Centralizing neurofibromatosis experimental tool knowledge with the NF Research Tools Database.

Experimental tools and resources, such as animal models, cell lines, antibodies, genetic reagents and biobanks, are key ingredients in biomedical research. Investigators face multiple challenges when trying to understand the availability, applicability and accessibility of these tools. A major challenge is keeping up with current information about the numerous tools available for a particular research problem. A variety of disease-agnostic projects such as the Mouse Genome Informatics database and the Resource Identification Initiative curate a number of types of research tools. Here, we describe our efforts to build upon these resources to develop a disease-specific research tool resource for the neurofibromatosis (NF) research community. This resource, the NF Research Tools Database, is an open-access database that enables the exploration and discovery of information about NF type 1-relevant animal models, cell lines, antibodies, genetic reagents and biobanks. Users can search and explore tools, obtain detailed information about each tool as well as read and contribute their observations about the performance, reliability and characteristics of tools in the database. NF researchers will be able to use the NF Research Tools Database to promote, discover, share, reuse and characterize research tools, with the goal of advancing NF research. Database URL: https://tools.nf.synapse.org/.

Identifying functional metabolic shifts in heart failure with the integration of omics data and a heart-specific, genome-scale model.

In diseased states, the heart can shift to use different carbon substrates, measured through changes in uptake of metabolites by imaging methods or blood metabolomics. However, it is not known whether these measured changes are a result of transcriptional changes or external factors. Here, we explore transcriptional changes in late-stage heart failure using publicly available data integrated with a model of heart metabolism. First, we present a heart-specific genome-scale metabolic network reconstruction (GENRE), iCardio. Next, we demonstrate the utility of iCardio in interpreting heart failure gene expression data by identifying tasks inferred from differential expression (TIDEs), which represent metabolic functions associated with changes in gene expression. We identify decreased gene expression for nitric oxide (NO) and N-acetylneuraminic acid (Neu5Ac) synthesis as common metabolic markers of heart failure. The methods presented here for constructing a tissue-specific model and identifying TIDEs can be extended to multiple tissues and diseases of interest.

Predicting changes in renal metabolism after compound exposure with a genome-scale metabolic model.

The kidneys are metabolically active organs with importance in several physiological tasks such as the secretion of soluble wastes into the urine and synthesizing glucose and oxidizing fatty acids for energy in fasting (non-fed) conditions. Once damaged, the metabolic capability of the kidneys becomes altered. Here, we define metabolic tasks in a computational modeling framework to capture kidney function in an update to the iRno network reconstruction of rat metabolism using literature-based evidence. To demonstrate the utility of iRno for predicting kidney function, we exposed primary rat renal proximal tubule epithelial cells to four compounds with varying levels of nephrotoxicity (acetaminophen, gentamicin, 2,3,7,8-tetrachlorodibenzodioxin, and trichloroethylene) for six and twenty-four hours, and collected transcriptomics and metabolomics data to measure the metabolic effects of compound exposure. For the transcriptomics data, we observed changes in fatty acid metabolism and amino acid metabolism, as well as changes in existing markers of kidney function such as Clu (clusterin). The iRno metabolic network reconstruction was used to predict alterations in these same pathways after integrating transcriptomics data and was able to distinguish between select compound-specific effects on the proximal tubule epithelial cells. Genome-scale metabolic network reconstructions with coupled omics data can be used to predict changes in metabolism as a step towards identifying novel metabolic biomarkers of kidney function and dysfunction.

Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity.

Identifying early indicators of toxicant-induced organ damage is critical to provide effective treatment. To discover such indicators and the underlying mechanisms of toxicity, we used gentamicin as an exemplar kidney toxicant and performed systematic perturbation studies in Sprague Dawley rats. We obtained high-throughput data 7 and 13 h after administration of a single dose of gentamicin (0.5 g/kg) and identified global changes in genes in the liver and kidneys, metabolites in the plasma and urine, and absolute fluxes in central carbon metabolism. We used these measured changes in genes in the liver and kidney as constraints to a rat multitissue genome-scale metabolic network model to investigate the mechanism of gentamicin-induced kidney toxicity and identify metabolites associated with changes in tissue gene expression. Our experimental analysis revealed that gentamicin-induced metabolic perturbations could be detected as early as 7 h postexposure. Our integrated systems-level analyses suggest that changes in kidney gene expression drive most of the significant metabolite alterations in the urine. The analyses thus allowed us to identify several significantly enriched injury-specific pathways in the kidney underlying gentamicin-induced toxicity, as well as metabolites in these pathways that could serve as potential early indicators of kidney damage.

