Name: MISSION esiRNA for RNAi Screening in Mammalian Cells (Video) | JoVE Journal
Uploaded: 2010-05-12T17:45:00.000+00:00
Duration: 15 min 31 s
Description: Learn esiRNA screening for cell cycle gene identification in mammalian cells using high-throughput RNAi methods. This protocol demonstrates optimized transfection, automated screening, and statistical validation for robust functional genomics research.

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5 minutes

We would like to acknowledge members of the Buchholz laboratory and the Sigma-Aldrich RNAi-team for discussion. We would like to thank the Max Planck Society and the Bundesministerium f&uuml;r Bildung und Forschung grands Go-Bio [0315105] for support.
MISSION &reg; is a registered trademark of Sigma-Aldrich Biotechnology L.P.

1. High-quality MISSION esiRNA libraries
<ol>
	<li>For every gene of interest the most susceptible and specific target region for RNAi is chosen utilizing the DEQOR algorithm (http://cluster-1.mpi-cbg.de/Deqor/deqor.html).4 DEQOR scores the silencing potential of all possible 21 nucleotides long siRNAs in a target-mRNA based on state-of-the art design-constraints4. In addition, each potential siRNA is analyzed for possible cross-reactivity with other genes by performing a BLAST search against the transcriptome of the organism studied. The program thereby provides an analysis of the overall quality and cross-silencing capacities of the potential esiRNA (300-600 bp length).</li>
	<li>The chosen region of the target-gene cDNA is amplified by PCR using gene-specific primers flanked by bacteriophage RNA-polymerase-promoter sequences.</li>
	<li>Every PCR product used for MISSION esiRNA production is verified for identity by sequencing and for purity by Caliper Labchip analysis.</li>
	<li>Long double-stranded RNA is transcribed from the PCR-product by RNA polymerase, followed by an annealing of the transcribed strands.</li>
	<li>esiRNAs are prepared by limited enzymatic digestion of the long double-stranded RNA using RNaseIII followed by purification via anion-exchange chromatography utilizing Q-sepharose spin columns.</li>
	<li>esiRNAs are precipitated and resuspended in TE buffer. The yield is measured by UV-absorption measurements and the concentration is adjusted by dissolving in an appropriate volume of TE buffer. The overall quality of the final product is checked by Caliper Labchip analysis.</li>
</ol>
2. Choosing a cell line and optimizing transfection for screening
<ol>
	<li>Titrate amounts of esiRNA (use Eg5 as positive and renilla-luciferase as negative control) and increasing amounts of transfection reagent in a 384-well plate, add cells and incubate for 48 hours. Eg5 is a kinesin motor protein required for bipolar spindle assembly and depletion leads to a mitotic arrest. Repeat this procedure for different transfection reagents and cell lines. Here, we use HeLa cells cultured following standard procedures and oligofectamine (Invitrogen) as transfection reagent.</li>
	<li>For choosing the optimal transfection conditions count the cells transfected with Eg5 esiRNAs that show a mitotic arrest (round shape) and the total number of cells transfected with renilla-luciferase (RLUC) esiRNA by light microscopy. Choose the condition with the least toxicity for RLUC and the most pronounced phenotype for Eg5. An alternative method for optimizing transfection conditions involves a stable cell line expressing EGFP (or another suitable reporter gene) under the control of a constitutive active promoter. After transfection of an esiRNA against EGFP (or another reporter gene) and RLUC (or another suitable negative control esiRNA) measure knock-down efficacy and toxicity by e.g. fluorescence assisted cell sorting (FACS). Make sure that the used esiRNA for EGFP is fully complementary to the target-mRNA.</li>
</ol>
3. Setting Up the Primary screen5,6
<ol>
	<li>Optimize the pipetting accuracy for all used components on an automated pipetting station (e.g. Aquarius, Tecan and WellMate, Matrix). Because pipetting parameters change depending on the type of solution, volume and plate type this optimization has to be repeated for every step separately. If possible, the pipetting station should be placed under a laminar flow hood to avoid contaminations. All used components should be sanitized before use either by autoclaving if applicable or by spraying with 75% ethanol. Optimize wash-protocols so that cross-contamination from well to well is excluded. Details for the optimization of automated pipetting cannot be give for space-constraints and depend largely on the utilized pipetting station. For further information refer to the manufactures protocol.</li>
	<li>Transfect cells in 384-well format using the optimized conditions from above with esiRNAs for Eg5 and RLUC. Use an alternating pattern for Eg5 and RLUC esiRNA covering the whole plate.</li>
	<li>After incubation for 48 hours fix the cells with cold 100% ethanol, rehydrate in PBS for 15 minutes, stain for 25 minutes in PBS containing 1 &mu;g/ml DAPI and 100 &mu;g/ml RNase A (Qiagen). Finally wash with PBS and store at 4&deg;C.</li>
