A mathematical modelling approach to assessing the reliability of biomarkers of glutathione metabolism

Multistability maintains redox homeostasis in human cells

Cells metabolize nutrients through a complex metabolic and signaling network that governs redox homeostasis. At the core of this, redox regulatory network is a mutually inhibitory relationship between reduced glutathione and reactive oxygen species (ROS)-two opposing metabolites that are linked to upstream nutrient metabolic pathways (glucose, cysteine, and glutamine) and downstream feedback loops of signaling pathways (calcium and NADPH oxidase). We developed a nutrient-redox model of human cells to understand system-level properties of this network. Combining in silico modeling and ROS measurements in individual cells, we show that ROS dynamics follow a switch-like, all-or-none response upon glucose deprivation at a threshold that is approximately two orders of magnitude lower than its physiological concentration. We also confirm that this ROS switch can be irreversible and exhibits hysteresis, a hallmark of bistability. Our findings evidence that bistability modulates redox homeostasis in human cells and provide a general framework for quantitative investigations of redox regulation in humans.

Sexual Dimorphism of Metabolite Profiles in Pigs Depends on the Genetic Background

The study aimed to investigate possible systematic effects in the basic underlying variability of individual metabolomic data. In this context, the extent of gender- and genotype-dependent differences reflected in the metabolic composition of three tissues in fattening pigs was determined. The 40 pigs belonged to the genotypes PIx(LWxGL) and PIxGL with gilts and boars, respectively. Blood and tissue samples from M. longissimus dorsi and liver were directly taken at the slaughtering plant and directed to GC × GC qMS metabolite analysis. Differences were observed for various metabolite classes like amino acids, fatty acids, sugars, or organic acids. Gender-specific differences were much more pronounced than genotype-related differences, which could be due to the close genetic relation of the fattening pigs. However, the metabolic dimorphism between gilts and boars was found to be genotype-dependent, and vice versa metabolic differences between genotypes were found to be gender-dependent. Most interestingly, integration into metabolic pathways revealed different patterns for carbon (C) and nitrogen (N) usage in boars and gilts. We suppose a stronger N-recycling and increased energy metabolism in boars, whereas, in gilts, more N is presumably excreted and remaining carbon skeletons channeled into lipogenesis. Associations of metabolites to meat quality factors confirmed the applicability of metabolomics approaches for a better understanding about the impact of drivers (e.g., gender, age, breed) on physiological processes influencing meat quality. Due to the huge complexity of the drivers-traits-network, the derivation of independent biomarkers for meat quality prediction will hardly be possible.

Complex Stability and an Irrevertible Transition Reverted by Peptide and Fibroblasts in a Dynamic Model of Innate Immunity

We here apply a control analysis and various types of stability analysis to an in silico model of innate immunity that addresses the management of inflammation by a therapeutic peptide. Motivation is the observation, both in silico and in experiments, that this therapy is not robust. Our modeling results demonstrate how (1) the biological phenomena of acute and chronic modes of inflammation may reflect an inherently complex bistability with an irrevertible flip between the two modes, (2) the chronic mode of the model has stable, sometimes unique, steady states, while its acute-mode steady states are stable but not unique, (3) as witnessed by TNF levels, acute inflammation is controlled by multiple processes, whereas its chronic-mode inflammation is only controlled by TNF synthesis and washout, (4) only when the antigen load is close to the acute mode's flipping point, many processes impact very strongly on cells and cytokines, (5) there is no antigen exposure level below which reduction of the antigen load alone initiates a flip back to the acute mode, and (6) adding healthy fibroblasts makes the transition from acute to chronic inflammation revertible, although (7) there is a window of antigen load where such a therapy cannot be effective. This suggests that triple therapies may be essential to overcome chronic inflammation. These may comprise (1) anti-immunoglobulin light chain peptides, (2) a temporarily reduced antigen load, and (3a) fibroblast repopulation or (3b) stem cell strategies.

Identification of a co-target for enhancing efficacy of sorafenib in HCC through a quantitative modeling approach

