A Model of Redox Kinetics Implicates the Thiol Proteome in Cellular Hydrogen Peroxide Responses

Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA.
Antioxidants & Redox Signaling (Impact Factor: 7.41). 09/2010; 13(6):731-43. DOI: 10.1089/ars.2009.2968
Source: PubMed


Hydrogen peroxide is appreciated as a cellular signaling molecule with second-messenger properties, yet the mechanisms by which the cell protects against intracellular H(2)O(2) accumulation are not fully understood. We introduce a network model of H(2)O(2) clearance that includes the pseudo-enzymatic oxidative turnover of protein thiols, the enzymatic actions of catalase, glutathione peroxidase, peroxiredoxin, and glutaredoxin, and the redox reactions of thioredoxin and glutathione. Simulations reproduced experimental observations of the rapid and transient oxidation of glutathione and the rapid, sustained oxidation of thioredoxin on exposure to extracellular H(2)O(2). The model correctly predicted early oxidation profiles for the glutathione and thioredoxin redox couples across a range of initial extracellular [H(2)O(2)] and highlights the importance of cytoplasmic membrane permeability to the cellular defense against exogenous sources of H(2)O(2). The protein oxidation profile predicted by the model suggests that approximately 10% of intracellular protein thiols react with hydrogen peroxide at substantial rates, with a majority of these proteins forming protein disulfides as opposed to protein S-glutathionylated adducts. A steady-state flux analysis predicted an unequal distribution of the intracellular anti-oxidative burden between thioredoxin-dependent and glutathione-dependent antioxidant pathways, with the former contributing the majority of the cellular antioxidant defense due to peroxiredoxins and protein disulfides.

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    • "Extra intracellular H 2 O 2 degrades through the cascade of oxidation/reduction reactions of the enzymes involving in ROS cellular scavenging systems (module 9, Fig. 1). The model reproduced the typical kinetics of peroxidase oxidised during treatment cells by H 2 O 2 (Adimora et al., 2010) (blue line, Fig. 9). The total concentration of peroxidase (Px) in the model increased, and this indicates a NRF2-KEAP1-dependent expression of peroxidase in response to redox perturbation (red line, Fig. 9). "
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    ABSTRACT: Cells are constantly exposed to Reactive Oxygen Species (ROS) produced both endogenously to meet phys- iological requirements and from exogenous sources. While endogenous ROS are considered as important signalling molecules, high uncontrollable ROS are detrimental. It is unclear how cells can achieve a bal- ance between maintaining physiological redox homeostasis and robustly activate the antioxidant system to remove exogenous ROS. We have utilised a Systems Biology approach to understand how this robust adaptive system fulfils homeostatic requirements of maintaining steady-state ROS and growth rate, while undergoing rapid readjustment under challenged conditions. Using a panel of human ovarian and normal cell lines, we experimentally quantified and established interrelationships between key elements of ROS homeostasis. The basal levels of NRF2 and KEAP1 were cell line specific and maintained in tight corre- lation with their growth rates and ROS. Furthermore, perturbation of this balance triggered cell specific kinetics of NRF2 nuclear–cytoplasmic relocalisation and sequestration of exogenous ROS. Our experi- mental data were employed to parameterise a mathematical model of the NRF2 pathway that elucidated key response mechanisms of redox regulation and showed that the dynamics of NRF2-H2O2 regulation defines a relationship between half-life, total and nuclear NRF2 level and endogenous H2O2 that is cell line specific.
    Full-text · Article · Nov 2014 · Journal of Biotechnology
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    ABSTRACT: The thioredoxin system, which consists of a family of proteins, including thioredoxin (Trx), peroxiredoxin (Prx), and thioredoxin reductase (TrxR), plays a critical role in the defense against oxidative stress by removing harmful hydrogen peroxide (H2O2). Specifically, Trx donates electrons to Prx to remove H2O2 and then TrxR maintains the reduced Trx concentration with NADPH as the cofactor. Despite a great deal of kinetic information gathered on the removal of H2O2 by the Trx system from various sources/species, a mechanistic understanding of the associated enzymes is still not available. We address this issue by developing a thermodynamically consistent mathematical model of the Trx system which entails mechanistic details and provides quantitative insights into the kinetics of the TrxR and Prx enzymes. Consistent with experimental studies, the model analyses of the available data show that both enzymes operate by a ping-pong mechanism. The proposed mechanism for TrxR, which incorporates substrate inhibition by NADPH and intermediate protonation states, well describes the available data and accurately predicts the bell-shaped behavior of the effect of pH on the TrxR activity. Most importantly, the model also predicts the inhibitory effects of the reaction products (NADP(+) and Trx(SH)2) on the TrxR activity for which suitable experimental data are not available. The model analyses of the available data on the kinetics of Prx from mammalian sources reveal that Prx operates at very low H2O2 concentrations compared to their human parasite counterparts. Furthermore, the model is able to predict the dynamic overoxidation of Prx at high H2O2 concentrations, consistent with the available data. The integrated Prx-TrxR model simulations well describe the NADPH and H2O2 degradation dynamics and also show that the coupling of TrxR- and Prx-dependent reduction of H2O2 allowed ultrasensitive changes in the Trx concentration in response to changes in the TrxR concentration at high Prx concentrations. Thus, the model of this sort is very useful for integration into computational H2O2 degradation models to identify its role in physiological and pathophysiological functions. Copyright © 2014 Elsevier Inc. All rights reserved.
    No preview · Article · Oct 2014 · Free Radical Biology and Medicine
    • "Nevertheless, important aspects of this system and how its design relates to function remain unclear. Mathematical modeling has consistently proved useful in clarifying the mechanisms of antioxidant defense and redox signaling [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20]. Kinetic models help identify gaps and inconsistencies in the state of the art, assessing alternative mechanistic hypotheses, understanding the interplay among multiple factors, and understanding the relationship between molecular-level design and phenotype. "
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    No preview · Article · Oct 2014
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