A systematic analysis of Nrf2 pathway activation dynamics during repeated xenobiotic exposure.

Oxidative stress leads to the activation of the Nuclear factor-erythroid-2-related factor 2 (Nrf2) pathway. While most studies have focused on the activation of the Nrf2 pathway after single chemical treatment, little is known about the dynamic regulation of the Nrf2 pathway in the context of repeated exposure scenarios. Here we employed single cell live imaging to quantitatively monitor the dynamics of the Nrf2 pathway during repeated exposure, making advantage of two HepG2 fluorescent protein reporter cell lines, expressing GFP tagged Nrf2 or sulfiredoxin 1 (Srxn1), a direct downstream target of Nrf2. High throughput live confocal imaging was used to measure the temporal dynamics of these two components of the Nrf2 pathway after repeated exposure to an extensive concentration range of diethyl maleate (DEM) and tert-butylhydroquinone (tBHQ). Single treatment with DEM or tBHQ induced Nrf2 and Srxn1 over time in a concentration-dependent manner. The Nrf2 response to a second treatment was lower than the response to the first exposure with the same concentration, indicating that the response is adaptive. Moreover, a limited fraction of individual cells committed themselves into the Nrf2 response during the second treatment. Despite the suppression of the Nrf2 pathway, the second treatment resulted in a three-fold higher Srxn1-GFP response compared to the first treatment, with all cells participating in the response. While after the first treatment Srxn1-GFP response was linearly related to Nrf2-GFP nuclear translocation, such a linear relationship was less clear for the second exposure. siRNA-mediated knockdown demonstrated that the second response is dependent on the activity of Nrf2. Several other, clinically relevant, compounds (i.e., sulphorophane, nitrofurantoin and CDDO-Me) also enhanced the induction of Srxn1-GFP upon two consecutive repeated exposure. Together the data indicate that adaptation towards pro-oxidants lowers the Nrf2 activation capacity, but simultaneously primes cells for the enhancement of an antioxidant response which depends on factors other than just Nrf2. These data provide further insight in the overall dynamics of stress pathway activation after repeated exposure and underscore the complexity of responses that may govern repeated dose toxicity.

Dynamic modeling of Nrf2 pathway activation in liver cells after toxicant exposure.

Cells are exposed to oxidative stress and reactive metabolites every day. The Nrf2 signaling pathway responds to oxidative stress by upregulation of antioxidants like glutathione (GSH) to compensate the stress insult and re-establish homeostasis. Although mechanisms describing the interaction between the key pathway constituents Nrf2, Keap1 and p62 are widely reviewed and discussed in literature, quantitative dynamic models bringing together these mechanisms with time-resolved data are limited. Here, we present an ordinary differential equation (ODE) based dynamic model to describe the dynamic response of Nrf2, Keap1, Srxn1 and GSH to oxidative stress caused by the soft-electrophile diethyl maleate (DEM). The time-resolved data obtained by single-cell confocal microscopy of green fluorescent protein (GFP) reporters and qPCR of the Nrf2 pathway components complemented with siRNA knock down experiments, is accurately described by the calibrated mathematical model. We show that the quantitative model can describe the activation of the Nrf2 pathway by compounds with a different mechanism of activation, including drugs which are known for their ability to cause drug induced liver-injury (DILI) i.e., diclofenac (DCF) and omeprazole (OMZ). Finally, we show that our model can reveal differences in the processes leading to altered activation dynamics amongst DILI inducing drugs.

Unraveling cellular pathways contributing to drug-induced liver injury by dynamical modeling.

INTRODUCTION: Drug-induced liver injury (DILI) is a significant threat to human health and a major problem in drug development. It is hard to predict due to its idiosyncratic nature and which does not show up in animal trials. Hepatic adaptive stress response pathway activation is generally observed in drug-induced liver injury. Dynamical pathway modeling has the potential to foresee adverse effects of drugs before they go in trial. Ordinary differential equation modeling can offer mechanistic insight, and allows us to study the dynamical behavior of stress pathways involved in DILI. Areas covered: This review provides an overview on the progress of the dynamical modeling of stress and death pathways pertinent to DILI, i.e. pathways relevant for oxidative stress, inflammatory stress, DNA damage, unfolded proteins, heat shock and apoptosis. We also discuss the required steps for applying such modeling to the liver. Expert opinion: Despite the strong progress made since the turn of the century, models of stress pathways have only rarely been specifically applied to describe pathway dynamics for DILI. We argue that with minor changes, in some cases only to parameter values, many of these models can be repurposed for application in DILI research. Combining both dynamical models with in vitro testing might offer novel screening methods for the harmful side-effects of drugs.

Modelling carbon and water exchange of a grazed pasture in New Zealand constrained by eddy covariance measurements.

We used two years of eddy covariance (EC) measurements collected over an intensively grazed dairy pasture to better understand the key drivers of changes in soil organic carbon stocks. Analysing grazing systems with EC measurements poses significant challenges as the respiration from grazing animals can result in large short-term CO2 fluxes. As paddocks are grazed only periodically, EC observations derive from a mosaic of paddocks with very different exchange rates. This violates the assumptions implicit in the use of EC methodology. To test whether these challenges could be overcome, and to develop a tool for wider scenario testing, we compared EC measurements with simulation runs with the detailed ecosystem model CenW 4.1. Simulations were run separately for 26 paddocks around the EC tower and coupled to a footprint analysis to estimate net fluxes at the EC tower. Overall, we obtained good agreement between modelled and measured fluxes, especially for the comparison of evapotranspiration rates, with model efficiency of 0.96 for weekly averaged values of the validation data. For net ecosystem productivity (NEP) comparisons, observations were omitted when cattle grazed the paddocks immediately around the tower. With those points omitted, model efficiencies for weekly averaged values of the validation data were 0.78, 0.67 and 0.54 for daytime, night-time and 24-hour NEP, respectively. While not included for model parameterisation, simulated gross primary production also agreed closely with values inferred from eddy covariance measurements (model efficiency of 0.84 for weekly averages). The study confirmed that CenW simulations could adequately model carbon and water exchange in grazed pastures. It highlighted the critical role of animal respiration for net CO2 fluxes, and showed that EC studies of grazed pastures need to consider the best approach of accounting for this important flux to avoid unbalanced accounting.