Integration of pharmacokinetic and NRF2 system biology models to describe reactive oxygen species production and subsequent glutathione depletion in liver microfluidic biochips after flutamide exposure

Signal amplification in the KEAP1-NRF2-ARE antioxidant response pathway

The KEAP1-NRF2-ARE signaling pathway plays a central role in mediating the adaptive cellular stress response to oxidative and electrophilic chemicals. This canonical pathway has been extensively studied and reviewed in the past two decades, but rarely was it looked at from a quantitative signaling perspective. Signal amplification, i.e., ultrasensitivity, is crucially important for robust induction of antioxidant genes to appropriate levels that can adequately counteract the stresses. In this review article, we examined a number of well-known molecular events in the KEAP1-NRF2-ARE pathway from a quantitative perspective with a focus on how signal amplification can be achieved. We illustrated, by using a series of mathematical models, that redox-regulated protein sequestration, stabilization, translation, nuclear trafficking, DNA promoter binding, and transcriptional induction - which are embedded in the molecular network comprising KEAP1, NRF2, sMaf, p62, and BACH1 - may generate highly ultrasensitive NRF2 activation and antioxidant gene induction. The emergence and degree of ultrasensitivity depend on the strengths of protein-protein and protein-DNA interaction and protein abundances. A unique, quantitative understanding of signal amplification in the KEAP1-NRF2-ARE pathway will help to identify sensitive targets for the prevention and therapeutics of oxidative stress-related diseases and develop quantitative adverse outcome pathway models to facilitate the health risk assessment of oxidative chemicals.

Mathematical modeling reveals quantitative properties of KEAP1-NRF2 signaling

Under oxidative and electrophilic stresses, cells launch an NRF2-mediated transcriptional antioxidant program. The activation of NRF2 depends on a redox sensor, KEAP1, which promotes the ubiquitination and degradation of NRF2. While a great deal has been learned about this duo, its quantitative signaling properties are largely unexplored. Here we examined these properties, including half-life, maximal activation, and response steepness (ultrasensitivity) of NRF2, through mathematical modeling. The models describe the binding of KEAP1 and NRF2 via ETGE and DLG motifs, NRF2 production, KEAP1-dependent and independent NRF2 degradation, and perturbations by different classes of NRF2 activators. Simulations revealed at the basal condition, NRF2 is sequestered by KEAP1 and the KEAP1-NRF2 complex is distributed comparably in an ETGE-bound (open) state and an ETGE and DLG dual-bound (closed) state. When two-step ETGE binding is considered, class I–V, electrophilic NRF2 activators shift the balance to a closed state incompetent to degrade NRF2, while the open and closed KEAP1-NRF2 complexes transition from operating in cycle mode to equilibrium mode. Ultrasensitive NRF2 activation (a steep rise of free NRF2) can occur when NRF2 nearly saturates KEAP1. The ultrasensitivity results from zero-order degradation through DLG binding and protein sequestration through ETGE binding. Optimal abundances of cytosolic and nuclear KEAP1 exist to maximize ultrasensitivity. These response characteristics do not require disruption of DLG binding as suggested by the hinge-latch hypothesis. In comparison, class VI NRF2 activators cause a shift to the open KEAP1-NRF2 complex and ultimately its complete dissociation, resulting in a fast release of NRF2 followed by stabilization. However, ultrasensitivity is lost due to decreasing free KEAP1 abundance. In summary, by simulating the dual role of KEAP1, i.e., sequestering and promoting degradation of NRF2, our modeling provides novel quantitative insights into NRF2 activation, which may help design novel NRF2 modulators and understand the oxidative actions of environmental stressors.

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Steep (ultrasensitive) NRF2 activation can occur when it rises to saturate KEAP1.

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Ultrasensitivity results from zero-order degradation and protein sequestration.

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Optimal cytosolic and nuclear KEAP1 abundances exist for maximal ultrasensitivity.

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Open and closed KEAP1-NRF2 complexes transition in cycle and equilibrium mode.

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NRF2 activation by KEAP1-NRF2 interaction inhibitors is more gradual.

Introduction to In Silico Modeling to Study ROS Dynamics

This book chapter is drafted for biologists with experimental experiences in ROS biology but being newcomers in the field of modeling. We start with a general introduction about computational modeling in biology and an overview of software tools suitable for beginners. This chapter encompasses an introduction to computational models with special focus on simulation of ROS dynamics. A step-by-step tutorial follows providing guidance for all relevant model development processes. This course of action gives a comprehensible way to understand the benefits of computational models and to gain the necessary knowledge to build own small equation-based models. Small models can be created without any special programming expertise or in-depth technical and mathematical knowledge. Afterward in the final section, a short overview of pitfalls, challenges, and limitations is provided, combined with suggestions for further reading to improve and expand modeling skills of biologists.

