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Title: Development of a multi-system screen for the high throughput analysis of subcellular protein localisation in Drosophila melanogaster
Author: Hewett, Michael Paul
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2006
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With sequencing projects identifying novel genes at a great rate, innovative techniques are required to confer information onto these genes in a high throughput manner. Several such techniques are at present being applied to this challenge. The eukaryotic cell is highly compartmentalized and structured, because of this the localisation of a protein is fundamentally linked to its function. Knowledge of the subcellular localisation of a protein can yield information on a protein’s function and on possible protein-protein interactions. In this thesis I describe the development of a multi-system screening methodology for the identification of the subcellular localisation of many individual proteins in a high throughput manner in Drosophila melanogaster. Genes are cloned using a recombinase based cloning system into fluorescently tagged expression vectors for use in cell culture. The candidates are then further analysed in whole animals by generating transgenic organisms which express a fluorescently tagged version of the protein and by in situ hybridization. The localisation data is then combined with data from other sources, such as bioinformatics and RNAi screens, to ascribe functional information onto the gene. In this thesis I concentrated my efforts on screening cytoskeletal proteins for a role in cellular polarity. More specifically proteins were screened for a role in cellular polarity within asymmetrically dividing neural precursors of the developing CNS. Several genes were implicated in this process, for example a possible role for pUf68 in regulating cellular proliferation within the CNS is discussed. In addition, information was discovered for several other genes in processes outside of CNS development. The methodology I describe is amenable to automation and as such is capable of being scaled up to a whole genome level.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available