The inner surface of our airways is lined by a mucous fluid film that is continuously propelled towards the throat. The propulsion of this airway surface liquid is generated by the collectively coordinated oscillatory motion of a myriad of subjacent motile cilia. Inhaled particles are entrapped by the mucus layer and transported towards the pharynx where they are swallowed. Therefore, mucociliary clearance contributes to our airway’s primary defense mechanism by protecting our airways from inhaled particles. We developed a computational high-speed video reflection microscopy (CVRM) system that enables imaging and quantitative characterization of the mucociliary activity – particularly in terms of the cilia-caused dynamic modulation of the mucus surface – in air-liquid interface cell cultures. Nasal epithelial cells from healthy volunteers and people with primary ciliary dyskinesia (PCD) were differentiated at the air-liquid interface, representing a sophisticated model widely used to study the mucociliary clearance mechanism. The cell cultures were imaged by reflection microscopy using a high-speed camera and the videos were quantitatively analyzed using a newly extended version of our Cilialyzer software. The primary aim of this study was to develop and validate CVRM as a quantitative method for characterizing collective mucociliary dynamics under physiological air–liquid interface conditions. We found that the dynamic modulations of the mucus surface closely correspond to the underlying ciliary motion. By using specifically developed video processing methods, we quantitatively characterized the collective mucociliary activity in terms of ten space-time features. This allowed us to distinguish cell cultures derived from people with PCD from those derived from healthy volunteers and demonstrates that CVRM has clear potential for future diagnostic applications in PCD and beyond.
