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The spatiotemporal dynamics of inflammatory neutrophil populations

Holmes, Geoffrey Robert (2013) The spatiotemporal dynamics of inflammatory neutrophil populations. PhD thesis, University of Sheffield.

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Geoffrey R Holmes PhD Thesis.pdf
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Inflammation is a natural response of the innate immune system. It has evolved over the course of millennia to deal with the threat of injury and infection. The neutrophil is a powerful immune cell that plays a vital role in inflammation but when dysfunctional it can cause chronic diseases such as asthma, chronic obstructive pulmonary disease and arthritis. These illnesses have a devastating impact on the lives of sufferers. A complete understanding of the inflammation response is, therefore, a vital ongoing area of research where breakthroughs will potentially bring huge benefit to individuals and to society. Neutrophils have been studied in vitro for over a hundred years. A new opportunity has recently arisen to observe their dynamics in vivo in transgenic zebrafish larvae which are transparent and have an immune system with similarities of form and function to our own. These new data present a modelling and system identification challenge: how to infer cell dynamics from limited amounts of data in a complex extra-cellular environment. This thesis addresses the problem by modelling populations of neutrophils using a drift-diffusion model of cell dynamics. Firstly, a weighted regression framework is developed which uses observations of mean squared cell displacements to identify neutrophil migration coefficients during recruitment and resolution phases of inflammation. As a result the recruitment dynamics of inflammatory neutrophils are successfully quantified in vivo. Whilst this framework is more rigorous than existing approaches, it was not conclusive for model determination. A second computational framework is therefore presented which reformulates the approximate Bayesian sequential Monte Carlo algorithm for use in the cell migration context. In particular, the Cha-Srihari distance is used to compare the distributions of cell populations. Drift-diffusion models are then extended to include chemoattractant receptor depletion dynamics and spatial variability in the extracellular environment. When this framework was applied to zebrafish neutrophils during inflammation resolution, a key result was that this migration is the unguided result of inherent stochastic cell movements. This contrasts with the externally guided dynamics during recruitment. An important conclusion is that the search for influences driving neutrophils away from a wound is futile and the focus should be on the mechanisms whereby neutrophils are desensitised to signals that retain them in the inflamed area.

Item Type: Thesis (PhD)
Keywords: data driven modelling, spatiotemporal, inflammation, neutrophil, zebrafish, diffusion, approximate Bayesian computation,
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Automatic Control and Systems Engineering (Sheffield)
Identification Number/EthosID: uk.bl.ethos.581650
Depositing User: Geoffrey Holmes
Date Deposited: 20 Sep 2013 12:36
Last Modified: 03 Oct 2016 10:46
URI: http://etheses.whiterose.ac.uk/id/eprint/4454

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