January 1, 2006 (Vol. 26, No. 1)
As Screening Methods Improve, RNAi Proves its Worth in Many Applications
As companies continue to develop assays and software to improve RNAi screening and data analysis, more applications of this assay are being discovered. Some of these potentially include toxicity and ADME assays, enhancing therapeutic potency, and high-throughput screening. Several companies presented information on their most recent RNAi technology and data at the “RNAi for Pathway Analysis” conference in San Francisco and the “RNAi Europe” conference, held in Amsterdam.
High-Content Screening
The combination of RNAi and high-content screening provides a way to gather multiparameter data on individual cellsallowing the user to see, for example, whether there is toxicity, phenotypic changes, or to track specific targets in the cells to understand what effect RNAi may be exerting.
In addition, said Joseph Zock, senior manager, high-content screening user services at Cellomics (www.cellomics.com), this also enables the user to look at primary endpoints and off-target effects, and allows internal control of how experiments are runa key aspect of high-content screening.
One of the challenges of RNAi involves false positives, Bill Marshall, vp of technology and business development at Fisher Biosciences (www.fishersci.com) said. “One of the ways to get around this is through high-content screening and high-content analysis because it’s a much more sophisticated readout. The positive and negative controls show whether you have uptake and enable you to show convincingly that inhibition of that particular gene is associated with the phenomenon you are looking for.”
One way to address off-target effects is to perform independent siRNAs to target the same gene and show the same outcome as in the cellular assays, said Marshall, verifying that target knockdowns correlate with the outcome the user is trying to reach. He added that Dharmacon (www.dharmacon.com) developed chemically modified siRNAs that inactivate the sense strand and lead to specificity enhancement in the targeting strand.
Target validation is one of the main current applications of RNAi. “It’s really introducing a cultural shift in how to approach understanding a target well enough to move to the rest of the drug discovery process,” stated Zock. The company said it is currently developing what it calls compound fingerprinting. This is based on the concept of using siRNA to target genes of interest and create a profile of what happens to the cell when the gene is inhibited.
This is used as a guidepost or fingerprint that points toward screening other drug entities that will match that profile. “This will facilitate and accelerate the development of small molecules and other potential drug entities,” Marshall added.
New Therapeutic Targets
Cenix BioScience (www.cenix-bioscience.com) presented information on its RNAi-based collaboration with Bayer HealthCare (www.bayerhealthcare.com) that produced several novel therapeutic targets. “This is a large study and a nice illustration of what high-throughput RNAi screening can provide,” said Christophe Echeverri, Ph.D., CEO and CSO.
“The screen I describe is in the area of atherosclerosis, identifying genes that, when silenced, cause an upregulation of LDL uptake. This is a major way to lower blood cholesterol levels.”
Bayer transfered cell-based assays in five different disease areas to Cenix. The first phase of the project was to optimize these so they could be run as high-throughput RNAi screens, with the hope that many of them would reach screenable conditions over the 5,000 genes chosen to be therapeutically relevant.
The company combined its high-throughput RNAi with high-content microscopy-based readouts, which integrated three parameters: LDL uptake, cell proliferation, and transferrin uptake as a secondary control assay to make sure the chosen hits specifically affected LDL uptake.
Dr. Echeverri said that a big advantage of high-throughput RNAi screens is that they can eliminate false positives if well-designed and controlled, providing direct links between therapeutic phenotypes and individual genes. However, like all other screening methods, high-throughput RNAi screens will inevitably produce false negatives.
As an example, he described a gene in the cholesterol-screening pathway they wanted to use as a positive control. Out of five different siRNAs designed to target this gene (all provided more than 80% silencing), only the best one, providing 95% silencing, showed the expected induction of LDL uptake.
“This tells you the gene is part of that pathway, but the silencing threshold needed to detect loss of function is extremely high and tight,” Dr. Echeverri added.
At the end of the screen, they had about 40 to 50 hits. “We decided that RNAi offers a great tool to identify those genes easiest to render rate-limiting. We realized we could take siRNAs targeting each of these hits and titrate down the expression of the genes by titrating the RNAi conditions. You can then relate back how much each one needs to be silenced before it starts being rate-limiting for the entire pathway,” explained Dr. Echeverri.
This new validation approach is called Pathway Titration, and provides information that previously was not available. “This can be used as a new criterion for prioritizing target candidates for launching compound screens,” according to Dr. Echeverri.
Adenoviruses provide high transduction efficiency and good reproducible results. This is why GE Healthcare (www.gehealthcare.com) recently launched its ready-to-use validated adenoviral gene-delivery reagents.
