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Modelling and analysis of peroxiredoxin kinetics for systems biology applications.

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dc.contributor.advisorPillay, Che Sobashkar.
dc.contributor.authorEagling, Beatrice Demelza.
dc.date.accessioned2016-10-03T09:01:42Z
dc.date.available2016-10-03T09:01:42Z
dc.date.created2015
dc.date.issued2015
dc.descriptionMaster of Science in Genetics.en_US
dc.description.abstractOxidative stress, caused by reactive oxygen species (ROS) such as hydrogen peroxide, can have harmful effects on important cellular components and processes which can lead to cell death. Cells have evolved extensive protein and non-protein antioxidant molecules to deal with hydrogen peroxide but it is now clear that hydrogen peroxide is also important signal molecule. It is not fully understood how cells maintain the balance between hydrogen peroxide detoxification and signal transduction. Peroxiredoxins are a ubiquitous family of antioxidant proteins that are the primary reductants of hydrogen peroxide and appear to be key molecules in mediating this balance. Using catalytic cysteines, peroxiredoxins reduce hydrogen peroxide and other ROS and in turn are reduced by thioredoxin and thioredoxin reductase. This coupled set of reactions collectively constitute the peroxiredoxin system and its precise role in redox signalling could be established using systems biology studies. However, there are some discrepancies on how peroxiredoxins should be described in these studies as three distinct kinetic models have been proposed for peroxiredoxin activity: the ping-pong enzyme, redox couple monomer and redox couple homodimer models. Further, different rate constants for hydrogen peroxide reduction by peroxiredoxins have been reported using steady state and competition assays and it is not clear which of these parameters should be used in computational models. In order to resolve these discrepancies, the three proposed peroxiredoxin kinetic models were simulated with core parameters and showed different responses to parameter changes. Computational modelling with in vitro datasets confirmed this result and also showed that many of the reported peroxiredoxin kinetic parameters have limited predictive value. Thus, the kinetic models for peroxiredoxin activity cannot be used interchangeably and computational models based on the reported peroxiredoxin kinetic parameters for hydrogen peroxide reduction should be viewed with caution. To confirm this result, the cytosolic peroxiredoxin thiolspecific antioxidant 1 (TSA1) from Saccharomyces cerevisiae was cloned, expressed and purified for in vitro analysis of this system. Data fitting of the peroxiredoxin kinetic models determined parameters that were able to predict independent datasets with increasing thioredoxin and peroxiredoxin concentrations using the ping-pong enzyme and redox couple monomer models but the redox couple homodimer model was unable to fit these datasets. A complex flux control pattern was also determined for the fitted models and whole system fitting to in vitro datasets is proposed to be a more accurate method for parameter determination for the peroxiredoxin system kinetic assays.en_US
dc.identifier.urihttp://hdl.handle.net/10413/13414
dc.language.isoen_ZAen_US
dc.subjectPeroxiredoxins.en_US
dc.subjectPeroxidase.en_US
dc.subjectSystems biology.en_US
dc.subjectPeroxidation.en_US
dc.subjectTheses -- Genetics.en_US
dc.titleModelling and analysis of peroxiredoxin kinetics for systems biology applications.en_US
dc.typeThesisen_US

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