Small interfering RNAs (siRNAs) are capable of effectively down-regulating gene expression in mammalian cells through RNA interference (RNAi). Analysis of the phenotypic effects of gene silencing can elucidate the role of a particular gene in various biological pathways. RNAi-based gene function analysis is particularly powerful when used in conjunction with high-content screening where phenotypic changes can be analyzed using multi-parametric assays at the single cell level. In this study, we performed parallel knockdown of 80 genes that are known or predicted to be involved in cell cycle regulation using SMARTpool siRNA reagents from Dharmacon, Inc., and monitored four relevant phenotypes (cell cycle, nuclear area, cell count, and localization of phospho-ERK) using ArrayScan VTI from Cellomics, Inc. We demonstrate that cell cycle status and phenotypic changes in cell populations can be easily assayed using a highly specific and functional siRNA library followed by data acquisition using high-content screening instrumentation and software. Our screen yielded several novel positive hits after gene silencing in addition to expected phenotypic changes for those genes known to be involved in cell cycle events. For example, silencing of CCNA2 and CDC2 results in an increase in nuclear area consistent with the phenotype of known CCNA2 and CDC2 mutations that result in an arrest in G2 (and concomitant increase in nuclear area). Similarly, knockdown of PLK1 induces an increase in the 4N population, a phenotype consistent with silencing of this key regulator of mitotic progression in mammalian cells. Overall, these results demonstrate the utility of merging two important technologies - high throughput RNAi-mediated silencing and high-content screening platforms. The combination can be extremely informative for high-throughput screens with collections of siRNAs targeting genes related by function or phylogeny and for determining the contribution of individual genes in various pathways. In particular, the use of an siRNA library targeting genes involved in cell cycle regulation in conjunction with automated cellular analyses and multiple cellular phenotypic readout assays can be used to identify genes involved in cancer development and progression.
[Proc Amer Assoc Cancer Res, Volume 47, 2006]