Organotypic sinonasal airway culture systems are predictive of the mucociliary phenotype produced by bronchial airway epithelial cells

Differentiated air–liquid interface models are the current standard to assess the mucociliary phenotype using clinically-derived samples in a controlled environment. However, obtaining basal progenitor airway epithelial cells (AEC) from the lungs is invasive and resource-intensive. Hence, we applied a tissue engineering approach to generate organotypic sinonasal AEC (nAEC) epithelia to determine whether they are predictive of bronchial AEC (bAEC) models. Basal progenitor AEC were isolated from healthy participants using a cytological brushing method and differentiated into epithelia on transwells until the mucociliary phenotype was observed. Tissue architecture was assessed using H&E and alcian blue/Verhoeff–Van Gieson staining, immunofluorescence (for cilia via acetylated α-tubulin labelling) and scanning electron microscopy. Differentiation and the formation of tight-junctions were monitored over the culture period (day 1–32) by quantifying trans-epithelial electrical resistance. End point (day 32) tight junction protein expression was assessed using Western blot analysis of ZO-1, Occludin-1 and Claudin-1. Reverse transcription qPCR-array was used to assess immunomodulatory and autophagy-specific transcript profiles. All outcome measures were assessed using R-statistical software. Mucociliary architecture was comparable for nAEC and bAEC-derived cultures, e.g. cell density P = 0.55, epithelial height P = 0.88 and cilia abundance P = 0.41. Trans-epithelial electrical resistance measures were distinct from day 1–14, converged over days 16–32, and were statistically similar over the entire culture period (global P < 0.001). This agreed with end-point (day 32) measures of tight junction protein abundance which were non-significant for each analyte (P > 0.05). Transcript analysis for inflammatory markers demonstrated significant variation between nAEC and bAEC epithelial cultures, and favoured increased abundance in the nAEC model (e.g. TGFβ and IL-1β; P < 0.05). Conversely, the abundance of autophagy-related transcripts were comparable and the range of outcome measures for either model exhibited a considerably more confined uncertainty distribution than those observed for the inflammatory markers. Organotypic air–liquid interface models of nAEC are predictive of outcomes related to barrier function, mucociliary architecture and autophagy gene activity in corresponding bAEC models. However, inflammatory markers exhibited wide variation which may be explained by the sentinel immunological surveillance role of the sinonasal epithelium.