Abstract
The exposure of human lung and skin to carbon black (CB) is continuous due to its widespread applications. Current toxicological testing uses 'healthy' cellular systems; however, questions remain whether this mimics the everyday stresses that human cells are exposed to, including infection. Staphylococcus aureus lung and skin infections remain prevalent in society, and include pneumonia and atopic dermatitis, respectively, but current in vitro toxicological testing does not consider infection stress. Therefore, investigating the effects of CB co-exposure in 'stressed' infected epithelial cells in vitro may better approximate true toxicity. This work aims to study the impact of CB exposure during Staphylococcus aureus infection stress in A549 (lung) and HaCaT (skin) epithelial cells. Physicochemical characterisation of CB confirmed its dramatic polydispersity and potential to aggregate. CB significantly inhibited S. aureus growth in cell culture media. CB did not induce cytokines or antimicrobial peptides from lung and skin epithelial cells, when given alone, but did reduce HaCaT and A549 cell viability to 55% and 77%, respectively. In contrast, S. aureus induced a robust interleukin (IL)-8 response in both lung and skin epithelial cells. IL-6 and human beta defensin (hβD)-2 could only be detected when cells were stimulated with S. aureus with no decreases in cell viability. However, co-exposure to CB (100 µg/mL) and S. aureus resulted in significant inhibition of IL-8 (compared to S. aureus alone) without further reduction in cell viability. Furthermore, the same co-exposure induced significantly more hβD-2 (compared to S. aureus alone). This work confirms that toxicological testing in healthy versus stressed cells gives significantly different responses. This has significant implications for toxicological testing and suggests that cell stresses (including infection) should be included in current models to better represent the diversity of cell viabilities found in lung and skin within a general population. This model will have significant application when estimating CB exposure in at-risk groups, such as factory workers, the elderly, and the immunocompromised.