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: 10675745
• 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/10675745
• 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; Dimensions; 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; Structure; Structure of respiratory bronchiole; Techniques; Terminal Bronchiole; Tissues; cell type; data integration; 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 cells; 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.

摘要 呼吸系统是复杂的结构和组成的许多隔间或壁龛负责 在呼吸过程中的独特功能。虽然人类呼吸系统表现出显著的相似性， 对于啮齿类动物，如小鼠，它包含独特的隔间和结构，这些结构知之甚少，但可能 对了解疾病的病因和进展很重要。作为一个例子，沿沿着 人类气道的近端-远端轴与小鼠明显不同，这可能是缺乏的原因 合适的啮齿类动物模型来研究人类肺部疾病。这种缺乏理解的情况与人类相似， 肺血管，其中存在很少的疾病如肺动脉高压的动物模型。详细 对这些区室和发育中的人肺中的其他区室的分析将导致鉴定新的肺组织。 穿过气道的近端-远端轴和沿气道的沿着的细胞谱系和单个细胞的分子特征 肺血管这些数据将需要与高分辨率成像技术相结合， 人类肺部发育的细胞图谱肺MAP联盟第二阶段的主要目标之一， 最初于2014年启动，旨在定义独特的结构，细胞和基因表达复杂性， 利用包括单细胞分析在内的尖端和新兴技术， 考虑到人类肺部在空间上的特定结构复杂性，我们建议关注三个重要的 隔室或小凹：1）近端气道，2）远端气道和肺泡，包括末端， 呼吸性细支气管（TB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来确定这三个小生境中的细胞和分子异质性 在单细胞水平，并传播此信息，使研究人员能够提取细胞间串扰， 在发育中的人肺中定义并维持这三个小生境。我们的团队开发并应用了 新的基因组和成像工具，并设计了交互式网络应用程序，以显示和询问多个 三维数据，允许对生成的数据进行特定的、交互式的和持续的分析， 肺MAP联盟重要的是，我们的团队已经证明了定义细胞间相互作用的能力， 通过将基因组数据与高分辨率成像相结合，我们的最终目标 建议是：1）在发育中的人类的三个关键小生境内鉴定和绘制细胞谱系， 呼吸系统，2）定义它们彼此相关的空间组织，3）提供新的数据集， 研究人员确定细胞间的相互作用，这对他们的出生后发展至关重要，和4）组织 并使用多维基因组和 蛋白质组学分析工具。