Collection, Expansion, and Differentiation of Primary Human Nasal Epithelial Cell Models for Quantification of Cilia Beat Frequency.

Abstract

Measurements of cilia function (beat frequency, pattern) have been established as diagnostic tools for respiratory diseases such as primary ciliary dyskinesia. However, the wider application of these techniques is limited by the extreme susceptibility of ciliary function to changes in environmental factors e.g., temperature, humidity, and pH. In the airway of patients with Cystic Fibrosis (CF), mucus accumulation impedes cilia beating. Cilia function has been investigated in primary airway cell models as an indicator of CF Transmembrane conductance Regulator (CFTR) channel activity. However, considerable patient-to-patient variability in cilia beating frequency has been found in response to CFTR-modulating drugs, even for patients with the same CFTR mutations. Furthermore, the impact of dysfunctional CFTR-regulated chloride secretion on ciliary function is poorly understood. There is currently no comprehensive protocol demonstrating sample preparation of in vitro airway models, image acquisition, and analysis of Cilia Beat Frequency (CBF). Standardized culture conditions and image acquisition performed in an environmentally controlled condition would enable consistent, reproducible quantification of CBF between individuals and in response to CFTR-modulating drugs. This protocol describes the quantification of CBF in three different airway epithelial cell model systems: 1) native epithelial sheets, 2) air-liquid interface models imaged on permeable support inserts, and 3) extracellular matrix-embedded three-dimensional organoids. The latter two replicate in vivo lung physiology, with beating cilia and production of mucus. The ciliary function is captured using a high-speed video camera in an environment-controlled chamber. Custom-built scripts are used for the analysis of CBF. Translation of CBF measurements to the clinic is envisioned to be an important clinical tool for predicting response to CFTR-modulating drugs on a per-patient basis.