Effects of prochloraz on DNA damage, lipid peroxidation and antioxidant system in vitro

Prochloraz is a broad-spectrum contact imidazol fungicide used against several diseases in wheat, barley and oleaginous plants but also for treatment of flower production. Although prochloraz has endocrine disrupting and hepatocarcinogenic effects, there is lack of data on toxic effects of prochloraz. Therefore, we aimed to investigate the DNA damage effects of prochloraz in NRK-52E cells by using Ames and Comet assay. By using a standard alkaline Comet assay procedure, there was no DNA damage observed after 24 h prochloraz exposure. It also showed that prochloraz caused neither base-pair substitution nor frame shift mutations by using TA98, TA100 strains, respectively, with/without metabolic activation in Ames assay. Both Comet and Ames assays, the exposure concentrations were 12.5, 25, 50 and 100 mu M. IC50 value of prochloraz was determined as 110.76 mu M in NRK-52E cells by MTT cytotoxicity test. Also, we evaluated possible effects of prochloraz on lipid peroxidation, reduced glutathione (GSH), oxidized glutathione (GSSG) and antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px) and glutathione reductase (GSH-Rd) in NRK-52E cells at 1-50 mu M concentrations. Prochloraz induced lipid peroxidation and altered glutathione contents and antioxidant enzyme activities in NRK-52E cells. Our results indicated that prochloraz showed no evidence of mutagenicity and DNA damage; however, some alterations were observed on lipid peroxidation and antioxidant systems in prochloraz treatment

Transcriptional signatures of regulatory and toxic responses to benzo-[a]-pyrene exposure

BACKGROUND: Small molecule ligands often have multiple effects on the transcriptional program of a cell: they trigger a receptor specific response and additional, indirect responses ("side effects"). Distinguishing those responses is important for understanding side effects of drugs and for elucidating molecular mechanisms of toxic chemicals. RESULTS: We explored this problem by exposing cells to the environmental contaminant benzo-[a]-pyrene (B[a]P). B[a]P exposure activates the aryl hydrocarbon receptor (Ahr) and causes toxic stress resulting in transcriptional changes that are not regulated through Ahr. We sought to distinguish these two types of responses based on a time course of expression changes measured after B[a]P exposure. Using Random Forest machine learning we classified 81 primary Ahr responders and 1,308 genes regulated as side effects. Subsequent weighted clustering gave further insight into the connection between expression pattern, mode of regulation, and biological function. Finally, the accuracy of the predictions was supported through extensive experimental validation. CONCLUSION: Using a combination of machine learning followed by extensive experimental validation, we have further expanded the known catalog of genes regulated by the environmentally sensitive transcription factor Ahr. More broadly, this study presents a strategy for distinguishing receptor-dependent responses and side effects based on expression time courses