	<li>Measure intensity of DAPI-fluorescence by microscopy e.g. on an Olympus ScanR system. Generate a histogram by plotting DAPI intensity against cell number and evaluate the cell cycle distribution by calculating the percentage of cells with the DNA-content 2N for G1-phase; &lt; 2N &gt; 4N for S-phase; 4N for G2/M-phase and &gt; 4N for aneuploidy/polyploidy.</li>
	<li>Evaluate the homogeneity of the results over the plate. Further optimization is needed if results differ significantly to exclude position effects. A common problem when using multi-well plates is enhanced evaporation at the edge wells during incubation time. This leads to different experimental conditions in different wells, which often translates to plate-position specific effects. For this reason, we recommend to leave all edge wells empty for a screen. To further minimize evaporation make sure that the incubators are kept at high humidity. We also routinely employ evaporation barriers such as Corning Breathable Sealing Tape which block evaporation. Also other resources for position effects have to be taken into consideration, e.g. technical variation of the readout system (microscope, plate reader, etc) or variations in liquid handling (gradients, inhomogeneity of solutions, etc).</li>
	<li>The statistical differences between positive and negative controls provide a measure for the significance of the assay employed. A large difference between negative control (or background noise; mock-control) and sample has to be established before starting the actual screening. A good measure for the statistical significance is the Z-factor. The Z-factor is calculated following the equation: 
 Z = 1- (3 SD[sample] + 3 SD[mock]) * (|Av[sample] - Av[mock]|)-1; with SD: standard deviation; Av: average. A Z-factor of 1 &gt; Z &gt; 0.5 indicates a statistically significant separation of negative controls (and noise) from the positive controls7.</li>
</ol>
4. Primary screen
<ol>
	<li>Prepare 384-well tissue culture plates for transfection of esiRNAs utilizing the optimized conditions from above. Here, we use 15ng esiRNA per well dissolved in 5&mu;l TE buffer. At least eight control positions per plate should be loaded with suitable positive and negative controls for the biological process studied (here: Eg5 and RLUC). To avoid position effects the edge wells are loaded with 5&mu;l TE buffer only.</li>
	<li>Add 5&mu;l OptiMEM (Invitrogen) containing 0.2&mu;l Oligofectamine per well, mix and incubate for 20 minutes at room temperature.</li>
	<li>Add cell suspension onto the transfection mixture (here: 40&mu;l of a HeLa cell suspension at 25 cells/&mu;l concentration; equivalent to 1000 cells per well) and incubate for 72 hours.</li>
	<li>Measure DNA-content on an automated microscope (Olympus ScanR, see above). Evaluate using Z-score statistics for hit selection: Z-scores are calculated for all sample esiRNAs using the signal for the negative control as reference. Note, the Z-score is not the same as the Z-factor. Z-scores provide a statistical measure for significance of sample values in comparison to a (mock-) control. It is calculated following the equation: 
 Z = (value[Sample] - average[mock]) * standard-deviation[mock]-1. 
 For hit selection a threshold has to be applied. Typically, a significance criteria like: 2 &lt; Z &lt; -2 is used, but depending on the quality of the dataset, the studied biological process or simply the scope of the screen, different thresholds may be applicable. Beside the fairly easy Z-score statistics also more elaborate mathematical evaluation methods can be used (a first inside into the wide field of statistical evaluation of screening data can be found in Malo et al.8).</li>
</ol>
5. Secondary screen and hit validation
<ol>
	<li>A secondary screen follows the primary screen to eliminate false positives due to experimental errors or off-target effects. For the selected hits the same procedure as used in the primary screen should be repeated for a bigger number of replicates (3-5) to allow a better statistical evaluation.</li>
	<li>For verified hits a secondary non-overlapping esiRNA (or another non-overlapping silencing trigger) against the targets identified in the initial screens should be used. The same assay and read-out should be applied as for the primary screen.</li>
	<li>Ultimately the selected genes can be validated by cross-species RNAi rescue9. Thereby a bacterial artificial chromosome (BAC) encoding e.g. the mouse ortholog of the gene is stably transfected into cells. BAC-constructs preserve a gene in its genomic context and allow for a nearly-physiological expression. RNAi against the endogenous human gene will leave the mouse transgene expression unaltered which rescues the RNAi-phenotype. RNAi-rescue provides the gold-standard for the verification of RNAi phenotypes available to date.</li>
	<li>Finally, the validated candidates are studied in more detail to eventually derive mechanistic understanding. In many cases RNAi can be used in these experiments, e.g. in secondary, more elaborate assays.</li>
</ol>

