Modelling and Analysis of Osmotic Stress in Escherichia Coli
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Microorganisms are known to be affected by stresses such as osmotic stressby reducing their growth rate. Understanding the mechanisms behindthis are important, as it can aid in the development of new methods of con-serving food a common source of pathogen infection for humans. One of the most common pathogenic infections for humans is Escherichiacoli (E. coli). In 2014, the Center for Disease Control and Prevention inthe USA reported two outbreaks of pathogenic E. coli, both transmittedthrough food. In developing countries, acute diarrhea is the second mostcommon cause of infant death, and infection by E. coli is one of the mostcommon sources. In order to effectively combat E. coli infection in hu-mans, it is important that accurate methods for predicting the organism sresponse to external stresses are developed.The goal of this master thesis was to investigate the metabolism of E. coliunder osmotic stress. In order to accomplish this, the project was set upas a collaboration with the Institute for Food Research (IFR) in Norwich,United Kingdom. Through collaboration with the Computational Micro-biology Research Group at IFR, gene expression data for E. coli growingunder different states of osmotic stress was collected and analyzed usingmetabolic modelling.The complex nature of osmotic stress required the development of a newmethod, dubbed Metabolic Flux Distribution by Translational Efficiencyand Enzyme Kinetics (MUTE). MUTE is able to predict changes in metabolicflux based on gene expression data, translation efficiencies and enzyme ki-netics. MUTE was shown to increase the sensitivity to expression datacompared to other methods such as Metabolic Adjustment by DifferentialExpression (MADE), resulting in new predictions on metabolic changesduring osmotic stress in E. coli. Another novelty of MUTE is its level ofdetail, where enzyme concentration predictions are levels reported by em-pirical data.