@article{2983, keywords = {Pseudomonas aeruginosa, Bacterial Proteins, Models, Biological, Nitric Oxide, Oxidoreductases}, author = {Jonathan Robinson and Jacob Jaslove and Allison Murawski and Christopher Fazen and Mark Brynildsen}, title = {An integrated network analysis reveals that nitric oxide reductase prevents metabolic cycling of nitric oxide by Pseudomonas aeruginosa.}, abstract = {
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) reductase (NirS), and NO has been shown to influence their virulence. Interestingly, P. aeruginosa also contain NO dioxygenase (Fhp) and nitrate (NO) reductases, which together with NirS provide the potential for NO to be metabolically cycled (NO{\textrightarrow}NO{\textrightarrow}NO{\textrightarrow}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, NO, and NO 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, which was relieved upon O depletion. As cell growth depleted dissolved O levels, NO was converted to NO at near-stoichiometric levels, whereas NO consumption did not coincide with NO or NO accumulation. Assimilatory NO 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.
}, year = {2017}, journal = {Metab Eng}, volume = {41}, pages = {67-81}, month = {2017 May}, issn = {1096-7184}, doi = {10.1016/j.ymben.2017.03.006}, language = {eng}, }