Genome-Scale Characterization of Toxicity-Induced Metabolic Alterations in Primary Hepatocytes.

Context-specific GEnome-scale metabolic Network REconstructions (GENREs) provide a means to understand cellular metabolism at a deeper level of physiological detail. Here, we use transcriptomics data from chemically-exposed rat hepatocytes to constrain a GENRE of rat hepatocyte metabolism and predict biomarkers of liver toxicity using the Transcriptionally Inferred Metabolic Biomarker Response algorithm. We profiled alterations in cellular hepatocyte metabolism following in vitro exposure to four toxicants (acetaminophen, carbon tetrachloride, 2,3,7,8-tetrachlorodibenzodioxin, and trichloroethylene) for six hour. TIMBR predictions were compared with paired fresh and spent media metabolomics data from the same exposure conditions. Agreement between computational model predictions and experimental data led to the identification of specific metabolites and thus metabolic pathways associated with toxicant exposure. Here, we identified changes in the TCA metabolites citrate and alpha-ketoglutarate along with changes in carbohydrate metabolism and interruptions in ATP production and the TCA Cycle. Where predictions and experimental data disagreed, we identified testable hypotheses to reconcile differences between the model predictions and experimental data. The presented pipeline for using paired transcriptomics and metabolomics data provides a framework for interrogating multiple omics datasets to generate mechanistic insight of metabolic changes associated with toxicological responses.

Mechanistic identification of biofluid metabolite changes as markers of acetaminophen-induced liver toxicity in rats.

Acetaminophen (APAP) is the most commonly used analgesic and antipyretic drug in the world. Yet, it poses a major risk of liver injury when taken in excess of the therapeutic dose. Current clinical markers do not detect the early onset of liver injury associated with excess APAP-information that is vital to reverse injury progression through available therapeutic interventions. Hence, several studies have used transcriptomics, proteomics, and metabolomics technologies, both independently and in combination, in an attempt to discover potential early markers of liver injury. However, the casual relationship between these observations and their relation to the APAP mechanism of liver toxicity are not clearly understood. Here, we used Sprague-Dawley rats orally gavaged with a single dose of 2 g/kg of APAP to collect tissue samples from the liver and kidney for transcriptomic analysis and plasma and urine samples for metabolomic analysis. We developed and used a multi-tissue, metabolism-based modeling approach to integrate these data, characterize the effect of excess APAP levels on liver metabolism, and identify a panel of plasma and urine metabolites that are associated with APAP-induced liver toxicity. Our analyses, which indicated that pathways involved in nucleotide-, lipid-, and amino acid-related metabolism in the liver were most strongly affected within 10 h following APAP treatment, identified a list of potential metabolites in these pathways that could serve as plausible markers of APAP-induced liver injury. Our approach identifies toxicant-induced changes in endogenous metabolism, is applicable to other toxicants based on transcriptomic data, and provides a mechanistic framework for interpreting metabolite alterations.

Network Modeling of Liver Metabolism to Predict Plasma Metabolite Changes During Short-Term Fasting in the Laboratory Rat.

The liver-a central metabolic organ that integrates whole-body metabolism to maintain glucose and fatty-acid regulation, and detoxify ammonia-is susceptible to injuries induced by drugs and toxic substances. Although plasma metabolite profiles are increasingly investigated for their potential to detect liver injury earlier than current clinical markers, their utility may be compromised because such profiles are affected by the nutritional state and the physiological state of the animal, and by contributions from extrahepatic sources. To tease apart the contributions of liver and non-liver sources to alterations in plasma metabolite profiles, here we sought to computationally isolate the plasma metabolite changes originating in the liver during short-term fasting. We used a constraint-based metabolic modeling approach to integrate central carbon fluxes measured in our study, and physiological flux boundary conditions gathered from the literature, into a genome-scale model of rat liver metabolism. We then measured plasma metabolite profiles in rats fasted for 5-7 or 10-13 h to test our model predictions. Our computational model accounted for two-thirds of the observed directions of change (an increase or decrease) in plasma metabolites, indicating their origin in the liver. Specifically, our work suggests that changes in plasma lipid metabolites, which are reliably predicted by our liver metabolism model, are key features of short-term fasting. Our approach provides a mechanistic model for identifying plasma metabolite changes originating in the liver.

