Magister Scientiae - MSc (Bioinformatics)

Permanent URI for this collectionhttps://hdl.handle.net/10566/15212

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Investigating the role of HLA class-1 polymorphisms within the Sub-Saharan African population, in the emergence, frequency, and persistence of SARS-CoV-2 variants.
(University of the Western Cape, 2025) Francis, Kriheska
RATIONALE: Various studies have shown the ability of the cytotoxic T cell (by CD8+ T cells) immune response in disease control in the absence of neutralizing antibodies in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) convalescent individuals. Thus, illustrating the important role of the cytotoxic immune response in clearing coronavirus disease 2019 (COVID-19). Human Leukocyte Antigen molecules (HLA) present virus peptides to T cells during the activation of an immune response. However, only a few studies have looked at how the HLA allele repertoire of the infected population impacts immune escape, and none have looked at how the high HLA polymorphism in the Sub-Saharan African (SSA) population impacts the immune escape patterns in viruses circulating within this population. AIM: The Aim of this study was to predict the HLA-mediated cytotoxic T cell immune escape mutations present in SARS-CoV-2 structural proteins isolated from SSA populations. The SARSCoV-2 isolates for the study were analyzed from five SSA countries namely, Kenya, Democratic Republic of Congo, Nigeria, Ghana and Senegal to ask the question: Do HLA class-1 polymorphisms in SSA populations result in locally specific immune escape mutations in SARSCoV-2?
Molecular modelling, docking and simulation studies to identify novel inhibitors against the mycobacterium tubercolosis drug target, Rv2194 (QcrC)
(University of the Western Cape, 2026) Ndlondlo, Mihlali
In the present age, tuberculosis (TB) is known as a complex infectious illness caused by Mycobacterium tuberculosis (M.tb). Through knowledge obtained from past efforts, the disease was uncovered to have the potential to last throughout an infected person’s lifetime and it remains amongst the most life-threatening diseases worldwide (WHO, 2023). To understand the disease, we have to review the historical milestones and discoveries related to our current knowledge of TB. The origins of tuberculosis are ancient, with the common ancestor of the modern strains of M.tb estimated to have appeared 20 000 to 15 000 years ago (Barberis et al., 2017). The oldest documentation about the disease to be recorded dates back to ~3300 years ago in India where the disease was recorded in the Vedas, which are the oldest religious texts of Hinduism (Natarajan et al., 2020). In oldest of the Vedas namely the Rigveda, TB was referred to as Rajayakshma, which means wasting disease, while in the Atharvaveda it was named balasa, which was described as scrofula (Natarajan et al., 2020; Panda, 2021; Zysk, 1996). The disease has had a variation of names throughout history, with the ancient Hebrews naming it schachepheth, in ancient Greece it was named phthisis and tabes in ancient Rome (Barberis et al., 2017; Daniel, 2006). One of the most notable names coined in the Middle Ages, was the “king’s evil”.
Spatiotemporal Patterns Of Rift Valley Fever Virus In Africa: A Retrospective Genomic Epidemiology And Phylodynamic Modelling Study
(Elsevier Ltd, 2026) Christoffels, Alan; Juma, John; Roesel, Kristina
Background Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic pathogen causing outbreaks in humans and ruminants across Africa and the Arabian Peninsula. Originally restricted to the Great Rift Valley, RVFV has expanded geographically, prompting its classification by WHO as a pathogen of pandemic potential. We investigated the evolutionary and spatial dynamics of RVFV across Africa. Methods We used genomic data generated at the International Livestock Research Institute Nairobi genomic laboratory (BioProject PRJNA1106221) and combined with publicly available datasets retrieved from the National Center for Biotechnology (NCBI) GenBank nucleotide database. In retrieving RVFV genome sequences from