Yale/NIDA Neuroproteomics Center

我们建议不断改进耶鲁/NIDA神经蛋白质组学中心， 耶鲁大学在蛋白质组学和信号转导在大脑中的强大计划与神经科学家从8 美国各地的其他机构创建一个国家资源，将合作确定适应性变化 在对滥用物质的反应中发生的蛋白质信号中。23个学院， 对精神活性成瘾药物分子作用的高度创新性研究记录，以及 神经生物学的其他基本方面，将在一个独特的协同作用与凯克基金会一起工作 生物技术实验室创建的中心，其主题是“蛋白质组学的改变信号成瘾”。 该中心将使用最先进的蛋白质组学技术来分析神经元信号转导机制 以及这些过程中因药物滥用而发生的适应性变化。与联合董事 安格斯奈恩（精神病学）和肯尼斯威廉姆斯（摩尔。Biophys.和生物化学）在行政核心中， 中心包括Discovery Proteomics（DPC）和Targeted Proteomics（TPC）核心。生物物理技术 将蛋白质谱分析扩展到功能域，而来自DPC的脂质分析将扩展到功能域。 DPC将利用蛋白质组水平的分析，提供一个越来越生物系统水平的方法。一 生物统计学和生物信息学核心（BBC），包括高性能计算和生物信息学 耶鲁大学医学图书馆的支持计划将提供必要的支持， 蛋白质组学技术核心。核心试点研究项目是我们努力鼓励 强有力的指导关系，这将有助于吸引和培养未来的杰出科学家。 人们认为，伴随药物成瘾的行为适应是短期和长期的结果。 大脑奖励中心的适应性变化。因此，暴露于滥用药物调节细胞内信号传导 改变基因表达、蛋白翻译和蛋白翻译后修饰的过程。 反复暴露于药物滥用导致这些信号系统的稳定改变，这些信号系统对 成瘾大脑的化学和结构变化。该中心的研究目标包括 分析大麻，可卡因，尼古丁和阿片类药物对这些细胞内信号通路的作用， 大脑奖赏区和开发的方法，使蛋白质组学分析的单一类型的神经元 定义了构成滥用药物的行为和成瘾特性的电路。目标和数据- 对与滥用药物的作用有关的信号蛋白的独立MS分析将用于 分析药物滥用对基于基序的神经蛋白质组的影响，“中间向下”MS/MS，以及 其他新的方法被用来研究蛋白质翻译后修饰，并揭示 关键蛋白质的相互作用组。英国广播公司的一项重大举措将是开发新的方法， 基因组、转录组和蛋白质组数据与脑区域、细胞类型和等位基因特异性的整合。

We propose to continuously improve the Yale/NIDA Neuroproteomics Center that brings exceptionally strong Yale programs in proteomics and signal transduction in the brain together with neuroscientists from 8 other institutions across the U.S. to create a national resource that will collaborate to identify adaptive changes in protein signaling that occur in response to substances of abuse. Twenty-three faculty with established records of highly innovative research into the molecular actions of psychoactive addictive drugs, as well as of other basic aspects of neurobiology, will work together in a unique synergy with the Keck Foundation Biotechnology Laboratory to create the Center, whose theme is “Proteomics of Altered Signaling in Addiction”. The Center will use cutting edge proteomic technologies to analyze neuronal signal transduction mechanisms and the adaptive changes in these processes that occur in response to drugs of abuse. With Co-Directors Angus Nairn (Psychiatry) and Kenneth Williams (Mol. Biophys. & Biochem.) in the Administrative Core, the Center includes Discovery Proteomics (DPC) and Targeted Proteomics (TPC) Cores. Biophysical technologies from the DPC will extend protein profiling analyses into the functional domain while lipid analyses from the DPC will leverage proteome level analyses to provide an increasingly biological systems level approach. A Biostatistics and Bioinformatics Core (BBC) that includes high performance computing and the Bioinformatics Support Program in the Yale Medical Library will provide essential support that will leverage the value of each of the proteomic technology cores. A Pilot Research Project Core is a cornerstone in our efforts to encourage strong mentoring relationships that will help attract and train future outstanding scientists. Behavioral adaptations that accompany drug addiction are believed to result from both short and long-term adaptive changes in brain reward centers. Thus, exposure to drugs of abuse regulates intracellular signaling processes that alter gene expression, protein translation, and protein post-translational modifications. Repeated exposure to drugs of abuse leads to stable alterations in these signaling systems that are critical for the changes in brain chemistry and structure of the addicted brain. The Center's research goals include analysis of the actions of cannabis, cocaine, nicotine, and opioids on these intracellular signaling pathways in brain reward areas and development of methods that enable proteomic analysis of the single types of neurons that define the circuits that underlie the actions and addictive properties of drugs of abuse. Targeted and data- independent MS analyses of signaling proteins implicated in the actions of drugs of abuse will be used to analyze the impact of substance abuse on the neuroproteome with motif-based, “Middle-down” MS/MS, and other novel approaches being used to study protein post-translational modifications and to uncover the interactomes of key proteins. A major initiative of the BBC will be to develop novel methods for deep integration of genomic, transcriptomic, and proteomic data with brain region, cell type and allele-specificity.