Multi-modal characterization of three human lung niches at the single cell level

单细胞水平上三个人肺生态位的多模式表征

• 批准号: 9815560
• 负责人: EDWARD E MORRISEY
• 金额: $ 88.59万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-19 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9815560
• 关键词: Alveolus; Animal Disease Models; Architecture; Atlases; Cell Communication; Cell Differentiation process; Cell Extracts; Cell Lineage; Cell Surface Proteins; Cell Survival; Cells; Chromatin; Communities; Complex; Coupled; Data; Data Analyses; Data Display; Data Set; Databases; Disease; Distal; Emerging Technologies; Epigenetic Process; Etiology; Exhibits; Gene Expression; Genetic Transcription; Genomics; Goals; Heterogeneity; Human; Imaging Device; Imaging Techniques; Individual; Lung; Lung diseases; Maps; Methods; Molecular; Molecular Profiling; Mus; Nuclear; Online Systems; Phase; Proteomics; Protocols documentation; Pulmonary Hypertension; Research Personnel; Respiration; Respiratory System; Rodent; Rodent Model; Stem cells; Structure; Structure of respiratory bronchiole; Techniques; Terminal Bronchiole; Tissues; cell type; data visualization; design; epigenome; epigenomics; genomic data; genomic tools; high resolution imaging; multidimensional data; multimodality; novel; postnatal development; single cell analysis; single-cell RNA sequencing; stem; tool; transcriptome; web app

ABSTRACT The respiratory system is architecturally complex and comprised of many compartments or niches responsible for unique functions during respiration. While the human respiratory system exhibits a significant level of similarity with rodents such as mice, it contains unique compartments and structures that are poorly understood but likely to be important in understanding disease etiology and progression. As an example, the heterogeneity along the proximal-distal axis of the human airway is significantly different than in the mouse, which may underlie the lack of appropriate rodent models for many human lung diseases. This lack of understanding is similar for the human pulmonary vasculature, where few animal models of diseases such as pulmonary hypertension exist. A detailed analysis of these compartments and others in the developing human lung will result in the identification of new cell lineages and molecular signatures of individual cells across the proximal-distal axis of the airways and along the pulmonary vasculature. These data will need to be coupled with high resolution imaging techniques to build a cellular atlas of the developing human lung. One of the major goals of Phase 2 of the LungMAP Consortium, which was originally initiated in 2014, is to define the unique architectural, cell, and gene expression complexities of the developing human lung using sophisticated and emerging technologies including single cell analytics. Given the spatially specific architectural complexities of the human lung, we propose to focus on three important compartments or niches: 1) the proximal airways, 2) the distal airways and alveolus including the terminal and respiratory bronchioles (TBs and RBs), and 3) the pulmonary vasculature. We will utilize multi-modal genomic, epigenomic, and proteomic techniques to define the cellular and molecular heterogeneity in these three niches at the single cell level, and disseminate this information to allow investigators to extract cell-cell crosstalk that defines and maintains these three niches in the developing human lung. Our group has developed and applied novel genomic and imaging tools and designed interactive web applications to display and interrogate multi- dimensional data that allows for specific, interactive, and continuous ongoing analysis of the data generated in the LungMAP Consortium. Importantly, our group has demonstrated the ability to define cell-cell interactions within specific lung niches by integrating genomic data with high resolution imaging. The ultimate goals of our proposal are to 1) identify and map the cell lineages within three critical niches of the developing human respiratory system, 2) define their spatial organization in relation to each other, 3) provide novel datasets to allow researchers to identify the cell-cell interactions that are critical for their postnatal development, and 4) organize and display the data for broad access throughout the scientific community using multi-dimensional genomic and proteomic analysis tools.

抽象的 呼吸系统在结构上是复杂的，由许多负责 对于呼吸过程中的独特功能。尽管人类呼吸系统表现出很大的相似性 啮齿动物（例如小鼠），它包含独特的隔室和结构，这些隔间和结构很少，但可能很可能 对于理解疾病的病因和进展很重要。例如，沿着的异质性 人类气道的近端轴与小鼠的近端轴显着不同，这可能是缺乏的。 许多人类肺部疾病的适当啮齿动物模型。缺乏理解对于人类是相似的 肺脉管系统，很少有疾病的动物模型，例如肺动脉高压。详细的 对这些隔室以及发展中的人肺中的其他分析将导致新的鉴定 单个细胞的细胞谱系和跨气道近端轴的单个细胞和分子特征 肺脉管系统。这些数据将需要与高分辨率成像技术结合起来以构建 发育中的人肺的细胞图中。 Lungmap财团2阶段的主要目标之一，是 最初于2014年启动的是定义独特的建筑，细胞和基因表达复杂性 使用包括单细胞分析在内的复杂技术和新兴技术的发展人类肺。 鉴于人肺的空间特定建筑复杂性，我们建议专注于三个重要的 车厢或利基市场：1）近端气道，2）远端气道和肺泡，包括码头和 呼吸道支气管（TBS和RB）和3）肺脉管系统。我们将利用多模式基因组， 表观基因组学和蛋白质组学技术，以定义这三个壁nir中的细胞和分子异质性 在单细胞水平上，并传播此信息，以使研究人员可以提取细胞细胞串扰 在发展中的人类肺中定义并维护这三个壁ni。我们的小组已经开发和应用 新颖的基因组和成像工具，并设计了交互式Web应用程序，以显示和询问多种 维度数据允许对生成的数据进行特定，互动和连续的持续分析 肺部财团。重要的是，我们的小组已经证明了定义细胞 - 细胞相互作用的能力 通过将基因组数据与高分辨率成像整合在一起，在特定的肺壁细分市场中。我们的最终目标 提案是1）识别并绘制发展中三个关键壁ni的细胞谱系 呼吸系统，2）定义其空间组织相互关系，3）提供新颖的数据集以允许 研究人员确定对产后发育至关重要的细胞细胞相互作用，4） 并使用多维基因组和 蛋白质组学分析工具。