Sorafenib (SFB), a multi-kinase inhibitor, is the only approved drug for treating hepatocellular carcinoma (HCC). However, SFB shows low efficacy in many cases. HCC related mortality therefore remains to be high worldwide. SFB, a multi-kinase inhibitor is also known to modulate the redox homeostasis in cancer cells. To understand the effect of SFB on the redox status, a quantitative understanding of the system is necessary. Kinetic modeling of the relevant pathways is a useful approach for obtaining a quantitative understanding of the pathway dynamics and to rank the individual factors based on the extent of influence they wield on the pathway. Here, we report a comprehensive model of the glutathione reaction network (GSH_net ), consisting of four modules and includes SFB-induced redox stress. We compared GSH_net simulations for HCC of six different etiologies with healthy liver, and correctly identified the expected variations in cancer. Next, we studied alterations induced in the system upon SFB treatment and observed differential H₂ O₂ dynamics in all the conditions. Using metabolic control analysis, we identified glutathione S-transferase (GST) as the enzyme with the highest selective control coefficient, making it an attractive co-target for potentiating the action of SFB across all six etiologies. As a proof-of-concept, we selected ethacrynic acid (EA), a known inhibitor of GST, and verified ex vivo that EA synergistically potentiates the cytotoxic effect of SFB. Being an FDA approved drug, EA is a promising candidate for repurposing as a combination therapy with SFB for HCC treatment.

Metabolic phenotyping applied to pre-clinical and clinical studies of acetaminophen metabolism and hepatotoxicity

Acetaminophen (APAP, paracetamol, N-acetyl-p-aminophenol) is a widely used analgesic that is safe at therapeutic doses but is a major cause of acute liver failure (ALF) following overdose. APAP-induced hepatotoxicity is related to the formation of an electrophilic reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI), which is detoxified through conjugation with reduced glutathione (GSH). One method that has been applied to study APAP metabolism and hepatotoxicity is that of metabolic phenotyping, which involves the study of the small molecule complement of complex biological samples. This approach involves the use of high-resolution analytical platforms such as NMR spectroscopy and mass spectrometry to generate information-rich metabolic profiles that reflect both genetic and environmental influences and capture both endogenous and xenobiotic metabolites. Data modeling and mining and the subsequent identification of panels of candidate biomarkers are typically approached with multivariate statistical tools. We review the application of multi-platform metabolic profiling for the study of APAP metabolism in both in vivo models and humans. We also review the application of metabolic profiling for the study of endogenous metabolic pathway perturbations in response to APAP hepatotoxicity, with a particular focus on metabolites involved in the biosynthesis of GSH and those that reflect mitochondrial function such as long-chain acylcarnitines. Taken together, this body of work sheds much light on the mechanism of APAP-induced hepatotoxicity and provides candidate biomarkers that may prove of translational relevance for improved stratification of APAP-induced ALF.

Multiscale modelling approach combining a kinetic model of glutathione metabolism with PBPK models of paracetamol and the potential glutathione-depletion biomarkers ophthalmic acid and 5-oxoproline in humans and rats

A key role of the antioxidant glutathione is detoxification of chemically reactive electrophilic drug metabolites within the liver. Therefore glutathione depletion can have severe toxic consequences. Ophthalmic acid and 5-oxoproline are metabolites involved in glutathione metabolism, which can be measured readily in the blood and urine and have been proposed as candidate biomarkers of hepatic glutathione content. However, currently it is unclear whether their concentrations in plasma exhibit a robust correlation with hepatic glutathione content. To explore this important question, we have developed a novel approach which combines a physiologically based pharmacokinetic (PBPK) model of metabolism and disposition of paracetamol (acetaminophen) with a previously developed mathematical systems model of hepatic glutathione homeostasis. Paracetamol is metabolised to reactive intermediates which deplete glutathione and cause toxicity when given at high doses. Our model correctly predicted that hepatic glutathione depletion following paracetamol administration resulted in elevated concentrations of 5-oxoproline and ophthalmic acid in blood and of 5-oxoproline in urine. However, we also found from the model that concentrations of both of the compounds were likely to be influenced by prolonged administration of paracetamol and by the concentrations of intracellular metabolites such as methionine. We conclude that care must be taken when extrapolating from concentrations of these biomarkers to hepatic glutathione status.

From top-down to bottom-up: computational modeling approaches for cellular redoxin networks

SIGNIFICANCE

Thioredoxin, glutaredoxin, and peroxiredoxin systems play critical roles in a large number of redox-sensitive cellular processes. These systems are linked to each other by coupled redox cycles and common reaction intermediates into a larger network. Given the scale and connectivity of this network, computational approaches are required to analyze its dynamics and organization.

RECENT ADVANCES

Theoretical advances, as well as new redox proteomic methods, have led to the development of both top-down and bottom-up systems biology approaches to analyze the these systems and the network as a whole. Top-down approaches have been based on modifications to the Nernst equation or on graph theoretical approaches, while bottom-up approaches have been based on kinetic or stoichiometric modeling techniques.

CRITICAL ISSUES

This review will consider the rationale behind these approaches and focus on their advantages and limitations. Further, the review will discuss modeling standards to ensure model accuracy and availability.

