Generation of Airway Epithelial Cell Air-Liquid Interface Cultures from Human Pluripotent Stem Cells

Diseases of the conducting airway such as asthma, cystic fibrosis (CF), primary ciliary dyskinesia (PCD), and viral respiratory infections are major causes of morbidity and mortality worldwide. In vitro platforms using human bronchial epithelial cells (HBECs) have been instrumental to our understanding of the airway epithelium in health and disease. Access to HBECs from individuals with rare genetic diseases or rare mutations is a bottleneck in lung research. Induced pluripotent stem cells (iPSCs) are readily generated by "reprogramming" somatic cells and retain the unique genetic background of the individual donor. Recent advances allow for the directed differentiation of iPSCs to lung epithelial progenitor cells, alveolar type 2 cells, as well as the cells of the conducting airway epithelium via basal cells, the major airway stem cells. Here we outline a protocol for the maintenance and expansion of iPSC-derived airway basal cells (hereafter iBCs) as well as their trilineage differentiation in air-liquid interface (ALI) cultures. iBCs are maintained and expanded as epithelial spheres suspended in droplets of extracellular matrix cultured in a primary basal cell medium supplemented with inhibitors of TGF-R and BMP signaling pathways. iBCs within these epithelial spheres express key basal markers TP63 and NGFR, can be purified by fluorescence activated cell sorting (FACS), and when plated on porous membranes in standard ALI culture conditions, differentiate into a functional airway epithelium. ALI cultures derived from healthy donors are composed of basal, secretory and multiciliated cells and demonstrate epithelial barrier integrity, motile cilia, and mucus secretion. Cultures derived from individuals with CF or PCD recapitulate the dysfunctional CFTR-mediated chloride transport or immotile cilia, the respective disease-causing epithelial defects. Here, we present a protocol for the generation of human cells that can be applied for modeling and understanding airway diseases.