Real-Time, Semi-Automated Fluorescent Measurement of the Airway Surface Liquid pH of Primary Human Airway Epithelial Cells

In recent years, the importance of mucosal surface pH in the airways has been highlighted by its ability to regulate airway surface liquid (ASL) hydration, mucus viscosity and activity of antimicrobial peptides, key parameters involved in innate defense of the lungs. This is of primary relevance in the field of chronic respiratory diseases such as cystic fibrosis (CF) where these parameters are dysregulated. While different groups have studied ASL pH both in vivo and in vitro, their methods report a relatively wide range of ASL pH values and even contradictory findings regarding any pH differences between non-CF and CF cells. Furthermore, their protocols do not always provide enough details in order to ensure reproducibility, most are low throughput and require expensive equipment or specialized knowledge to implement, making them difficult to establish in most labs. Here we describe a semi-automated fluorescent plate reader assay that enables the real-time measurement of ASL pH under thin film conditions that more closely resemble the in vivo situation. This technique allows for stable measurements for many hours from multiple airway cultures simultaneously and, importantly, dynamic changes in ASL pH in response to agonists and inhibitors can be monitored. To achieve this, the ASL of fully differentiated primary human airway epithelial cells (hAECs) are stained overnight with a pH-sensitive dye in order to allow for the reabsorption of the excess fluid to ensure thin film conditions. After fluorescence is monitored in the presence or absence of agonists, pH calibration is performed in situ to correct for volume and dye concentration. The method described provides the required controls to make stable and reproducible ASL pH measurements, which ultimately could be used as a drug discovery platform for personalized medicine, as well as adapted to other epithelial tissues and experimental conditions, such as inflammatory and/or host-pathogen models.