FUTURE DIRECTIONS

Top-down and bottom-up approaches have distinct strengths and limitations in describing cellular redoxin networks. The availability of methods to overcome these limitations, together with the adoption of common modeling standards, is expected to increase the pace of model-led discovery within the redox biology field.

Glutathione metabolism modeling: a mechanism for liver drug-robustness and a new biomarker strategy

BACKGROUND

Glutathione metabolism can determine an individual's ability to detoxify drugs. To increase understanding of the dynamics of cellular glutathione homeostasis, we have developed an experiment-based mathematical model of the kinetics of the glutathione network. This model was used to simulate perturbations observed when human liver derived THLE cells, transfected with human cytochrome P452E1 (THLE-2E1 cells), were exposed to paracetamol (acetaminophen).

METHODS

Human liver derived cells containing extra human cytochrome P4502E1 were treated with paracetamol at various levels of methionine and in the presence and absence of an inhibitor of glutamyl-cysteine synthetase (GCS). GCS activity was also measured in extracts. Intracellular and extracellular concentrations of substances involved in glutathione metabolism were measured as was damage to mitochondria and proteins. A bottom up mathematical model was made of the metabolic pathways around and including glutathione.

RESULTS

Our initial model described some, but not all the metabolite-concentration and flux data obtained when THLE-2E1 cells were exposed to paracetamol at concentrations high enough to affect glutathione metabolism. We hypothesized that the lack of correspondence could be due to upregulation of expression of glutamyl cysteine synthetase, one of the enzymes controlling glutathione synthesis, and confirmed this experimentally. A modified model which incorporated this adaptive response adequately described the observed changes in the glutathione pathway. Use of the adaptive model to analyze the functioning of the glutathione network revealed that a threshold input concentration of methionine may be required for effective detoxification of reactive metabolites by glutathione conjugation. The analysis also provided evidence that 5-oxoproline and ophthalmic acid are more useful biomarkers of glutathione status when analyzed together than when analyzed in isolation, especially in a new, model-assisted integrated biomarker strategy.

CONCLUSION

A robust mathematical model of the dynamics of cellular changes in glutathione homeostasis in cells has been developed and tested in vitro.

GENERAL SIGNIFICANCE

Mathematical models of the glutathione pathway that help examine mechanisms of cellular protection against xenobiotic toxicity and the monitoring thereof, can now be made.

Modeling cellular compartmentation in one-carbon metabolism

Folate-mediated one-carbon metabolism (FOCM) is associated with risk for numerous pathological states including birth defects, cancers, and chronic diseases. Although the enzymes that constitute the biological pathways have been well described and their interdependency through the shared use of folate cofactors appreciated, the biological mechanisms underlying disease etiologies remain elusive. The FOCM network is highly sensitive to nutritional status of several B-vitamins and numerous penetrant gene variants that alter network outputs, but current computational approaches do not fully capture the dynamics and stochastic noise of the system. Combining the stochastic approach with a rule-based representation will help model the intrinsic noise displayed by FOCM, address the limited flexibility of standard simulation methods for coarse-graining the FOCM-associated biochemical processes, and manage the combinatorial complexity emerging from reactions within FOCM that would otherwise be intractable.

Systematic review of ophthalmate as a novel biomarker of hepatic glutathione depletion

BACKGROUND

Sustainability of hepatic glutathione (GSH) homeostasis is an important cellular defense against oxidative stress. Therefore, knowledge of liver GSH status is important. However, measurement of plasma GSH and tissue is difficult due to its instability. Alternatively, ophthalmate (OPH), an endogenous tripeptide analog of GSH, has been suggested as a potential indicator to assess GSH depletion.

AIM

To provide an overview of present knowledge with respect to the usefulness of OPH as a biomarker for oxidative stress and hepatic GSH homeostasis.

METHODS

A systematic, computerized search combined with a cross-reference search of the literature described in PubMed (January 1975 to January 2012) was conducted, key words: 'ophthalmate' and 'ophthalmic acid'.

RESULTS

Twenty-two articles were included. Hepatic OPH levels increase inversely proportional to a drop in hepatic GSH in mice with paracetamol (PCM) induced hepatotoxicity. Little is known about the stability of OPH in human plasma. To measure the very low physiological concentrations of plasma OPH, liquid chromatography-mass spectrometry techniques can be employed. OPH synthesis can be measured in humans, using stable isotope labeling with a deuterated water ((2)H2O) load.

CONCLUSION

OPH may be a promising biomarker to indicate hepatic glutathione depletion, but the suggested biological pathways need further unraveling.

