Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia.
Respiratory and Sleep Medicine, Women's and Children's Hospital, Adelaide, SA, Australia.
Sci Rep. 2022 Nov 10;12(1):19225. doi: 10.1038/s41598-022-23667-y.
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.
分化的气液界面模型是目前在受控环境中使用临床来源的样本评估纤毛表型的标准方法。然而,从肺部获得基底祖细胞气道上皮细胞(AEC)是具有侵入性的,且资源密集。因此,我们应用组织工程方法生成器官型鼻内 AEC(nAEC)上皮,以确定它们是否可预测支气管 AEC(bAEC)模型。使用细胞学刷法从健康参与者中分离出基底祖细胞 AEC,并在 Transwell 上分化为上皮细胞,直到观察到纤毛表型。使用 H&E 和阿尔辛蓝/矾酸-凡戈尔森染色、免疫荧光(通过乙酰化α-微管蛋白标记检测纤毛)和扫描电子显微镜评估组织结构。通过量化跨上皮电阻来监测培养期间(第 1-32 天)的分化和紧密连接的形成。使用 Western blot 分析 ZO-1、Occludin-1 和 Claudin-1 评估终点(第 32 天)紧密连接蛋白表达。使用逆转录 qPCR 阵列评估免疫调节和自噬特异性转录谱。所有结果测量均使用 R 统计软件进行评估。nAEC 和 bAEC 衍生培养物的纤毛结构相似,例如细胞密度 P=0.55、上皮高度 P=0.88 和纤毛丰度 P=0.41。跨上皮电阻测量值在第 1-14 天之间存在差异,在第 16-32 天之间收敛,在整个培养期间具有统计学相似性(总体 P<0.001)。这与终点(第 32 天)紧密连接蛋白丰度的测量结果一致,每个分析物均无显著性差异(P>0.05)。炎症标志物的转录分析表明,nAEC 和 bAEC 上皮培养物之间存在显著差异,并且 nAEC 模型中丰度增加(例如 TGFβ 和 IL-1β;P<0.05)。相反,自噬相关转录物的丰度相似,并且两种模型的结果测量范围的不确定性分布比观察到的炎症标志物的不确定性分布更为狭窄。nAEC 的器官型气液界面模型可预测相应 bAEC 模型中与屏障功能、纤毛结构和自噬基因活性相关的结果。然而,炎症标志物表现出广泛的变化,这可能是由于鼻内上皮的哨兵免疫监视作用。