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Title: Statistical mechanics of protein interaction networks
Author: Graham, I.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2005
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The chemotaxis signalling network of Escherichia coli is a paradigm for signal transduction and sensation in biology. A chemical signal, perceived by receptor proteins, is relayed to the bacterial motor through the network. The network components are localized in a large structure that is anchored to the polar membrane. Most of the components have been characterized, and many network interactions and rate constants have been measured. The network consists of a small number of interacting proteins, yet exhibits many fascinating features. There is a remarkable sensitivity to small changes in the chemical composition of the cell environment. The network adapts to an unchanging environment: Following a change in chemical concentration, the network slowly resets itself to the pre-stimulus state. Chemotaxis is robust – cells can respond to stimuli even when chemotaxis proteins are under-expressed or mutated. This thesis is concerned with the study of these network properties. The first issue addressed is the sensitivity of the chemotaxis response. One way to model sensitivity is to allow the conformation of each chemotaxis receptor to be coupled to the conformations of its neighbours. This simple model exhibits large amplification of changes in the concentration of one chemical species. The general problem of maintaining a sensitive response in a stochastic environment comprised of different chemicals is addressed. The results are applied to the chemotaxis network, and its sensitivity, as chemical species and background concentrations change, is analyzed. Different adaptation mechanisms are introduced, and their ability to maintain a sensitive response to different chemicals and different background concentrations is discussed. The second issue considered is the mechanism by which the chemotaxis network localizes at the cell pole.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available