A spatially resolved high-dimensional approach towards investigating HIV infection in situ

Abstract

Exploring viral diseases in the tissue context is important as it accounts for factors within the microenvironment that can influence infection. In the context of HIV, in situ studies using human tissue have been conducted to a significantly lesser extent than suspension-based studies. A key contributing factor to this is the limitations of traditional methods for the detection of HIV and immune cells. Emerging imaging modalities have become available that redefine the limits of detection, in terms of the sensitivity and the number of targets that can be identified. In light of these advancements, and the need to understand the events underpinning HIV transmission in the human colorectum, in this thesis we present an optimised 35 marker imaging mass cytometry panel for the co-detection of HIV RNA and protein markers. This is achieved by implementing RNAscope, a highly sensitive in situ hybridisation technique that can detect HIV with up to single molecule sensitivity. A drawback of IMC datasets however are the challenging image processing requirements. To that end, we developed a computational pipeline that facilitates multiple processing requirements relevant for the study of host-virus interactions. Using the optimised panel along with this pipeline, we then applied this to human colorectal explants in order to spatially profile the immune landscape during steady state, inflammation, and HIV transmission. We find there are differences in the immune cell compositions across the mucosal compartments, and that inflammation can alter the proportions of specific subsets, with potential implications for viral transmission. We observe spatial heterogeneity amongst lymphoid aggregates and expand on the repertoire of cells that can interact with HIV in situ. Finally, we observe differences in the dynamics between cells in the presence of HIV, suggesting that exposure to HIV can alter the complex interplay that occurs at the tissue level.