Identifying Protein-Protein Network Interactions between COPD Susceptibility Genes

识别 COPD 易感基因之间的蛋白质-蛋白质网络相互作用

• 批准号: 10323060
• 负责人: Edwin K Silverman
• 金额: $ 79.47万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323060
• 关键词: Address; Affinity Chromatography; Alveolar Macrophages; Biological; Biological Assay; Biological Process; Bronchoscopy; CRISPR/Cas technology; Cell Aging; Cell Death; Cell Death Process; Cell Line; Cells; Chronic Obstructive Pulmonary Disease; Clustered Regularly Interspaced Short Palindromic Repeats; Co-Immunoprecipitations; Complex; Data; Databases; Disease; Disease susceptibility; Epithelial Cells; Excision; Future; Gene Proteins; Gene Silencing; Genes; Genetic Determinism; Genetic Diseases; Genetic Predisposition to Disease; Genomic Segment; Human; Inflammation; Laboratories; Link; Lung; Mass Spectrum Analysis; Methods; Microfibrils; Minority; Modeling; Molecular; Mus; Mutation; Network-based; Pathogenesis; Pathway interactions; Phenotype; Proteins; Public Health; Pulmonary Emphysema; Research; Sampling; Structure of parenchyma of lung; Susceptibility Gene; TGFB2 gene; Tissue-Specific Gene Expression; Trans-Omics for Precision Medicine; Transforming Growth Factor beta; base; bronchial epithelium; cell type; cigarette smoking; disorder risk; effective therapy; experimental study; exposure to cigarette smoke; extracellular; gene network; gene product; genome wide association study; genomic locus; innovation; insight; interest; novel; protein protein interaction; transcriptome sequencing; transcriptomics

PROJECT SUMMARY Genome-wide association studies (GWAS) of complex diseases like COPD have identified many genomic regions associated with disease, but the molecular mechanisms by which these genetic loci influence disease pathogenesis are largely unknown. The phenotypic effects of genetic alterations can result from disruptions of the coordinated interactions between proteins. However, the key genes within COPD GWAS loci have only been proven in a minority of those COPD GWAS regions, and network connections between the COPD GWAS gene products have rarely been identified. In this project, we will utilize COPD susceptibility genes supported by both GWAS and murine emphysema models to develop cell type-specific and disease-specific protein-protein interaction network modules related to COPD. We hypothesize that building disease network modules based on experimentally validated protein-protein interactions between COPD GWAS genes will identify novel biological connections that influence COPD-related disease processes of cell death, cellular senescence, and/or inflammation. We will perform affinity purification/mass spectrometry (AP-MS) assays of nine well-established COPD GWAS gene products. Interacting proteins that are part of network links between COPD GWAS genes based on the AP-MS assays will be further validated with co-immunoprecipitation assays. We will utilize disease network module building approaches that combine the new AP-MS experiments with existing molecular interactome data to find biological linkages between COPD GWAS gene products. We will identify cell type- specific protein-protein interaction networks by removing non-expressed genes based on RNA-Seq data in bronchial epithelial cells and alveolar macrophages, and disease-specific protein-protein interaction networks based on TOPMed RNA-Seq data from lung tissue in the Lung Tissue Research Consortium. For network paths linking COPD GWAS genes in the protein-protein interaction network, we will perturb disease network module components using CRISPR-Cas9 approaches. First, we will assess the effects of these perturbations on protein interactions of putative disease network paths. Second, we will assess the impact of these network node removal perturbations on cell-based COPD-related readouts, including cell death, cellular senescence, and inflammation. Positive phenotypic readouts in cell line experiments will be validated in primary human lung cells. This project will combine state-of-the-art computational and laboratory approaches to identify the protein-protein interaction network relationships between COPD GWAS genes within multiple lung cell types and to validate those network relationships using cell-based readouts of relevant biological processes for COPD pathogenesis.

项目摘要 COPD等复杂疾病的全基因组关联研究（GWAS）已经确定了许多基因组 与疾病相关的区域，但是这些遗传基因座影响疾病的分子机制 发病机理在很大程度上未知。遗传改变的表型作用可能是由 蛋白质之间的协调相互作用。但是，COPD GWAS基因座中的关键基因仅是 在少数COPD GWAS地区证明了COPD GWAS基因之间的网络连接 产品很少被识别。在这个项目中，我们将利用两者支持的COPD易感基因 GWAS和鼠肺气肿模型以开发细胞类型特异性和疾病特异性蛋白质蛋白 与COPD相关的交互网络模块。我们假设基于 经过实验验证的COPD GWAS基因之间的蛋白质 - 蛋白质相互作用将识别新的生物学 影响COPD相关疾病的连接的细胞死亡，细胞衰老和/或 炎。我们将执行九个公认的亲和力纯化/质谱法（AP-MS）测定 COPD GWAS基因产品。相互作用的蛋白质是COPD GWAS基因之间网络链接的一部分 基于AP-MS测定，将通过共免疫沉淀测定进一步验证。我们将利用疾病 网络模块构建方法将新的AP-MS实验与现有分子结合在一起 相互作用的数据以找到COPD GWAS基因产品之间的生物学联系。我们将确定细胞类型 - 特定的蛋白质 - 蛋白质相互作用网络通过基于RNA-seq数据去除非表达基因 支气管上皮细胞和肺泡巨噬细胞以及疾病特异性蛋白质 - 蛋白质相互作用网络 基于肺组织研究联盟中肺组织的顶级RNA-SEQ数据。对于网络路径 在蛋白质 - 蛋白质相互作用网络中链接COPD GWAS基因，我们将扰动疾病网络模块 使用CRISPR-CAS9方法的组件。首先，我们将评估这些扰动对蛋白质的影响 推定疾病网络路径的相互作用。其次，我们将评估这些网络节点删除的影响 对基于细胞的COPD相关读数的扰动，包括细胞死亡，细胞衰老和炎症。 细胞系实验中的阳性表型读数将在原代人肺细胞中进行验证。这个项目 将结合最先进的计算和实验室方法来识别蛋白质 - 蛋白质相互作用 多种肺细胞类型中COPD GWAS基因之间的网络关系，并验证这些网络 使用基于细胞的COPD发病机理的基于细胞的读数。