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Publications [#229596] of H. Frederik Nijhout

Papers Published

  1. Geenen, S; du Preez, FB; Reed, M; Nijhout, HF; Kenna, JG; Wilson, ID; Westerhoff, HV; Snoep, JL, A mathematical modelling approach to assessing the reliability of biomarkers of glutathione metabolism., European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences, vol. 46 no. 4 (July, 2012), pp. 233-243, ISSN 1879-0720 [21888969], [doi]
    (last updated on 2019/10/18)

    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.

    Acetaminophen • Animals • Biological Markers • Computer Simulation* • Glutathione • Humans • Liver • Metabolic Detoxication, Drug • Methionine • Models, Biological* • Oligopeptides • Pyrrolidonecarboxylic Acid • Reproducibility of Results • Systems Biology* • drug effects • metabolism • metabolism* • toxicity