A simplified metabolic network reconstruction to promote understanding and development of flux balance analysis tools.

GEnome-scale Network REconstructions (GENREs) mathematically describe metabolic reactions of an organism or a specific cell type. GENREs can be used with a number of constraint-based reconstruction and analysis (COBRA) methods to make computational predictions on how a system changes in different environments. We created a simplified GENRE (referred to as iSIM) that captures central energy metabolism with nine metabolic reactions to illustrate the use of and promote the understanding of GENREs and constraint-based methods. We demonstrate the simulation of single and double gene deletions, flux variability analysis (FVA), and test a number of metabolic tasks with the GENRE. Code to perform these analyses is provided in Python, R, and MATLAB. Finally, with iSIM as a guide, we demonstrate how inaccuracies in GENREs can limit their use in the interrogation of energy metabolism.

Metabolic network-based predictions of toxicant-induced metabolite changes in the laboratory rat.

In order to provide timely treatment for organ damage initiated by therapeutic drugs or exposure to environmental toxicants, we first need to identify markers that provide an early diagnosis of potential adverse effects before permanent damage occurs. Specifically, the liver, as a primary organ prone to toxicants-induced injuries, lacks diagnostic markers that are specific and sensitive to the early onset of injury. Here, to identify plasma metabolites as markers of early toxicant-induced injury, we used a constraint-based modeling approach with a genome-scale network reconstruction of rat liver metabolism to incorporate perturbations of gene expression induced by acetaminophen, a known hepatotoxicant. A comparison of the model results against the global metabolic profiling data revealed that our approach satisfactorily predicted altered plasma metabolite levels as early as 5 h after exposure to 2 g/kg of acetaminophen, and that 10 h after treatment the predictions significantly improved when we integrated measured central carbon fluxes. Our approach is solely driven by gene expression and physiological boundary conditions, and does not rely on any toxicant-specific model component. As such, it provides a mechanistic model that serves as a first step in identifying a list of putative plasma metabolites that could change due to toxicant-induced perturbations.

Systems-level computational modeling demonstrates fuel selection switching in high capacity running and low capacity running rats.

High capacity and low capacity running rats, HCR and LCR respectively, have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise. HCR rats can maintain fatty acid (FA) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization. We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density. To test this hypothesis and to investigate mechanisms of fuel selection, we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats. Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis, the TCA cycle, and mitochondrial FA transport and oxidation. The model can effectively match the observed relative rates of oxidation of glucose versus FA, as a function of ATP demand. In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats, it was determined that the whole-body metabolic phenotype of LCR, compared to the HCR, could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity. Finally, we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes.

Estrogen maintains mitochondrial content and function in the right ventricle of rats with pulmonary hypertension.

The typical cause of death in pulmonary hypertension (PH) is right ventricular (RV) failure, with females showing better survival rates than males. Recently, metabolic shift and mitochondrial dysfunction have been demonstrated in RV failure secondary to PH In light of evidence showing that estrogen protects mitochondrial function and biogenesis in noncardiovascular systems, we hypothesized that the mechanism by which estrogen preserves RV function is via protection of mitochondrial content and oxidative capacity in PH We used a well-established model of PH (Sugen+Hypoxia) in ovariectomized female rats with/without estrogen treatment. RV functional measures were derived from pressure-volume relationships measured via RV catheterization in live rats. Citrate synthase activity, a marker of mitochondrial density, was measured in both RV and LV tissues. Respiratory capacity of mitochondria isolated from RV was measured using oxygraphy. We found that RV ventricular-vascular coupling efficiency decreased in the placebo-treated SuHx rats (0.78 ± 0.10 vs. 1.50 ± 0.13 in control, P < 0.05), whereas estrogen restored it. Mitochondrial density decreased in placebo-treated SuHx rats (0.12 ± 0.01 vs. 0.15 ± 0.01 U citrate synthase/mg in control, P < 0.05), and estrogen attenuated the decrease. Mitochondrial quality and oxidative capacity tended to be lower in placebo-treated SuHx rats only. The changes in mitochondrial biogenesis and function paralleled the expression levels of PGC-1α in RV Our results suggest that estrogen protects RV function by preserving mitochondrial content and oxidative capacity. This provides a mechanism by which estrogen provides protection in female PH patients and paves the way to develop estrogen and its targets as a novel RV-specific therapy for PH.

