 predominantly localizes to presynaptic terminals in neurons and regulates presynaptic vesicular release. However, the function of neuronal BIN1 in relation to LOAD is not yet fully understood. A significant gap in the field is the unbiased characterization of neuronal BIN1-interacting proteins and proximal neighbors. To address this gap and help define the functions of neuronal BIN1 in the brain, we employed TurboID-based proximity labeling to identify proteins biotinylated by the neuronal BIN1 isoform 1-TurboID fusion protein (BIN1iso1-TID) in cultured mouse neuroblastoma (N2a) cells in vitro and in adult mouse brain neurons in vivo. Label-free quantification-based proteomic analysis of the BIN1iso1-TID biotinylated proteins led to the discovery of 360 proteins in N2a cells and 897 proteins in mouse brain neurons, identified as BIN1iso1-associated (proximal) or interacting proteins. A total of 92 proteins were common in both datasets, indicating that these are high-confidence BIN1-interacting or proximity proteins. SynapticGO analysis of the mouse brain dataset revealed that BIN1iso1-TurboID labeled 159 synaptic proteins, with 60 corresponding to the synaptic vesicle cycle. Based on phosphorylation site analysis of the neuronal BIN1iso1-TID interactome and related kinase prediction, we selected and validated AAK1, CDK16, SYNJ1, PP2BA, and RANG through immunostaining and proximity ligation assays as members of the BIN1 interactome in the mouse brain. This study establishes a foundation for further investigations into the function of neuronal BIN1 by identifying several previously unknown proximal and potential interacting proteins of BIN1.

阿尔茨海默病危险因子BIN1相互作用组的蛋白质组学特征。
基因BIN1是迟发性阿尔茨海默病(LOAD)的第二大遗传风险因素。它在大脑的神经元和胶质细胞中以细胞类型特异性和普遍存在的亚型表达。BIN1是一种在许多细胞类型中调节膜动力学的衔接蛋白。先前,我们报道了BIN1主要定位于神经元的突触前末端,并调节突触前囊泡释放。然而,神经元BIN1在LOAD中的作用尚不完全清楚。该领域的一个重要空白是神经元b1相互作用蛋白和近端邻居的无偏表征。为了解决这一空白并帮助确定神经元BIN1在大脑中的功能,我们采用基于turboid的接近标记方法,在体外培养的小鼠神经母细胞瘤(N2a)细胞和体内成年小鼠脑神经细胞中鉴定被神经元BIN1异构体1-TurboID融合蛋白(BIN1iso1-TID)生物素化的蛋白质。对BIN1iso1-TID生物素化蛋白进行无标记定量的蛋白质组学分析,在N2a细胞中发现360个蛋白,在小鼠脑神经元中发现897个蛋白,被鉴定为bin1iso1相关蛋白(近端)或相互作用蛋白。在两个数据集中共有92种蛋白质,表明这些是高置信度的b1相互作用或邻近蛋白。对小鼠大脑数据集的SynapticGO分析显示,BIN1iso1-TurboID标记了159个突触蛋白,其中60个与突触囊泡周期相对应。基于神经元BIN1iso1-TID相互作用组的磷酸化位点分析和相关激酶预测,我们通过免疫染色和邻近结扎实验,选择并验证了AAK1、CDK16、SYNJ1、PP2BA和RANG作为小鼠脑内BIN1相互作用组的成员。本研究通过鉴定几个先前未知的与BIN1近端和潜在相互作用的蛋白,为进一步研究神经元BIN1的功能奠定了基础。
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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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