Successful siRNA Experiments

Labelled siRNA transfected into HL-60

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  • Critical Parameters - Overview

    Prior to beginning siRNA experiments multiple parameters associated with experimental design need to be optimized. In particular, did you for instance know:

    • How to use our optimized protocols for siRNA experiments?
    • It is essential to choose appropriate controls?
    • You should test different siRNA concentrations to find out the optimal amount for your target gene in your cell type, as the knockdown level can be cell-type specific (i.e. you might see different results with one and the same siRNA if you transfer it in different cell types) and/or target-specific (i.e. different targets in one and the same cell type may require different conditions)
    • The kinetics of down-regulation vary depending on your target gene and on the analysis level?
    • It is important to identify a suitable and robust readout assay for your particular application (i.e. mRNA, protein or phenotypic analysis)
  • Optimized Protocols

    For the transfection of siRNA oligonucleotides into your specific cell-type, we recommend following our normal cell-type specific Optimized Protocol.

    Optimal Nucleofection™ Conditions for a particular cell type are identical whether you are transfecting DNA or RNA. So we recommend the following steps:

    • First, in order to establish/verify the optimal Nucleofection™ Conditions for your cells perform an experiment with our pmaxGFP™ Positive Control Vector (included in every kit).
    • Then, use the identical conditions for your siRNA experiments, but replace pmaxGFP™ Vector with your siRNA oligo. You may wish to include a sample with pmaxGFP™ Vector in order to measure the success of Nucleofection™ or you can even co-transfect pmaxGFP™ and your siRNA within the same sample. However, if you are using this as a means of estimating transfection efficiency for your siRNA, do keep in mind that the transfection efficiency for siRNA duplexes is even higher than for plasmid DNA.

    Positive controls for easy establishment of siRNA Nucleofection™:

    • Co-transfection of pmaxGFP™ Vector with an siRNA against maxGFP™ mRNA (siRNA Test Kit – For Cell Lines and Adherent Primary Cells)
    • Down-regulation of a house-keeping gene
    • Experiments with fluorescently labeled siRNAs have shown transfection efficiencies of up to 99%. Generally, unless a confocal microscope or FACS is available, the use of fluorescently labeled siRNA for initial set-up experiments is not advisable as many fluorescent labels fade quickly and microscopic analysis may lead to false positive results.

    Stability of siRNA duplexes in the Nucleofector™ Solutions: The Nucleofector™ Solutions were tested for RNAse activity. Incubation of RNA in the solutions for 2 hours at 37°C did not affect RNA stability.

  • Experimental Controls

    To ensure that the conclusions drawn from siRNA experiments are accurate, it is necessary to include the appropriate experimental controls. We recommend including at least four types of experimental controls in every RNAi experiment.

    1) Positive siRNA control: This should be a validated siRNA pool or individual siRNA targeting a well-characterized housekeeping gene, such as cyclophilin B (also known as PPIB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), or Lamin. A good positive control reagent targeting a well-expressed but non-essential gene is useful for establishing experimental parameters without affecting cellular viability and can also be used as negative control that is unassociated with any particular pathway under study (i.e., it fails to generate a observable phenotype in the assay being employed).

    2) Negative siRNA control: Negative siRNA control reagents are bioinformatically designed to have no known target in the cell line of choice. These reagents are important for distinguishing sequence-specific silencing from sequence-independent effects that are associated with the delivery of siRNA into the cell. Such sequence independent effects can include toxicity resulting from the process of transfection in conjunction with nucleic acid delivery or hyper-sensitivity to introduction of double stranded RNA. Investigators are encouraged to test multiple candidates in their own experimental systems to empirically confirm that the negative controls do not result in any observable and unintended off-target effects.

    3) Untreated transfection control: The untreated control sample is comprised of cells that have neither been treated with siRNA nor subjected to the transfection process. This control serves as an indicator of baseline cellular activity to which all other conditions can be compared.

    4) Mock-treated control: The mock-treated control sample is one in which the cells are subjected to the transfection procedure in the absence of siRNA. In the case of Nucleofection™, the cells would be exposed to the Nucleofector™ Solution and subjected to the Nucleofection™ Procedure in the absence of siRNA. The analysis of mock-treated cells will indicate whether the transfection process results in cytotoxicity or other non-specific effects.

