Single Cell Transcriptomic Analysis of Pulmonary Fibrosis

PROJECT SUMMARY This proposal for an ATS Foundation Pulmonary Fibrosis Research Grant 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 singlecell transcriptomic profiling can provide novel insights into the biology 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 incorporating 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 to develop novel biomarkers of disease. Multiple techniques for single-cell transcriptomic profiling have been developed, including single-cell RNA sequencing (scRNA-Seq) and single-nucleus RNA sequencing (snRNA-Seq), but it is not known which technique is superior for investigating the pathobiology of pulmonary fibrosis, or whether these techniques can be used on clinically obtained specimens to develop biomarkers for pulmonary fibrosis. Our preliminary data suggest that scRNA-Seq of lung identifies profibrotic gene expression in patients with pulmonary fibrosis that is heterogenous between individuals. We also found that scRNA-Seq undersampled certain constituent lung cellular populations. Accordingly, we designed this proposal to test the hypotheses that snRNA-Seq is superior to scRNA-Seq for estimating the lung cellular composition and performs comparably for identifying transcriptomic changes between healthy and diseased states, and that biomarker development for pulmonary fibrosis using samples obtained routinely in clinical care is feasible. In Specific Aim 1, the candidate will determine whether snRNA-Seq is superior to scRNA-Seq for providing insight into the pathobiology of pulmonary fibrosis. In Specific Aim 2, the candidate will determine whether scRNA-Seq can identify transcriptional changes in alveolar macrophages from patients with pulmonary fibrosis from SSc-associated interstitial lung disease. Over the course of this award, the candidate will learn gain new skills including in snRNA-Seq, analyzing complementary genomic datasets, and incorporating 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.