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: 10213132
• 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/10213132
• 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; 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; 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