Single-cell analysis of the lung immune microenvironment and cell-cell interactions across healthy and diseased patients

项目摘要 肺部疾病如哮喘被认为是由于细胞类型比例、细胞功能 以及呼吸系统不同隔室中的组织结构。最近的进展高- 通过单细胞RNA测序（scRNA-seq），能够全面表征 肺的细胞普查，这导致了新的细胞类型和细胞的显着数量的新发现， 包括我们团队最近发现的肺离子细胞。 然而，我们对细胞类型关系及其更高级组织结构的理解仍然是有限的。 在健康和疾病方面缺乏。到2020年，来自健康和健康人群的scRNA-seq数据将超过100万个细胞。 患病的肺部患者将变得可用，这将提供前所未有的分辨率和统计能力 研究健康人和患病人不同解剖部位肺微环境的变化， 个体这种奋进由于其高维性而提出了若干计算挑战。 scRNA-seq数据中细胞通讯的数据和分析工具，以及与空间 信息仍处于初级阶段。我们建议整合高维scRNA-seq数据并校正 实验室之间的批量效应，以建立一个统一注释的单细胞图谱， 数百名健康和哮喘患者。这样的地图集将使我们能够描述相似之处， 沿近端-远端轴沿着不同位置的细胞组成和细胞间相互作用的差异 并评估临床相关因素（如年龄和吸烟史）对健康人肺的影响， 细胞组成和组织。位置特异性肺微环境分析对于 了解肺部疾病发病机制的背景，特别是在哮喘的背景下。此外，委员会认为， 在数百名正常人的解剖学匹配区域中的肺微环境之间的比较 哮喘患者将发现通常失调的细胞比例和细胞间的相互作用， 提供关于治疗目标的共享途径的信息。在本研究的范围之外，我们的目标是验证 使用基于序列或荧光的空间数据新发现的细胞间相互作用，可供我们 通过人类细胞图谱网络和我们在西奈山正在进行的合作，

PROJECT SUMMARY Lung diseases, such as asthma, are believe to arise due to alterations in cell type proportion, cellular function, and tissue organization in different compartments of the respiratory system. Recent advances in high- throughput single cell RNA-sequencing (scRNA-seq) have enabled comprehensive characterization of the cellular census of the lung, which has led to a remarkable number of novel findings in new cell types and cell states at homeostasis and in disease, including our team’s recent discovery of the pulmonary ionocyte. However, our understanding of the cell type relationships and their higher order tissue organization is still lacking in the context of health and disease. In 2020, over 1 million cells of scRNA-seq data from healthy and diseased lung patients will become available, which will provide unprecedented resolution and statistical power to study the variation in the lung microenviroment across different anatomical locations in healthy and diseased individuals. Such an endeavor presents several computational challenges due to the high-dimensionality of the data and because analysis tools of cellular communication in scRNA-seq data and integration with spatial information are still at their infancy. We propose to integrate high-dimensional scRNA-seq data and correct for batch effects between laboratories in order to build a uniformly annotated single-cell atlas of more than one hundred healthy and asthma patients. Such an atlas would enable us to characterize the similarities and differences in cellular composition and cell-cell interactions at different locations along the proximal-distal axis of the healthy human lung and assess the effects of clinical correlates, such as age and smoking history, on cellular composition and organization. Location specific lung microenvironment analysis is critical to understand the context of lung disease pathogenesis, especially in the context of asthma. Furthermore, comparison between the lung microenvironment in anatomically matched regions across hundreds of normal and asthma patients will uncover commonly dysregulated cellular proportions and cell-cell interactions that can inform on shared pathways to target therapeutically. Beyond the scope of this study, we aim to validate the newly discovered cell-cell interactions using sequence- or fluoresce-based spatial data, that is available to our lab through the Human Cell Atlas network and through our ongoing collaborations at Mount Sinai.