A Systems Biology Approach to Deciphering the Etiology of Steatosis Employing Patient-Derived Dermal Fibroblasts and iPS Cells

Non-alcoholic fatty liver disease comprises a broad spectrum of disease states ranging from simple steatosis to non-alcoholic steatohepatitis. As a result of increases in the prevalences of obesity, insulin resistance, and hyperlipidemia, the number of people with hepatic steatosis continues to increase. Differences in susceptibility to steatohepatitis and its progression to cirrhosis have been attributed to a complex interplay of genetic and external factors all addressing the intracellular network. Increase in sugar or refined carbohydrate consumption results in an increase of insulin and insulin resistance that can lead to the accumulation of fat in the liver. Here we demonstrate how a multidisciplinary approach encompassing cellular reprogramming, transcriptomics, proteomics, metabolomics, modeling, network reconstruction, and data management can be employed to unveil the mechanisms underlying the progression of steatosis. Proteomics revealed reduced AKT/mTOR signaling in fibroblasts derived from steatosis patients and further establishes that the insulin-resistant phenotype is present not only in insulin-metabolizing central organs, e.g., the liver, but is also manifested in skin fibroblasts. Transcriptome data enabled the generation of a regulatory network based on the transcription factor SREBF1, linked to a metabolic network of glycerolipid, and fatty acid biosynthesis including the downstream transcriptional targets of SREBF1 which include LIPIN1 (LPIN) and low density lipoprotein receptor. Glutathione metabolism was among the pathways enriched in steatosis patients in comparison to healthy controls. By using a model of the glutathione pathway we predict a significant increase in the flux through glutathione synthesis as both gamma-glutamylcysteine synthetase and glutathione synthetase have an increased flux. We anticipate that a larger cohort of patients and matched controls will confirm our preliminary findings presented here.

Systems biology tools for toxicology

An important goal of toxicology is to understand and predict the adverse effects of drugs and other xenobiotics. For pharmaceuticals, such effects often emerge unexpectedly in man even when absent from trials in vitro and in animals. Although drugs and xenobiotics act on molecules, it is their perturbation of intracellular networks that matters. The tremendous complexity of these networks makes it difficult to understand the effects of xenobiotics on their ability to function. Because systems biology integrates data concerning molecules and their interactions into an understanding of network behaviour, it should be able to assist toxicology in this respect. This review identifies how in silico systems biology tools, such as kinetic modelling, and metabolic control, robustness and flux analyse, may indeed help understanding network-mediated toxicity. It also shows how these approaches function by implementing them vis-à-vis the glutathione network, which is important for the detoxification of reactive drug metabolites. The tools enable the appreciation of the steady state concept for the detoxification network and make it possible to simulate and then understand effects of perturbations of the macromolecules in the pathway that are counterintuitive. We review how a glutathione model has been used to explain the impact of perturbation of the pathway at various molecular sites, as would be the effect of single-nucleotide polymorphisms. We focus on how the mutations impact the levels of glutathione and of two candidate biomarkers of hepatic glutathione status. We conclude this review by sketching how the various systems biology tools may help in the various phases of drug development in the pharmaceutical industry.

Ophthalmate detection in human plasma with LC-MS-MS

Based on animal experimentations, ophthalmate (OPH) has recently been suggested as a potential plasma biomarker to probe hepatic GSH homeostasis. Up until now, the inability to accurately determine OPH concentrations in human plasma prohibited further studies of OPH metabolism in humans. This study therefore aimed to study the influence of delayed sample preparation on OPH concentrations using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Venous plasma samples from 5 healthy human volunteers were incubated for varying times (5, 30, 60 and 120 min) at temperatures of 4 °C and 37 °C to investigate potential enzymatic degradation. At 37 °C, the decrease in OPH reached significance after 120 min (74.6% (range: 56.2-100.0%; p<0.0001)). At 4 °C, the same trend was observed but did not reach significance. These findings indicate ongoing enzymatic activity, stressing the need for immediate sample deproteinization to obtain reliable plasma concentrations. To investigate the feasibility of the here developed method, baseline arterial plasma values of 21 patients scheduled for partial liver resection were determined to be 0.06±0.03 μmol/l (mean±s.d.). In addition, in pooled samples from 3 patients, an OPH calibration curve was spiked to arterial plasma, arterial whole blood and liver biopsy material, resulting in a linear calibration curve in all cases. Individual measurements of baseline samples revealed that both arterial whole blood and liver biopsy material contained significant levels of endogenous OPH, namely 16.1 (11.8-16.4) μmol/l and 80.0 (191.8-349.2) μmol/kg, respectively. In conclusion, the present LC-MS/MS assay enables the accurate measurement of OPH in human plasma, whole blood and liver biopsies. Freshly prepared samples and immediate deproteinization are mandatory to block enzymatic degradation.