“We’ve demonstrated that by comparing this to traditional plasmid-based transient transfection techniques, the adenovirus allows you to put the gene of interest, in our case the assay sensor, to as wide a variety of cells as possible. People want to have a rapid turn-around to produce a new cell sensor,” stated Stephen Game, Ph.D., technology manager, in-cell assays.
The adenovirus is simply added to the cells to quickly allow optimization of the protocol. It can be used with a wide variety of primary and transformed cell types, and the vectors allow interrogation of multiple pathways within a cell.
“We’re trying to cover as many signaling pathways as possible; right now about 12 to 20 key signaling pathways are represented,” added Dr. Game. “At the moment we’re looking at the cytokine signaling pathway associated with statin-signaling responses.”
Each Ad-A-Gene Vector contains a gene encoding a protein target fused to either EGFP (emerald green fluorescent protein) or a gene encoding a response element controlling the expression of the NTR (nitroreductase) reporter gene. The first tends to measure the earlier cell signaling in the transduction pathway, and the second follows a later stage of signal transduction.
Dr. Game says that this new gene-delivery reagent opens the door to high-throughput. “One of the things we want to do is show this is compatible with formats that can be automated. In principal, we would see these being used upstream and downstream of primary screening, like validation efforts associated with profiling against cell-signaling pathways.” The company currently offers eight Ad-A-Gene Vectors. Its goal is to have 50 commercially available by the end of this year.
High-Content Screening and Informatics
Scientists at Wyeth Research (www. wyeth.com) are developing data-analysis techniques and applying statistical approaches to transcriptional profiling sciences. “We have been working with experienced biostatisticians to capture high-content data. The data analysis challenge is huge, but we now have the right hardware and computer processing available,” said Stephen Haney, Ph.D., senior scientist, biological technologies.
“There are good algorithms for designing RNAi against any gene. The challenge is when the knockout is not the same as what occurs with a therapeutic. We use GFP (green fluorescent protein) as a model system for knockdown to show the complexity. In a whole cell assay, you have a control well and a knockdown well.
“This works fine for small molecules, but for RNAi there are many processes that happen in transfection. What you see is a wide range of protein expression at the cell-basis,” explained Dr. Haney.
When two averages are combined, according to Dr. Haney, it hides the fact that there may be up to a 50-fold variation in the protein levels within each sample and the control. Therefore, the mean doesn’t reflect what’s really happening in the cells.
“This is key to what high-content screening can do. It removes the idea of dealing with only two averages and allows users to work with the complexity of the cell itself. That’s very important in thinking about developing therapeutics,” he added.
In addition, high-content allows the user to track subpopulations within a single cell line. This is important since there has been more focus placed on the total dynamics of cell populations. “You can pull them out as groups or you can use unbiased clustering algorithms to discern what’s happening within all the cell populations, much like transcriptional profiling,” said Dr. Haney.
His research group is currently focused on developing tools to provide more information on the complexity of diseases.
Efficient Target Knockdown
Scientists at Integrated DNA Technologies (IDT; www.idtdna.com) have developed compounds that can trigger RNAi at a lower dose. The project, initiated as a research collaboration with John Rossi at the City of Hope, initially looked at using slightly larger RNA duplexes than the traditional 21mers as triggers of RNAi.
“About two years ago, it was known in some model systems that DICER itself could be involved with loading the RISC (RNA-induced silencing complex). We speculated that maybe something might be happening in mammals, that DICER might be involved in RISC loading and wondered if we gave DICER a substrate, would it be more potent or would it have different effects if you gave it a product?” explained Mark Behlke, Ph.D., vp, molecular genetics and biophysics.
IDT created slightly longer RNAs (longer than the traditional 21mers), explained Dr. Behlke, and found that the potency increased. “It surprised us that this hadn’t been noticed before. The optimal size turned out to be around 27mer,” he stated. The researchers then performed further experiments to check if these RNAs were being processed by DICER; it turns out they were. This confirmed the mechanism.
The first example studied had a 100-fold improvement in potency. The scientists redesigned the 27mer and made it asymmetrical so it had an attractive and unattractive binding site. “This forces DICER to bind specifically to one location and cut 21 bases away, giving us the same 21mer cut that we want,” he added.
IDT also discovered that if the 3 overhang resides in the antisense strand, it favors antisense loading into RISC, which is required to target siRNA. Dr. Behlke said they are now developing modifications that can be placed in the 27mers.
