Theses and Dissertations (Bioinformatics and Computational Biology Unit)

Permanent URI for this collectionhttp://hdl.handle.net/2263/32447

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    Investigation of cystic fibrosis transmembrane conductance regulator variants in South African patients with cystic fibrosis
    (University of Pretoria, 2023) Pepper, Michael Sean; Joubert, Fourie; u17081786@tuks.co.za; Le Grange, Odette
    Cystic Fibrosis is a genetic disease caused by variants in the CFTR gene. It is one of the most thoroughly studied genetic diseases, with remarkable advances being seen in the ability to diagnose and specifically treat CF patients based on the nature of their variants. Diagnostic protocols have gained in specificity and sensitivity, with high variant detection rates being achieved using new-born screening in populations with higher frequencies of known, common mutations. However, there are several obstacles impeding the improvement of care in LMICs with diverse populations carrying CFTR variants, including challenges in establishing accurate and reliable diagnostics and overcoming misdiagnosis. African populations are known to have high genomic diversity but remain largely understudied. In South Africa, greater knowledge of the CFTR variant spectrum and clinical presentation is needed to enable earlier diagnosis with more specific gene panels, since the variants common to European populations are less frequent in this population. To bridge this gap, next generation sequencing data from a cohort of 60 South African patients and 5 parents of CF patients was used for variant discovery across the exon regions of the CFTR gene. Thereafter, variant effect prediction was performed, and potentially pathogenic variants were identified. Lastly, these potential variants were validated experimentally using Sanger sequencing. Next-generation sequencing of this cohort enabled 27 individuals that were lacking a complete molecular diagnosis to be fully genotyped. 23 confirmed variants have been functionally studied and proven to cause CF; however, 11 variants are yet to have their functional significance characterised. This study demonstrates the extent of diversity that is likely present in the southern African CF population. As the emerging field of precision medicine and the development of specific CFTR therapies gains momentum with the help of high-throughput screening, individuals with CF in LMICs such as South Africa stand to benefit greatly through earlier molecular diagnosis as well as more specific treatment protocols.
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    In silico inference of immunological relationship between protein antigens based on their cytotoxic T-lymphocyte epitope repertoires
    (University of Pretoria, 2011-06-07) Joubert, Fourie; werner.smidt@gmail.com; Smidt, Werner
    The importance of Cytotoxic T-Cell (CTL) reponses during the course of intracellular infections has received a lot of attention during the past few decades. CTLs respond to epitopes presented by the Major Histocompatibility Complex (MHC) originating from intracellular proteins for which they have an appropriate T-Cell Receptor (TCR) for. This response is crucial for the control of pathogens such as Influenza, Hepatitis, HIV and others by destroying the cell in which the pathogen replicates. Due to the extreme polymorphism of MHC molecules, Computational Immunology techniques have been developed to detect potential MHC ligands and as a consequence, potential CTL epitopes. The polymorphism factor needs to be taken into account especially when concerning the design of vaccines with a CTL response component to maximize population coverage. Tools have been constructed that combine the predictions tools concerning major steps in this pathway, that is, proteasomal cleavage, Transporter associated with Antigen Presentation (TAP) affinity, Major Histocompatibility Complex (MHC) affinity and Immunogenicity. In this study, a novel method is developed to combine the different steps in the pathway, which includes the development of a novel TAP predictor. Furthermore, by using a BLOSUM-based score in conjunction with the epitope prediction results, a novel CTL epitopebased clustering method was developed. Two pathogens with major CTL epitope components, but vastly different mutation rates were chosen to infer whether the aforementioned methods can be used to detect potential CTL epitopes and group sequences together based on shared immunogenicity.