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RNAi Screens at the Alberta Institute for Viral Immunology The commercial availability of mammalian siRNA libraries combined with recent developments in high-throughput screening technologies opens new vistas for reverse genetic studies in complex mammalian cell culture systems. With funding provided by the Canada Foundation for Innovation, we have established an RNAi screening core at the Alberta Institute for Viral Immunology. The purpose of the core is to facilitate highthroughput, genome-wide RNAi screens in fly, mouse and human cell culture systems. This guide highlights common variables that may affect the quality of raw screen data and suggests potential solutions. This guide is only intended as a general overview of the preparations required for an RNAi screen and we expect that each experimental protocol will require its own unique adaptations. The process of preparing for a screen is not a linear sequence of events and many of the steps detailed below can be performed in parallel. This guide will not discuss issues such as data analysis and secondary evaluation of screen hits. 1. Identify the biological question. Prior to the initiation of an RNAi screen, we recommend precisely formulating the question you wish to address. A very generally formulated question (e.g. which genes are required for viability of human cells in culture) will likely yield a large and diverse set of “hits” that regulate numerous cellular events. A more specific question (e.g. which genes modify the viability of human cells treated with a specific toxin) will likely identify a narrower, more closely related set of genes. 2. Determine the scope of the screen. Several factors such as cost considerations, reagent availability and user interest determine the amount of siRNAs tested in a given screen. We are in a position to facilitate a range of screens in human, mouse and fly cell lines that range from functional libraries (e.g. kinases/phosphatases/druggable genes) through to whole-genome libraries. Larger screens involve greater investments in terms of time, reagents and disposables and will likely generate a larger set of putative hits to pursue in secondary analysis. 3. Establish a suitable assay. The success of the screen ultimately depends on the quality of the cell culture assay used to investigate the cellular event of interest. There are numerous plate-based assays (luminescence, fluorescence, etc.) each with their respective merits and challenges. When selecting a cell culture assay, we recommend considering the following variables. Specificity. An ideal assay specifically probes the question you are interested in and effectively discriminates against non-specific effects. In many situations, issues such as throughput, reagent costs, instrumentation, etc. place functional limits on the assay you can develop. In this case, a common practice is to develop a less specific primary screen that allows high-throughput identification of all siRNAs that modify the assay under investigation. You can then test putative hits from the primary screen in secondary screens that are more specific for the process being investigated. For example, if you are interested in proteins that mediate apoptosis it is possible to perform a rapid primary screen for genes that affect general cell viability and then test candidate hits from the primary screen in a secondary assay that specifically identifies genes that affect apoptosis. This approach permits a cost-effective identification of a limited number of candidate hits from a rapid screen of thousands of siRNAs. More specific secondary assays validate the role of primary hits in the cellular pathway under investigation. Model system. The cell type used in your screen should reliably “report” the phenomenon you are interested in. However, practical considerations might require you 1 to compromise with the ideal cell type. For example, many primary cell lines and lymphocytes are not accessible to RNAi through standard transfection protocols. In such cases, it is possible to perform the screen in a more assay or RNAi-friendly cell line and test putative hits with secondary assays in a physiologically relevant cell line. This approach allows you to identify a narrow set of potential hits in a convenient primary assay and to verify those hits in a more relevant cell line. Given that the cell line is a critical determinant for success of the screen, we recommend testing several cell lines for assay sensitivity and RNAi efficiency prior to initiation of the screen. Ideally, you would like to identify a cell type that reliably reports your assay and is accessible to RNAi-dependent transcript destruction. Sensitivity. Ideally, the assay will have a large signal to noise ratio, i.e. a large difference between a positive signal and a background signal. Given, that many siRNAs only partially knock down their targets, you can expect that many RNAi phenotypes will