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J Biomol Screen. 2007 Jun;12(4):546-59. Epub 2007 Apr 13.

Optimization procedure for small interfering RNA transfection in a 384-well format.

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1
Genome and Proteome Sciences Department Platform and Chemical Biology Unit Novartis Institutes for Biomedical Research, Cambridge, Massachusetts 02139, USA.

Abstract

High-throughput screening of RNAi libraries has become an essential part of functional analysis in academic and industrial settings. The transition of a cell-based RNAi assay into a 384-well format requires several optimization steps to ensure the phenotype being screened is appropriately measured and that the signal-to-background ratio is above a certain quantifiable threshold. Methods currently used to assess small interfering RNA (siRNA) efficacy after transfection, including quantitative PCR or branch DNA analysis, face several technical limitations preventing the accurate measurement of mRNA levels in a 384-well format. To overcome these difficulties, the authors developed an approach using a viral-based transfection system that measures siRNA efficacy in a standardized 384-well assay. This method allows measurement of siRNA activity in a phenotypically neutral manner by quantifying the knockdown of an exogenous luciferase gene delivered by a lentiviral vector. In this assay, the efficacy of a luciferase siRNA is compared to a negative control siRNA across many distinct assay parameters including cell type, cell number, lipid type, lipid volume, time of the assay, and concentration of siRNA. Once the siRNA transfection is optimized as a 384-well luciferase knockdown, the biologically relevant phenotypic analysis can proceed using the best siRNA transfection conditions. This approach provides a key technology for 384-well assay development when direct measurement of mRNA knockdown is not possible. It also allows for direct comparison of siRNA activity across cell lines from almost any mammalian species. Defining optimal conditions for siRNA delivery into mammalian cells will greatly increase the speed and quality of large-scale siRNA screening campaigns.

PMID:
17435168
DOI:
10.1177/1087057107300172
[Indexed for MEDLINE]
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