Fabrication of All-Inkjet-Printed 3D Alveolar Barrier Model and Application of Fine Dust Hazard Assessment

Fine dust particles in the air travel into our body via the airway tract and cause damages to our respiratory system. Since this damage causes severe respiratory diseases, the need for studies to analyze the effects of dust particles on the respiratory system has been emphasized. However, most studies about the toxicity of dust have been carried out in two-dimensional cell culture, animal models, and epidemiological investigations. To figure out how dust can cause respiratory disease, it is necessary to examine using a reliable three-dimensional structured model, which mimics human nature alveoli. In this study, we applied atmospheric dust particles in a dose- and time-dependent manner on our previously developed three-dimensional alveolar barrier, which is generated by the inkjet bioprinting process. As result, we observed the destruction of tissue architecture along with cell death in our bioprinted alveolar barrier. Based on the damages in cellular levels, we observed increased pro-inflammatory cytokines, which trigger the signal transduction pathway leading to the activation of transcription factors. As cascades of the release of cytokines, we confirmed degradation of extracellular matrix, which might induce a collapse of the structure, loss of cell polarity, and a decreased barrier tightness. We further investigated pulmonary surfactant protein-related genes in dust-treated alveolar tissue then we could estimate the possible harmful effect of dust on pulmonary surfactant dysfunction. This study demonstrated the physiological impact of dust on cytotoxicity effects, alveolar barrier rigidity, and surfactant secretion using inkjet bioprinted alveolar barrier in gene expression level. It has also been demonstrated that dust can have serious consequences that can lead to the collapse of the tissue architecture. We expect that this strategy using in vitro inkjet bioprinted three-dimensional alveolar barrier can be a valuable tool for identifying air pollutant exposure-related diseases.2