correspond to partial loss-of-function phenotypes. Thus, moderate or weak dynamic ranges reduce the likelihood of an assay successfully identifying modifier siRNAs. Assays with large dynamic ranges will typically return the greatest number of true positive hits and will provide greater insights into the process under investigation. It is often instructive to test siRNAs that target known components of the pathway under investigation prior to initiating a large-scale screen. Such siRNAs will provide an insight into the extent to which your assay will “identify” modifiers of the process under investigation and may ultimately serve as useful positive controls throughout the screen. Throughput. This issue sets an effective limit on the scale of your screen. The goal should be to screen as many samples as possible under the same experimental conditions. Ideally, you would complete the entire screen in one run and treat and measure each sample at the same time. In practice, you will likely have to divide your screen into subsets that you will set up on different days, but to keep the sample-tosample variation minimal, you should aim for an assay with high throughput. This includes establishing simple assay protocols with the possibility of automation and to work in 96-well or 384-well plate formats. You should choose an assay that is suitable for these plate formats. Typical readouts of high-throughput assays are fluorescent or luminescent signals on a plate reader, or fluorescent signals on a flow cytometer. We have several automated liquid handlers and plate readers designed to facilitate highthroughput screens and are happy to discuss the needs of an individual investigator. Reproducibility. As screens are typically performed over a period of days to weeks, it is valuable to eliminate assay variability as much as possible. For this reason, we recommend that the assay chosen for the screen functions in a robust, reproducible manner both from day-to-day and in relation to user-defined control siRNAs. To this end, we recommend performing trial runs of several plates with control siRNAs to identify potential sources of assay variability. Counter detection. Variables such as cell number and cell viability can have considerable impact on signal strength in cell culture assays. For example, cell-lethal siRNAs will erroneously appear as modifiers of numerous biological processes and can be a significant source of false-positives in a screen. To discriminate against such siRNAs, we recommend developing a control assay that normalizes your assay signal to the cell number/viability in each well. Typically, we perform RNAi screens with duplicate measurements of the impact of each siRNA on the assay in the presence and absence of the experimental stimulus. In this way, we can quantify and control for the direct effect of each siRNA on the assay. RNAi controls. The siRNA libraries are plated in such a format that each plate contains a minimum of one column devoid of any siRNAs. We recommend spiking control siRNAs into some of these wells as assay controls and also to facilitate plate-to- 2 plate normalization. Typical control siRNAs are scrambled, non-silencing siRNAs that serve as reliable “canaries in the coalmine” for possible non-specific effects of the transfection procedure. Additional potential control siRNAs are pathway-specific siRNAs that negatively or positively influence the process and assay under investigation. These wells serve as positive controls for the detection of modifier siRNAs. We often leave several control wells devoid of any siRNAs to confirm that the assay worked effectively in the assay plate on the day in question. These wells serve as controls for the “health” of the cells and the efficiency of the assay and experimental regime for each plate. Costs. High-throughput RNAi assays are expensive. Typical costs are; plates, transfection reagent, cell culture reagents and assay-specific reagents. We recommend preparing a workflow of your entire screen from assay setup to secondary analysis. It is advisable to evaluate the cost of the planned screen and make sure it matches your budget. 4. Optimizing the RNAi transfections. Optimizing gene knock-down increases the likelihood you will successfully identify modifiers of a particular process. When optimizing knock-down, we recommend you consider the following variables. Duration of RNAi incubation period. The length of time required for a given siRNA to generate a loss-of-function phenotype can vary from gene to gene and from siRNA to siRNA. In most screens, the investigator incubates cells with siRNAs for 48, 72, or 96 hours. Plate format. Performing screens in 96 and 384 well formats has several advantages. Reagent costs per siRNA are greatly reduced in comparison to larger plate formats and the number of sample screened in a single session is greatly increased. Thus, condensing a screen into microplate format increases throughput and decreases reagent