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与蛋白质相互作用和蛋白质构象状态与 衰老和疾病过程。相互作用研究的起点将是大蛋白质相互作用 在模型系统中突变时，涉及已知会增加寿命的蛋白质直系同源物的网络 衰老。使用高吞吐量酵母双杂交方法生成的无标度网络包括2,172 与165种已知寿命蛋白相互作用的人蛋白在3,219中高度相互连接的独特二进制 成对。由于它们与已知寿命蛋白的相互作用，这2,172被认为是新颖的 候选长寿蛋白。编码已知和候选寿命蛋白的基因分析表明 它们在人类衰老期间的表达变化的基因高度丰富（根据微阵列 来自年轻人和老年人肌肉组织产生的数据）。 “长寿互动”将使用 生物信息学方法和新的寿命基因将使用秀丽隐杆线虫进行验证 寿命测定法。 一种互补的方法来发现与衰老有关的新蛋白 蛋白质组学方法是发现随着时间的流逝，衰老和疾病而变得不溶的蛋白质。我们 将确定蛋白质组在衰老模型生物体中的蛋白质组不溶性组的含量，衰老 小鼠组织和神经疾病小鼠模型的大脑。蛋白质发现将 在衰老和/或疾病期间的不溶性状态将进一步研究，以便在这些中可能作用 使用无脊椎动物和鼠标模型的过程。 特定目的1。发现和表征与寿命相关的新型基因 蛋白质相互作用网络。我们将挖掘现有的蛋白质相互作用网络以识别新型蛋白质 参与衰老和寿命。候选蛋白将使用信息方法优先考虑 年龄特异性的微阵列数据集并在衰老模型生物中对实验进行了验证。蛋白质 通过基于MS的蛋白质组学方法，将进一步研究为在衰老中具有角色的验证。 具体目的2。开发蛋白质溶解度年龄依赖性变化的蛋白质组规模图。 我们将使用基于MS的方法来确定哪些蛋白质以年龄的依赖方式变得不溶。 这将在衰老酵母，衰老和患病小鼠的衰老酵母中（例如大脑和大脑和患病小鼠） 肌肉）。蛋白质溶解度变化的动力学将在长寿突变酵母和线虫中进行测试，以及 同样在晚期神经变性的遗传模型中（e：g。AD，HD和PD小鼠模型）。蛋白质 被证明容易受到年龄依赖和疾病依赖性的不溶性的影响 以适当的无脊椎动物，基于细胞和小鼠的衰老和疾病模型为特征。