Assessing the toxicity of traffic-derived air pollution using a primary human air-liquid interface airway in vitro model

Abstract

Traffic-derived air pollution (TDAP) frequently exceeds the 2021 World Health Organization air quality guideline levels and is linked to respiratory diseases through molecular mechanisms such as oxidative stress and inflammation. To determine these mechanisms without relying on animal models and inter-species extrapolation, physiologically relevant human in vitro models are promising tools. We sought to investigate the oxidative stress and inflammatory responses to TDAP in a co-culture model of the human lung. Additionally, we aimed to examine the variability arising from different exposure days and across primary human in vitro models from different donors. Therefore, primary human bronchial epithelial cultures from three donors, each combined with primary alveolar macrophages, were exposed to a continuous flow of ambient TDAP from a high-traffic street in Düsseldorf, Germany on three consecutive days. A versatile aerosol concentration enrichment system was used to increase the fine particulate matter levels from 8 to 42 μg/cm2 to 54–143 μg/cm2. Gene expression of four oxidative stress markers and four inflammatory cytokines was analyzed by quantitative reverse transcriptase PCR. Compared to incubator controls, even low airflow itself induced the expression of the oxidative stress marker heme oxygenase 1 and the cytokines interleukin 8 and tumor necrosis factor alpha. TDAP exposure, compared to clean air controls, upregulated interleukin 6 in one of the three co-cultures. Because TDAP exposure had minimal effects, exposure day-specific responses could not be discerned. In four of twelve genes, we observe exposure-independet donor differences. Transcriptomic analysis suggested TDAP-induced differential expression of four lung disease-related genes which, however, could not be confirmed by qRT-PCR. Higher TDAP concentrations or repeated exposures may be required to detect robust effects in this system. Our findings highlight inter-donor variability, underscoring the need for larger donor panels. Future studies should also minimize background effects from airflow to enhance model reliability for real-time TDAP exposure studies.