<ol><li>Ghildiyal, M., Zamore, P. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Small+silencing+RNAs%3A+an+expanding+universe%5BTitle%5D)+AND+%22Nat+Rev+Genet%22%5BJournal%5D)">Small silencing RNAs: an expanding universe.</a> Nat Rev Genet. 10, 94-108 (2009).</li>
<li>Jackson, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Expression+profiling+reveals+off-target+gene+regulation+by+RNAi%5BTitle%5D)+AND+%22Nat+Biotechnol%22%5BJournal%5D)">Expression profiling reveals off-target gene regulation by RNAi.</a> Nat Biotechnol. 21, 635-637 (2003).</li>
<li>Echeverri, C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Minimizing+the+risk+of+reporting+false+positives+in+large-scale+RNAi+screens%5BTitle%5D)+AND+%22Nat+Methods%22%5BJournal%5D)">Minimizing the risk of reporting false positives in large-scale RNAi screens.</a> Nat Methods. 3, 777-779 (2006).</li>
<li>Henschel, A., Buchholz, F., Habermann, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((DEQOR%3A+a+web-based+tool+for+the+design+and+quality+control+of+siRNAs%5BTitle%5D)+AND+%22Nucleic+Acids+Res%22%5BJournal%5D)">DEQOR: a web-based tool for the design and quality control of siRNAs.</a> Nucleic Acids Res. 32, W113-W120 (2004).</li>
<li>Kittler, R., Pelletier, L., Buchholz, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Systems+biology+of+mammalian+cell+division%5BTitle%5D)+AND+%22Cell+Cycle%22%5BJournal%5D)">Systems biology of mammalian cell division.</a> Cell Cycle. 7, 2123-2128 (2008).</li>
<li>Kittler, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Genome-scale+RNAi+profiling+of+cell+division+in+human+tissue+culture+cells%5BTitle%5D)+AND+%22Nat+Cell+Biol%22%5BJournal%5D)">Genome-scale RNAi profiling of cell division in human tissue culture cells.</a> Nat Cell Biol. 9, 1401-1412 (2007).</li>
<li>Zhang, J. H., Chung, T. D., Oldenburg, K. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+Simple+Statistical+Parameter+for+Use+in+Evaluation+and+Validation+of+High+Throughput+Screening+Assays%5BTitle%5D)+AND+%22J+Biomol+Screen%22%5BJournal%5D)">A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.</a> J Biomol Screen. 4, 67-73 (1999).</li>
<li>Malo, N., Hanley, J. A., Cerquozzi, S., Pelletier, J., Nadon, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Statistical+practice+in+high-throughput+screening+data+analysis%5BTitle%5D)+AND+%22Nat+Biotechnol%22%5BJournal%5D)">Statistical practice in high-throughput screening data analysis.</a> Nat Biotechnol. 24, 167-175 (2006).</li>
<li>Kittler, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((RNA+interference+rescue+by+bacterial+artificial+chromosome+transgenesis+in+mammalian+tissue+culture+cells%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci+U+S+A%22%5BJournal%5D)">RNA interference rescue by bacterial artificial chromosome transgenesis in mammalian tissue culture cells.</a> Proc Natl Acad Sci U S A. 102, 2396-2401 (2005).</li>
<li>Kittler, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Genome-wide+resources+for+endoribonuclease-prepared+short+interfering+RNAs+for+specific+loss-of-function+studies%5BTitle%5D)+AND+%22Nat+Methods%22%5BJournal%5D)">Genome-wide resources for endoribonuclease-prepared short interfering RNAs for specific loss-of-function studies.</a> Nat Methods. 4, 337-344 (2007).</li>
</ol>

