Ames mutagenicity tests on purified 3-nitropropionic acid

Sulforaphane alleviates the meiosis defects induced by 3-nitropropionic acid in mouse oocytes

3-Nitropropionic acid (3-NP) is a mycotoxin commonly found in plants and fungi that has been linked to mammalian intoxication. Previously, we found 3-NP treatment exhibited reproductive toxicity by inducing oxidative stress in mouse ovary; however, the toxic effects of 3-NP on mouse oocyte maturation have not been investigated. Sulforaphane (SFN) is a naturally bioactive phytocompound derived from cruciferous vegetables that has been shown to possess cytoprotective properties. The present study was designed to investigate the cytotoxicity of 3-NP during mouse oocyte maturation and the protective effects of SFN on oocytes challenged with 3-NP. The results showed 3-NP had a dose-dependent inhibitory effect on oocyte maturation, and SFN significantly alleviated the defects caused by 3-NP, including failed first polar body extrusion and abnormal spindle assembly. Furthermore, 3-NP caused abnormal mitochondrial distribution in oocytes and disrupted mitochondrial functions, including mitochondrial depolarization, decreased ATP levels, and increased mitochondrial-derived ROS. Finally, 3-NP induced oxidative stress in oocytes, leading to increased apoptosis and autophagy, while SFN supplementation had significant cytoprotective effects on these damages. Collectively, our results provide insight on the mechanism of 3-NP toxicity in mouse oocytes and suggest the application of SFN may be a viable intervention strategy to mitigate 3-NP-induced reproductive toxicity.

MicotoXilico: An Interactive Database to Predict Mutagenicity, Genotoxicity, and Carcinogenicity of Mycotoxins

Mycotoxins are secondary metabolites produced by certain filamentous fungi. They are common contaminants found in a wide variety of food matrices, thus representing a threat to public health, as they can be carcinogenic, mutagenic, or teratogenic, among other toxic effects. Several hundreds of mycotoxins have been reported, but only a few of them are regulated, due to the lack of data regarding their toxicity and mechanisms of action. Thus, a more comprehensive evaluation of the toxicity of mycotoxins found in foodstuffs is required. In silico toxicology approaches, such as Quantitative Structure-Activity Relationship (QSAR) models, can be used to rapidly assess chemical hazards by predicting different toxicological endpoints. In this work, for the first time, a comprehensive database containing 4360 mycotoxins classified in 170 categories was constructed. Then, specific robust QSAR models for the prediction of mutagenicity, genotoxicity, and carcinogenicity were generated, showing good accuracy, precision, sensitivity, and specificity. It must be highlighted that the developed QSAR models are compliant with the OECD regulatory criteria, and they can be used for regulatory purposes. Finally, all data were integrated into a web server that allows the exploration of the mycotoxin database and toxicity prediction. In conclusion, the developed tool is a valuable resource for scientists, industry, and regulatory agencies to screen the mutagenicity, genotoxicity, and carcinogenicity of non-regulated mycotoxins.

In vivo treatment with a subacute low dose of 3-nitropropionic acid does not induce genotoxicity or mutagenicity in rats

3-nitropropionic acid (3-NP) is a toxin that causes neural damage in the striatum and can lead to the development of Huntington's disease manifestations in animal models. Several studies have shown genotoxicity related to the 3-NP treatment. This study investigated potential genotoxicity and mutagenicity that was induced by a low dose (6.25 mg/kg i. p.) 3-NP subacute treatment (daily, over 6 days) in a rat model. The arterial blood and the frontal cortex were analyzed by the comet assay and the bone marrow by micronucleus. Surprisingly, the 3-NP subacute treatment with the low dose did not show genotoxic or mutagenic effects.

Development of a toxicogenomics signature for genotoxicity using a dose-optimization and informatics strategy in human cells

The development of in vitro molecular biomarkers to accurately predict toxicological effects has become a priority to advance testing strategies for human health risk assessment. The application of in vitro transcriptomic biomarkers promises increased throughput as well as a reduction in animal use. However, the existing protocols for predictive transcriptional signatures do not establish appropriate guidelines for dose selection or account for the fact that toxic agents may have pleiotropic effects. Therefore, comparison of transcriptome profiles across agents and studies has been difficult. Here we present a dataset of transcriptional profiles for TK6 cells exposed to a battery of well-characterized genotoxic and nongenotoxic chemicals. The experimental conditions applied a new dose optimization protocol that was based on evaluating expression changes in several well-characterized stress-response genes using quantitative real-time PCR in preliminary dose-finding studies. The subsequent microarray-based transcriptomic analyses at the optimized dose revealed responses to the test chemicals that were typically complex, often exhibiting substantial overlap in the transcriptional responses between a variety of the agents making analysis challenging. Using the nearest shrunken centroids method we identified a panel of 65 genes that could accurately classify toxicants as genotoxic or nongenotoxic. To validate the 65-gene panel as a genomic biomarker of genotoxicity, the gene expression profiles of an additional three well-characterized model agents were analyzed and a case study demonstrating the practical application of this genomic biomarker-based approach in risk assessment was performed to demonstrate its utility in genotoxicity risk assessment.