UCT researchers working at the CSIR are making use of image analysis on ICTS's HPC cluster to attempt to identify microRNA molecules that have the potential to inhibit HIV infection. Below is a description of their work by Rethabile Khutlang:
Globally, an estimated 34 million people are infected with the Human Immunodeficiency Virus (HIV-1). HIV is the causative agent of AIDS, a disease for which there is no vaccine, no cure and limited availability of treatment in Africa. As an intracellular pathogen, HIV-1 relies on host cellular machinery to complete its life cycle. Integral to this is the modulation of host gene expression to ensure a co-ordinated regulation of pro- and anti-viral host factors.
MicroRNAs (miRNAs) are short non-coding RNA molecules that represent an endogenous mechanism of interference RNA (RNAi) based regulation of gene expression. miRNAs are able to effect gene silencing by facilitating RNA induced silencing complex (RISC) -mediated degradation of their target messenger RNA (mRNA) molecules. A single miRNA can regulate multiple mRNA molecules that can in turn also be acted upon by numerous miRNAs. Thus, the endogenous miRNA pathway represents a highly efficient system to simultaneously fine-tune the expression of numerous genes as well as modulate specific functional pathways. HIV-1 has been shown to actively manipulate the expression of some host miRNAs during infection but this has not been validated across the current complement of known host miRNAs (miRNAome).
The basic principle of this study is to utilize a high content imaging based approach on a miRNAome-wide scale to identify human miRNAs that are able to differentially modulate HIV-1 infectivity. HIV-1 infectivity will be assayed based on a quantitative fluorescent reporter readout in combination with a multiparimetric analysis of cellular phenotypes. Molecules able to enhance or inhibit the functionality of specific endogenous miRNAs will be transfected into a GFP-based reporter cell line, which will then be infected with HIV-1 virus. Custom image analysis algorithms will be used to quantify GFP fluorescence, evaluate specific cellular phenotypes and identify host miRNAs capable of modulating HIV-1 infectivity.
The results of this study will contribute to a greater understanding of host-pathogen interactions in context of HIV-1 infection and may also lead to the identification of novel targets for therapeutic intervention in the treatment of HIV/AIDS.