the NCBI GenBank, we applied the search terms “Rift Valley fever virus segment L AND 6404[SLEN]”, “Rift Valley fever virus segment M AND 3885[SLEN]”, and “Rift Valley fever virus segment S AND 1520:1690[SLEN]” for L (Large), M (Medium), and S (Small) segments, respectively. For sequences without additional spatiotemporal information, we searched PubMed to extract the associated sequence metadata. We performed molecular clock analysis, phylogenetic inference, phylodynamic modelling (continuous phylogeographic reconstruction), and landscape phylogeography on the three RVFV genome segments (L, M, and S). We aimed to assess evolutionary rates, dispersal patterns, and environmental drivers. Focus was placed on lineage C, the most widely distributed variant. Findings The global dataset used in this study consisted of large (n=236), medium (n=237), and small (n=247), which were further filtered to exclude potential reassortants and vaccine strains. Genome sequences retrieved from NCBI GenBank database comprised large (n=180), medium (n=184), and small (n=202). The genome sequences from retrospective human and livestock isolates comprised large (n=56), medium (n=53), and small (n=45) collected in Burundi (2018), Kenya (2007, 2018, 2019, 2021, and 2022), and Rwanda (2018 and 2022). Our dataset revealed that RVFV exhibited low overall genetic diversity. Lineage C, however, showed evidence of active evolution, with substitution rates ranging from 3·58 × 10−4 to 9·76 × 10−4 substitutions per site per year. This lineage probably originated in Zimbabwe in the mid-1970s and has since expanded across eastern and southern Africa. Phylogeographic reconstructions revealed rapid spread, with diffusion coefficients exceeding 50 000 km2 per year. Interpretation Lineage C appears capable of establishing endemic transmission in new regions, with ongoing diversification observed during interepidemic periods. These observations reinforce the value of continuous genomic surveillance, particularly during cryptic transmission phases when adaptive mutations might emerge. Although further evidence is needed, observed trends in climate variability and land-use change point to the potential benefit of targeted surveillance in settings that could be at increased risk, including urban centres and wetlands. Funding This work was supported by the German Federal Ministry for Economic Cooperation and Development, the Rockefeller Foundation, and the Africa Centres for Disease Control and Prevention.
Three-Dimensional (3D) pharmacophore-based identification of possible ATP-synthase inhibitors for mycobacterium tuberculosis (Mtb)
(University of the Western Cape, 2024) Fredericks, Ridaa
Tuberculosis (TB) is defined as a chronic infectious disease caused by the air-borne transmission of Mycobacterium tuberculosis (Mtb). Due to high prevalence of Mtb in South Africa, it is classified as a high burden country by the World Health Organization (WHO). Multi-drug resistant TB (MDR-TB) strains display a resistance to both Isoniazid and Rifampicin, while extensively drug resistant (XDR-TB) includes resistance to fluoroquinolone as well as other second- line drugs (Capreomycin, Kanamycin and Amikacin). Bedaquiline (BDQ) is a diarylquinoline aimed at inhibiting the adenosine triphosphate (ATP) synthase of MDR-TB, thereby targeting the energy metabolism mechanism of Mtb. Drug regimens utilized prior to BDQ have shown low success rates in patients with XDR-TB. The technologies of computer-aided drug discovery (CADD) has proven to be a powerful tool in reducing costs, as well as time, and ensures the efficiency of lead compound identification. CADD can be divided into two categories; structure-based (SB) and ligand-based (LB) drug discovery. The categories are employed are based on the input data; in this study the LB method was employed as the known descriptors were found to inhibit Mtb ATP-synthase. These descriptors (ligands) were then used to generate pharmacophore models of varying quality and features. A pharmacophore model is a set of features that a ligand requires to be recognized by the drug target, Mtb ATP-synthase.
