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Temporal encoding and homeostatic control in the IKK- kappaNF-kappaB signaling system


The transcription factor NF-kappaB is part of a signaling system that interprets a variety of physiological stimuli. NF-kappaB regulates numerous genes that play important roles in inter- and intracellular signaling, cellular stress responses, cell growth, survival, and apoptosis. This dissertation is an examination of the hypothesis that dynamic control of NF-kappaB is key to understanding the processing that allows these specific responses. This study investigates the existence, mechanisms, and implications of temporal coding within the IKK-IkappaB-NF- kappaB system. The starting point of this work is a previously published, biochemically detailed ordinary differential equation model of NF-kappaB signaling whose predictions for dynamic responses to a single stimuli (TNF) corresponded with experiments. I extend this model in a number of ways. First, I refine its parameters and reaction list. Doing so allows me to improve the model's equilibrium predictions for resting cells. It also leads me to highlight the importance of a second degradation pathway (IKK independent free IkappaB degradation) for steady-state regulation, in addition to IKK induced degradation of complexed IkappaB. Second, I apply three additional computational techniques to investigate its signal processing characteristics. Clustering allows me to gain insight into the temporal encoding of IKK, such as the lesser importance of early IKK plateaus and greater impact (and fine-grained regulation) of later IKK plateaus. Information theory guides the design and testing of a mutant cell which loses the ability to distinguish stimuli that are distinguished by wild type cells. Principal component analysis allows me to identify common mechanisms whose alterations have stimulus specific effects, altering the responses to some stimuli much more strongly than others. Third, I test and validate its utility against a much wider range of experiments. Using the experimental work of my collaborators, I am able to link simulations to experiments for multiple stimuli, with genetic and pharmacological interventions, and with multiple doses and timings. In conclusion, this dissertation breaks new ground in using simulations and experiments to understand temporal control in a cell signaling system of great scientific interest, and develops techniques which have relevance for other efforts to understand cell signaling

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