The advent and establishment of systems biology has cemented the idea that real understanding of biological systems requires quantitative models, that can be integrated to provide a complete description of the cell and its complexities. At the same time, synthetic biology attempts to leverage such quantitative models to efficiently engineer novel, predictable behaviour in biological systems. Together, these advances indicate that the future understanding and application of biology will require the ability to create, parameterise and discriminate between quantitative models of cellular processes in a rigorous and statistically sound manner. In this thesis we take the regulation of GAL1 expression in Saccharomyces cerevisiae as a test case and look at all aspects of this process: from reporter selection to data acquisition and statistical analysis. In chapter B we will discuss optimal fluorescent reporter selection and construction for investigating transcriptional dynamics, as well as procedures for quantifying and correcting the various sources of error in our microscope system. In chapter 3 we will describe software developed to analyse fluorescent microscopy images and convert them to gene expression data. A number of iterations of the software are tested against manually curated data sets, and the measurement error produced by its imperfections is quantified and discussed. In chapter 4 a method, based on fluctuations in photobleaching, is developed for quantifying both measurement error and the relationship between protein concentration and measured fluorescence. The method is refined and its efficacy discussed. In the last section I make a preliminary application of these methods to investigating the regulatory effect of the GAL10-lncRNA. Interesting phenomena are observed and further investigated using two new strains: genetic variants expressing a fluorescent reporter from the GAL1 promoter, one harbouring a wild type GAL1 promoter and one in which the binding site for the Gal10 noncoding RNA has been removed. The methods developed throughout the thesis are applied and the data analysed. A heterogeneous response, distinguishable between the two strains, is observed and related to cell-to-cell variations in growth rate.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:705333 |
| Date | January 2016 |
| Creators | Bakker, Elco |
| Contributors | Swain, Peter |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/20403 |
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