Abstract
The host’s genetic background is a key determinant of the replication kinetics of the human immunodeficiency virus type 1 (HIV-1). As the virus exploits the cellular machinery, the balance between factors that aid or block infection, known as dependency and restriction factors respectively, will dictate the outcome of infection. For example, deletions in the entry coreceptor CCR5 and variant alleles of the peptide presentation molecule HLA, part of the major histocompatibility complex, can explain protection against this pathogen in some individuals. However, a comprehensive understanding of the interplay between host genetics and its impact on proteins interacting with HIV-1 has remained elusive, stimulating additional research for identification of the complete repertoire of host factors capable of modulating infection.The use of stem cell technologies offers a promising avenue for investigating the impact of host genetics in the context of infections. The HipSci Consortium encompasses a library of reprogrammed pluripotent stem cells (iPSCs) from hundreds of individuals, thereby capturing inherent genetic diversity from distinct genetic backgrounds. Additionally, this platform offers the opportunity to obtain cells naturally targeted by HIV-1, namely blood cells such as CD4+ T cells and macrophages. Although CD4+ T cells are the main targets of the virus, macrophages also contribute to pathogenesis and disease progression. Importantly, these cells can be readily derived from iPSCs, offering an invaluable experimental tool.
In this thesis, I described the development of a novel experimental model that captures naturally occurring genetic variation by differentiating a panel of 25 iPSC lines into macrophages (referred to as iMacs). Firstly, I validated the macrophage identity of these iMacs using transcriptional analysis with bulk RNA-sequencing, surface marker expression through flow cytometry, and functional assays to quantify phagocytosis. I then established a pipeline to characterise the susceptibility to HIV-1infection in this panel, using a HIV-1 based lentiviral vector expressing GFP and replication-competent viruses. Through a series of analytical approaches, I quantified the percentage of GFP-expressing cells and the accumulation of capsid protein Gag in vitro over three timepoints post-infection, which allowed me to assign infection susceptibilities to the cell lines employed in this study, comprising high, average, and low susceptibility to HIV-1. Subsequently, I developed a bioinformatics pipeline to correlate the infection phenotypes with intrinsic transcriptional variation. This approach resulted in the identification of candidate genes that may underpin different susceptibilities to HIV-1 infection. Finally, I illustrated the use of this pipeline by testing potential regulators of HIV-1 infection (i.e., genes that were overexpressed in cell lines showing low levels of infection when compared to highly infected cell lines and vice versa) using an siRNA knockdown library.
Taken together, these findings enhance our understanding of the host variability in susceptibility to HIV-1 and offer novel insights into HIV-1 regulatory networks that will guide further studies.
| Date of Award | 1 Jul 2024 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Michael Malim (Supervisor) & Joana Neves (Supervisor) |