Kinetics of Glutathione Depletion and Antioxidant Gene Expression as Indicators of Chemical Modes of Action Assessed in Vitro in Mouse Hepatocytes with Enhanced Glutathione Synthesis

Abstract

Here we report a vertically integrated in vitroin silico study that aims to elucidate the molecular initiating events involved in the induction of oxidative stress (OS) by seven diverse chemicals (cumene hydroperoxide, t-butyl hydroperoxide, hydroquinone, t-butyl hydroquinone, bisphenol A, Dinoseb, and perfluorooctanoic acid). To that end, we probe the relationship between chemical properties, cell viability, glutathione (GSH) depletion, and antioxidant gene expression. Concentration-dependent effects on cell viability were assessed by MTT assay in two Hepa-1 derived mouse liver cell lines: a control plasmid vector transfected cell line (Hepa-V), and a cell line with increased glutamate-cysteine ligase (GCL) activity and GSH content (CR17). Changes to intracellular GSH content and mRNA expression levels for the Nrf2-driven antioxidant genes Gclc, Gclm, heme oxygenase-1 (Hmox1), and NADPH quinone oxidoreductase-1 (Nqo1) were monitored after sublethal exposure to the chemicals. In silico models of covalent and redox reactivity were used to rationalize differences in activity of quinones and peroxides. Our findings show CR17 cells were generally more resistant to chemical toxicity and showed markedly *

Toward Less Hazardous Industrial Compounds: Coupling Quantum Mechanical Computations, Biomarker Responses, and Behavioral Profiles To Identify Bioactivity of SN2 Electrophiles in Alternative Vertebrate Models

“…Electrophilicity index (ω) was the chemical descriptor that emerged to have the highest correlation with experimental metrics examined in this study and was significantly ( p < 0.05) related to S N 2 electrophile influences on antioxidant (GSH) levels in both larval fish models. The relevance and predictive power of FMO-derived reactivity indices demonstrated herein is a natural extension of our previous efforts in the context of acute and chronic aquatic toxicity, ,,, skin sensitization, and oxidative stress . While often overlooked for more sophisticated computational and statistical modeling approaches, calculations of global and local reactivity indices are not only invaluable in rapid screening of large data sets of chemicals or in assessing general reactivity across multiple MOAs but, due to significant advancements in hybrid density functional methods, can also provide highly accurate and reliable, endpoint-specific models (CADRE-SS, CADRE-AT , ).…”

“…Predicting attributes, such as desired functions and limited hazards, of commercial chemicals has recently been identified through the Global Horizon Scanning Project as important priority research questions to protect public health and the environment. − Previous research by our team reported several computational parameters that appear useful to identify attributes of contaminants that trend with acute and chronic toxicity from standardized experimental designs. ,− In fact, Connors et al observed that if two chemical design guidelines (log K o/w and Δ E ) were followed, then the proportion of chemicals eliciting high toxicity to these standardized acute and chronic toxicity responses would be markedly diminished. Though we recently observed relationships between computational predictions for oxidative stress and GSH in vitro, similar efforts coupling computational, biochemical, and behavioral activity patterns in vivo have not been engaged. In the present study, we advanced our earlier work to examine a specific chemical domain (S N 2) for compounds with electrophilic reactivity using computational modeling of an electrophilic index (ω) and identified significant relationships among ω, GSH, and also subtle sublethal behavioral PMR and refractory responses in two common alternative vertebrate models.…”

Going All In: A Strategic Investment in In Silico Toxicology

“…It could also be argued that mechanistic insights provided by in vitro and in chemico methods better align with the needs of explicit mechanistic models than highly sophisticated statistical approaches, by providing vital clues for the key toxicokinetic and toxicodynamic events implicated in the toxic response (Figure 2b). 6,51 Lastly, a strong case can be made that such highly mechanistic models do not require extensive training sets, alleviating issues associated with data quality and time-consuming curation efforts. Since one of the key attributes of any model's predictive power is its applicability domain, which sets the boundaries of predictivity based on training-set data, one might argue that relying on smaller training sets will lead to narrow applicability domains.…”

“…Crucially, this direction of explicit description of molecular initiating and other key events in toxicity pathways is in line with our strive for fundamental understanding of natural phenomena. It could also be argued that mechanistic insights provided by in vitro and in chemico methods better align with the needs of explicit mechanistic models than highly sophisticated statistical approaches, by providing vital clues for the key toxicokinetic and toxicodynamic events implicated in the toxic response (Figure b). , …”

Cold atmospheric plasma treatment enhances recombinant model protein production in yeast Pichia pastoris

“…To counter the oxidant stress after exposure to tolerated doses, the antioxidant defense system, which includes various cellular tools such as small antioxidant molecules, inducible antioxidant proteins, as well as UPR is activated 38 . Interestingly, different studies showed that inducing low doses of oxidative stress responses (in the range of oxidative eustress) positively affects recombinant protein production.…”