     

  • siRNA Concentration

    When performing siRNA-mediated knockdown experiments it is advisable to conduct a dose-response (concentration) analysis to determine the minimum siRNA concentration necessary for sufficient target knockdown on mRNA, protein or functional level:

    • For Nucleofection™, the optimal siRNA concentration can range from lower than 2 nM up to 2 µM, depending on multiple factors such as the cell type, and the half-life of the mRNA and/or protein of the gene target. To determine the optimal concentration for your cell type and target, we suggest to perform an initial titration of the siRNA concentration within the range of 2 nM-2 µM (0.2 - 200 pmol in 100 µl; 0.04 - 40 pmol in 20 µl). Starting concentrations for a minimum titration would be 30 and 300 nM.
    • Target specificity: In a given cell type at a given siRNA concentration and time point knockdown levels of different targets can vary. Thus, it is important to optimize experimental conditions for each new target.
    • Cell type specificity: For a given target at a given siRNA concentration and analysis time point, knockdown levels may vary from cell-type to cell-type.


     

    HUVEC - Vimentin siRNA dose response

    More than 75% knockdown of vimentin mRNA in HUVECs with low siRNA amounts. HUVEC cells (2 x 105 cells/sample) were transfected by Nucleofection™ using the 96-well Shuttle™ System with Dharmacon SMARTpool reagents against different targets, 2 pmol (100 nM) each. Dharmacon siCONTROL non-targeting siRNA #1 was used as negative control. 24 h post Nucleofection™ cells were analyzed for mRNA level (measured by branched DNA assay) which were normalized to siCONTROL. (Data generated in collaboration with Thermo Fisher Scientific, Dharmacon Products).


     

    HUVEC - Different siRNA targets

    Target specificity of mRNA knockdown at a given siRNA concentration. HUVEC cells (2 x 105 cells/sample) were transfected by Nucleofection™ using the 96-well Shuttle™ System with Dharmacon SMARTpool reagents against different targets, 2 pmol (100 nM) each. Dharmacon siCONTROL non-targeting siRNA #1 was used as negative control. 24 h post Nucleofection™ cells were analyzed for mRNA level (measured by branched DNA assay) which were normalized to siCONTROL. (Data generated in collaboration with Thermo Fisher Scientific, Dharmacon Products).


    siRNA_Celltype specificity 

    Cell type specificity of mRNA knockdown at a given siRNA concentration. Various cells (2 x 105 cells/sample) were transfected by Nucleofection™ using the 96-well Shuttle™ System with 2 pmol (100 nM) Dharmacon SMARTpool reagent against vimentin. Dharmacon siCONTROL non-targeting siRNA #1 was used as negative control. 24 h post Nucleofection™ cells were analyzed for mRNA level (measured by branched DNA assay) which were normalized to siCONTROL. (Data generated in collaboration with Thermo Fisher Scientific, Dharmacon Products).

     

  • Knockdown Kinetics

    As the stability and half-life of various mRNAs and their protein products varies, it is important to empirically determine the best time points for assessing target knockdown. For example, it has been documented that in mammalian cells, mRNA half-life can range from minutes to days (Ross J, 1995, Microbiol Rev 59:423-50) while the T1/2 of protein products can range from less than a few minutes to several days. Taking this into consideration, the experimental design should allow sufficient time for the siRNA to associate with RISC and deplete mRNA/protein concentrations to desired levels.

    In general, the recommended time course ranges are 12 to 72 hours to deplete target mRNA and 24 to 96 hours to adequately knockdown target proteins and assess phenotypic outcomes.

     
    siRNA-mediated mRNA knockdown kinetics in Jurkat  siRNA-mediated Fas mRNA and protein knockdown in Jurkat

    Different kinetics for different targets (top) and for mRNA and protein (bottom). Jurkat cells clone E6-1 were transfected by Nucleofection™ with 10 pmol (500 nM) Dharmacon SMARTpool reagent against GAPDH or FAS. Dharmacon siCONTROL non-targeting siRNA #1 was used as negative control. GAPDH and Fas mRNA levels were analyzed 24 and 48 h post Nucleofection™ by branched DNA assay and normalized to siCONTROL. Fas protein levels were determined 24 and 48 h post Nucleofection™ by flow cytometry and normalized to siCONTROL. (Data generated in collaboration with Thermo Fisher Scientific, Dharmacon Products).

     

  • Read-out Assays

    A variety of detection assays may be used to assess cell viability, mRNA levels, and associated phenotypes during the optimization and implementation of a siRNA experiment.

    • mRNA (Northern-Blot, branched-DNA assay)
    • Protein (Western-Blot, ELISA, Microscopy)
    • Phenotypic response (proliferation, apoptosis, toxicity,...)

    Establishing robust assays for RNAi is important for meaningful results. Moreover, multiparametric measurements through the use of several complementary phenotypic assays are particularly helpful in interpreting biological results and performing hit stratification (Echeverri et al., 2006, Nat Methods 3(10):777-9).