Protein Interactions and Protein Conformation in Aging and Disease (6 of 11)

衰老和疾病中的蛋白质相互作用和蛋白质构象（11 中的 6）

• 批准号: 7872975
• 负责人: ROBERT E HUGHES
• 金额: $ 47.1万
• 依托单位: BUCK INSTITUTE FOR RESEARCH ON AGING
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-28 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7872975
• 关键词: Age; Aging; Animal Model; Bioinformatics; Biological Assay; Biological Models; Brain; Caenorhabditis elegans; Cells; Data; Data Set; Disease; Genes; Genetic Models; Human; Informatics; Invertebrates; Kinetics; Life; Longevity; Maps; Methods; Mining; Molecular Conformation; Mus; Muscle; Mutate; Nematoda; Nerve Degeneration; Orthologous Gene; Process; Protein Conformation; Proteins; Proteome; Proteomics; Role; Solubility; Testing; Time; Tissues; Two-Hybrid System Techniques; Yeasts; age related; base; brain tissue; longevity gene; mouse model; mutant; nervous system disorder; novel; protein protein interaction

We propose to define and characterize protein interactions and protein conformational states relevant to aging and disease processes. A starting point for the interaction studies will be a large protein interaction network involving human orthologs of proteins known to increase longevity when mutated in models systems of aging. This scale-free network, generated using high throughput yeast two-hybrid methods, includes 2,172 human proteins interacting with 165 known longevity proteins in 3,219 highly interconnected unique binary pairs. Because of their interaction with known longevity proteins, these 2,172 are considered to be novel candidate longevity proteins. Analysis of genes encoding known and candidate longevity proteins show that they are highly enriched for genes whose expression changes during human aging (according to microarray data generated from young and old human muscle tissue). The "longevity interactome" will be mined using bioinformatic methods and novel longevity genes derived from the network will be validated using C. elegans life span assays. A complementary approach to discovering novel proteins involved in aging will be to use mass spectrometrybased proteomic methods to discover proteins that become insoluble over time, in aging and disease. We will determine the content of the SDS insoluble fraction of the proteome in aging model organisms, aging mouse tissues and brains from mouse models of neurological disease. Proteins found to partition into insoluble states during aging and/or disease will be investigated further for possible functional roles in these processes using invertebrate and mouse models. Specific Aim 1. To discover and characterize novel genes relevant to longevity using an aging protein interaction network. We will mine an existing protein interaction network to identify novel protein involved in aging and longevity. Candidate proteins will be prioritized using informatic methods, compared to age-specific microarray datasets and validated experimentally in model organisms of aging. Proteins validated as having roles in aging will be studied further using MS-based proteomic methods. Specific Aim 2. To develop proteome-scale maps of age-dependent changes in protein solubility. We will use MS-based methods to determine which proteins become insoluble in an age-dependent manner. This will be done in aging yeast, nematodes and tissues from aging and diseased mice (e.g. brain and muscle). Kinetics of changes in protein solubility will be tested in long-lived mutant yeast and nematodes and also in genetic models of late-onset neurodegeneration (e:g. AD, HD and PD mouse models). Proteins shown to be susceptible to age-dependent and disease-dependent insolubility will be functionally characterized in appropriate invertebrate, cell-based and mouse models of aging and disease.

我们建议定义和表征蛋白质相互作用和蛋白质构象状态相关的 衰老和疾病过程。相互作用研究的起点将是一个大的蛋白质相互作用 涉及已知在模型系统中突变时增加寿命的蛋白质的人类直系同源物的网络 衰老的迹象这个无标度网络，使用高通量酵母双杂交方法产生，包括2172个 人类蛋白质与165种已知长寿蛋白质在3，219种高度互连的独特二进制中相互作用 对.由于它们与已知的长寿蛋白相互作用，这2，172被认为是新的 候选长寿蛋白。对编码已知和候选长寿蛋白的基因的分析表明， 它们高度富集在人类衰老过程中表达变化的基因（根据微阵列 从年轻和年老的人肌肉组织产生的数据）。“长寿互动组”将使用 生物信息学方法和新的长寿基因来自网络将使用C. elegans 寿命测定。 一种发现与衰老有关的新蛋白质的补充方法是使用基于质谱的方法。 蛋白质组学方法发现随着时间的推移，在衰老和疾病中变得不可溶的蛋白质。我们 将确定老化模型生物体中蛋白质组的SDS不溶性部分的含量，老化 小鼠组织和大脑的神经系统疾病的小鼠模型。发现蛋白质分配到 将进一步研究衰老和/或疾病期间的不溶性状态在这些疾病中的可能功能作用。 使用无脊椎动物和小鼠模型进行处理。 具体目标1。利用老化的方法发现和表征与长寿相关的新基因， 蛋白质相互作用网络我们将挖掘一个现有的蛋白质相互作用网络，以确定新的蛋白质 与衰老和长寿有关。将使用信息学方法对候选蛋白进行优先排序， 年龄特异性微阵列数据集，并在衰老的模型生物体中进行实验验证。蛋白 将使用基于MS的蛋白质组学方法进一步研究经验证在衰老中具有作用的蛋白质。 具体目标2。建立蛋白质溶解度随年龄变化的蛋白质组图谱。 我们将使用基于MS的方法来确定哪些蛋白质以年龄依赖性方式变得不溶。 这将在老化酵母、线虫和来自老化和患病小鼠的组织（例如脑和组织）中进行。 肌肉）。蛋白质溶解度变化的动力学将在长寿命突变酵母和线虫中进行测试， 也在迟发性神经变性的遗传模型中（例如，AD、HD和PD小鼠模型）。蛋白 显示易受年龄依赖性和疾病依赖性不溶性影响， 其特征在于适当的无脊椎动物、基于细胞和小鼠衰老和疾病模型。