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.

抽象的 呼吸系统结构复杂，由许多负责的室或壁龛组成 在呼吸过程中发挥独特的功能。虽然人类呼吸系统表现出显着的相似性 对于老鼠等啮齿类动物，它包含独特的隔间和结构，人们对这些隔间和结构知之甚少，但很可能 对于了解疾病的病因和进展很重要。举个例子，沿线的异质性 人类气道的近端-远端轴与小鼠气道显着不同，这可能是缺乏的基础 适合许多人类肺部疾病的啮齿动物模型。这种缺乏理解对于人类来说是相似的 肺血管系统，很少存在肺动脉高压等疾病的动物模型。详细的 对发育中的人肺中的这些隔室和其他隔室的分析将导致识别新的 气道近远端轴和沿气道近远端轴的单个细胞的细胞谱系和分子特征 肺血管系统。这些数据需要与高分辨率成像技术相结合来构建 人类肺部发育的细胞图谱。 LungMAP 联盟第二阶段的主要目标之一是 该项目最初于 2014 年启动，旨在定义独特的结构、细胞和基因表达复杂性 使用包括单细胞分析在内的复杂和新兴技术来研究人类肺部的发育过程。 鉴于人肺的空间特定结构复杂性，我们建议重点关注三个重要的方面 隔室或壁龛：1) 近端气道，2) 远端气道和肺泡，包括终端和肺泡 呼吸细支气管（TB 和 RB），3) 肺血管系统。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定义这三个生态位的细胞和分子异质性 在单细胞水平上，并传播这些信息，使研究人员能够提取细胞间的串扰 定义并维持发育中的人类肺部的这三个生态位。我组开发并应用 新颖的基因组和成像工具，并设计了交互式网络应用程序来显示和询问多个 维度数据，允许对生成的数据进行特定的、交互式的、持续的分析 LungMAP 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，在特定的肺生态位内进行研究。我们的最终目标 建议 1) 识别并绘制人类发育中三个关键生态位内的细胞谱系 呼吸系统，2）定义它们彼此之间的空间组织，3）提供新颖的数据集以允许 研究人员确定对其出生后发育至关重要的细胞间相互作用，并且 4）组织 并使用多维基因组和显示数据以供整个科学界广泛访问 蛋白质组分析工具。