A mathematical modelling approach to assessing the reliability of biomarkers of glutathione metabolism
Graphical abstract
Introduction
Glutathione is often associated with toxicology due to its role in detoxifying electrophilic metabolites leading to the production of N-acetyl cysteinyl conjugates (mercapturates) (Meister, 1988). This is particularly true in the case of paracetamol (acetaminophen, APAP). APAP is subject to cytochrome (CYP) P450-based oxidative metabolism via CYP 2E1. This results in the formation of a reactive metabolite that is nucleophilic and at high therapeutic doses is detoxified by reacting with cellular glutathione to form glutathione conjugates. At high concentrations of paracetamol this protective mechanism depletes the system for glutathione leading to high levels of reactive metabolites which in turn can result in oxidative stress and covalent modification of cellular macromolecules (Mitchell et al., 1973).
Many factors can influence the rate of glutathione synthesis and therefore the amount of glutathione available in the cell for drug detoxification (Lu, 2009). These range from the expression level (regulation of enzyme production) to metabolism (effect of surrounding metabolism such as methionine cycle) to environmental (effect of nutrition and uptake of amino acids). Predicting how an individual’s glutathione level will react to a xenobiotic attack on the liver is currently difficult. Predictive biomarkers that indicate the level of glutathione metabolism could predict individual responses to drugs and thereby allow prediction of maximum drug dose levels, or aid in the assessment of glutathione levels in clinical trials (Mendrick and Schnackenberg, 2009).
Recently the tripeptide ophthalmic acid, a non-sulphur-containing structural analogue of glutathione, was suggested as a biomarker following APAP administration to mice (Soga et al., 2006). In that study, metabolic profiles were obtained, enabling the determination of global changes in a wide range of metabolites in serum and liver extracts of APAP-treated mice. Ophthalmic acid concentrations had increased within one hour after drug administration, remaining above normal for the next 3 h with significant decreases in glutathione concentrations in the same time period.
A number of studies have also shown increases in the concentration of 5-oxoproline following the administration of hepatic toxicants such as acetaminophen and bromobenzene, where CYP dependent bioactivation produces metabolites that require deactivation via glutathione dependent mechanisms, thereby resulting in glutathione depletion. Originally 5-oxoproline was identified in rat urine by NMR spectroscopy after dosing rats with paracetamol (Ghauri et al., 1993). Oxoprolinuria has also been observed in humans (Creer et al., 1989) following deficiency in enzymes of the glutamyl cycle, i.e. 5-oxoprolinase and glutathione synthase. A recent integrated metabonomic study into bromobenzene-induced hepatotoxicity also identified an increase in 5-oxoproline production in rats (Waters et al., 2006) and an LC-MS assay has shown an increase in 5-oxoproline in THLE-2E1 cell system with paracetamol dosing (Geenen et al., in press).
The studies above suggested a link between ophthalmic acid, 5-oxoproline and glutathione depletion. However, it was not investigated why a correlation in changes in their concentrations should exist and without a mechanistic interpretation of the biomarker’s functioning it is unknown whether any such correlation is robust. Recent publications did not show an increase in ophthalmic acid (Geenen et al., 2011) concentrations after methapyrilene toxicity in rat plasma samples. In addition measurements where 2E1 THLE-cells (SV40 large T antigen immortalised human liver epithelial cells transfected with individual cytochrome P450 enzymes (Macé et al., 1997)) were dosed with paracetamol, have not shown a significant increase in extracellular ophthalmic acid concentrations (Geenen et al., in press). Here we make use of a mathematical model of what is known about glutathione metabolism. We ask whether one should expect 5-oxoproline and ophthalmic acid to be robust biomarkers for glutathione depletion.
Section snippets
Steady state analysis of the model
For the construction of our mathematical model we adapted an existing model on glutathione metabolism (Reed et al., 2008a). The original model was simplified from 60 to 24 reactions, mostly by removing the folate pathway, and was extended to 41 reactions with relevant parts of drug detoxification metabolism (a schema of the model is shown in Fig. 1). After the adaptations we changed some of the model parameters (Vmax values and unknown kinetic parameters, a list of which is included in Appendix
Discussion
The effectiveness, toxicity and thereby maximal dosage of many drugs depend on hepatic detoxification pathways. Predictive biomarkers, which would allow assessment of an individual’s drug metabolism activity, might indirectly but dramatically enhance individualized therapies by allowing doses to be optimized and dose-related toxicity avoided.
A kinetic model of glutathione metabolism and its detoxification pathway for paracetamol was constructed and used for a tentative investigation of the
Modifying the Reed model
The model of glutathione metabolism was based on the model by Reed et al. (Reed et al., 2008b). The Reed model is available from the JWS Online website (Olivier and Snoep, 2004) and can be simulated in a web browser at any of the JWS Online servers (e.g. http://jjj.mib.ac.uk/webMathematica/Examples/run.jsp?modelName=reed). We coded the Reed model in Mathematica (http://www.wolfram.com) and the same steady state was obtained as calculated by Reed. The folate pathway, which was modelled very
Acknowledgement
We thank the BBSRC, EPSRC (BBD0190791, BBC0082191, BBF0035281, BBF0035521, BBF0035521, BBF0035361, BBG5302251, SySMO), EU-FP7 (BioSim, NucSys, EC-MOAN), ZON-MW (91206069) and other funders for systems biology support (http://www.systembiology.net/support).
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