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Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions
HIV and Mycobacterium tuberculosis (Mtb) co-infection causes treatment and diagnostic difficulties, which places a major burden on health care systems in settings with high prevalence of both infectious diseases, such as South Africa. Human genetic variation adds further complexity, with variants af...
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| Format: | Thesis |
| Language: | English |
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Department of Clinical Laboratory Sciences
2022
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| _version_ | 1867613778752831489 |
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| access_status_str | Open Access |
| author | Heekes, Alexa Storme |
| author2 | Mulder, Nicola |
| author_browse | Heekes, Alexa Storme Mulder, Nicola |
| author_facet | Mulder, Nicola Heekes, Alexa Storme |
| author_sort | Heekes, Alexa Storme |
| collection | Thesis |
| description | HIV and Mycobacterium tuberculosis (Mtb) co-infection causes treatment and diagnostic difficulties, which places a major burden on health care systems in settings with high prevalence of both infectious diseases, such as South Africa. Human genetic variation adds further complexity, with variants affecting disease susceptibility and response to treatment. The identification of variants in African populations is affected by reference mapping bias, especially in complex regions like the Major Histocompatibility Complex (MHC), which plays an important role in the immune response to HIV and Mtb infection. We used a graph-based approach to identify novel variants in the MHC region within African samples without mapping to the canonical reference genome. We generated a host-pathogen functional interaction network made up of inter- and intraspecies protein interactions, gene expression during co-infection, drug-target interactions, and human genetic variation. Differential expression and network centrality properties were used to prioritise proteins that may be important in co-infection. Using the interaction network we identified 28 human proteins that interact with both pathogens (”bridge” proteins). Network analysis showed that while MHC proteins did not have significantly higher centrality measures than non-MHC proteins, bridge proteins had significantly shorter distance to MHC proteins. Proteins that were significantly differentially expressed during co-infection or contained variants clinically-associated with HIV or TB also had significantly stronger network properties. Finally, we identified common and consequential variants within prioritised proteins that may be clinically-associated with HIV and TB. The integrated network was extensively annotated and stored in a graph database that enables rapid and high throughput prioritisation of sets of genes or variants, facilitates detailed investigations and allows network-based visualisation. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/36779 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:41:33.763Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Department of Clinical Laboratory Sciences |
| publisherStr | Department of Clinical Laboratory Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/36779 Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions Heekes, Alexa Storme Mulder, Nicola Bioinformatics HIV and Mycobacterium tuberculosis (Mtb) co-infection causes treatment and diagnostic difficulties, which places a major burden on health care systems in settings with high prevalence of both infectious diseases, such as South Africa. Human genetic variation adds further complexity, with variants affecting disease susceptibility and response to treatment. The identification of variants in African populations is affected by reference mapping bias, especially in complex regions like the Major Histocompatibility Complex (MHC), which plays an important role in the immune response to HIV and Mtb infection. We used a graph-based approach to identify novel variants in the MHC region within African samples without mapping to the canonical reference genome. We generated a host-pathogen functional interaction network made up of inter- and intraspecies protein interactions, gene expression during co-infection, drug-target interactions, and human genetic variation. Differential expression and network centrality properties were used to prioritise proteins that may be important in co-infection. Using the interaction network we identified 28 human proteins that interact with both pathogens (”bridge” proteins). Network analysis showed that while MHC proteins did not have significantly higher centrality measures than non-MHC proteins, bridge proteins had significantly shorter distance to MHC proteins. Proteins that were significantly differentially expressed during co-infection or contained variants clinically-associated with HIV or TB also had significantly stronger network properties. Finally, we identified common and consequential variants within prioritised proteins that may be clinically-associated with HIV and TB. The integrated network was extensively annotated and stored in a graph database that enables rapid and high throughput prioritisation of sets of genes or variants, facilitates detailed investigations and allows network-based visualisation. 2022-08-30T10:16:05Z 2022-08-30T10:16:05Z 2022 2022-08-29T10:52:03Z Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/36779 eng application/pdf Department of Clinical Laboratory Sciences Faculty of Health Sciences |
| spellingShingle | Bioinformatics Heekes, Alexa Storme Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions |
| thesis_degree_str | Doctoral |
| title | Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions |
| title_full | Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions |
| title_fullStr | Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions |
| title_full_unstemmed | Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions |
| title_short | Investigation of HIV-TB co-infection through analysis of the potential impact of host genetic variation on host-pathogen protein interactions |
| title_sort | investigation of hiv tb co infection through analysis of the potential impact of host genetic variation on host pathogen protein interactions |
| topic | Bioinformatics |
| url | http://hdl.handle.net/11427/36779 |
| work_keys_str_mv | AT heekesalexastorme investigationofhivtbcoinfectionthroughanalysisofthepotentialimpactofhostgeneticvariationonhostpathogenproteininteractions |