Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658966
Title: Modelling shape fluctuations during cell migration
Author: Jefferyes, Samuel D. R.
ISNI:       0000 0004 5357 4876
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2014
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Abstract:
Cell migration is of crucial importance for many physiological processes, including embryonic development, wound healing and immune response. Defects in cell migration are the cause of chronic in ammatory diseases, mental retardation and cancer metastasis. Cell movement is driven by actin-mediated cell protrusion, substrate adhesion and contraction of the cell body. The emergent behaviour of the intracellular processes described above is a change in the morphology of the cell. This inspires the main hypothesis of this work which is that there is a measurable relationship between cell morphology dynamics and migratory behaviour, and that quantitative models of this relationship can create useful tools for investigating the mechanisms by which a cell regulates its own motility. Here we analyse cell shapes of migrating human retinal pigment epithelial cells with the aim to map cell shape changes to cellular behaviour. We develop a non-linear model for learning the intrinsic low-dimensional structure of cell shape space and use the resultant shape representation to analyse quantitative relationships between shape and migration behaviour. The biggest algorithmic challenge overcome in this thesis was developing a method for efficiently and appropriately measuring the shape difference between pairs of cells that may have come from independent image scenes. This difference measure must be capable of coping with the widely varying morphologies exhibited by migrating epithelial cells. We present a new, rapid, landmark-free, shape difference measure called the Best Alignment Metric (BAM). We show that BAM performs highly within our framework, generating a shape space representation of a very large dataset without any prior information on the importance of any given shape feature. We demonstrate quantitative evidence for a model of cell turning based on repolarisation and discuss the impact our proposed framework could have on the continued study of migratory mechanisms.
Supervisor: Not available Sponsor: Biotechnology and Biological Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.658966  DOI: Not available
Keywords: QR Microbiology
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