The endothelial lining of the cardiovascular system is a target for cardiovascular gene therapy and anti-tumor genetic therapies in vascularized tumors. Nonviral vectors are amenable to large-scale production and are safer than viral vectors. However, the gene transfer efficiency of nonviral vectors is quite low compared to viral vectors, because they are made from engineered materials such as lipids or polymers that lack the targeting and delivery moieties of viral vectors. The shortcomings of nonviral vectors are only exacerbated in non-dividing or confluent cell types, such as endothelial cells.
To improve the efficiency of lipid-based nonviral vectors, a detailed understanding of the lipofection mechanism is necessary. A powerful method to understand the importance of host factors is loss-of-function analysis. RNA interference (RNAi) is a rapidly growing technique capable of silencing the expression of every gene in the human genome, which is transferable to loss-of-function mechanistic studies.
Here, we used RNAi to probe the mechanism of nonviral gene transfer to human aortic endothelial cells with two approaches. In the first approach, human lysosomal DNase II was silenced using shRNAs and siRNAs. Following the knock down of DNase II, we found no change in lipofection efficiency, which indicates that DNase II was not a significant barrier in our system.
In a second approach, we performed an RNAi-based high-throughput screen to determine the importance of 5,520 genes on lipofection. Following confirmation studies, 33 genes, when silenced, improved lipofection with 1 or more siRNAs and 18 genes improved lipofection with 2 or more siRNAs. We selected 5 lead candidates, from which we identified 3 gene targets corresponding to cell cycle regulatory proteins. In larger scale experiments, knocking down the gene PPP2R2C using the leading candidate siRNA caused a 75% increase in raw luminescence from nonviral gene transfer, and a 10% increase in the number of cells transfected. Therefore, this work demonstrates the utility of using RNAi to understand the mechanism of lipofection, specifically by identifying host proteins that can enhance or reduce gene transfer efficiency.
