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

项目总结 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间的组织结构。高科技的最新进展 吞吐量单细胞RNA测序(scRNA-seq)使全面表征 对肺的细胞普查，这导致了在新细胞类型和细胞中的大量新发现 处于稳态和疾病状态，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的组织结构的理解仍然是 缺乏健康和疾病的背景。2020年，超过100万个细胞的scRNA-seq数据来自健康和 将提供患病的肺病患者，这将提供前所未有的分辨率和统计能力 健康人与疾病人不同解剖部位肺微环境变化的研究 个人。这种努力带来了几个计算挑战，这是由于 数据和因为scRNA-seq数据中的蜂窝通信分析工具以及与空间的整合 信息仍处于初级阶段。我们建议整合高维scRNA-seq数据并修正 实验室之间的批量效应，以便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 近、远轴不同位置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 细胞的组成和组织。特定部位的肺微环境分析对 了解肺部疾病的发病机制，特别是在哮喘的背景下。此外， 数百名正常人解剖配对区域肺微环境的比较 哮喘患者将发现常见的细胞比例失调和细胞-细胞相互作用 告知共同的治疗靶向路径。超出本研究的范围，我们的目标是验证 使用基于序列或荧光的空间数据的新发现的细胞-细胞相互作用，可用于我们的 实验室通过人类细胞图谱网络和我们在西奈山的持续合作。

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.