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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01w3763909r
Title: Development and Validation of a Kinetic Model for NO● Metabolism in Pseudomonas aeruginosa
Authors: Catovic, Ismael Abd-Allah
Advisors: Brynildsen, Mark P.
Department: Chemical and Biological Engineering
Class Year: 2015
Abstract: As incidences of antibiotic resistance increase day by day, novel strategies are being employed to enhance and upgrade the antibacterial arsenal that is being rendered ineffective over time. While pharmaceutical companies pursue the development of new chemical agents for dealing with the problem, new methods of treatment are being looked at as well. One potential method of treatment could involve Nitric Oxide (NO•) and other reactive nitrogen species (RNS). These RNS target numerous pathways and mechanisms in bacteria, and therefore have the potential to thwart potentially drug resistant bacteria. Prior to pursuing NO• or potential drugs that affect the NO• detoxification network, it is important to first develop a better understanding of how it is metabolized by pathogenic bacteria. To this end, we extended and validated a kinetic model in order to predict how NO• is processed by the pathogen Pseudomonas aeruginosa. In so doing, we determined which components of the NO detoxification network play the biggest role in NO• metabolism and gather fundamental insights regarding the fate of NO• in P. aeruginosa. The backbone of this model was a previously developed kinetic platform for NO• metabolism in Escherichia coli. The transformation of the model into P. aeruginosa represents the first attempt to use the E. coli NO• model as a template for other bacteria and helps to confirm its versatility for widespread investigation of NO• stress in other organisms. The model was modified and updated to reflect the reaction network of P. aeruginosa. Multiple iterations of the model were found to fit wild-type data reasonably well and adequately predicted NO• metabolism in Δfhp and ΔnorC mutant strains. The ability of the model to capture and predict NO• metabolism in P. aeruginosa makes it a useful tool to be improved by further testing under different environmental conditions.
Extent: 44 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01w3763909r
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Chemical and Biological Engineering, 1931-2016

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