Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging

Erben, Dan (2016) Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging. PhD thesis, University of Glasgow.

Abstract

This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval.
A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature.
In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines.
In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging.
In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field.
In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: Multi-photon, two-photon, cell movement, network movement, cell interactions, state-space model, FRC, fibroblast reticular network, T cells, dendritic cells, microscopy, imaging, lymph node, Bayesian, spatial statistics, clustering, Ripley's K.
• Subjects: Q Science > QH Natural history > QH301 Biology; Q Science > QR Microbiology > QR180 Immunology
• Colleges/Schools: College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
• Supervisor's Name: Haydon, Prof. Daniel, Garside, Prof. Paul and Brewer, Prof. James
• Date of Award: 2016
• Depositing User: Dan Erben
• Unique ID: glathesis:2016-7285
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 03 Oct 2016 07:15
• Last Modified: 31 Oct 2016 10:35
• URI: https://theses.gla.ac.uk/id/eprint/7285