Regulatory attributes of the carotenoid biosynthetic pathway in Arabidopsis Thaliana under abiotic stress
(University of the Western Cape, 2012) Khan, Firdous; Christoffels, Alan
Carotenoids are tetraprenoid (C40) molecules synthesized in plants, fungi, bacteria and algae, via the carotenoid biosynthetic pathway (CBP). Some carotenoids are readily converted to vitamin A (VA) in humans, e.g. 13-carotene, c(-carotene and B-cryptoxanthin 1,2. Vitamin a deficiency (VAD) affect millions especially children under the age of five. The CBP in plants is a key source of pro-vitamin A and is vital to the biofortification of staple crops such as maize, rice and sorghum, could alleviate the global VAD problem. However the incomplete understanding of regulation of the pathway is a limiting factor to predictably control carotenoid content at the systems level. Previous studies have shown that growth conditions, such as light, play a major role in the biosynthesis of carotenoids. A systems biology approach was therefore used to analyse microarray data sets derived from A. thaliana grown under various conditions and treated with different stimuli. Thirty two genes have previously been identified as being involved in the CBP. These genes were found to be highly differentially expressed depending on stress type. All stimuli including drought, cold, heat, osmotic, oxidative and salt but wounding had a significant influence on the CBP genes. Gene expression induced by abiotic stress occured 30 min after exposure. These findings are indicative that an immediate systemic signal is sent to the rest of the plant in response to stress. A correlation analyses revealed strongly positive correlation between PSY and its co-expressed genes, suggesting they share a common regulatory mechanism. Promoter content analyses identified 20 enriched TFBMs among carotenoid genes. The most prevalent TFBMs found in the promoter regions of the CBP genes show a 1.25-3 fold increase in prevalence with a p-value < 0.05. Similar GO terms are enriched for CBP genes and their co-expressed genes. These findings indicate that carotenoid biosynthetic pathway genes and their co-expressed genes are involved in similar metabolic pathways and functional processes. This study identified cold, drought and heat to influence carotenoid gene expression and has led to the identification of molecular switches that can be modulated to control the biosynthetic pathway. Four motifs without any GO annotation and no specific known motif in plant databases were identified using MEME suite. In this study I propose that these predictions might be novel motifs and could be specific to carotenoid genes, and may be directly involved in the regulation of carotenoid biosynthesis. These findings may lead to a better understanding of the underlying regulatory mechanisms involved in the biosynthesis of carotenoids. Furthermore, these findings may assist in establishing ways of enhancing the production of carotenoids, especially pro-vitamin A, in Arabidopsis thaliana.
Analyses of sequence divergence using completely sequenced genomes
(University of the Western Cape, 2003) Nembaware, Victoria P.; Seoighe, Cathal
Using the complete genome, Saccharomyces cerevisiae, which duplicated after its speciation fuom Kluyveromyces lactics, a dataset of 119 putative S. cerevisiae - K. lactis ortholog-pairs was constructed. S. cerevisiae paralogous pairs that are likely to have duplicated during the whole genome duplication of S. cerevisiae were obtained and the approach taken in our previous work (Nembaware et al., 20OZ), was repeated to test whether the presence of a paralogue in S. cerevisiae had an effect on the rate of sequence divergence of the 119 pairs of orthologous genes. We found, however, that substitutions at synonymous sites had reached saturation and this prevented us from being able to repeat the previous finding with S. cerevistae and K. lactis . From this study a publicly available web-server (http://hamlyn.sanbi.ac.zal-victoria) that automates the calculation of Ka:Ks values given a pairs homologous CDS sequences is presented.
Development and implementation of ontology-based systems for mammalian gene expression profiling
(University of the Western Cape, 2009) Kruger, Adele; Hide, Winston
The use of ontologies in the mapping of gene expression events provides an effective and comparable method to determine the expression profile of an entire genome across a large collection of experiments derived from different expression sources. In this dissertation I describe the development of the developmental human and mouse e voe ontologies and demonstrate the ontologies by identifying genes showing a bias for developmental brain expression in human and mouse, identifying transcription factor complexes, and exploring the mouse orthologs of human cancer/testis genes.
Identification of insertion-induced enhancers linked to gene drivers within non-coding DNA using a pipeline for diffuse large b-cell lymphoma H3K27ac ChIP-seq data
(University of the Western Cape, 2022) Jassiem, Wardah; Bendou, Hocine
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL) and incorporates a diverse range of illnesses with varying biology, clinical manifestations, and therapeutic responses. Functional insertion mutations represent the driving mechanism behind many oncologic illnesses. Research has shown that variants associated with cancer in the non-coding portion of the genome, which is enriched with enhancer elements, is greatly underappreciated. The present study designed a bioinformatics pipeline using Nextflow DSL2 to identify insertion-induced enhancers associated with DLBCL oncogenes within the non-coding genome using H3K27ac ChIP-seq data. Gapped DLBCL reads identified by bowtie were mapped to the human reference genome with bowtie2. Non-coding insertions were identified with BEDTools and verified by pBla.
