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Nitric oxide (NO) is a chemical weapon within the arsenal of immune cells, but is also generated endogenously by different bacteria. Pseudomonas aeruginosa are pathogens that contain an NO-generating nitrite (NO 2 - ) reductase (NirS), and NO has been shown to influence their virulence. Interestingly, P. aeruginosa also contain NO dioxygenase (Fhp) and nitrate (NO 3 - ) reductases, which together with NirS provide the potential for NO to be metabolically cycled (NO→NO 3 - →NO 2 - →NO). Deeper understanding of NO metabolism in P. aeruginosa will increase knowledge of its pathogenesis, and computational models have proven to be useful tools for the quantitative dissection of NO biochemical networks. Here we developed such a model for P. aeruginosa and confirmed its predictive accuracy with measurements of NO, O 2 , NO 2 - , and NO 3 - in mutant cultures devoid of Fhp or NorCB (NO reductase) activity. Using the model, we assessed whether NO was metabolically cycled in aerobic P. aeruginosa cultures. Calculated fluxes indicated a bottleneck at NO 3 - , which was relieved upon O 2 depletion. As cell growth depleted dissolved O 2 levels, NO 3 - was converted to NO 2 - at near-stoichiometric levels, whereas NO 2 - consumption did not coincide with NO or NO 3 - accumulation. Assimilatory NO 2 - reductase (NirBD) or NorCB activity could have prevented NO cycling, and experiments with ΔnirB, ΔnirS, and ΔnorC showed that NorCB was responsible for loss of flux from the cycle. Collectively, this work provides a computational tool to analyze NO metabolism in P. aeruginosa, and establishes that P. aeruginosa use NorCB to prevent metabolic cycling of NO., (Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

Nitric oxide (NO) detoxification enzymes, such as NO dioxygenase (NOD) and NO reductase (NOR), are important to the virulence of numerous bacteria. Pathogens use these defense systems to ward off immune-generated NO, and they do so in environments that contain additional stressors, such as reactive oxygen species, nutrient deprivation, and acid stress. NOD and NOR both use reducing equivalents to metabolically deactivate NO, which suggests that nutrient deprivation could negatively impact their functionality. To explore the relationship between NO detoxification and nutrient deprivation, we examined the ability of Escherichia coli to detoxify NO under different levels of carbon source availability in aerobic cultures. We observed failure of NO detoxification under both carbon source limitation and starvation, and those failures could have arisen from inabilities to synthesize Hmp (NOD of E. coli) and/or supply it with sufficient NADH (preferred electron donor). We found that when limited quantities of carbon source were provided, NO detoxification failed due to insufficient NADH, whereas starvation prevented Hmp synthesis, which enabled cells to maintain their NADH levels. This maintenance of NADH levels under starvation was confirmed to be dependent on the absence of Hmp. Intriguingly, these data show that under NO stress, carbon-starved E. coli are better positioned with regard to reducing power to cope with other stresses than cells that had consumed an exhaustible amount of carbon., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The virulence of many pathogens depends upon their ability to cope with immune-generated nitric oxide (NO·). In Escherichia coli, the major NO· detoxification systems are Hmp, an NO· dioxygenase (NOD), and NorV, an NO· reductase (NOR). It is well established that Hmp is the dominant system under aerobic conditions, whereas NorV dominates anaerobic conditions; however, the quantitative contributions of these systems under the physiologically relevant microaerobic regime remain ill defined. Here, we investigated NO· detoxification in environments ranging from 0 to 50 μM O2, and discovered a regime in which E. coli NO· defenses were severely compromised, as well as conditions that exhibited oscillations in the concentration of NO·. Using an integrated computational and experimental approach, E. coli NO· detoxification was found to be extremely impaired at low O2 due to a combination of its inhibitory effects on NorV, Hmp, and translational activities, whereas oscillations were found to result from a kinetic competition for O2 between Hmp and respiratory cytochromes. Because at least 777 different bacterial species contain the genetic requirements of this stress response oscillator, we hypothesize that such oscillatory behavior could be a widespread phenomenon. In support of this hypothesis,Pseudomonas aeruginosa, whose respiratory and NO· response networks differ considerably from those of E. coli, was found to exhibit analogous oscillations in low O2 environments. This work provides insight into how bacterial NO· defenses function under the low O2 conditions that are likely to be encountered within host environments.

The importance of NO(∙) to immunity is highlighted by the diversity of pathogens that require NO(∙)-defensive systems to establish infections. Proteases have been identified to aid pathogens in surviving macrophage attack, inspiring us to investigate their role during NO(∙) stress in Escherichia coli. We discovered that the elimination of ClpP largely impaired NO(∙) detoxification by E. coli. Using a quantitative model of NO(∙) stress, we employed an ensemble-guided approach to identify the underlying mechanism. Iterations of in silico analyses and corresponding experiments identified the defect to result from deficient transcript levels of hmp, which encodes NO(∙) dioxygenase. Interestingly, the defect was not confined to hmp, as ΔclpP imparted widespread perturbations to the expression of NO(∙)-responsive genes. This work identified a target for anti-infective therapies based on disabling NO(∙) defenses, and demonstrated the utility of model-based approaches for exploring the complex, systems-level stress exerted by NO(∙)., (Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

Nitric oxide (NO•) is generated by the innate immune response to neutralize pathogens. NO• and its autoxidation products have an extensive biochemical reaction network that includes reactions with iron-sulfur clusters, DNA, and thiols. The fate of NO• inside a pathogen depends on a kinetic competition among its many targets, and is of critical importance to infection outcomes. Due to the complexity of the NO• biochemical network, where many intermediates are short-lived and at extremely low concentrations, several species can be measured, but stable products are non-unique, and damaged biomolecules are continually repaired or regenerated, kinetic models are required to understand and predict the outcome of NO• treatment. Here, we have constructed a comprehensive kinetic model that encompasses the broad reactivity of NO• in Escherichia coli. The incorporation of spontaneous and enzymatic reactions, as well as damage and repair of biomolecules, allowed for a detailed analysis of how NO• distributes in E. coli cultures. The model was informed with experimental measurements of NO• dynamics, and used to identify control parameters of the NO• distribution. Simulations predicted that NO• dioxygenase (Hmp) functions as a dominant NO• consumption pathway at O2 concentrations as low as 35 µM (microaerobic), and interestingly, loses utility as the NO• delivery rate increases. We confirmed these predictions experimentally by measuring NO• dynamics in wild-type and mutant cultures at different NO• delivery rates and O2 concentrations. These data suggest that the kinetics of NO• metabolism must be considered when assessing the importance of cellular components to NO• tolerance, and that models such as the one described here are necessary to rigorously investigate NO• stress in microbes. This model provides a platform to identify novel strategies to potentiate the effects of NO•, and will serve as a template from which analogous models can be generated for other organisms.

Many pathogens depend on nitric oxide (NO) detoxification and repair to establish an infection, and inhibitors of these systems are under investigation as next-generation antibiotics. Because of the broad reactivity of NO and its derivatives with biomolecules, a deep understanding of how pathogens sense and respond to NO, as an integrated system, has been elusive. Quantitative kinetic modeling has been proposed as a method to enhance analysis and understanding of NO stress at the systems-level. Here we review the motivation for, current state of, and future prospects of quantitative modeling of NO stress in bacteria, and suggest that such mathematical approaches would prove equally useful in the study of other broadly reactive antimicrobials, such as hydrogen peroxide (H2O2). [ABSTRACT FROM AUTHOR]