Improving the physiological realism of experimental models.

The Virtual Physiological Human (VPH) project aims to develop integrative, explanatory and predictive computational models (C-Models) as numerical investigational tools to study disease, identify and design effective therapies and provide an in silico platform for drug screening. Ultimately, these models rely on the analysis and integration of experimental data. As such, the success of VPH depends on the availability of physiologically realistic experimental models (E-Models) of human organ function that can be parametrized to test the numerical models. Here, the current state of suitable E-models, ranging from in vitro non-human cell organelles to in vivo human organ systems, is discussed. Specifically, challenges and recent progress in improving the physiological realism of E-models that may benefit the VPH project are highlighted and discussed using examples from the field of research on cardiovascular disease, musculoskeletal disorders, diabetes and Parkinson's disease.

Mitochondrial structure and function are not different between nonfailing donor and end-stage failing human hearts.

During human heart failure, the balance of cardiac energy use switches from predominantly fatty acids (FAs) to glucose. We hypothesized that this substrate shift was the result of mitochondrial degeneration; therefore, we examined mitochondrial oxidation and ultrastructure in the failing human heart by using respirometry, transmission electron microscopy, and gene expression studies of demographically matched donor and failing human heart left ventricular (LV) tissues. Surprisingly, respiratory capacities for failing LV isolated mitochondria (n = 9) were not significantly diminished compared with donor LV isolated mitochondria (n = 7) for glycolysis (pyruvate + malate)- or FA (palmitoylcarnitine)-derived substrates, and mitochondrial densities, assessed via citrate synthase activity, were consistent between groups. Transmission electron microscopy images also showed no ultrastructural remodeling for failing vs. donor mitochondria; however, the fraction of lipid droplets (LDs) in direct contact with a mitochondrion was reduced, and the average distance between an LD and its nearest neighboring mitochondrion was increased. Analysis of FA processing gene expression between donor and failing LVs revealed 0.64-fold reduced transcript levels for the mitochondrial-LD tether, perilipin 5, in the failing myocardium (P = 0.003). Thus, reduced FA use in heart failure may result from improper delivery, potentially via decreased perilipin 5 expression and mitochondrial-LD tethering, and not from intrinsic mitochondrial dysfunction.-Holzem, K. M., Vinnakota, K. C., Ravikumar, V. K., Madden, E. J., Ewald, G. A., Dikranian, K., Beard, D. A., Efimov, I. R. Mitochondrial structure and function are not different between nonfailing donor and end-stage failing human hearts.

Influence of metabolic dysfunction on cardiac mechanics in decompensated hypertrophy and heart failure.

Alterations in energetic state of the myocardium are associated with decompensated heart failure in humans and in animal models. However, the functional consequences of the observed changes in energetic state on mechanical function are not known. The primary aim of the study was to quantify mechanical/energetic coupling in the heart and to determine if energetic dysfunction can contribute to mechanical failure. A secondary aim was to apply a quantitative systems pharmacology analysis to investigate the effects of drugs that target cross-bridge cycling kinetics in heart failure-associated energetic dysfunction. Herein, a model of metabolite- and calcium-dependent myocardial mechanics was developed from calcium concentration and tension time courses in rat cardiac muscle obtained at different lengths and stimulation frequencies. The muscle dynamics model accounting for the effect of metabolites was integrated into a model of the cardiac ventricles to simulate pressure-volume dynamics in the heart. This cardiac model was integrated into a simple model of the circulation to investigate the effects of metabolic state on whole-body function. Simulations predict that reductions in metabolite pools observed in canine models of heart failure can cause systolic dysfunction, blood volume expansion, venous congestion, and ventricular dilation. Simulations also predict that myosin-activating drugs may partially counteract the effects of energetic state on cross-bridge mechanics in heart failure while increasing myocardial oxygen consumption. Our model analysis demonstrates how metabolic changes observed in heart failure are alone sufficient to cause systolic dysfunction and whole-body heart failure symptoms.