An investigation into the genetic basis of autosomal recessive Osteogenesis imperfecta (OI) III in a South African family of mixed ancestry
(University of the Western Cape, 2022) Fernol, Susan Alicia; Christoffels, Alan
Osteogenesis Imperfecta (OI) is a rare skeletal dysplasia that is primarily characterized by bone fragility, recurrent fractures, and bone deformities. Over the years there has been an increase in the number of genes associated with OI. Currently there are twenty causative genes involved in OI spread across an autosomal dominant form, autosomal recessive form, and an X-linked form. Among the different types of OI, the progressively deforming OI, has more than one causative OI gene associated with it, and both AD and AR mode of inheritance. A severe autosomal recessive form of OI type III has been studied in SA for more than 40 years.
A comparative genomics approach towards classifying immunity-related proteins in the tsetse fly
(University of the western cape, 2009) Mpondo, Feziwe; Hide, Winston; Christoffels, Alan
Tsetse flies (Glossina spp) are vectors of African trypanosome (Trypanosoma spp) parasites, causative agents of Human African trypanosomiasis (sleeping sickness) and Nagana in livestock. Research suggests that tsetse fly immunity factors are key determinants in the success and failure of infection and the maturation process of parasites. An analysis of tsetse fly immunity factors is limited by the paucity of genomic data for Glossina spp. Nevertheless, completely sequenced and assembled genomes Drosophila melanogaster, Anopheles gambiae and Aedes aegypti provide an opportunity to characterize protein families in species such as G/ossiza by using a comparative genomics approach. In this study, we characterize thioester-containing proteins (TEPs), a sub-family of immunity-related proteins, in Glossinaby leveraging the EST data for G. morsitans and the genomic resources of D. melanogaster, A. gambiae as well as A. aegypti
A deep learning approach to predicting potential virus species crossover using convolutional neural networks and viral protein sequence patterns
(University of the Western Cape, 2022) Serage, Rudolph; Anderson, Dominique
Medical science has made substantial progress toward diagnosing, understanding the pathogenesis, and treating various causative agents of infectious disease; however, novel microbial pathogens continue to emerge, and existing pathogens continue to evolve alternative means to thrive in ever-changing environments. Various infectious disease etiological agents originate from animal reservoirs, and many have, over time, acquired the ability to cross the species barrier and alter their host range. The emergence and re-emergence of zoonotic pathogens is reported to be a consequence of changes in several factors, including ecological, behavioural, and socioeconomic variables which are arguably impossible to control. Computational methods with the capacity to evaluate large datasets, are considered invaluable tools for predicting and tracking disease outbreaks and are especially powerful when combined with machine learning techniques.
Reconstruction of gene regulatory networks of inflammation-associated genes in different clinical stages of diffuse large B-cell lymphoma
(University of the Western Cape, 2022) Mfuphi, Nomlindelo Witness; Bendou, Hocine
Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy that is driven by complex gene regulatory networks (GRNs). Numerous genes exert distinct effects on the progression and therapeutic outcome of DLBCL. Previous studies have associated DLBCL with inflammation but the GRNs involved in this mechanism have not yet been explored. The objectives of this current study are to reconstruct inflammation-associated networks and to understand the effects of inflammation on the pathogenesis and progression of DLBCL in different clinical stages.
HIV Subtype C Diversity: Analysis of the Relationship of Sequence Diversity to Proposed Epitope Locations
(University of the Western Cape, 2002) Ernstoff, Elana Ann; Hide, Winston
Southern Africa is facing one of the most serious HIV epidemics. This project contributes to the HIVNET, Network for Prevention Trials cohort for vaccine development. HIV's biology and rapid mutation rate have made vaccine design difficult. We examined HIV-l subtype C diversity and how it relates to CTL epitope location along viral gag sequences. We found a negative correlation between codon sites under positive selection and epitope regions; suggesting epitope regions are evolutionarily conserved. It is possible that detected due to the reference regions, yet fail to be viral population. To test if CTL clustering is an we calculated differences between the gag codons and the a weak negative correlation, suggesting epitopes in less conserved regions maybe evading detection. Locating conserved and optimal epitopes that can be recognized by CTLs is essential for the design of vaccine reagents.
