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

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.

The metabolic and epigenetic effects of the isocitrate dehydrogenase-1 mutation in glioma

Cancer cells have been noted to have an altered metabolic phenotype for over ninety years. In the presence of oxygen, differentiated cells predominately utilise the tricarboxylic acid (TCA) cycle and oxidative phosphorylation to efficiently produce energy and the metabolites necessary for protein and lipid synthesis. However, in hypoxia, this process is altered and cells switch to a higher rate of glycolysis and lactate production to maintain their energy and metabolic needs. In cancer cells, glycolysis is maintained at a high rate, even in the presence of oxygen; a term described as “aerobic glycolysis”. Tumour cells are rapidly dividing and have a much greater need for anabolism compared to normal differentiated cells. Rapid glucose metabolism enables faster ATP production as well as a greater redistribution of carbons to nucleotide, protein, and fatty acid synthesis, thus maximising cell growth. Recently, other metabolic changes, driven by mutations in genes related to the TCA cycle, indicate an alternative role for metabolism in cancer, the “oncometabolite”. This is where a particular metabolite builds up within the cell and contributes to the tumorigenic process. One of these genes is isocitrate dehydrogenase (IDH) IDH is an enzyme that forms part of the tricarboxylic acid (TCA) cycle and converts isocitrate to α-ketoglutarate (α-KG). It exists in three isoforms; IDH1, IDH2 and IDH3 with the former present in the cytoplasm and the latter two in the mitochondria. Point mutations have been identified in the IDH1 and IDH2 genes in glioma which result in a gain of function by converting α-KG to 2-hydroxyglutarate (2HG), an oncometabolite. 2HG acts as a competitive inhibitor of the α-KG dependent dioxygenases, a superfamily of enzymes that are involved in numerous cellular processes such as DNA and histone demethylation. It was hypothesised that the IDH1 mutation would result in other metabolic changes in the cell other than 2HG production, and could potentially identify pathways which could be targeted for therapeutic treatment. In addition, 2HG can act as a potential competitive inhibitor of α-KG dependent dioxygenases, so it was hypothesised that there would be an effect on histone methylation. This may alter gene expression and provide a mechanism for tumourogenesis and potentially identify further therapeutic targets. Metabolic analysis of clinical tumour samples identified changes associated with the IDH1 mutation, which included a reduction in α-KG and an increase in GABA, in addition to the increase in 2HG. This was replicated in several cell models, where 13C labelled metabolomics was also used to identify a possible increase in metabolic flux from glutamate to GABA, as well as from α-KG to 2HG. This may provide a mechanism whereby the cell can bypass the IDH1 mutation as GABA can be metabolised to succinate in the mitochondria by GABA transaminase via the GABA shunt. JMJ histone demethylases are a subset of the α-KG dependent dioxygenases, and are involved in removing methyl groups from histone tails. Changes in histone methylation are associated with changes in gene expression depending on the site and extent of chemical modification. To identify whether the increase in 2HG and fall in α-KG was associated with inhibition of histone demethylases a histone methylation screen was used. The IDH1 mutation was associated with an increase in methylation of H3K4, which is associated with gene activation. ChiP and RNA sequencing identified an increase in H3K4me3 at the transcription start site of the GABRB3 subunit, resulting in an increase in gene expression. The GABRB3 subunit forms part of the GABA-A receptor, a chloride channel, which on activation can reduce cell proliferation. The IDH1 mutation was associated with an increase in GABA and GABRB3 subunit of the GABA-A receptor. This raises the possibility of GABA transaminase as a potential therapeutic target. Inhibition of this enzyme could reduce GABA metabolism, potentially reducing any beneficial effect of the GABA shunt in IDH1 mutant tumours, and increasing activation of the GABA-A receptor by increasing the concentration of GABA in the brain. This in turn may reduce cell proliferation, and could be achieved by using Vigabatrin, a GABA transaminase inhibitor licensed for use in epilepsy.