Authors declare financial relationships with commercial entities that might have an interest in the submitted work.

RNA interference has become a standard technique to study loss-of-function phenotypes. Large-scale collections of RNAi-mediators are available from different suppliers and provide an easy, cost-effective and rapid method for gene-silencing. This opened the gate for systematic screening for key-players in many biological processes allowing a genome-scale perspective on a wide range of different species and cell types.
High false positive and false negative rates are a common challenge in RNAi screens. To address this problem, considerable efforts have been invested to improve the efficacy and in particular the specificity of the silencing triggers. An important discovery was that a pool of different siRNAs targeting the same transcript greatly enhances target specificity. Because a very complex pool of different siRNAs is produced by the endoribonuclease, esiRNAs are high target specificity triggers, reducing the false positive rate in RNAi screens. esiRNAs have also demonstrated to achieve efficient knockdowns, reducing also the false negative rate.
Because RNAi screens are technically demanding, they will likely remain challenging to perform on a routine basis for some time. However, as reagents and instruments get better and more laboratories share their expertise, the use of RNAi screens in modern biology are deemed to increase in the future.

<table><tbody><tr><td>MISSION esiRNA</td><td>Sigma-Aldrich</td><td></td><td>For additional information contact: rnai@sial.com</td></tr><tr><td>Wellmate</td><td>Thermo Fisher Scientific, Inc.</td><td></td><td></td></tr><tr><td>Breathable sealing tape</td><td>Corning</td><td>Breathable Sealing Tape, Sterile (Product #3345)</td><td></td></tr><tr><td>OptiMEM</td><td>Invitrogen</td><td></td><td></td></tr><tr><td>&lt;a href=&quot;http://www.sigmaaldrich.com/catalog/ProductDetail.do?lang=en&amp;amp;N4=E7023%7CSIAL&amp;amp;N5=SEARCH_CONCAT_PNO%7CBRAND_KEY&amp;amp;F=SPEC&amp;amp;cm_sp=affiliate-_-Jove-_-12346&quot;&gt;Ethanol&lt;/a&gt;</td><td>Sigma-Aldrich</td><td>E7023</td><td>200 proof (absolute), for molecular biology</td></tr><tr><td>&lt;a href=&quot;http://www.sigmaaldrich.com/catalog/ProductDetail.do?lang=en&amp;amp;N4=P5493%7CSIGMA&amp;amp;N5=SEARCH_CONCAT_PNO%7CBRAND_KEY&amp;amp;F=SPEC&amp;amp;cm_sp=affiliate-_-Jove-_-12347&quot;&gt;Phosphate buffered saline&lt;/a&gt;</td><td>Sigma-Aldrich</td><td>P5493</td><td>BioReagent, 10x concentrate, suitable for cell culture, for molecular biology</td></tr><tr><td>&lt;a href=&quot;http://www.sigmaaldrich.com/catalog/ProductDetail.do?lang=en&amp;amp;N4=D8417%7CSIGMA&amp;amp;N5=SEARCH_CONCAT_PNO%7CBRAND_KEY&amp;amp;F=SPEC&amp;amp;cm_sp=affiliate-_-Jove-_-12348&quot;&gt;4&amp;#8242;,6-Diamidino-2-phenylindole dihydrochloride&lt;/a&gt;</td><td>Sigma-Aldrich</td><td>D8417</td><td>Poweder, BioReagent, suitable for cell culture, &amp;gt;98% (HPLC and TLC)</td></tr><tr><td>&lt;a href=&quot;http://www.sigmaaldrich.com/catalog/ProductDetail.do?lang=en&amp;amp;N4=R6513%7CSIGMA&amp;amp;N5=SEARCH_CONCAT_PNO%7CBRAND_KEY&amp;amp;F=SPEC&amp;amp;cm_sp=affiliate-_-Jove-_-12349&quot;&gt;Ribonuclease A from bovine pancreas&lt;/a&gt;</td><td>Sigma-Aldrich</td><td>R6513</td><td>For molecular biology, &amp;#8805;70 Kunitz units/mg protein, lyophilized powder</td></tr><tr><td>&lt;a href=&quot;http://www.sigmaaldrich.com/catalog/ProductDetail.do?lang=en&amp;amp;N4=T9285%7CSIGMA&amp;amp;N5=SEARCH_CONCAT_PNO%7CBRAND_KEY&amp;amp;F=SPEC&amp;amp;cm_sp=affiliate-_-Jove-_-12350&quot;&gt;Tris-EDTA buffer solution&lt;/a&gt;</td><td>Sigma-Aldrich</td><td>T9285</td><td>100 x, for molecular biology</td></tr></tbody></table>

