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Title: A high-speed microscopy approach to single-molecule studies of eukaryote signal transduction
Author: Hedlund, Erik G.
ISNI:       0000 0004 6348 1534
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2016
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Metabolic processes underlie all forms of life. An organism’s ability to utilise chemical energy to stay alive and eventually reproduce is a central feature of life, regardless of organism length scale. To achieve this, an organism must be adaptable. That is, it must be able to adjust to varying surrounding environmental conditions. Cells must be able to sense this environment, ‘transduce’ the signal and bring about some cell level response. Cells respond to external stimuli by releasing chemical cascades along often intricate signalling pathways which regulate cellular function. In this thesis, I have developed a novel optical microscopy system coupled to microfluidics and image analysis tools to help address challenging biological questions relating to metabolic sensing in eukaryotic life, using Saccharomyces cerevisiæ, as a model system. A set of biophysical tools was developed to monitor signal transduction events in live yeast cells. A bespoke optical microscope was developed that can monitor single living cells and determine their response to controlled variations in environmental nutrient concentration at high sampling speeds comparable to the molecular diffusion time scale in a cells internal environment. High-speed imaging at up to 200 frames per second and exposure times of 4.7 ms can be achieved. An electronic gain of 300x makes the camera system sensitive enough to track diffusion of single or small clusters of fluorescent protein molecules under physiological conditions. A high intensity laser excitation system was developed to deliver the light required to follow single fluorescent proteins in the living cells. A bespoke microfluidics system was built wherein cells can be exposed to rapidly changing extracellular environments and make it possible to follow individual cell responses to changing glucose conditions. Image analysis tools were adapted and developed to facilitate the automated measurement of protein mobility, stoichiometry and copy number, one cell at a time.
Supervisor: Leake, Mark C. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available