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Double RNAi Screen Provides Insights Into Signaling Networks

NEW YORK (GenomeWeb News) – New research is highlighting the value of double-knockdown experiments for untangling complex signaling networks in fruit fly cells.
In a paper appearing in today’s issue of Science, an international team of researchers studying a cellular stress response pathway used RNA interference to systematically knock down pairs of genes in fruit fly cells. Using an algorithm, they integrated the genetic information with phosphoproteomic data to come up with a more complete view of their pathways and networks of interest. And, researchers say, the approach may aid systems biology research on other animal models as well.
“Data from our novel double RNAi screens provide panoramic views of cellular processes,” senior author Norbert Perrimon, a Howard Hughes Medical Institute investigator who is also affiliated with Harvard Medical School, said in a statement. “By using this approach to expose interactions between genes, researchers may accelerate the pace of discovery in systems biology and advance personalized medicine.”
Perrimon and his team were interested in unraveling a signaling network involved in cell stress response and other processes. The pathway includes proteins known as stress-activated protein kinases, or SAPKs (also called JUN NH2-terminal kinases, or JNKs). In Drosophila, this pathway involves a JNK, which is phosphorylated by a JNK-kinase that is itself phosphorylated by a so-called mixed-lineage kinase.
A few players in this pathway have been identified. But researchers still don’t have a clear understanding of how players in the pathway are regulated, what prompts them to perform different functions, and how they are influenced by other networks.
In an effort to get more insights into the JNK-related network, the researchers first did a traditional RNAi screen in fruit fly cells from several genetic backgrounds, using fluorescence resonance energy transfer reporters to measure JNK activity.
While they were able to detect some JNK regulators, the researchers noticed that the RNAi screen did not pick up genes that were previously shown to influence JNK activity through classical genetic experiments. That made the researchers suspicious that “fail safe” genes were cushioning the pathways, leading to false negatives in the screen.
“Most of these cells and pathways are buffered to take a single hit,” lead author Chris Bakal, a post-doctoral researcher in Perrimon’s lab, told GenomeWeb Daily News. “We’ve evolved so we can take multiple hits, multiple mutations.”
The researchers decided to target two genes at once, reasoning that this would remove some of the cell’s buffering and uncover additional players in the pathway. To do this, they did RNAi screens in fruit fly cells that had specific genes knocked down ahead of time.
The researchers targeted known components of the stress-response pathway, as well as clinically relevant genes, such tumor suppressors, and genes whose absence would induce the stress response, Bakal explained. By individually knocking down a dozen of these carefully selected genes, including PTEN, Rac1, Cdc42, and ERK, the researchers were able to look at the effects of 17,724 double knockdown combinations in the fruit fly cells.
And with some of the fail safes out of the way, the researchers started to see more hits, Bakal said. The team turned up 55 new JNK suppressors and enhancers.
Once they had these hits, Bakal said, the researchers wanted to move from having just a list of genes to a network view. To start with, they pulled together phosphoproteomic data from public databases and used computer models to predict protein-protein interactions and kinase-substrate relationships. Then, using an algorithm, they superimposed the genetic data to see whether the genetic screen supported their predictions and began grouping potential JNK regulators based on biological function.
“[W]e demonstrate that combinatorial RNAi screening is a powerful strategy to reduce the false-negatives present in current screens and reveals functions for a large fraction of genes,” the authors concluded. “Moreover, our data-integrative-powered approach unraveled both mechanistic and hierarchical associations of components in the JNK regulatory system and provides an invaluable starting point for understanding the genetic interactions and signaling networks that underpin various diseases.”

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