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An Air-liquid Interface Bronchial Epithelial Model for Realistic, Repeated Inhalation Exposure to Airborne Particles for Toxicity Testing
Published on: May 13, 2020
Human bronchial air-liquid interface responses to nebulised protease exposure
Georgina Hopkins1,2, David Sheffield3, Hugh Barlow3
1School of Life Sciences, The University of Nottingham, Nottingham, United Kingdom.
Background:
As part of a programme developing human-relevant new approach methodologies (NAMs) for next-generation risk assessment (NGRA), we utilised a human air-liquid interface (ALI) bronchial epithelial model (MucilAir™) to assess epithelial responses to nebulised protease exposure.
Methods:
Protease doses of 0.005, 0.08, 2, and 24 µg/cm2 were applied to MucilAir™ inserts via nebulisation using a Vitrocell® Cloud Alpha. Effects on epithelial barrier integrity, cytokine release, extracellular vesicle (EV) profiles, and EV transcriptomic cargo were evaluated.
Results:
Phosphate-buffered saline (PBS) nebulisation produced no detectable barrier effects using the methods described. Protease doses of 2 µg/cm2 or lower caused no significant responses compared with PBS controls. Protease doses of 24 µg/cm2 induced reductions in TEER, GRO-α, IL-8/CXCL8, IL-9, and VEGF production, but increased MIF production, and EV alterations, indicating barrier disruption. Transcriptomic analysis of MucilAir™-derived EVs indicates a protease dose-dependent increase in differentially expressed microRNAs (miRNAs) that were enriched for pathways involved in epithelial signalling, immune and inflammatory regulation, cytoskeletal organisation, and cell survival and repair.
Discussion:
These findings demonstrate the suitability of nebulised dosing for assessing airborne protease effects in bronchial ALI cultures. These data also highlight EV-miRNA profiling as a powerful, non-invasive readout that captures early molecular perturbations not detectable by conventional functional assays alone. Through identification of TEER, EV, and cytokine disruption thresholds to protease through statistical modelling, this work strengthens the methodological basis for generating NAM-aligned in vitro data to support risk assessment of inhaled enzymes and other airborne materials.
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