mission esirna for rnai screening in mammalian cells

MISSION esiRNA for RNAi Screening in Mammalian Cells

RNA interference (RNAi) is a basic cellular mechanism for the control of gene expression. RNAi is induced by short double-stranded RNAs also known as small interfering RNAs (siRNAs). The short double-stranded RNAs originate from longer double stranded precursors by the activity of Dicer, a protein of the RNase III family of endonucleases. The resulting fragments are components of the RNA-induced silencing complex (RISC), directing it to the cognate target mRNA. RISC cleaves the target mRNA thereby reducing the expression of the encoded protein1,2,3. RNAi has become a powerful and widely used experimental method for loss of gene function studies in mammalian cells utilizing small interfering RNAs.
Currently two main methods are available for the production of small interfering RNAs. One method involves chemical synthesis, whereas an alternative method employs endonucleolytic cleavage of target specific long double-stranded RNAs by RNase III in vitro. Thereby, a diverse pool of siRNA-like oligonucleotides is produced which is also known as endoribonuclease-prepared siRNA or esiRNA. A comparison of efficacy of chemically derived siRNAs and esiRNAs shows that both triggers are potent in target-gene silencing. Differences can, however, be seen when comparing specificity. Many single chemically synthesized siRNAs produce prominent off-target effects, whereas the complex mixture inherent in esiRNAs leads to a more specific knockdown10.
In this study, we present the design of genome-scale MISSION esiRNA libraries and its utilization for RNAi screening exemplified by a DNA-content screen for the identification of genes involved in cell cycle progression. We show how to optimize the transfection protocol and the assay for screening in high throughput. We also demonstrate how large data-sets can be evaluated statistically and present methods to validate primary hits. Finally, we give potential starting points for further functional characterizations of validated hits.

Here we use a human esiRNA library in a high-throughput screen for genes involved in cell division. We demonstrate how to set up and conduct an esiRNA screens, as well as how to analyze and validate the results.

RNA interference (RNAi) is a basic cellular mechanism for the control of gene expression. RNAi is induced by short double-stranded RNAs also known as ...

