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

来自质谱学实验的蛋白质组和磷酸蛋白质组数据提供了独特的机会 以公正和全面的方式审问细胞信号通路和网络。的作用 在阿尔茨海默病(AD)的发展过程中，磷酸化连接的信号过程是公认的， 然而，关于这种信号在性别、年龄/疾病阶段、组织和病因学方面的变化知之甚少。这 补充剂将提供与该细胞信号有关的新数据，而亲本R01提供新的 蛋白质组和磷蛋白质组数据的系统级分析的计算工具 描述了阿尔茨海默氏症的信号特征。 在父奖项R01-LM-012980(根据PAR-18-896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背景下对磷蛋白质组数据的基于网络的分析。 我们的项目正在通过开发预测激酶-底物关联的算法来推动该领域的发展， 推断激酶活性，识别细胞信号中特定于上下文的变化。一次机会 扩大该奖项的重点是围绕阿尔茨海默病模型的存在，这是由于与 马克·钱斯博士(蛋白质组学专家，家长奖联合研究员)和辛琪博士(神经退行性疾病 疾病专家、家长奖顾问)。这些联合调查员最近得到了补充资金。 从NIGMS/NIA(3 R01 GM117208-03S1)收集关于脑的关键蛋白质组和磷酸蛋白质组数据 来自疾病发展不同阶段的5XFAD小鼠模型的组织。时间级数 在5XFAD小鼠模型中以斑块为中心的疾病的研究突出了 神经炎症性“蛋白质组表型”紧随其后的是神经变性相关的分子表型， 包括从所研究的数据中特异地上调许多阿尔茨海默病相关蛋白，如突触核蛋白和tau 在海马体中。 在(NOT-AG-18-008)下的此补充中，我们将利用我们基于网络的算法来加速 AD研究通过进一步表征导致神经元变性的特定信号变化 自闭症小鼠模型(PS19)作为性别、发育阶段和组织类型的功能提供 互补的基础科学系统提高了对AD小鼠模型中疾病进展的理解水平。vbl.使用 在这些小鼠模型中，我们将识别由特定的激酶、底物和 在雄性和雌性小鼠中表现出异常的磷酸化位点，代表不同的病因 阿尔茨海默病(补充目标1)和有助于诊断和预后的潜在生物标志物 阿尔茨海默病的不同阶段(补充目标2)。

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).