The postsynaptic density (PSD) is a complex, dynamic structure composed of ~2000 distinct proteins, found at the postsynaptic membrane. Interactions, of transient and non-transient nature, organise the PSD’s constituent parts into a protein complex, which functions as an intricately regulated molecular machine, orchestrating the mediation and regulation of synaptic transmission and synaptic plasticity. Furthermore, many of the proteins found in this complex have been linked to synaptic and behavioural plasticity, basic cognition or disease. Although, through proteomics we have accumulated a lot of information on the constituent parts of this machine as well smaller sub-networks representing pathways, not a lot is known about the organisational principles of the PSD. In this project our aim is to develop a standardised approach to reconstructing protein interaction networks from PSD proteomics data, providing a descriptive integrative model. Using these models we also performed an analysis elucidating parts of these organisational principles. We applied this method on two murine postsynaptic density proteomics datasets and found a persistent modular architecture of biological significance. Furthermore, given the lack of substantial evidence on the composition and architecture of postsynaptic density interaction networks of other model organisms, we decided to perform an affinity purification of Drosophila melanogaster postsynaptic density proteins and perform a similar analysis. The resulting model corroborated theoretical predictions of a lower complexity but similar functionality and also showed a modular architecture. As a final analysis we compared the two models from a structural and evolutionary perspective attempting to elucidate the mechanisms of evolution of this molecular machine. The results of this analysis implied that a whole component rather than just individual proteins of the fly protein interaction network have been conserved, highlighting the importance of the aforementioned organisational principles.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:578361 |
| Date | January 2012 |
| Creators | Zografos, Lysimachos |
| Contributors | Armstrong, Douglas; Pocklington, Andrew |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/7706 |
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