Subcellular Localisation of Type II Membrane Proteins

Rajith Aturaliya (2008). Subcellular Localisation of Type II Membrane Proteins PhD Thesis, Institute for Molecular Bioscience, The University of Queensland.

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Author Rajith Aturaliya
Thesis Title Subcellular Localisation of Type II Membrane Proteins
School, Centre or Institute Institute for Molecular Bioscience
Institution The University of Queensland
Publication date 2008-07-01
Thesis type PhD Thesis
Supervisor Grimmond, Sean M.
Teasdale, Rohan D.
Subjects 270000 Biological Sciences
Formatted abstract
Recent advancements in technology have resulted in the birth of the genomic era. In the past 10 years, numerous sequencing projects have unveiled the coding potential of entire genomes. These sequencing projects have highlighted a number of interesting features, including a large proportion of proteins with uncharacterised function. The task now at hand is to ascribe biological functions to these proteins to help us to understand cellular processes and disease mechanisms. This represents an interesting challenge for biology in the current age, requiring the development of high-content screens to address these questions. Subcellular localisation plays an integral role in determining a protein’s biological function. The distinct physical environment/s in which a protein resides, governs the functional role that it can perform by restricting interactions that can be made. Thus, determining subcellular localisation provides useful insights into potential functional roles for novel proteins. This thesis focuses on defining the entire complement of type II membrane proteins in the murine transcriptome. Initially, functional annotation of transcripts in the FANTOM3 project resulted in a high quality dataset. The entire complement of type II membrane proteins were then predicted using a computational algorithm, MemO. The subcellular localisation of this computationally defined dataset was then characterised using two approaches. Initially, literature mining was performed to identify proteins with previously determined, published subcellular localisation data. This approach was complemented with a high¬throughput, PCR¬based approach to generate N-terminal, myc-tagged expression constructs. These constructs were then expressed in HeLa cells to determine subcellular localisation. Collectively these methods presented localisation data for ~26% of the dataset. Finally, two novel proteins that demonstrated phenotypes of interest were pursued in greater depth.

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Created: Wed, 20 Aug 2008, 19:46:43 EST by Noela Stallard on behalf of Library - Information Access Service