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High-Content Imaging Analysis of the Knockdown Effects of Validated siRNAs and Antisense Oligonucleotides
Jonathan Low
Cancer Growth and Translational Genetics. Eli Lilly and Company, Indianapolis, IN
Shuguang Huang
Genomic and Molecular Informatics, Eli Lilly and Company, Indianapolis, Indiana
Michele Dowless
Cancer Growth and Translational Genetics. Eli Lilly and Company, Indianapolis, IN
Wayne Blosser
Cancer Growth and Translational Genetics. Eli Lilly and Company, Indianapolis, IN
Thomas Vincent
Oncology, Isis Pharmaceuticals, Carlsbad, California
Scott Davis
Oncology, Isis Pharmaceuticals, Carlsbad, California
Jeff Hodson
Oncology, Isis Pharmaceuticals, Carlsbad, California
Erich Koller
Oncology, Isis Pharmaceuticals, Carlsbad, California
Eric Marcusson
Oncology, Isis Pharmaceuticals, Carlsbad, California
Kerry Blanchard
Cancer Growth and Translational Genetics. Eli Lilly and Company, Indianapolis, IN
Louis Stancato
Cancer Growth and Translational Genetics. Eli Lilly and Company, Indianapolis, IN, l.stancato{at}lilly.com
High-content imaging (HCI) provides researchers with a powerful tool for understanding cellular processes. Although phenotypic analysis generated through HCI is a potent technique to determine the overall cellular effects of a given treatment, it frequently produces complex data sets requiring extensive interpretation. The authors developed statistical analyses to decrease the time spent to determine the outcome of each HCI assay and to better understand complex phenotypic changes. To test these tools, the authors performed a comparison experiment between 2 types of oligonucleotide-mediated gene silencing (OMGS), antisense oligonucleotides (ASOs), and short, double-stranded RNAs (siRNAs). Although similar in chemical structure, these 2 methods differ in cellular mechanism of action and off-target effects. Using a library of 50 validated ASOs and siRNAs to the same targets, the authors characterized the differential effects of these 2 technologies using a HeLa cell G2-M cell cycle assay. Although knockdown of a variety of targets by ASOs or siRNAs affected the cell cycle profile, few of those targets were affected by both ASOs and siRNAs. Distribution analysis of population changes induced through target knockdown led to the identification of targets that, when inhibited, could affect the G2-M transition in the cell cycle in a statistically significant manner. The distinctly different mechanisms of action of these 2 forms of gene silencing may help define the use of these treatments in both clinical and research environments. (Journal of Biomolecular Screening 2007:775-788)
Key Words: mitosis • high-content screening • siRNA • antisense oligonucleotide • distribution analysis
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This version was published on September
1, 2007
Journal of Biomolecular Screening, Vol. 12, No. 6,
775-788 (2007)
DOI: 10.1177/1087057107302675
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