Investigation of acetaminophen toxicity in HepG2/C3a microscale cultures using a system biology model of glutathione depletion

Abstract

We have integrated in vitro and in silico information to investigate acetaminophen (APAP) and its metabolite N-acetyl-p-benzoquinone imine (NAPQI) toxicity in liver biochip. In previous works, we observed higher cytotoxicity of HepG2/C3a cultivated in biochips when exposed to 1 mM of APAP for 72 h as compared to Petri cultures. We complete our investigation with the present in silico approach to extend the mechanistic interpretation of the intracellular kinetics of the toxicity process. For that purpose, we propose a mathematical model based on the coupling of a drug pharmacokinetic model (PK) with a systemic biology model (SB) describing the reactive oxygen species (ROS) production by NAPQI and the subsequent glutathione (GSH) depletion. The SB model was parameterized using (i) transcriptomic data, (ii) qualitative results of time lapses ROS fluorescent curves for both control and 1-mM APAP-treated experiments, and (iii) additional GSH literature data. The PK model was parameterized (i) using the in vitro kinetic data (at 160 μM, 1 mM, 10 mM), (ii) using the parameters resulting from a physiologically based pharmacokinetic (PBPK) literature model for APAP, and (iii) by literature data describing NAPQI formation. The PK-SB model predicted a ROS increase and GSH depletion due to the NAPQI formation. The transition from a detoxification phase and NAPQI and ROS accumulation was predicted for a NAPQI concentration ranging between 0.025 and 0.25 μM in the cytosol. In parallel, we performed a dose response analysis in biochips that shows a reduction of the final hepatic cell number appeared in agreement with the time and doses associated with the switch of the NAPQI detoxification/accumulation. As a result, we were able to correlate in vitro extracellular APAP exposures with an intracellular in silico ROS accumulation using an integration of a coupled mathematical and experimental liver on chip approach.

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

“…Although many models have been developed for toxicity pathways, currently there are only a few models specifically designed for liver cells. As discussed, Leclerc et al adapted a general oxidative stress model to describe liver cell dynamics [22]. The question arises whether all dynamical models designed for a particular organ or cell line can be applied to a different organ, in our case the liver.…”

“…This indeed is consistent with the hypothesis that adjusting the parameter values is often sufficient to reuse a model for a different tissue or cell line. The oxidative stress model by Leclerc et al [22] focuses on the effect of a single drug and its mechanism of action. To be able to evaluate if drugs are potentially harmful to the liver, we need a model that is sufficiently general to be employed for many different drugs.…”

“…The oxidative stress and the heat-shock response (HSR) pathways have already been applied to the liver [22,23], but to our knowledge, this is not yet the case for other stress pathways. As we will discuss below in more detail, general models or models for different cell types or organs can be repurposed for liver cells.…”

“…Later, the same group [22] adapted this PK-SB model for liver cells, by recalibrating the model using transcriptomic data, including ROS data at different time points and literature-based GSH data. They used the compound Acetyl-paraaminophenol (APAP) to induce cytotoxicity in a liver-on-a-chip and compared the results with the PK-SB model.…”

“…Finally, PK and PK-PD modeling are employed to translate this threshold to a corresponding tolerable drug intake in humans. This process was illustrated by Leclerc et al [22] who integrated their dynamical model of the oxidative stress pathway with a PK model predicting how much of the drug actually reaches the cell. Experimental measurements were performed with an organ-on-a-chip setup, and the PK model described the amount of the drug flowing into the extracellular compartments, taking into account adsorption and desorption rates.…”