Mechanistic Similarities between 3D Human Bronchial Epithelium and Mice Lung, Exposed to Copper Oxide Nanoparticles, Support Non‐Animal Methods for Hazard Assessment. Issue 36 (30th April 2020) - Ndika, Joseph; Ilves, Marit; Kooter, Ingeborg M.; Gröllers‐Mulderij, Mariska; Duistermaat, Evert; Tromp, Peter C.; Kuper, Frieke; Kinaret, Pia; Greco, Dario; Karisola, Piia; Alenius, Harri
Abstract: The diversity and increasing prevalence of products derived from engineered nanomaterials (ENM), warrants implementation of non‐animal approaches to health hazard assessment for ethical and practical reasons. Although non‐animal approaches are becoming increasingly popular, there are almost no studies of side‐by‐side comparisons with traditional in vivo assays. Here, transcriptomics is used to investigate mechanistic similarities between healthy/asthmatic models of 3D air–liquid interface (ALI) cultures of donor‐derived human bronchial epithelia cells, and mouse lung tissue, following exposure to copper oxide ENM. Only 19% of mouse lung genes with human orthologues are not expressed in the human 3D ALI model. Despite differences in taxonomy and cellular complexity between the systems, a core subset of matching genes cluster mouse and human samples strictly based on ENM dose (exposure severity). Overlapping gene orthologue pairs are highly enriched for innate immune functions, suggesting an important and maybe underestimated role of epithelial cells. In conclusion, 3D ALI models based on epithelial cells, are primed to bridge the gap between traditional 2D in vitro assays and animal models of airway exposure, and transcriptomics appears to be a unifying dose metric that links in vivo and in vitro test systems. Abstract : After exposure to copper oxide nanoparticles, the transcriptomes of 3D air–liquid interface cultures of human bronchial epithelial cells are compared to mouse lung tissues. Both models share an unprecedented functional core of 1936 differentially expressed gene orthologues, corresponding to 266 highly enriched pathways. The data increases knowledge that is relevant for regulatory validation of non‐animal alternative testing systems.