Direct transcriptomic comparison of xenobiotic metabolism and toxicity pathway induction of airway epithelium models at an air–liquid interface generated from induced pluripotent stem cells and primary bronchial epithelial cells

Abstract The airway epithelium represents the main barrier between inhaled air and the tissues of the respiratory tract and is therefore an important point of contact with xenobiotic substances into the human body. Several studies have recently shown that in vitro models of the airway grown at an ai...
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Abstract The airway epithelium represents the main barrier between inhaled air and the tissues of the respiratory tract and is therefore an important point of contact with xenobiotic substances into the human body. Several studies have recently shown that in vitro models of the airway grown at an air–liquid interface (ALI) can be particularly useful to obtain mechanistic information about the toxicity of chemical compounds. However, such methods are not very amenable to high throughput since the primary cells cannot be expanded indefinitely in culture to obtain a sustainable number of cells. Induced pluripotent stem cells (iPSCs) have become a popular option in the recent years for modelling the airways of the lung, but despite progress in the field, such models have so far not been assessed for their ability to metabolise xenobiotic compounds and how they compare to the primary bronchial airway model (pBAE). Here, we report a comparative analysis by TempoSeq (oligo-directed sequencing) of an iPSC-derived airway model (iBAE) with a primary bronchial airway model (pBAE). The iBAE and pBAE were differentiated at an ALI and then evaluated in a 5-compound screen with exposure to a sub-lethal concentration of each compound for 24 h. We found that despite lower expression of xenobiotic metabolism genes, the iBAE similarly predicted the toxic pathways when compared to the pBAE model. Our results show that iPSC airway models at ALI show promise for inhalation toxicity assessments with further development. Graphical abstract Ausführliche Beschreibung