Open-Loop Control of Oxidative Phosphorylation in Skeletal and Cardiac Muscle Mitochondria by Ca(2.).

In cardiac muscle, mitochondrial ATP synthesis is driven by demand for ATP through feedback from the products of ATP hydrolysis. However, in skeletal muscle at higher workloads there is an apparent contribution of open-loop stimulation of ATP synthesis. Open-loop control is defined as modulation of flux through a biochemical pathway by a moiety, which is not a reactant or a product of the biochemical reactions in the pathway. The role of calcium, which is known to stimulate the activity of mitochondrial dehydrogenases, as an open-loop controller, was investigated in isolated cardiac and skeletal muscle mitochondria. The kinetics of NADH synthesis and respiration, feedback from ATP hydrolysis products, and stimulation by calcium were characterized in isolated mitochondria to test the hypothesis that calcium has a stimulatory role in skeletal muscle mitochondria not apparent in cardiac mitochondria. A range of respiratory states were obtained in cardiac and skeletal muscle mitochondria utilizing physiologically relevant concentrations of pyruvate and malate, and flux of respiration, NAD(P)H fluorescence, and rhodamine 123 fluorescence were measured over a range of extra mitochondrial calcium concentrations. We found that under these conditions calcium stimulates NADH synthesis in skeletal muscle mitochondria but not in cardiac mitochondria.

Catalytic Coupling of Oxidative Phosphorylation, ATP Demand, and Reactive Oxygen Species Generation.

Competing models of mitochondrial energy metabolism in the heart are highly disputed. In addition, the mechanisms of reactive oxygen species (ROS) production and scavenging are not well understood. To deepen our understanding of these processes, a computer model was developed to integrate the biophysical processes of oxidative phosphorylation and ROS generation. The model was calibrated with experimental data obtained from isolated rat heart mitochondria subjected to physiological conditions and workloads. Model simulations show that changes in the quinone pool redox state are responsible for the apparent inorganic phosphate activation of complex III. Model simulations predict that complex III is responsible for more ROS production during physiological working conditions relative to complex I. However, this relationship is reversed under pathological conditions. Finally, model analysis reveals how a highly reduced quinone pool caused by elevated levels of succinate is likely responsible for the burst of ROS seen during reperfusion after ischemia.

Feedback Regulation and Time Hierarchy of Oxidative Phosphorylation in Cardiac Mitochondria.

To determine how oxidative ATP synthesis is regulated in the heart, the responses of cardiac mitochondria oxidizing pyruvate to alterations in [ATP], [ADP], and inorganic phosphate ([Pi]) were characterized over a range of steady-state levels of extramitochondrial [ATP], [ADP], and [Pi]. Evolution of the steady states of the measured variables with the flux of respiration shows that: (1) a higher phosphorylation potential is achieved by mitochondria at higher [Pi] for a given flux of respiration; (2) the time hierarchy of oxidative phosphorylation is given by phosphorylation subsystem, electron transport chain, and substrate dehydrogenation subsystems listed in increasing order of their response times; (3) the matrix ATP hydrolysis mass action ratio [ADP] × [Pi]/[ATP] provides feedback to the substrate dehydrogenation flux over the entire range of respiratory flux examined in this study; and finally, (4) contrary to previous models of regulation of oxidative phosphorylation, [Pi] does not modulate the activity of complex III.

Determination of the catalytic mechanism for mitochondrial malate dehydrogenase.

