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.

From steady-state to synchronized yeast glycolytic oscillations II: model validation.

UNLABELLED: In an accompanying paper [du Preez et al., (2012) FEBS J279, 2810-2822], we adapt an existing kinetic model for steady-state yeast glycolysis to simulate limit-cycle oscillations. Here we validate the model by testing its capacity to simulate a wide range of experiments on dynamics of yeast glycolysis. In addition to its description of the oscillations of glycolytic intermediates in intact cells and the rapid synchronization observed when mixing out-of-phase oscillatory cell populations (see accompanying paper), the model was able to predict the Hopf bifurcation diagram with glucose as the bifurcation parameter (and one of the bifurcation points with cyanide as the bifurcation parameter), the glucose- and acetaldehyde-driven forced oscillations, glucose and acetaldehyde quenching, and cell-free extract oscillations (including complex oscillations and mixed-mode oscillations). Thus, the model was compliant, at least qualitatively, with the majority of available experimental data for glycolytic oscillations in yeast. To our knowledge, this is the first time that a model for yeast glycolysis has been tested against such a wide variety of independent data sets. DATABASE: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/dupreez/index.html.

From steady-state to synchronized yeast glycolytic oscillations I: model construction.

UNLABELLED: An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. Using a small subset of experimental data, the original model was adapted by adjusting its parameter values in three optimization steps. Only small adaptations to the original model were required for realistic simulation of experimental data for limit-cycle oscillations. The greatest changes were required for parameter values for the phosphofructokinase reaction. The importance of ATP for the oscillatory mechanism and NAD(H) for inter-and intra-cellular communications and synchronization was evident in the optimization steps and simulation experiments. In an accompanying paper [du Preez F et al. (2012) FEBS J279, 2823-2836], we validate the model for a wide variety of experiments on oscillatory yeast cells. The results are important for re-use of detailed kinetic models in modular modeling approaches and for approaches such as that used in the Silicon Cell initiative. DATABASE: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/dupreez/index.html.

Sustained glycolytic oscillations in individual isolated yeast cells.

UNLABELLED: Yeast glycolytic oscillations have been studied since the 1950s in cell-free extracts and intact cells. For intact cells, sustained oscillations have so far only been observed at the population level, i.e. for synchronized cultures at high biomass concentrations. Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. This is the first time that sustained limit-cycle oscillations have been demonstrated in isolated yeast cells. DATABASE: The mathematical model described here has been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/gustavsson/index.html free of charge.

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

One of the main pathways for the detoxification of reactive metabolites in the liver involves glutathione conjugation. Metabolic profiling studies have shown paradoxical responses in glutathione-related biochemical pathways. One of these is the increase in 5-oxoproline and ophthalmic acid concentrations with increased dosage of paracetamol. Experimental studies have thus far failed to resolve these paradoxes and the robustness of how these proposed biomarkers correlate with liver glutathione levels has been questioned. To better understand how these biomarkers behave in the glutathione system a kinetic model of this pathway was made. By using metabolic control analysis and by simulating biomarker levels under a variety of conditions, we found that 5-oxoproline and ophthalmic acid concentrations may not only depend on the glutathione but also on the methionine status of the cell. We show that neither of the two potential biomarkers are reliable on their own since they need additional information about the methionine status of the system to relate them uniquely to intracellular glutathione concentration. However, when both biomarkers are measured simultaneously a direct inference of the glutathione concentration can be made, irrespective of the methionine concentration in the system.

The SEEK: a platform for sharing data and models in systems biology.

Systems biology research is typically performed by multidisciplinary groups of scientists, often in large consortia and in distributed locations. The data generated in these projects tend to be heterogeneous and often involves high-throughput "omics" analyses. Models are developed iteratively from data generated in the projects and from the literature. Consequently, there is a growing requirement for exchanging experimental data, mathematical models, and scientific protocols between consortium members and a necessity to record and share the outcomes of experiments and the links between data and models. The overall output of a research consortium is also a valuable commodity in its own right. The research and associated data and models should eventually be available to the whole community for reuse and future analysis. The SEEK is an open-source, Web-based platform designed for the management and exchange of systems biology data and models. The SEEK was originally developed for the SysMO (systems biology of microorganisms) consortia, but the principles and objectives are applicable to any systems biology project. The SEEK provides an index of consortium resources and acts as gateway to other tools and services commonly used in the community. For example, the model simulation tool, JWS Online, has been integrated into the SEEK, and a plug-in to PubMed allows publications to be linked to supporting data and author profiles in the SEEK. The SEEK is a pragmatic solution to data management which encourages, but does not force, researchers to share and disseminate their data to community standard formats. It provides tools to assist with management and annotation as well as incentives and added value for following these recommendations. Data exchange and reuse rely on sufficient annotation, consistent metadata descriptions, and the use of standard exchange formats for models, data, and the experiments they are derived from. In this chapter, we present the SEEK platform, its functionalities, and the methods employed for lowering the barriers to adoption of standard formats. As the production of biological data continues to grow, in systems biology and in the life sciences in general, the need to record, manage, and exploit this wealth of information in the future is increasing. We promote the SEEK as a data and model management tool that can be adapted to the specific needs of a particular systems biology project.