Screening for cell cycle Associated genes by RNA AI starts with choosing an appropriate knockdown technology mission.Easy. RNA libraries from Sigma Aldridge makes use of the high efficiency and specificity of endo ribonuclease prepared si. A easy RNAs are complex pools of individual SI RNAs, prepared by enzymatic digest of long double stranded RNA, complementary to the target MNA pooling of SI RNAs targeting the same transcript, increases specificity, and prevents the laborious search for efficient and specific individual SI RNAs.This makes easy RNA especially suitable for large and medium scale loss of function screens. Here we show the steps necessary for performing a large scale RNA eye screen, starting from setting up high throughput transfect to the development of an appropriate assay. This is exemplified by setting up a screen for genes involved in mammalian cell cycle progression.First, we show how transfection of hilar cells as optimized, followed by statistical evaluation of the assay quality. Finally, a genome scale screen is performed measuring cell cycle distribution after target gene depletion. The hits are selected using the zco statistic and verified by secondary independent easy RNAs.Furthermore, we outline potential experimental procedures that can be used to follow up the RNA eye screen. Hi, I am Ty from the Max Plank Institute of Molecular Cell Biology and Genetics. And Tristan.I'm Frank Al, also from the Marx Plunk Institute in Dresden. Today we will show you a procedure for setting up a loss of function screen in mammalian cells utilizing mission easy RNAs from Sigma Aldridge. An essay for measuring cell cycle distribution in a population of tissue culture cells will be used as an example to demonstrate how genes can be linked to biological process using RNAi screening.So let's get started. Every RNAi screening project starts with a choice of silencing triggers, employed endo ribonuclease prepared si, RNAs, or easy RNAs for short are generated by limited enzymatic digestion of long double stranded RNA using RNAs three. Every easy RNA is verified for identity by sequencing and for purity by caliper lab chip analysis.Pooling of individual siRNAs all targeting the same transcript increases specificity because every irna in the pool shares the same on target, whereas the off-target effects are diluted out. Therefore, easy RNAs have good silencing efficacy and high target specificity, avoiding off-target effects. Genome scale easy.RNA libraries are provided by Sigma Aldrich. In 384, well plates with the edge wells empty. Additionally, eight positions in the center of the plate are left empty for controls.Sub libraries of easy RNAs are provided in 96 well plates with all wells occupied here, the customers can decide on how the easy RNAs will be arrayed in those plates. Individual easy RNAs are provided in single tubes. Transfection of easy RNA requires optimization for different transfection reagents and cell lines.Here heal our cells cultured following standard procedures and oligo as transfection reagent is used. Use EEG five E-Z-R-N-A-A kinesin motor protein required for bipolar spindle assembly as a positive control and ran luciferase easy RNA as a negative control. In a 384 well plate titrate different amounts of easy RNA, for instance, from one nanogram to 56 nanograms with an increment of five nanograms and increasing amounts of transfection reagent from 0.1 microliters to 0.9 microliters with an increment of 0.05 microliters.After mixing the RNA and the transfection reagent, add the cells and incubate for 48 hours. When the incubation period has finished, check the cells under a light microscope. Count the cells transfected with eeg.Five easy RNAs that show a round shape indicative of mitotic. Rest also count the total number of cells transfected with a negative control. Gran vanilla luciferase easy RNA.The optimal transfection condition shows the least toxicity for vanilla luciferase and the most pronounced phenotype for EEG five. Now that the transfection parameters are optimized, proceed to set up and primary screen. Automated pipetting stations such as Matrix Wellm Mate or Tecan Aquarius used to prepare the primary screens should be placed under lamina flow hood to avoid contamination.All used components should be sanitized before use, either by autoclaving if applicable or by spraying with 75%ethanol prior to the screen. These instruments should be optimized according to the manufacturer's protocols. Optimize the pipetting accuracy for all used components on the automated pipetting station because pipetting parameters change depending on the type of solution volume and plate type.This optimization has to be repeated for every step separately. In addition, optimize the wash protocols so that cross-contamination from well to well is excluded when the automated pipetting stations are ready. Transfect cells in 384 well format using the optimized conditions previously determined to make sure that no position effects are observed.Use easy RNAs for EEG five and vanilla luciferase with an alternating pattern covering the whole plate. Leave all edge wells empty since a common problem when using multi-well plates is enhanced evaporation at the edge wells during incubation time. This leads to different experimental conditions in different wells, which often translates to plate position effects to further minimize evaporation, employee evaporation barriers such as Corning, breathable ceiling tape.Also make sure that the incubators are kept at high humidity. However, remember that there are the possible sources for position effects such as variation in liquid handling or the readout system such as a plate reader. After incubation for 48 hours, fix the cells with ice cold, 100%ethanol for two hours, then rehydrate in PBS for 15 minutes.Stain the fixed cells for 25 minutes in PBS containing one microgram per milliliter of DPI and 100 