The kinetics of malate dehydrogenase (MDH) catalyzed oxidation/reduction of L-malate/oxaloacetate is pH-dependent due to the proton generated/taken up during the reaction. Previous kinetic studies on the mitochondrial MDH did not yield a consensus kinetic model that explains both substrate and pH dependency of the initial velocity. In this study, we propose, to our knowledge, a new kinetic mechanism to explain kinetic data acquired over a range of pH and substrate concentrations. Progress curves in the forward and reverse reaction directions were obtained under a variety of reactant concentrations to identify associated kinetic parameters. Experiments were conducted at physiologically relevant ionic strength of 0.17 M, pH ranging between 6.5 and 9.0, and at 25 °C. The developed model was built on the prior observation of proton uptake upon binding of NADH to MDH, and that the MDH-catalyzed oxidation of NADH may follow an ordered bi-bi mechanism with NADH/NAD binding to the enzyme first, followed by the binding of oxaloacetate/L-malate. This basic mechanism was expanded to account for additional ionic states to explain the pH dependency of the kinetic behavior, resulting in what we believe to be the first kinetic model explaining both substrate and pH dependency of the reaction velocity.

Characterization of the kinetics of cardiac cytosolic malate dehydrogenase and comparative analysis of cytosolic and mitochondrial isoforms.

Because the mitochondrial inner membrane is impermeable to pyridine nucleotides, transport of reducing equivalents between the mitochondrial matrix and the cytoplasm relies on shuttle mechanisms, including the malate-aspartate shuttle and the glycerol-3-phosphate shuttle. These shuttles are needed for reducing equivalents generated by metabolic reactions in the cytosol to be oxidized via aerobic metabolism. Two isoenzymes of malate dehydrogenase (MDH) operate as components of the malate-aspartate shuttle, in which a reducing equivalent is transported via malate, which when oxidized to oxaloacetate, transfers an electron pair to reduce NAD to NADH. Several competing mechanisms have been proposed for the MDH-catalyzed reaction. This study aims to identify the pH-dependent kinetic mechanism for cytoplasmic MDH (cMDH) catalyzed oxidation/reduction of MAL/OAA. Experiments were conducted assaying the forward and reverse directions with products initially present, varying pH between 6.5 and 9.0. By fitting time-course data to various mechanisms, it is determined that an ordered bi-bi mechanism with coenzyme binding first followed by the binding of substrate is able to explain the kinetic data. The proposed mechanism is similar to, but not identical to, the mechanism recently determined for the mitochondrial isoform, mMDH. cMDH and mMDH mechanisms are also shown to both be reduced versions of a common, more complex mechanism that can explain the kinetic data for both isoforms. Comparing the simulated activity (ratio of initial velocity to the enzyme concentration) under physiological conditions, the mitochondrial MDH (mMDH) activity is predicted to be higher than cMDH activity under mitochondrial matrix conditions while the cMDH activity is higher than mMDH activity under cytoplasmic conditions, suggesting that the functions of the isoforms are kinetically tuned to their individual physiological roles.

Analysis of the kinetics and bistability of ubiquinol:cytochrome c oxidoreductase.

Ubiquinol:cytochrome c oxidoreductase, bc1 complex, is the enzyme in the respiratory chain of mitochondria responsible for the transfer reducing potential from ubiquinol to cytochrome c coupled to the movement of charge against the electrostatic potential across the mitochondrial inner membrane. The complex is also implicated in the generation of reactive oxygen species under certain conditions and is thus a contributor to cellular oxidative stress. Here, a biophysically detailed, thermodynamically consistent model of the bc1 complex for mammalian mitochondria is developed. The model incorporates the major redox centers near the Qo- and Qi-site of the enzyme, includes the pH-dependent redox reactions, accounts for the effect of the proton-motive force of the reaction rate, and simulates superoxide production at the Qo-site. The model consists of six distinct states characterized by the mobile electron distribution in the enzyme. Within each state, substates that correspond to various electron localizations exist in a rapid equilibrium distribution. The steady-state equation for the six-state system is parameterized using five independent data sets and validated in comparison to additional experimental data. Model analysis suggests that the pH-dependence on turnover is primarily due to the pKa values of cytochrome bH and Rieske iron sulfur protein. A previously proposed kinetic scheme at the Qi-site where ubiquinone binds to only the reduced enzyme and ubiquinol binds to only the oxidized enzyme is shown to be thermodynamically infeasible. Moreover, the model is able to reproduce the bistability phenomenon where at a given overall flux through the enzyme, different rates of superoxide production are attained when the enzyme is differentially reduced.