Uncovering Developmental Trajectories of Airway Cells With Single-Cell RNA-Sequencing

Abstract

The lung is a complex organ that requires proper development, maintenance, and renewal of specialized cell types to support every stage of life. A better understanding of the biological and molecular processes that regulate normal lung cell function is essential for identifying etiologies of respiratory disease that may prove as useful therapeutic targets. In order to study this intricate multicellular system we need tools, such as single-cell RNA-sequencing (scRNA-seq), that can capture cell specific expression. Here, I expand the utility of scRNA-seq to airway samples which may prove as a useful research and clinical tool. Additionally, I apply scRNA-seq to evaluate a commonly used in vitro model system of airway regeneration. Rapid technology advancements have greatly expanded the accessibility and resolution of genomic tools. The research presented in this dissertation extends the single-cell gene expression profiling toolkit to clinical samples and an experimental model.Chapter 2 outlines methods that can be used to generate high-quality scRNA-seq data from induced sputum samples. Induced sputum is a non-invasive sampling method, making for a desirable technique in large-scale and/or longitudinal studies. Despite challenges presented by working with these samples, such as mucus contamination and dead cells, we established a processing method with superior quality metrics. Importantly, we found cells isolated from sputum with this protocol could be cryopreserved, enabling flexible study design. With this processing method, we identified major cell types like alveolar macrophages (AMs) and rarer immune cells, highlighting the utility of these methodologies for understanding lung homeostasis, development, and disease. Chapter 3 presents the first, to our knowledge, single-cell study of mouse tracheal epithelial cells in an air-liquid interface culture. Our data emphasizes the importance of evaluating established model systems with high-resolution tools like scRNA-seq. This analysis revealed both anticipated and unanticipated, novel cell populations, challenging the current understanding of this model system. The data presented underscores the importance of evaluating commonly-used models to advise future studies on the benefits or limitations of a given model for appropriate selection and data interpretation. Chapter 4 broadens our single-cell clinical sample toolset to readily-available endotracheal aspirates from premature neonates. These results provide the first transcriptional analysis of human airways during the golden hour of birth. By performing pseudotime analyses, we identified differentiation trajectories within neonatal myeloid precursors to distinct macrophage types relevant to respiratory health. Our data offers insight to airway development at a critical developmental period, where the lungs adapt to air exposure and permit breathing. Future studies may draw on our baseline data to identify potential disease biomarkers or therapeutic targets. The goal of this dissertation is to lay the groundwork for expanding single-cell tools in respiratory research, towards the objective of bridging knowledge gaps in human health and disease with novel technologies. Establishing robust protocols and reference datasets for clinical (sputum and endotracheal aspirate) sample profiling and model evaluation paves the way for advancements in respiratory biology. Technology development in genomic tools, like scRNA-seq, hold great promise to unveil new insights into human respiratory health and disease.