Inhibition of endotoxin-induced perinatal asthma protection by pollutants in an experimental mouse model.

BACKGROUND: One of the most promising strategies to face the increasing asthma prevalence and to prevent disease development might be an early contact with microbial compounds. However, little is known about an interaction between an early-life contact to microbial compounds leading to asthma protection in the offspring and a co-exposure to allergy-promoting pollutants. METHODS: Pregnant BALB/c mice were repeatedly exposed to aerosolized endotoxin (lipopolysaccharide, LPS). The offspring was further exposed to aerosolized LPS before allergen sensitization with ovalbumin (OVA). Some of the mice were co-exposed to mycotoxins or diesel exhaust particles (DEP) during pregnancy. The 6-week-old offspring was immunized with OVA and analyzed in a murine asthma model. RESULTS: While the offspring of naïve mothers developed an asthma-like phenotype, the offspring of mice perinatally exposed to LPS was significantly protected. Co-exposure of mice to mycotoxins or DEP during pregnancy inhibited the LPS-induced protection leading to the development of eosinophilic airway inflammation, airway hyperactivity, and increased antigen-specific IgE levels in the offspring. Furthermore, the asthma-preventive effect of perinatal LPS exposure was IFN-gamma dependent. Additionally, the IFN-gamma promoter of CD4+ T cells in the LPS-exposed offspring revealed a significant protection against loss of histone 4 acetylation, which was abolished after prenatal co-exposure to pollutants. Prenatal treatment of mice with the antioxidant N-acetylcysteine reversed the pollutant-induced increased asthma risk in the offspring. CONCLUSION: Our results show that exposure to pollutants during pregnancy may cause the development of allergic asthma in the offspring by inhibiting the endotoxin-induced perinatal asthma protection.

Measuring and modeling of binary mixture effects of pharmaceuticals and nickel on cell viability/cytotoxicity in the human hepatoma derived cell line HepG2.

The interaction of drugs and non-therapeutic xenobiotics constitutes a central role in human health risk assessment. Still, available data are rare. Two different models have been established to predict mixture toxicity from single dose data, namely, the concentration addition (CA) and independent action (IA) model. However, chemicals can also act synergistic or antagonistic or in dose level deviation, or in a dose ratio dependent deviation. In the present study we used the MIXTOX model (EU project ENV4-CT97-0507), which incorporates these algorithms, to assess effects of the binary mixtures in the human hepatoma cell line HepG2. These cells possess a liver-like enzyme pattern and a variety of xenobiotic-metabolizing enzymes (phases I and II). We tested binary mixtures of the metal nickel, the anti-inflammatory drug diclofenac, and the antibiotic agent irgasan and compared the experimental data to the mathematical models. Cell viability was determined by three different methods the MTT-, AlamarBlue(R) and NRU assay. The compounds were tested separately and in combinations. We could show that the metal nickel is the dominant component in the mixture, affecting an antagonism at low-dose levels and a synergism at high-dose levels in combination with diclofenac or irgasan, when using the NRU and the AlamarBlue assay. The dose-response surface of irgasan and diclofenac indicated a concentration addition. The experimental data could be described by the algorithms with a regression of up to 90%, revealing the HepG2 cell line and the MIXTOX model as valuable tool for risk assessment of binary mixtures for cytotoxic endpoints. However the model failed to predict a specific mode of action, the CYP1A1 enzyme activity.