costs. However, multiwell plates limit the number of cells that can be screened in a single well and are more susceptible to plate effects. Our RNAi libraries are in 96well format, and can be plated into 384-well plate if needed. An additional option for screening is to pool the siRNAs. In this case, the investigator pools all siRNAs targeting a single gene into a single well. Pooling has several potential advantages and disadvantages. On the one hand, pooling decreases the amount of reagents required for a screen and increases the throughput of a single screen. On the other hand, it is not possible to tell how many siRNAs from a given pool generate a particular phenotype, which may increase the number of false-positives or false negatives. Typically, putative hits from pooled siRNA screens are evaluated by testing each siRNA alone. If an identical phenotype is observed for more than one siRNA, the likelihood of either the phenotype being a false-positive is reduced as it is unlikely that two non-overlapping siRNAs will produce overlapping off-target effects. Cell numbers. For many assays, the cell density critically influences the results. Optimize cell numbers by plating dilution series of cells into your desired plate format and observe their growth over the desired time frame. We recommend performing these assays with control non-silencing siRNAs to determine the extent to which the siRNA protocol will impact on cell growth. The cell density that should be reached by the end of the incubation time depends on the assay that you want to perform afterwards. siRNA concentration. Large siRNA concentrations may be toxic and cause offtarget effects and lower ones may be insufficient to cause a phenotype. Many screens use concentrations of 10 – 30nM siRNAs, while newer generation siRNAs can be used at concentrations as low as 5nM. Transfection conditions. Transfection efficiency is one of the most important variables in a screen. The better you can deplete proteins from cells, the clearer your loss-of-function phenotypes will be. In an ideal situation, you will develop a transfection 3 protocol that gives 100% transfection efficiency and causes no cellular toxicity. We recommend testing several different transfection reagents for toxicity and knock-down efficiency in the cell line to be used in your screen. The transfection conditions should be optimized for the final plate format of your screen (96 or 384 well). We find functional plate assays ideal for optimization of transfection conditions, e.g. measure loss of GAPDH activity after incubation with GAPDH siRNA. We usually test several different transfection reagents against each cell line and identify the transfection reagent that gives optimal knock-down of GAPDH activity and minimal toxicity after the desired incubation period. 5. Screen Optimization. After developing a suitable cell culture assay and determining optimal RNAi conditions, we recommend a trial run prior to embarking on a large-scale screen. At this stage, you should have; determined the plate format, established protocols for all necessary instruments (e.g. liquid handlers, plate readers, etc.), identified appropriate control siRNAs (non-silencing and positive), validated your assay for the given plate format and confirmed detectable gene knock down in the experimental cell type in the chosen plate format. Once these variables have been optimized it is often instructive to perform a mini-screen of a small collection of genes. Such screens can often be completed in a single run and will give insights into potential areas of concern such as; plate effects, assay sensitivity, apparent hit frequency, etc. 6. Screen. When you are satisfied with your trial screen, you are in a position to complete a larger screen. We recommend adhering to the plate layout developed during assay optimization, including the use of non-silencing and positive control siRNAs. Most screens involve at least duplicate measurements of each siRNA under control (e.g. no virus/stimulus) and experimental (e.g. with virus/stimulus) assay conditions. Factors such as handling times, reagent availability and instrument limitations determine the number of samples you can process in a single day. The screen should be set up in such a way that experimental and control replicates for any given plate are processed at the same time under the same experimental conditions. 7. Recommended reading. Reviews. Boutros, M. and Ahringer, J., The art and design of genetic screens: RNA interference. Nat Rev Genet 9 (7), 554 (2008). Primary literature. Friedman, A. and Perrimon, N., A functional RNAi screen for regulators of receptor tyrosine kinase and ERK signalling. Nature 444 (7116), 230 (2006). Konig, R. et al., Global analysis of host-pathogen interactions that regulate early-stage HIV-1 replication. Cell 135 (1), 49 (2008). Simpson, K. J. et al., Identification of genes that regulate epithelial cell migration using an siRNA screening approach. Nat Cell Biol (2008). 4