Inferring Binding Energies from Selected Binding Sites

We employ a biophysical model that accounts for the non-linear relationship between binding energy and the statistics of selected binding sites. The model includes the chemical potential of the transcription factor, non-specific binding affinity of the protein for DNA, as well as sequence-specific parameters that may include non-independent contributions of bases to the interaction. We obtain maximum likelihood estimates for all of the parameters and compare the results to standard probabilistic methods of parameter estimation. On simulated data, where the true energy model is known and samples are generated with a variety of parameter values, we show that our method returns much more accurate estimates of the true parameters and much better predictions of the selected binding site distributions. We also introduce a new high-throughput SELEX (HT-SELEX) procedure to determine the binding specificity of a transcription factor in which the initial randomized library and the selected sites are sequenced with next generation methods that return hundreds of thousands of sites. We show that after a single round of selection our method can estimate binding parameters that give very good fits to the selected site distributions, much better than standard motif identification algorithms

Defining microglial phenotypic diversity and the impact of ageing

Microglia are the resident macrophages of the central nervous system (CNS) and, as key immune effector cells, form the first line of defence. Microglial cells also provide support for maintaining neuronal homeostasis and more generally normal brain physiology and cognitive function. It has been speculated that in order to support homeostasis, microglia adapt to a variety of brain microenvironments leading to regional phenotypic heterogeneity. To date this hypothesis lacks convincing empirical evidence, yet is critical to better understand microglial function in health and age-related neurodegenerative disease. In 2010 it was estimated that in the UK approximately 10 million people are over the age of 65, which is expected to double by 2050. Ageing is one of the strongest risk factors for neurodegenerative diseases such as Alzheimer’s and Parkinson‘s disease and growing evidence implicates neuroinflammatory mechansims that may involve microglial dysfunction in disease aetiology. The majority of age-related neurodegenerative diseases develop in a region-specific manner but the reasons are poorly understood. Accordingly, the work described in this thesis sought to determine the extent and nature of regional transcriptional heterogeneity of microglia and how this is affected by ageing. To examine the function and phenotype of these cells a technique for isolating pure microglia from the adult mouse brain was established. Microglia were consistently extracted by density-gradient and immunomagnetic cell separation. In vitro assays showed purified microglia retained key functional properties including phagocytosis, polarisation and production of pro-inflammatory cytokines in response to exogenous stimulation. Thus, freshly isolated microglia are not altered or dysfunctional during the extraction process and are likely to adequately represent the 'real' in vivo state. Genome-wide transcriptional network analysis of young adult mouse microglia from four discrete regions of the brain (cerebellum, cerebral cortex, hippocampus and striatum) uncovered regional heterogeneity in the microglial transcriptome driven particularly by bioenergetic and immunoregulatory functions. Transcriptional profiles of cerebellar and hippocampal microglia suggest a higher immune vigilance and alertness, which was supported by functional differences in the capability of microglia to phagocytose and control replication of bacteria. Region-dependent heterogeneity of microglia was largely consistent throughout the ageing process; however the region-specific phenotypes were more pronounced as age increased indicating region-dependent kinetics of microglial ageing. Collectively, the outcome of this study implies that microglia adapt to region-specific demands of brain tissue under steady-state conditions and are susceptible to ageing. Region was found to have a greater impact on microglial diversity than age. Overall, these findings will generate a substantial advance in our understanding of microglial function in the healthy brain and in age-related neurodegeneration