Molecular modeling and simulation studies to prioritize sequence variants identified by whole-exome sequencing in a South African family with Parkinson's disease
(University of Western Cape, 2021) Hassan, Maryam; Cloete, Ruben
Parkinson’s disease (PD) is a neurodegenerative disorder that occurs due to a loss of dopaminergic neurons in the substantia nigra. It is one of the most common neurodegenerative disorders, ranking second only to Alzheimer’s disease. Research on the genetic causes of PD over the past two decades has led to the discovery of several PD-associated genes. Currently, researchers have identified 23 genes that are linked to rare monogenic forms of PD with Mendelian inheritance. In sub-Saharan Africa (SSA), PD has received little attention due to factors such as underfunded healthcare infrastructure, the absence of epidemiological data, and a scarcity of neurologists. In the relatively few published studies, it has been shown that the known PD mutations play a minor role in disease etiology in SSA populations. In the current study, we follow up on previous work done in an MMed study investigating a South African family with several family members (mother and three sons) suffering from PD.
Molecular dynamic simulation studies of the South African HIV-1 Integrase subtype C protein to understand the structural impact of naturally occurring polymorphisms
(University of the Western Cape, 2021) Isaacs, Matthew Darren; Cloete, Ruben Earl Ashley
The viral Integrase (IN) protein is an essential enzyme of all known retroviruses, including HIV-1. It is responsible for the insertion of viral DNA into the human genome. It is known that HIV-1 is highly diverse with a high mutation rate as evidenced by the presence of a large number of subtypes and even strains that have become resistant to antiretroviral drugs. It remains inconclusive what effect this diversity in the form of naturally occurring polymorphisms/variants exert on IN in terms of its function, structure and susceptibility to IN inhibitory antiretroviral drugs. South Africa is home to the largest HIV-1 infected population, with (group M) subtype C being the most prevalent subtype. An investigation into IN is therefore pertinent, even more so with the introduction of the IN strand-transfer inhibitor (INSTI) Dolutegravir (DTG). This study makes use of computational methods to determine any structural and DTG drug binding differences between the South African subtype C IN protein and the subtype B IN protein. The methods employed included homology modelling to predict a three-dimensional model for HIV-1C IN, calculating the change in protein stability after variant introduction and molecular dynamics simulation analysis to understand protein dynamics. Here we compared subtype C and B IN complexes without DTG and with DTG.
Molecular dynamic simulation studies of the South African HIV-1 Integrase subtype C protein to understand the structural impact of naturally occurring polymorphisms
(University of Western Cape, 2021) Isaacs, Darren Mathew; Cloete, Ruben Earl Ashley
The viral Integrase (IN) protein is an essential enzyme of all known retroviruses, including HIV-1. It is responsible for the insertion of viral DNA into the human genome. It is known that HIV-1 is highly diverse with a high mutation rate as evidenced by the presence of a large number of subtypes and even strains that have become resistant to antiretroviral drugs. It remains inconclusive what effect this diversity in the form of naturally occurring polymorphisms/variants exert on IN in terms of its function, structure and susceptibility to IN inhibitory antiretroviral drugs. South Africa is home to the largest HIV-1 infected population, with (group M) subtype C being the most prevalent subtype. An investigation into IN is therefore pertinent, even more so with the introduction of the IN strand-transfer inhibitor (INSTI) Dolutegravir (DTG).
