Model-driven identification of dosing regimens that maximize the antimicrobial activity of nitric oxide

Robinson, Jonathan L.; Miller, Richard V; Brynildsen, Mark P.

doi:10.1016/j.meteno.2014.08.001

Cited by 18 publications

(20 citation statements)

References 37 publications

(63 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The E. coli NO · model was constructed (37) and further developed (36,38) in previous studies. Briefly, the model is comprised of a system of ordinary differential equations (ODEs) describing the change in concentration of biochemical species (C) as a function of intensive reaction rates (r I ) and reaction stoichiometries (Ŝ):…”

Section: δCytmentioning

confidence: 99%

Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network ofEscherichia coli

Robinson

Brynildsen

2016

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

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 O 2 , 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 O 2 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 O 2 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 O 2 environments. This work provides insight into how bacterial NO · defenses function under the low O 2 conditions that are likely to be encountered within host environments.nitrosative stress | E. coli | microaerobic | Pseudomonas aeruginosa | kinetic modeling N itric oxide (NO · ) plays a critical role in mammalian innate immunity as a potent antimicrobial (1-3), where its broad reactivity contributes to a diverse repertoire of cytotoxic effects including respiratory inhibition, thiol nitrosation, iron-sulfur cluster ([Fe-S]) destruction, DNA deamination, and tyrosine nitration/ nitrosylation (4, 5). To cope with this stress, many pathogens harbor defenses to detoxify NO · and its reaction products, and repair NO · -mediated damage to biomolecules (6, 7). Disruption of these defenses has been shown to attenuate virulence in many pathogenic species, such as Neisseria meningitides, Pseudomonas aeruginosa, Yersinia pestis, Mycobacterium tuberculosis, Vibrio cholerae, uropathogenic and enterohemorrhagic Escherichia coli (UPEC and EHEC, respectively), Staphylococcus aureus, and Salmonella enterica serovar Typhimurium (4, 6), which underscores the importance of NO · to immune function and highlights microbial NO · defense networks as a promising source of targets for the development of next-generation antiinfectives (8). This potential has inspired many investigations of bacterial NO · stress, from which major defense systems, such as NO · dioxygenase (NOD) (9, 10) and NO · reductase (NOR) (11, 12), have been identified. NODs are widely distributed among dif...

show abstract

Section: δCytmentioning

confidence: 99%

Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network ofEscherichia coli

Robinson

Brynildsen

2016

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

show abstract

“…To allow continuous [NO•] measurements in a growing culture, all assays (unless stated otherwise) were conducted in a stirred batch bioreactor, identical to our previous studies [29,30].…”

Section: Bioreactormentioning

confidence: 99%

“…The kinetic model of the E. coli NO• biochemical network used here was developed and described in previous studies [29,30]. Briefly, the model is comprised of a system of differential mass balances describing the change in species concentrations (X) subject to a network of chemical reactions (organized into a stoichiometry matrix, S), whose rates (r) are a function of kinetic parameters (p) and concentrations (x) of individual species.…”

Section: Kinetic Model Descriptionmentioning

confidence: 99%

An ensemble-guided approach identifies ClpP as a major regulator of transcript levels in nitric oxide-stressed Escherichia coli

Robinson

Brynildsen

2015

Metabolic Engineering

Self Cite

View full text Add to dashboard Cite

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(∙).

show abstract

“…The bioreactor consisted of 10 ml medium in a 50-ml Falcon tube with a sterile magnetic stirring bar (0.5 in.) and immersed in a 37°C stirred water bath (ϳ400-rpm stirring), and it was used in previous studies (29)(30)(31)(32)(33).…”

Section: Chemicals the No· Donor Dpta Nonoate {(Z)-1-[n-(3-aminopropmentioning

confidence: 99%

“…The H 2 O 2 and NO· biochemical reaction networks of E. coli are complex, and dynamic models have proven useful in quantifying the distributions of these toxic metabolites and exploring system behaviors (29)(30)(31)(32)(33)(34)(35). These previously developed models included detoxification by antioxidants and enzymes, transcriptional regulation and inactivation of enzymes, damage and repair of DNA and Fe-S clusters, and destruction of amino acids by the hydroxyl radical, ·OH, and they were compartmentalized (intracellular, media, and gaseous) to account for the cell-dependent and cell-independent reactions.…”

mentioning

confidence: 99%

Transcriptional Regulation Contributes to Prioritized Detoxification of Hydrogen Peroxide over Nitric Oxide

2019

Self Cite

View full text Add to dashboard Cite

Hydrogen peroxide (H 2 O 2 ) and nitric oxide (NO·) are toxic metabolites that immune cells use to attack pathogens. These antimicrobials can be present at the same time in phagosomes, and it remains unclear how bacteria deal with these insults when simultaneously present. Here, using Escherichia coli, we observed that simultaneous exposure to H 2 O 2 and NO· leads to prioritized detoxification, where enzymatic removal of NO· is impeded until H 2 O 2 has been eliminated. This phenomenon is reminiscent of carbon catabolite repression (CCR), where preferred carbon sources are catabolized prior to less desirable substrates; however, H 2 O 2 and NO· are toxic, growth-inhibitory compounds rather than growth-promoting nutrients. To understand how NO· detoxification is delayed by H 2 O 2 whereas H 2 O 2 detoxification proceeds unimpeded, we confirmed that the effect depended on Hmp, which is the main NO· detoxification enzyme, and used an approach that integrated computational modeling and experimentation to delineate and test potential mechanisms. Plausible interactions included H 2 O 2 -dependent inhibition of hmp transcription and translation, direct inhibition of Hmp catalysis, and competition for reducing equivalents between Hmp and H 2 O 2 -degrading enzymes. Experiments illustrated that Hmp catalysis and NAD(P)H supply were not impaired by H 2 O 2 , whereas hmp transcription and translation were diminished. A dependence of this phenomenon on transcriptional regulation parallels CCR, and we found it to involve the transcriptional repressor NsrR. Collectively, these data suggest that bacterial regulation of growth inhibitor detoxification has similarities to the regulation of growth substrate consumption, which could have ramifications for infectious disease, bioremediation, and biocatalysis from inhibitor-containing feedstocks. IMPORTANCE Bacteria can be exposed to H 2 O 2 and NO· concurrently within phagosomes. In such multistress situations, bacteria could have evolved to simultaneously degrade both toxic metabolites or preferentially detoxify one over the other. Here, we found that simultaneous exposure to H 2 O 2 and NO· leads to prioritized detoxification, where detoxification of NO· is hampered until H 2 O 2 has been eliminated. This phenomenon resembles CCR, where bacteria consume one substrate over others in carbon source mixtures. Further experimentation revealed a central role for transcriptional regulation in the prioritization of H 2 O 2 over NO·, which is also important to CCR. This study suggests that regulatory scenarios observed in bacterial consumption of growth-promoting compound mixtures can be conserved in bacterial detoxification of toxic metabolite mixtures.

show abstract

Model-driven identification of dosing regimens that maximize the antimicrobial activity of nitric oxide

Cited by 18 publications

References 37 publications

Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network ofEscherichia coli

Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network ofEscherichia coli

An ensemble-guided approach identifies ClpP as a major regulator of transcript levels in nitric oxide-stressed Escherichia coli

Transcriptional Regulation Contributes to Prioritized Detoxification of Hydrogen Peroxide over Nitric Oxide

Contact Info

Product

Resources

About