RightField: embedding ontology annotation in spreadsheets.

MOTIVATION: In the Life Sciences, guidelines, checklists and ontologies describing what metadata is required for the interpretation and reuse of experimental data are emerging. Data producers, however, may have little experience in the use of such standards and require tools to support this form of data annotation. RESULTS: RightField is an open source application that provides a mechanism for embedding ontology annotation support for Life Science data in Excel spreadsheets. Individual cells, columns or rows can be restricted to particular ranges of allowed classes or instances from chosen ontologies. The RightField-enabled spreadsheet presents selected ontology terms to the users as a simple drop-down list, enabling scientists to consistently annotate their data. The result is 'semantic annotation by stealth', with an annotation process that is less error-prone, more efficient, and more consistent with community standards. AVAILABILITY AND IMPLEMENTATION: RightField is open source under a BSD license and freely available from http://www.rightfield.org.uk

Data and model integration using JWS Online.

Systems Biology requires a tight integration of experimental data and detailed computer models to obtain a quantitative understanding of the system under study. To facilitate this integration a standardization of data and model representation and storage is important. We illustrate here such an integration using JWS Online, the modeling tool developed in our group. We follow the approach of the Silicon Cell project for the construction and validation of kinetic models and discuss some issues with respect to storage of experimental data and models. The majority of the published kinetic models for biological systems have been developed for metabolic networks and this will be our focus in this manuscript. It is not our aim to present here an all encompassing method for data and model integration, but rather to present our work on this topic to start a discussion in which the different initiatives, methods and tools can be compared.

Is photosynthetic transcriptional regulation in Triticum aestivum L. cv. 'TugelaDN' a contributing factor for tolerance to Diuraphis noxia (Homoptera: Aphididae)?

Diuraphis noxia (Russian wheat aphid, RWA) is a major pest on wheat in South Africa and most other wheat growing countries. Being a probing-sucking insect, RWAs insert their stylets into the phloem sieve elements and feed on the phloem sap. This feeding causes necrotic lesions in resistant varieties, or decoloration of leaves and death in susceptible varieties. In an effort to broaden our understanding on the response of the plant to RWA feeding, we synthesized and analyzed expressed sequence tags (ESTs) from suppression subtractive hybridization (SSH) libraries. These libraries were constructed using near isogenic wheat lines susceptible "Tugela" and resistant "TugelaDN" (Dn1) to RWA, as well as accession lines PI137739 (Dn1) and PI294994 (Dn5). Analysis of 200 ESTs from the libraries revealed the involvement of transcripts encoding genes involved in cell maintenance, growth and regulation, plant defense and signaling, photosynthesis and energy production, and of unknown function. A selection of these ESTs, in combination with clones obtained from other sources, were used on a custom array to study the expression profiles of 256 candidate wheat sequences putatively involved in plant defense against RWA. The selected sequences included wheat genomic clones with putative nucleotide binding site (NBS) motifs, rapid amplification of cDNA ends PCR (RACE-PCR), and cDNA clones from RWA induced libraries. Genomic banana and flax clones that were obtained using representative difference analysis (RDA), and suspected to be involved in abiotic stress responses, were also spotted onto the microarray slides. The spotted custom arrays were then hybridized against cDNA isolated from a resistant cultivar "TugelaDN" on 0, 2, 5, and 8 days after infestation, post-labeled with Cy3- or Cy5-fluorescent dyes. The subsequent expression profiling using DNA microarray, RT-PCR, and Northern Blot analysis identified 29 transcripts associated with the feeding response. These transcripts encoded proteins functioning in direct defense and signaling, oxidative burst, cell wall degradation, cell maintenance, photosynthesis, and energy production. Results indicate that plants co-ordinately regulate gene expression when attacked by RWA. It is hypothesized that the NBS-LRR proteins are important in receptor recognition and signaling, which enable the plant to overcome the stresses inflicted by RWA feeding. It is further suggested that the ability to maintain photosynthetic function with resultant energy production is one of the determining factors ensuring the survival of the resistant varieties when coping with the RWA feeding.