Investigating the structural effect of Raltegravir resistance associated mutations on the South African HIV-1 Integrase subtype C protein structure
(University of the Western Cape, 2020) Chitongo, Rumbidzai; Cloete, Ruben
Background and Aims Human Immunodeficiency Virus (HIV) type 1 group M subtype C (HIV-1C) accounts for nearly half of global HIV-1 infections, with South Africa (SA) being one of the countries with the highest infection burden. In recent years, SA has made great strides in tackling its HIV epidemic, resulting in the country being recognized globally as the one sub-Saharan country with the largest combination antiretroviral therapy (cART) programme. Regardless of the potency of cART, the efficacy of the treatment is limited and hampered by the emergence of drug resistance. The majority of research on HIV-1 infections, effect of antiretroviral (ARV) drugs and understanding resistance to ARV drugs has been extensively conducted, but mainly on HIV-1 subtype B (HIV-1B), with less information known about HIV-1C. HIV-1’s viral Integrase (IN) enzyme has become a viable target for highly specific cART, due to its importance in the infection and replication cycle of the virus. The lack of a complete HIV-1C IN protein structure has negatively impacted the progress on structural studies of nucleoprotein reaction intermediates. The mechanism of HIV-1 viral DNA’s integration has been studied extensively at biochemical and cellular levels, but not at a molecular level. This study aims to use in silico methods that involve molecular modeling and molecular dynamic (MD) simulations to prioritize mutations that could affect HIV-1C IN binding to DNA and the IN strand-transfer inhibitor (INSTI) dolutegravir (DTG). The purpose is to help tailor more effective personalized treatment options for patients living with HIV in SA. This study will in part use patient derived sequence data to identify mutations and model them into the protein structure to understand their impact on the HIV-1C IN protein structure folding and dynamics. Methods Our sample cohort consisted of 11 sample sequences derived from SA HIV-1 treatmentexperienced patients who were being treated with the INSTI raltegravir (RAL). The sequences were submitted to the Stanford HIV resistance database (HIVdb) to screen for any new/novel variants resulting from possible RAL failure. Some of these new variants were analyzed to analyse their effect, if any, on the binding of DTG to the HIV-1C IN protein. Additionally, an HIV-1C IN consensus sequence constructed from SA’s HIV-1 infected population was used to model a complete three-dimensional wild type (WT) HIV-1C IN homology model. All samples were sequenced by our collaborators at the Division of Medical Virology, Stellenbosch University together with the National Health Laboratory Services (NHLS), SA. The HIV-1CZA WT-IN protein enzyme was predicted using SWISS-MODEL, and the quality of the resulting model validated. Various analyses were conducted in order to study and assess the effect of the selected new variants on the protein structure and binding of DTG to the IN protein. The mutation Cutoff Scanning Matrix (mCSM) program was used to predict protein stability after mutation, while PyMol helped to study any changes in polar contact activity before and after mutation. PyMol was also used to generate four mutant HIV-1C IN complex structures and these structures together with the WT IN were subjected to production MD simulations for 150 nanoseconds (ns). Trajectory analyses of the MD simulations were also conducted and reported. Results A total of 21 new variants were detected in our sample cohort, from which only six were chosen for further analyses within the study. A homology model of HIV-1C IN was successfully constructed and validated. The structural quality assessment indicated high reliability of the HIV-1C IN tetrameric structure, with more than 90.0% confidence in modelled regions. Of the six selected variants, only one (S119P) was calculated to be slightly stabilizing to the protein structure, with the other five found to be destabilizing to the IN protein structure. Variant S119P showed a loss in polar contacts that could destabilize the protein structure, while variant Y143R, resulted in the gain of polar contacts which could reduce flexibility of the 140’s region affecting drug binding. Similarly, mutant systems P3 (S119P, Y143R) and P4 (V150A, M154I) showed reduced hydrogen bond formation and the weakest non-bonded pairwise interaction energy. These two systems, P3 and P4, also showed significantly reduced to none polar contacts between DTG, magnesium (MG) ions and the IN protein, compared to the WT IN and P2 mutant IN systems. Interestingly, the WT structure and systems P1 (I113V) and P2 (L63I, V75M, Y143R) showed the highest non-bonded interaction energy, compared to systems P3 and P4. This was further supported by the polar interaction analyses of simulation clusters from the WT IN and mutant IN system P2 (L63I, V75M, Y143R), which were the only protein structures that formed polar contacts with DTG, MG ions and DDE motif residues, while P1 only made contacts with DNA and IN residues. Conclusion Findings from this study leads to a conclusion that double mutants (S119P, Y143R) and (V150A, M154I) may result in a reduction in the efficacy of DTG, especially when in combination. Furthermore, variants identified in systems P1 and P2 may still allow for effective DTG binding to IN and outcompete viral DNA for host DNA to prevent strand transfer. To the best of our knowledge, this is the first study that uses the consensus WT HIV1C IN sequence to build an accurate 3D homology model to understand the effect of less frequently detected/reported variants on DTG binding in a South African context. https://etd.
