Development of novel therapeutics and in vitro models for spinal cord injury

Spinal cord injury (SCI) is a devastating condition, which results from trauma to the cord, resulting in a primary injury response which leads to a secondary injury cascade, causing damage to both glial and neuronal cells. Following trauma, the central nervous system (CNS) fails to regenerate due to a plethora of both intrinsic and extrinsic factors. Unfortunately, these events lead to loss of both motor and sensory function and lifelong disability and care for sufferers of SCI. There have been tremendous advancements made in our understanding of the mechanisms behind axonal regeneration and remyelination of the damaged cord. These have provided many promising therapeutic targets. However, very few have made it to clinical application, which could potentially be due to inadequate understanding of compound mechanism of action and reliance on poor SCI models. This thesis describes the use of an established neural cell co-culture model of SCI as a medium throughput screen for compounds with potential therapeutic properties. A number of compounds were screened which resulted in a family of compounds, modified heparins, being taken forward for more intense investigation. Modified heparins (mHeps) are made up of the core heparin disaccharide unit with variable sulphation groups on the iduronic acid and glucosamine residues; 2-O-sulphate (C2), 6-O-sulphate (C6) and N-sulphate (N). 2-O-sulphated (mHep6) and N-sulphated (mHep7) heparin isomers were shown to promote both neurite outgrowth and myelination in the SCI model. It was found that both mHeps decreased oligodendrocyte precursor cell (OPC) proliferation and increased oligodendrocyte (OL) number adjacent to the lesion. However, there is a difference in the direct effects on the OL from each of the mHeps; mHep6 increased myelin internode length and mHep7 increased the overall cell size. It was further elucidated that these isoforms interact with and mediate both Wnt and FGF signalling. In OPC monoculture experiments FGF2 treated OPCs displayed increased proliferation but this effect was removed when co-treated with the mHeps. Therefore, suggesting that the mHeps interact with the ligand and inhibit FGF2 signalling. Additionally, it was shown that both mHeps could be partially mediating their effects through the Wnt pathway. mHep effects on both myelination and neurite outgrowth were removed when co-treated with a Wnt signalling inhibitor, suggesting cell signalling mediation by ligand immobilisation and signalling activation as a mechanistic action for the mHeps. However, the initial methods employed in this thesis were not sufficient to provide a more detailed study into the effects the mHeps have on neurite outgrowth. This led to the design and development of a novel microfluidic device (MFD), which provides a platform to study of axonal injury. This novel device is a three chamber device with two chambers converging onto a central open access chamber. This design allows axons from two points of origin to enter a chamber which can be subjected to injury, thus providing a platform in which targeted axonal injury and the regenerative capacity of a compound study can be performed. In conclusion, this thesis contributes to and advances the study of SCI in two ways; 1) identification and investigation of a novel set of compounds with potential therapeutic potential i.e. desulphated modified heparins. These compounds have multiple therapeutic properties and could revolutionise both the understanding of the basic pathological mechanisms underlying SCI but also be a powered therapeutic option. 2) Development of a novel microfluidic device to study in greater detail axonal biology, specifically, targeted axonal injury and treatment, providing a more representative model of SCI than standard in vitro models. Therefore, the MFD could lead to advancements and the identification of factors and compounds relating to axonal regeneration.

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.