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Title: Modelling microdomain-mediated protein sorting in immunological signalling
Author: Long, E. A. G.
ISNI:       0000 0004 2732 6289
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2012
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Compartmentalisation is a fundamental feature of biological systems. The organism as a whole can be seen as a single compartment of the wider ecosystem. At lower scales, we observe biological processes compartmentalised into organs, cells, cell subtypes and organelles. In the highly complex discipline of immunology, compartmentalisation is key in order to respond e ciently to foreign antigens and to maintain the balance between immunity and tolerance. Recent studies have raised questions about the role of compartmentalisation in lipid membranes, from the relatively well described immunological synapse, to the smaller, more transient lipid raft or microdomain. This thesis asks whether, and how, microdomains could in uence the formation of small receptor complexes. Speci cally, we approach what appears to be a simple surface reaction-di usion problem from multiple viewpoints: explicitly simulating particle di usion using a probabilistic pixel-based model, and deriving a deterministic relation between spatial parameters and the timecourse of chemical concentrations throughout the model space. We also show the equivalence between the predictions of these two models, further supporting the validity of our approach. We also embed the results of our model output in an existing model of the immunological response in order to determine the downstream consequences of enhanced receptor organisation. The study gives a broader understanding of the mechanisms involved in microdomain-mediated protein sorting, highlights the degree of interdependence on multiple spatial and chemical parameters and suggests numerous avenues for future research.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available