Exploring the influence of organisational, environmental, and technological factors on information security policies and compliance at South African higher education institutions: Implications for biomedical research.
(University of the Western Cape, 2020) Abiodun, Oluwafemi Peter; Christoffels, Alan
Headline reports on data breaches worldwide have resulted in heightened concerns about information security vulnerability. In Africa, South Africa is ranked among the top ‘at-risk’ countries with information security vulnerabilities and is the most the most cybercrime-targeted country. Globally, such cyber vulnerability incidents greatly affect the education sector, due, in part, to the fact that it holds more Personal Identifiable Information (PII) than other sectors. PII refers to (but is not limited to) ID numbers, financial account numbers, and biomedical research data. In response to rising threats, South Africa has implemented a regulation called the Protection of Personal Information Act (POPIA), similar to the European Union General Data Protection Regulation (GDPR), which seeks to mitigate cybercrime and information security vulnerabilities. The extent to which African institutions, especially in South Africa, have embraced and responded to these two information security regulations remains vague, making it a crucial matter for biomedical researchers. This study aimed to assess whether the participating universities have proper and reliable information security practices, measures and management in place and whether they fall in line with both national (POPIA) and international (GDPR) regulations. In order to achieve this aim, the study undertook a qualitative exploratory analysis of information security management across three universities in South Africa. A Technology, Organizational, and Environmental (TOE) model was employed to investigate factors that may influence effective information security measures. A Purposeful sampling method was employed to interview participants from each university. From the technological standpoint, Bring Your Own Device (BYOD) policy, whereby on average, a student owns and connects between three to four internet-enabled devices to the network, has created difficulties for IT teams, particularly in the areas of authentication, explosive growth in bandwidth, and access control to security university servers. In order to develop robust solutions to mitigate these concerns, and which are not perceived by users as overly prohibitive, executive management should acknowledge that security and privacy issues are a universal problem and not solely an IT problem and equip the IT teams with the necessary tools and mechanisms to allow them to overcome commonplace challenges. At an organisational level, information security awareness training of all users within the university setting was identified as a key factor in protecting the integrity, confidentiality, and availability of information in highly networked environments. Furthermore, the University’s information security mission must not simply be a link on a website, it should be constantly re-enforced by informing users during, and after, the awareness training. In terms of environmental factors, specifically the GDPR and POPIA legislations, one of the most practical and cost-effective ways universities can achieve data compliance requirements is to help staff (both teaching and non-teaching), students, and other employees understand the business value of all information. Users which are more aware of sensitivity of data, risks to the data, and their responsibilities when handling, storing, processing, and distributing data during their day to day activities will behave in a manner that would makes compliance easier at the institutional level. Results obtained in this study helped to elucidate the current status, issues, and challenges which universities are facing in the area of information security management and compliance, particularly in the South African context. Findings from this study point to organizational factors being the most critical when compared to the technological and environmental contexts examined. Furthermore, several proposed information security policies were developed with a view to assist biomedical practitioners within the institutional setting in protecting sensitive biomedical data.
Exploring the influence of organisational, environmental, and technological factors on information security policies and compliance at South African higher education institutions: Implications for biomedical research.
(University of Western Cape, 2020) Abiodun, Oluwafemi Peter; Christoffels, Alan; Anderson, Dominique
Headline reports on data breaches worldwide have resulted in heightened concerns about information security vulnerability. In Africa, South Africa is ranked among the top ‘at-risk’ countries with information security vulnerabilities and is the most cybercrime-targeted country. Globally, such cyber vulnerability incidents greatly affect the education sector, due, in part, to the fact that it holds more Personal Identifiable Information (PII) than other sectors. PII refers to (but is not limited to) ID numbers, financial account numbers, and biomedical research data.
Establishing a framework for an African Genome Archive
(University of Western Cape, 2019) Southgate, Jamie; Christoffels, Alan
The generation of biomedical research data on the African continent is growing, with numerous studies realizing the importance of African genetic diversity in discoveries of human origins and disease susceptibility. The decrease in costs to purchase and utilize such tools has enabled research groups to produce datasets of significant scientific value. However, this success story has resulted in a new challenge for African Researchers and institutions. An increase in data scale and complexity has led to an imbalance of infrastructure and skills to manage, store and analyse this data

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