Extrinsic Perturbations of Cell Physiology and Associated Regulatory Networks

细胞生理学和相关调节网络的外在扰动

• 批准号: 8925126
• 负责人: JOE W. GRAY
• 金额: $ 171.46万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-10 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8925126
• 关键词: Adhesions; Antibodies; Apoptosis; Archives; Behavior; Binding; Biological; Cell Line; Cell physiology; Cells; Communities; DNA Damage; Data; Data Analyses; Data Quality; Databases; Extracellular Matrix; Generations; Genes; Genetic Transcription; Glycoproteins; Goals; Growth; Image; Institutes; Internet; Machine Learning; Measurement; Measures; Metadata; Methods; Microarray Analysis; Modeling; Molecular; Molecular Profiling; Non-Malignant; Pathway interactions; Peptides; Phase; Phenotype; Phosphoproteins; Physiological; Printing; Process; Protein Array; Proteins; Proteomics; RNA; Resolution; Sampling; Signal Pathway; Signal Transduction; Site; Synapses; System; Technology; Tern; Testing; Therapeutic Agents; Time; Tissues; Transcript; Validation; base; cell behavior; cell motility; combinatorial; design; fluorescence imaging; genetic regulatory protein; human tissue; image processing; novel; public health relevance; response; senescence; transcriptomics

DESCRIPTION (provided by applicant): The overall goal of the Data Generation Aim is to produce high quality data measuring phenotypes, protein and phosphoproteomics, and RNA expression in 30 cell lines grown on diverse microenvironments (ME). This approach will significantly enhance the LINCS data matrix by providing phenotypic, proteomic, and transcriptomic data for cell lines under unique ME conditions. Furthermore, the data will be utilized for subsequent generation of cellular network signatures in the Data Analysis Aim. Sub aim 1.1 will be generate 10 different phenotypic endpoints for 30 cell lines grown on 3,060 MEs. We will utilize Microenvironment Microarrays (MEMA) to assess the effects of the ME on proliferation, apoptosis, differentiation state, cell binding, and motility in each cell line. Statistical analysis will identify 50 significnt MEs for validation each year in years 2-6 in sub aim 1.2.A (total of 250 conditions). Each of the 50 ME conditions will be re-tested with the same endpoints at a second site using MEMA technology to provide independent validation of the primary results. At the same time, the cells will be tested using the 50 ME conditions on a second set of arrays designed to model the elastic modulus of human tissues to determine the effects on phenotypes of the matrix stiffness. From the 50 conditions tested in the validation aims, 30 of the most concordant between the primary and validation sites will be selected annually for analysis by Reverse Phase Protein Array (RPPA) aim 1.2.B and RNA expression analysis (aim I.2.C.). The RPPA aim will produce data using 500 validated antibodies against proteins and phosphoproteins in key signaling pathways under each of the ME perturbations. The RNA expression analysis will examine 1000 key genes using Luminex bead technology developed by the LINCS group at the Broad Institute, who will perform the same analysis for us using RNA prepared from each of the cell lines grown under the ME conditions. In total, the RPPA and RNA expression analysis will generate data for 150 different ME conditions under 2 different elastic moduli. All data will be carefully curated, with extensive metadata collected, and provided to the LINCS community for populating the data matrix.

描述（由申请人提供）： 数据生成目的的总体目标是生产高质量的数据测量表型，蛋白质和磷酸蛋白质组学以及在不同的微环境（ME）生长的30个细胞系中的RNA表达（ME）。这种方法将通过在独特的ME条件下为细胞系提供表型，蛋白质组学和转录组数据，从而显着增强LINCS数据矩阵。此外，数据将在数据分析目标中随后生成蜂窝网络特征。 Sub Aim 1.1将生成10个不同的表型终点，用于3060 MES上生长的30个细胞系。我们将利用微环境 微阵列（MEMA）评估ME对每个细胞系中的增殖，细胞凋亡，分化状态，细胞结合和运动的影响。统计分析将在第2-6年中确定50个标志MES在SUB AIM 1.2.a（总计250条条件）中的验证。 50个ME条件中的每一个都将使用MEMA技术在第二个站点进行相同的端点重新测试，以提供对主要结果的独立验证。同时，将使用50个ME条件在第二组阵列上进行测试，旨在模拟人体组织的弹性模量，以确定对基质刚度表型的影响。从验证目标中测试的50条条件中，每年将选择主要和验证位点之间的最一致的30个条件，以通过反相蛋白阵列（RPPA）AIM 1.2.b和RNA表达分析（AIM I.2.C.）进行分析。 RPPA AIM将使用500种对蛋白质和磷蛋白进行的验证抗体在每个ME扰动下的关键信号通路中产生数据。 RNA表达分析将使用由Luminex珠技术在Broad Institute开发的Luminex珠技术检查1000个关键基因，该基因将使用从ME条件下生长的每个细胞系制备的RNA对我们进行相同的分析。总共，在2种不同的弹性模量下，RPPA和RNA表达分析将生成150个不同ME条件的数据。所有数据都将仔细策划，并收集了广泛的元数据，并提供给Lincs社区以填充数据矩阵。