Construction, Analysis, and Utilization of Co-Phosphorylation Networks to Characterize Cellular Signaling

构建、分析和利用共磷酸化网络来表征细胞信号传导

• 批准号: 10289148
• 负责人: Mehmet Koyuturk
• 金额: $ 38.85万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-15 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10289148
• 关键词: Age; Algorithmic Software; Algorithms; Alzheimer' s Disease; Alzheimer' s disease model; Amyloid; Award; Basic Science; Biological Markers; Collaborations; Data; Development; Diagnosis; Disease; Disease Progression; Etiology; Exhibits; Female; Funding; Gender; Hippocampus (Brain); Lead; Light; Link; Mass Spectrum Analysis; Modeling; Mus; National Institute of General Medical Sciences; Nerve Degeneration; Network-based; Neurodegenerative Disorders; Parents; Phenotype; Phosphorylation; Phosphorylation Site; Phosphotransferases; Process; Prognosis; Proteins; Proteomics; Qi; Research; Research Personnel; Role; Signal Pathway; Signal Transduction; System; Tauopathies; Tissues; Up-Regulation; Variant; algorithm development; base; brain tissue; computerized tools; data modeling; experimental study; gender difference; male; molecular phenotype; mouse model; neuroinflammation; novel; phosphoproteomics; potential biomarker; prediction algorithm; sex; synuclein; tau Proteins; tool

Proteomic and phospho-proteomic data derived from mass spectrometry experiments offer unique opportunities to interrogate cellular signaling pathways and networks in an unbiased and comprehensive manner. The role of phosphorylation linked signaling processes in the development of Alzheimer's Disease (AD) is well-established, yet little is known about gender, age/disease stage,tissue, and etiology based variations in this signaling. This supplement will provide novel data that pertains to this cellular signaling, and the parent R01 provides novel computational tools for systems-level analysis of proteomic and phosphoproteomic data essential to characterizing the signaling landscape of Alzheimer's Disease. In the parent award, R01-LM-012980 (funded under PAR-18-896), we are developing enabling systems and network-based analyses of phosphoproteomic data in the context of a broad range of biomedical problems. Our project is advancing the field through development of algorithms for predicting kinase-substrate associations, inference of kinase activity, and identification of context-specific changes in cellular signaling. An opportunity to expand the focus of this award around Alzheimer's disease models exists due to an emerging collaboration with Dr. Mark Chance (proteomics expert, co-investigator for parent award) and Dr. Xin Qi (neurodegenerative disease expert, consultant for parent award). These co-investigators recently received supplemental funding from NIGMS/NIA (3 R01 GM117208-03S1) to collect pivotal proteomics and phosphoproteomics data on brain tissue from the 5XFAD AD mouse model at various stages of disease development. The temporal progression of the plaque-centered disease in the 5XFAD mouse model highlights the initial development of neuroinflammation “proteomic phenotypes” followed by neurodegeneration-linked molecular phenotypes, including specific upregulation of many Alzheimer's related proteins like synucleins and tau from data examined in the hippocampus. In this supplement under (NOT-AG-18-008), we will leverage our network-based algorithms to accelerate AD research by further characterizing the specific signaling changes that underlie neuronal degeneration in a tauopathy mouse model (PS19) as a function of gender, stage of development, and tissue type to provide complementary basic science systems level understanding of disease progression in AD mouse models. Using these mouse models , we will identify signaling networks composed of specific kinases, substrates, and phosphorylation sites that exhibit dysregulation in male and female mice representing different etiologies of Alzheimer's Disease (Supplement Aim 1) and potential biomarkers that can aid in the diagnosis and prognosis of Alzheimer's Disease at different stages (Supplement Aim 2).

来自质谱实验的蛋白质组学和磷酸化蛋白质组学数据提供了独特的机会 以公正和全面的方式询问细胞信号通路和网络。的作用 在阿尔茨海默病（AD）的发展中磷酸化相关的信号传导过程是公认的， 然而，对该信号传导中基于性别、年龄/疾病阶段、组织和病因学的变化知之甚少。这 补充物将提供与这种细胞信号传导有关的新数据，并且亲本R 01提供了新的 用于蛋白质组学和磷酸化蛋白质组学数据的系统级分析的计算工具， 描绘了阿尔茨海默病的信号景观。 在母公司奖R 01-LM-012980（在PAR-18-896下资助）中，我们正在开发使能系统 以及在广泛的生物医学问题的背景下对磷酸化蛋白质组数据进行基于网络的分析。 我们的项目是通过开发预测激酶-底物关联的算法来推进该领域， 激酶活性的推断，以及细胞信号传导中环境特异性变化的鉴定。的机会 扩大围绕阿尔茨海默病模型的这个奖项的重点存在，由于一个新兴的合作， 博士Mark Chance（蛋白质组学专家，父母奖共同研究者）和Xin Qi博士（神经退行性疾病 疾病专家、家长奖顾问）。这些合作研究人员最近获得了补充资金 从NIGMS/NIA（3 R 01 GM 117208 - 03 S1）收集大脑关键蛋白质组学和磷酸化蛋白质组学数据 在疾病发展的各个阶段，来自5XFAD AD小鼠模型的组织。时间进程 在5XFAD小鼠模型中的斑块中心性疾病的研究强调了 神经炎症“蛋白质组表型”之后是神经变性相关的分子表型， 包括许多阿尔茨海默氏症相关蛋白质如突触核蛋白和tau蛋白的特异性上调， 在海马区。 在（NOT-AG-18-008）的补充中，我们将利用基于网络的算法来加速 通过进一步表征AD研究中神经元变性的特定信号变化， tau蛋白病小鼠模型（PS19）作为性别、发育阶段和组织类型的函数，以提供 补充基础科学系统水平的理解，在AD小鼠模型的疾病进展。使用 这些小鼠模型，我们将确定由特定激酶，底物， 在雄性和雌性小鼠中表现出失调的磷酸化位点，代表了不同的病因， 阿尔茨海默病（补充目标1）和潜在的生物标志物，可以帮助诊断和预后 阿尔茨海默病在不同阶段的变化（补充目标2）。