micrograms per milliliter of RNAs. A finally wash three times with PBS and store at four degrees Celsius. Next, measure the intensity of DPI fluorescence by microscopy.An Olympus scanner system is used here for each. Well examine the cells and determine the relative DPI intensity. Generate a histogram by plotting DPI intensity against cell number based on the histogram.Evaluate the cell cycle distribution by calculating the percentage of cells with A DNA content two N for G one G zero phase between two N and four N for S-phase four, N for G two MPH phase and larger than four N for aneuploidy or polyploidy. In order to evaluate the homogeneity of the results over the plate, compare the cell cycle distribution between the different wells by comparing the percentage of cells in G two M phase for the EEG five and luciferase transfect if the results differ significantly over the plate, further optimization is required to eliminate position effects. Once satisfied with the consistency of the results, calculate the statistical differences between the positive and negative controls.Use the Z factor equation shown here to determine the statistical significance of the results. SD stands for standard deviation and AV stands for average. A Z factor between one and 0.5 indicates a statistically significant separation of negative controls and noise from the positive controls.If such a statistical difference has been established, one can proceed to the primary screen. Prepare 384. Well tissue culture plates for transfection of easy RNAs utilizing the predetermined optimized conditions here.15 nanograms of easy RNA per well are dissolved in five microliters of TE buffer. At least eight control positions per plate are loaded with suitable positive and negative controls for the biological process. Studied here, EEG five and ranil luciferase.Easy RNAs are used to avoid position effects. The edge wells are loaded with five microliters of TE buffer only. Next, add five microliters of opti MEM containing 0.2 microliters of oligo per well mix and incubate for 20 minutes at room temperature.After mixing the RNA with the transfection reagent, add the cell suspension here. 40 microliters of a he R cell suspension are added at 25 cells per microliter concentration equivalent to 1000 cells per well incubate for 72 hours. After the 72 hour incubation.Measure the DNA content on an automated microscope such as the Olympus scan R as previously shown. Repeat this procedure for all plates of the library for hit selection. Evaluate the DNA content values using Z-score statistics.Note that the Z-score is not the same as the Z factor Z-score. Provide a statistical measure for significance of sample value in comparison to a negative or mock control. It is calculated following the equation shown here.Calculate the zco for all the easy RNA samples using the signal for the negative vanilla luciferase control as reference for hit selection, A threshold has to be applied. Typically, a significance criterion for Z greater than two or smaller than minus two is used. However, depending on the studied biological process or the scope of the screen, different thresholds may be applied.More elaborate mathematical evaluation methods like the Q can also be used for hit selection. Next, the selected hits are subjected to a secondary screen and HIIT validation. A secondary screen of the selected HIIT genes follows the primary screen to eliminate false positives due to experimental variation.First, verify the selected hits using the same procedure as in the primary screen, except set up the hits with a bigger number of replicates between three and five to allow for a better statistical evaluation. For the verified hits, use the same assay and readout as in the primary screen, but with a secondary non-overlapping easy RNA or another non-overlapping silencing trigger, such as a chemically synthesized si. RNA Ultimately validate the selected genes by cross-species.RNAI rescue the gold standard for the verification of RNAi phenotypes available to date. In short, a bacterial artificial chromosome abbreviated back encoding an ortho log from a different species of the selected gene is stably transfected into cells. Back constructs preserve a gene in its genomic context and allow for a nearly physiological expression.RNAi against the endogenous gene will leave the ortho transgene expression unaltered, which rescues the RNAi phenotype. Finally, the validated candidates has studied in more detail to eventually derive mechanistic understanding. In many cases, RNAi can be used in these secondary more elaborate assays as well.For example, time-lapse microscopy of RNAi phenotypes. Here is an example of a cell cycle screen in which the DNA content of heal R cells were measured after knockdown of more than 16, 000 genes from the human genome. 1, 351 primary hits were identified to be required for cell division.In the secondary screen, 743 hits were verified with a secondary independent easy RNA trigger using a secondary assay. Knockdowns that resulted in a G two arrest was separated from knockdowns that resulted in mitotic arrest. Finally, across species RNA eye rescue experiment for the gene, Lin 54 was used to validate its role for proper cell division.Further downstream experiments showed that depletion of Lin 54 altered the expression of many cell cycle genes. We have just shown you how to set up high throughput transfection of mission, easy RNAs, and analysis of cell cycle distribution in the human tissue culture cell line. When doing This procedure, it is important to remember that transfection conditions and assays have to be optimized separately for any cellular system and any biological process.The use of automated liquid handling systems is recommended but not indispensable, especially for small scale screens. Manual handling is feasible as well. So that's It.Thanks for watching and good luck with your experiments.

