High-throughput technology for automated single cell expression analysis for C. e

用于大肠杆菌自动单细胞表达分析的高通量技术

• 批准号: 7830334
• 负责人: STUART K KIM
• 金额: $ 50万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7830334
• 关键词: Adult; Age; Aging; Algorithms; Animal Model; Animals; Area; Atlases; Automated Annotation; Caenorhabditis elegans; Cell Lineage; Cell Nucleus; Cells; Cellular Morphology; Complex; Computer Analysis; DNA Microarray Chip; Data; Data Sources; Databases; Development; Feedback; Gene Expression; Genes; Genomics; Graph; Image; Image Analysis; Individual; Knowledge; Larva; Machine Learning; Maps; Markov Chains; Measurement; Measures; Methods; Molecular; Molecular Profiling; Names; Output; Pattern; Play; Population; Principal Investigator; Property; Proteomics; Reporter; Research; Resolution; Resources; Role; Scientist; Source; Staging; Technology; Time; Tissues; Training; Transgenic Organisms; abstracting; base; cell analyzer; cell type; digital; high throughput technology; improved; metabolomics; molecular phenotype; mutant; programs

DESCRIPTION (provided by applicant): Research Area: This proposal is for 06: Enabling Technologies and specific Challenge Topic HG-102 Technologies for obtaining genomic, proteomic, and metabolomic data from individual viable cells in complex tissues. Abstract Most existing technologies can only measure the properties of a population of cells and not the properties of individual cells. C. elegans is unique among model organisms in that the complete cell lineage is known, enabling one to identify each nucleus in an individual. We have developed an automated cell lineage analyzer capable of extracting digital, single-cell expression information from confocal images of worms expressing GFP reporters. This cell analyzer can be used to extract expression data in a semi-high throughput manner. As proof-of-principle, we generated expression profiles of 93 genes in 363 specific cells from L1 stage larvae, and were able to quantitatively analyze expression of each gene as well as the molecular expression signature for each cell. This proposal is to first develop a generalized method to automatically annotate nuclei from confocal images, by assigning them a specific name from the cell lineage. We will then use the automated cell lineage analyzer in a data pipeline to analyze images from 1000 genes at six different developmental stages in 8000 confocal images. By generating a single cell expression database over the next two years, we will create a rich, new source of data for many years to come. Currently, images of worms in confocal data stacks can only be browsed manually, one gene at a time. Our database will convert images to quantitative expression values in an expression table that is suitable for computational analysis. Single cell expression analysis is a conceptually new way to study development and aging in C. elegans, using quantitative molecular signatures rather than cellular morphology. For instance, we can use the molecular signatures to determine how many different cell types are formed out of the total 959 cells in the lineage, to determine when and where during development cells begin to express different sets of genes, and to look for the way in which molecular fates are repeated in the cell lineage in order to extract the underlying regulatory modules that guide developmental pattern. This digital, single-cell expression database will be unique because C. elegans is the only model organism in which we can map the identities of individual nuclei and to our knowledge, we are the only group with a cell lineage annotator capable of extracting single cell expression information from larvae and adults.

描述（由申请人提供）：研究领域：本提案针对06：使能技术和特定挑战主题HG-102技术，用于从复杂组织中的单个活细胞中获得基因组学、蛋白质组学和代谢组学数据。摘要现有的大多数技术只能测量细胞群体的性质，而不能测量单个细胞的性质。C.秀丽线虫在模式生物中是独特的，因为完整的细胞谱系是已知的，使得人们能够识别个体中的每个细胞核。我们已经开发了一种自动化的细胞谱系分析仪，能够提取数字，单细胞表达信息的共聚焦图像的蠕虫表达GFP报告。该细胞分析仪可用于以半高通量方式提取表达数据。作为原理证明，我们在来自L1期幼虫的363个特定细胞中生成了93个基因的表达谱，并且能够定量分析每个基因的表达以及每个细胞的分子表达特征。该建议是首先开发一种通用的方法，通过从细胞谱系中为细胞核分配一个特定的名称来自动注释共聚焦图像中的细胞核。然后，我们将在数据管道中使用自动化细胞谱系分析仪来分析8000张共聚焦图像中6个不同发育阶段的1000个基因的图像。通过在接下来的两年中生成一个单细胞表达数据库，我们将为未来的许多年创建一个丰富的新数据源。目前，共聚焦数据栈中的蠕虫图像只能手动浏览，一次一个基因。我们的数据库将图像转换为适合计算分析的表达表中的定量表达值。单细胞表达分析是一种概念上的新方法，研究发育和衰老的C。elegans，使用定量分子标记，而不是细胞形态。例如，我们可以使用分子特征来确定谱系中总共959个细胞中形成了多少种不同的细胞类型，确定发育期间细胞开始表达不同基因组的时间和地点，并寻找分子命运在细胞谱系中重复的方式，以提取指导发育模式的潜在调节模块。这个数字化的单细胞表达数据库将是独一无二的，因为C。秀丽线虫是唯一一种我们可以绘制单个细胞核身份的模式生物，据我们所知，我们是唯一一个拥有能够从幼虫和成虫中提取单细胞表达信息的细胞谱系注释器的群体。