ArticlePLoS computational biology2015
A Kinetic Platform to Determine the Fate of Hydrogen Peroxide in Escherichia coli.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 28 citations in OpenAlex.
- Understanding Iron and Oxidative Stress Response inbioRxiv : the preprint server for biology · 2026Article
- CzcR-dependent reduction of catalase gene expression and induction of catalase activity in Pseudomonas aeruginosa during zinc excess.BMC microbiology · 2024Article
- Article
- Recent trends in the applications of sonochemical reactors as an advanced oxidation process for the remediation of microbial hazards associated with water and wastewater: A critical review.Ultrasonics sonochemistry · 2023Review
- Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli.mSystems · 2023Article
- Analysis of a logical regulatory network reveals how Fe-S cluster biogenesis is controlled in the face of stress.microLife · 2023Article
- Pseudomonas aeruginosa prioritizes detoxification of hydrogen peroxide over nitric oxide.BMC research notes · 2021Article
- Metabolites Potentiate Nitrofurans in Nongrowing Escherichia coli.Antimicrobial agents and chemotherapy · 2021Article
- Synergy Screening Identifies a Compound That Selectively Enhances the Antibacterial Activity of Nitric Oxide.Frontiers in bioengineering and biotechnology · 2020Article
- Transcriptional Regulation Contributes to Prioritized Detoxification of Hydrogen Peroxide over Nitric Oxide.Journal of bacteriology · 2019Article
- Persister formation in Escherichia coli can be inhibited by treatment with nitric oxide.Free radical biology & medicine · 2016Article
- Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network of Escherichia coli.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Construction and Experimental Validation of a Quantitative Kinetic Model of Nitric Oxide Stress in EnterohemorrhagicBioengineering (Basel, Switzerland) · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hydrogen peroxide (H2O2) is used by phagocytic cells of the innate immune response to kill engulfed bacteria. H2O2 diffuses freely into bacteria, where it can wreak havoc on sensitive biomolecules if it is not rapidly detoxified. Accordingly, bacteria have evolved numerous systems to defend themselves against H2O2, and the importance of these systems to pathogenesis has been substantiated by the many bacteria that require them to establish or sustain infections. The kinetic competition for H2O2 within bacteria is complex, which suggests that quantitative models will improve interpretation and prediction of network behavior. To date, such models have been of limited scope, and this inspired us to construct a quantitative, systems-level model of H2O2 detoxification in Escherichia coli that includes detoxification enzymes, H2O2-dependent transcriptional regulation, enzyme degradation, the Fenton reaction and damage caused by •OH, oxidation of biomolecules by H2O2, and repair processes. After using an iterative computational and experimental procedure to train the model, we leveraged it to predict how H2O2 detoxification would change in response to an environmental perturbation that pathogens encounter within host phagosomes, carbon source deprivation, which leads to translational inhibition and limited availability of NADH. We found that the model accurately predicted that NADH depletion would delay clearance at low H2O2 concentrations and that detoxification at higher concentrations would resemble that of carbon-replete conditions. These results suggest that protein synthesis during bolus H2O2 stress does not affect clearance dynamics and that access to catabolites only matters at low H2O2 concentrations. We anticipate that this model will serve as a computational tool for the quantitative exploration and dissection of oxidative stress in bacteria, and that the model and methods used to develop it will provide important templates for the generation of comparable models for other bacterial species.
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