Single-Cell Transcriptomic Analysis to Identify Drivers of Pulmonary Fibrosis

项目总结 这个K08奖项的提议是出于两个首要目标：1)支持科学和专业人员 候选人保罗·雷夫曼博士朝着实现他作为一名内科医生的成功职业目标的方向发展 具有系统生物学方法应用于研究的科学家和独立调查员 慢性肺部疾病，以及2)调查单细胞转录图谱是否能提供新的见解 肺纤维化的病理生物学。肺纤维化是一种致命的进行性疾病， 诊断方法仍然不精确，缺乏有效的治疗方法。与他的导师们一起，戴维斯博士。 斯科特·布丁格和路易斯·S·阿马拉尔，候选人已经制定了一项全面的培训计划，将确保Dr。 雷夫曼在开发假设、设计和完善方面获得了新的知识和熟练程度 进行实验，分析数据，并将发现传达给科学界。作为一个必不可少的组件 在此培训计划中，候选人将使用系统生物学方法来开发分析工具 来自肺纤维化患者的单细胞转录数据集。 单细胞转录图谱越来越多地用于研究人类疾病的病理生物学和 作为开发新的疾病生物标志物的基础。开发和验证用于快速分析的工具 不断增长的单细胞转录数据与精炼技术一样具有挑战性 来自健康和患病组织的数据。特别是，目前还不知道单细胞RNA的分析是否 测序(scRNA-Seq)和单核RNA测序(SnRNA-Seq)数据可用于量化 准确地测定肺的细胞成分并识别健康人和健康人之间的基因表达差异 肺纤维化。我们的初步数据表明，肺中的scRNA-Seq可识别促纤维化基因的表达 在肺纤维化患者中，这是个体之间的异质性。我们还发现scRNA-Seq 对某些构成肺细胞的群体采样不足。因此，我们设计了这个方案来测试 假设肺纤维化患者肺样本的单细胞转录分析可以 用于识别疾病内型。在具体目标1中，候选人将确定SnRNA-Seq是否能够 肺纤维化期间肺细胞成分的量化。在具体目标2中，候选人 将开发工具来使用在从SSC-ILD患者和正常患者获得的样本上进行的scRNA-Seq 对照，以获得对疾病病理生物学的新见解。在这个奖项的过程中，候选人将获得 新技术，包括从冷冻保存的肺组织中产生SnRNA-Seq，肺体视学，原位RNA 杂交、互补基因组数据集的分析和临床表型的纳入 将信息转化为基因组分析。完成拟议的工作将为以下人员提供严格的培训计划 Reyfman博士，并将提供可能导致改善肺纤维化患者治疗方法的见解。

PROJECT SUMMARY This proposal for a K08 Award is motivated by two overarching goals: 1) to support the scientific and professional development of the candidate, Dr. Paul Reyfman, towards achieving his career goal of succeeding as a physician scientist and independent investigator with expertise in systems biology approaches applied to the study of chronic lung disease, and 2) to investigate whether single-cell transcriptomic profiling can provide novel insights into the pathobiology of pulmonary fibrosis. Pulmonary fibrosis is a deadly and progressive condition for which diagnostic approaches remain imprecise and effective therapies are lacking. Together with his mentors, Drs. Scott Budinger and Luís Amaral, the candidate has developed a comprehensive training plan that will ensure Dr. Reyfman acquires new knowledge and proficiencies in developing hypotheses, designing and completing experiments, analyzing data, and communicating findings to the scientific community. As an essential component of this training plan, the candidate will employ systems biology approaches to developing tools for analysis of single-cell transcriptomic datasets generated from patients with pulmonary fibrosis. Single-cell transcriptomic profiling is increasingly used to investigate the pathobiology of disease in humans and as a basis for developing novel biomarkers of disease. Developing and validating tools for analyzing the rapidly growing quantity of single-cell transcriptomic data is as much of a challenge as refining techniques for generating data from healthy and diseased tissues. In particular, it is not known whether analysis of single-cell RNA sequencing (scRNA-Seq) and single-nucleus RNA sequencing (snRNA-Seq) data can be used to quantify accurately the cellular composition of the lung and to identify gene expression differences between health and pulmonary fibrosis. Our preliminary data suggest that scRNA-Seq of lung identifies profibrotic gene expression in patients with pulmonary fibrosis that is heterogeneous between individuals. We also found that scRNA-Seq undersampled certain constituent lung cellular populations. Accordingly, we designed this proposal to test the hypothesis that single-cell transcriptomic analysis of lung samples from patients with pulmonary fibrosis can be used to identify disease endotypes. In Specific Aim 1, the candidate will determine whether snRNA-Seq enables quantification of the cellular composition of the lung during pulmonary fibrosis. In Specific Aim 2, the candidate will develop tools for using scRNA-Seq performed on specimens obtained from patients with SSc-ILD and normal controls to gain novel insights into disease pathobiology. Over the course of this award, the candidate will gain new skills including in generating snRNA-Seq from cryopreserved lung tissue, in lung stereology, in RNA in situ hybridization, in analysis of complementary genomic datasets, and in incorporation of clinical phenotypic information into genomic analyses. Accomplishing the proposed work will provide a rigorous training program for Dr. Reyfman and will provide insights that could lead to improved therapies for patients with pulmonary fibrosis.