Nitric oxide (NO•) is an important antimicrobial produced by the immune system to impair pathogens. Many pathogens, such as Mycobacterium tuberculosis, Salmonella enterica, and pathogenic Escherichia coli, harbor NO• detoxification and repair systems which have been linked to their virulence, and thus present an attractive target toward which novel anti-infective therapies could be designed. Unfortunately, the few compounds that have been found to inhibit major NO• detoxification systems in bacteria suffer from poor intracellular transport or severe toxicity toward humans, warranting a search for additional targets in bacterial NO• defense systems. The broad reactivity of NO• and its reaction products give rise to an expansive, complex reaction network, necessitating the use of a computational approach to effectively study the system in its entirety. To facilitate quantitative exploration of the E. coli NO• stress response, we previously constructed a kinetic model of the intracellular NO• biochemical network, including relevant processes such as enzymatic NO• detoxification, iron-sulfur cluster nitrosylation and repair, DNA deamination and repair, transcriptional regulation, and NO• autoxidation. Model simulations were validated with experimental measurements of [NO•], [NO2−], [NO3−], and [O2] in E. coli cultures, and facilitated the discovery of a strong decrease in utility of the main aerobic NO• detoxification enzyme, NO• dioxygenase (Hmp), with increasing NO• delivery rate. Furthermore, Hmp was predicted to dominate cellular NO• consumption even into the microaerobic regime (35 μM dissolved O2), which was confirmed experimentally.
Given that O2 levels at E. coli infection sites in vivo range from anaerobic to microaerobic, we used the NO• model to investigate the dynamics of the E. coli NO• response network within this medically-important regime. Although the two major NO• detoxification systems in E. coli, Hmp and NorV, are known to dominate NO• consumption under aerobic and anaerobic conditions, respectively, little is known about their participation and dynamics within the microaerobic regime that lies between these two extremes. The model predicted a deficiency in the overall rate of NO• detoxification for O2 environments between anaerobic (0 μM O2) and the upper-end of microaerobic (50 μM O2), which was attributed to an insufficient overlap of Hmp and NorV activity. Experimental measurements of NO• detoxification at these intermediate O2 concentrations (5, 10, and 20 μM O2) confirmed the predicted trend; however, the extent to which NO• detoxification was impaired was underestimated, and oscillations appeared in the [NO•] curves measured at 5 and 10 μM O2. Efforts to reconcile the predictions with experimental measurements yielded a model that could quantitatively capture NO• dynamics throughout the microaerobic regime. An investigation of model parameters contributing to the oscillations predicted a mechanism involving competition between Hmp and respiratory cytochrome oxidases for O2, which was confirmed experimentally through model-guided biochemical and genetic analyses. This demonstrates the utility of a modeling approach to quantitatively study the bacterial NO• defense network even under previously uncharacterized environmental conditions, and how it can facilitate the dissection of complex phenomena to yield novel insight about the quantitative interplay between network components.
See more of this Group/Topical: Topical Conference: Emerging Frontiers in Systems and Synthetic Biology