Viral-mediated gene delivery for cell-based assays in drug discovery
- PMID: 23489124
- DOI: 10.1517/17460440902751599
Viral-mediated gene delivery for cell-based assays in drug discovery
Abstract
Background: Adenovirus, retrovirus and lentivirus-based vectors, originally engineered and optimized for in vivo and ex vivo gene therapy, have become increasingly useful for viral-mediated gene delivery to support in vitro cell-based assays. Viral vectors underpin functional genomics screening of cDNA, shRNA and aptamer libraries, are used for a variety of target validation studies and importantly, for high-throughput cell-based drug discovery and compound profiling assays. The baculovirus/insect cell expression system had gained prevalence as a tool for recombinant protein production when it was observed that recombinant baculovirus vectors too could serve as efficient gene delivery vehicles for a wide range of mammalian cells. Although the use of baculovirus vectors in vivo has lagged behind retroviral, adenoviral and lentiviral vectors, they have gained prominence for development of in vitro cell-based assays due to the ease of generation, broad host range and excellent biosafety profile. There is an increasing emphasis on cell-based assays in high-throughput automated drug discovery laboratories and a variety of commercially available viral-vectors can be used for supporting these assays.
Objective: We compare and contrast the current viral-mediated gene delivery vector systems and highlight their suitability for cell-based drug discovery assays.
Conclusion: Viral-mediated gene delivery is increasingly being used in support of genome scale target validation studies and cell-based assay development for specific drug target genes such as ion channels, G protein-coupled receptors and intracellular enzymes. The choice of a delivery system over another for a particular application is largely dictated by the cell types and cell lines in use, virus cellular tropism, assay throughput, safety requirements and ease/cost of reagent generation.
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