Protein biochips based on macroporous polymer supports: Material properties and analytical potential

A series of rigid macroporous polymer layers differed by hydrophobic-hydrophilic properties was synthesized in situ in preliminary fabricated wells and applied as the platforms for protein biochips. Scanning electron microscopy, etalon porosimetry and BET analysis were used for materials characterization. The comparison of analytical efficiency of the developed platforms allowed for the choice of the most optimal polymer, as well as the evaluation of impact of material porous properties. The quantitative parameters of affinity interaction between two different protein pairs were calculated depending on biochip characteristics using the developed analytical protocol. Moreover, the described biochips were successfully tested to detect acetylcholinesterase via catalytic reaction followed by the formation of fluoresceine as a product. Different parameters of enzymatic reaction were calculated for the reaction on a chip and compared to those established for in solution process.

Engineered Liver Platforms for Different Phases of Drug Development

Drug-induced liver injury (DILI) remains a leading cause of drug withdrawal from human clinical trials or the marketplace. Owing to species-specific differences in liver pathways, predicting human-relevant DILI using in vitro human liver models is crucial. Microfabrication tools allow precise control over the cellular microenvironment towards stabilizing liver functions for weeks. These tools are used to engineer human liver models with different complexities and throughput using cell lines, primary cells, and stem cell-derived hepatocytes. Including multiple human liver cell types can mimic cell-cell interactions in specific types of DILI. Finally, organ-on-a-chip models demonstrate how drug metabolism in the liver affects multi-organ toxicities. In this review we survey engineered human liver platforms within the needs of different phases of drug development.

Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing

The recent advent of microphysiological systems - microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro - is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-six experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale.

Microfluidic Organ/Body-on-a-Chip Devices at the Convergence of Biology and Microengineering

Recent advances in biomedical technologies are mostly related to the convergence of biology with microengineering. For instance, microfluidic devices are now commonly found in most research centers, clinics and hospitals, contributing to more accurate studies and therapies as powerful tools for drug delivery, monitoring of specific analytes, and medical diagnostics. Most remarkably, integration of cellularized constructs within microengineered platforms has enabled the recapitulation of the physiological and pathological conditions of complex tissues and organs. The so-called “organ-on-a-chip” technology, which represents a new avenue in the field of advanced in vitro models, with the potential to revolutionize current approaches to drug screening and toxicology studies. This review aims to highlight recent advances of microfluidic-based devices towards a body-on-a-chip concept, exploring their technology and broad applications in the biomedical field.

Investigation of ifosfamide and chloroacetaldehyde renal toxicity through integration of in vitro liver-kidney microfluidic data and pharmacokinetic-system biology models

We have integrated in vitro and in silico data to describe the toxicity of chloroacetaldehyde (CAA) on renal cells via its production from the metabolism of ifosfamide (IFO) by hepatic cells. A pharmacokinetic (PK) model described the production of CAA by the hepatocytes and its transport to the renal cells. A system biology model was coupled to the PK model to describe the production of reactive oxygen species (ROS) induced by CAA in the renal cells. In response to the ROS production, the metabolism of glutathione (GSH) and its depletion were modeled by the action of an NFE2L2 gene-dependent pathway. The model parameters were estimated in a Bayesian context via Markov Chain Monte Carlo (MCMC) simulations based on microfluidic experiments and literature in vitro data. Hepatic IFO and CAA in vitro intrinsic clearances were estimated to be 1.85 x 10(-9) μL s(-1) cell(-1) and 0.185 x 10(-9) μL s(-1) cell(-1) ,respectively (corresponding to an in vivo intrinsic IFO clearance estimate of 1.23 l h(-1) , to be compared to IFO published values ranging from 3 to 10 l h(-1) ). After model calibration, simulations made at therapeutic doses of IFO showed CAA renal intracellular concentrations ranging from 11 to 131 μM. Intracellular CAA concentrations above 70 μM induced intense ROS production and GSH depletion. Those responses were time and dose dependent, showing transient and non-linear kinetics. Those results are in agreement with literature data reporting that intracellular CAA toxic concentrations range from 35 to 320 μM, after therapeutic ifosfamide dosing. The results were also consistent with in vitro CAA renal cytotoxicity data.

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

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.

Quantitative in vitro to in vivo extrapolation of tissues toxicity

Predicting repeated-dosing in vivo drug toxicity from in vitro testing and omics data gathering requires significant support in bioinformatics, mathematical modeling and statistics. We present here the major aspects of the work devoted within the framework of the European integrated Predict-IV to pharmacokinetic modeling of in vitro experiments, physiologically based pharmacokinetic (PBPK) modeling, mechanistic models of toxicity for the kidney and brain, large scale dose-response analyses methods and biomarker discovery tools. All of those methods have been applied to various extent to the drug datasets developed by the project's partners. Our approach is rather generic and could be adapted to other drugs or drug candidates. It marks a successful integration of the work of the different teams toward a common goal of predictive quantitative in vitro to in vivo extrapolation.