mission-esirna-for-rnai-screening-in-mammalian-cells

Research

JoVE Journal

Biology

The endoplasmic reticulum plays a key role in protein biogenesis and in calcium homeostasis. We have established an experimental system that allows us to address the role of Ca2+ leak channels and to characterize their putative regulatory mechanisms. This system involves siRNA mediated gene silencing and live cell Ca2+ imaging.

Live Cell Calcium Imaging Combined with siRNA Mediated Gene Silencing Identifies Ca2+ Leak Channels in the ER Membrane and their Regulatory Mechanisms

The Target ID Library is a plasmid-based, genome-wide collection of cloned cDNA used to identify miRNA targets. Here we demonstrate its use and application.

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Here we use a human LentiPlex pooled library and traditional sequencing methods to identify gene targets promoting cell survival. We demonstrate how to set up and deconvolute a LentiPlex screen and validate the results.

MISSION LentiPlex Pooled shRNA Library Screening in Mammalian Cells

We describe a sensitized method to identify postembryonic regulators of protein expression and localization in C. elegans using an RNAi-based genomic screen and an integrated transgene that expresses a functional, fluorescently tagged protein.

RNAi Screening to Identify Postembryonic Phenotypes in C. elegans

A step by step protocol to isolating and identifying RNA associated complexes through RIP-Chip.

Method for the Isolation and Identification of mRNAs, microRNAs and Protein Components of Ribonucleoprotein Complexes from Cell Extracts using RIP-Chip

In this protocol, we describe methods to efficiently transfect murine macrophage cell lines with siRNAs using the Amaxa Nucleofector 96-well Shuttle System, stimulate the macrophages with lipopolysaccharide, and monitor the effects on inflammatory cytokine production.

Using RNA-interference to Investigate the Innate Immune Response in Mouse Macrophages

Here, we describe a methodology to perform a targeted siRNA “ubiquitome” screen to identify novel ubiquitin and ubiquitin-like regulators of the HIF1A-mediated cellular response to hypoxia.  This can be adapted to any biological pathway where a robust read out of reporter activity is available.

siRNA Screening to Identify Ubiquitin and Ubiquitin-like System Regulators of Biological Pathways in Cultured Mammalian Cells

Here we present a protocol to analyze RNA/protein interactions. The electrophoretic mobility shift assay (EMSA) is based on the differential migration of RNA/protein complexes and free RNA during native gel electrophoresis. By using a radiolabeled RNA probe, RNA/protein complexes can be visualized by autoradiography.

Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example

This report describes a fast and reliable method for validating mRNA targets of cellular miRNAs. The method uses synthetic biotinylated Locked Nucleic Acid (LNA)-based miRNA mimics to capture target mRNA. Subsequently, streptavidin-coated magnetic beads are employed to pulldown the target mRNA for quantification by qPCR polymerase chain reaction.

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

SINEUPs are synthetic antisense non-coding RNAs, which contain a binding domain (BD) and an effector domain (ED) and up-regulate translation of target mRNA. Here, we describe detection methods for SINEUPs in cultured cell lines, analysis of their translation-promoting activity by Western-blot and a semi-automated high throughput imaging system.

Cell Based Assays of SINEUP Non-coding RNAs That Can Specifically Enhance mRNA Translation

We developed an intronic microRNA biogenesis reporter assay to be used in cells in vitro with four plasmids: one with intronic miRNA, one with the target, one to overexpress a regulatory protein, and one for Renilla luciferase. The miRNA was processed and could control luciferase expression by binding to the target sequence.

A Reporter Assay to Analyze Intronic microRNA Maturation in Mammalian Cells

Learn esiRNA screening for cell cycle gene identification in mammalian cells using high-throughput RNAi methods. This protocol demonstrates optimized transfection, automated screening, and statistical validation for robust functional genomics research.

MISSION esiRNA for RNAi Screening in Mammalian Cells

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