Practical Guidance for siRNA Screening

Summary: The goal of this document is to communicate practical guidance that can be applied during development of siRNA high throughput screens, and their presentation in papers and grants. The sources of guidance are literature papers, federal grant evaluation criteria, and conversations with scientific contacts overseeing grants from multiple NIH institutes.

Assay Development and Screening

  • “A well-defined phenotype is the single most important consideration in designing a screen.” Robustness and reproducibility of the phenotype are essential (Eggert, 2013).
  • Describe how positive and negative controls are used to set assay window and comment on the level of biological response expected relative to them. Describe calculations for data normalization based on controls. Describe your hit scoring strategy (Inglese et al., 2007).
  • Indicate sources of all reagents, including batch numbers, in methods (Inglese et al., 2007).
  • Experimental procedure should include specifics instruments and settings used for liquid handling and reading assay. Add information about the number of assay plates screened and duration of screen (Inglese et al., 2007).
  • If you are going to use siRNA approaches of pathway targets with known small molecule treatments of same, making assays as similar as possible will help prevent confounding factors (Eggert, 2013). At the same time, “results with small molecule inhibition and siRNA knock down will not necessarily align at the phenotype level, for example, when a small molecule inhibits an enzyme but protein-protein interactions are intact, or that effect stoichiometry in downstream processes”  (Weiss et al., 2007).
  • Negative controls must engage the RNAi machinery (Weiss et al., 2007).
  • High correlation coefficients (Pearson r =0.75 or higher) between experiments run on separate plates have to be demonstrated, especially if the screen was performed without replicates.

Additional  considerations for image-based assays

  • User should review images from a least three full plates to get a sense of expected and unexpected phenotypic changes to monitor (Eggert, 2013).
  • Include description of image analysis algorithm in terms of what metrics of the phenotype are being quantified.

Validation of siRNA targets

On-target effects can be promoted by the following recommendations from Weiss et al., 2007:

  • Use siRNA at lowest possible concentration, as off-target effects are concentration-dependent.
  • Multiple different probes to the same target should result in same phenotype, such as validation of several individual siRNAs against the same target (especially if pooled library was used in a primary screen). Ideally, sequences should be completely independent.
  • Demonstrate knockdown of target at mRNA and protein level. “Monitoring protein expression may be more informative than mRNA levels for highly stable proteins.)
  • Demonstrate siRNA effect on functional readout.
  • Manipulate target gene to a form that is no longer affected by siRNA.
  • NIH siRNA screening Center is promoting use of C911 controls to rule out off-target phenotypes (Buehler et al., 2012).
  • Orthogonal secondary assays are required.
  • Complementation assays or alternative gene knockdown studies (TALENs, CRISPRs) should be ideally performed for the best hit candidates.

References

Eggert US. The why and how of phenotypic small-molecule screens. Nat Chem Biol. 2013 Apr;9(4):206-9.

Inglese J, Shamu CE, Guy RK. Reporting data from high-throughput screening of small-molecule libraries. Nat Chem Biol. 2007 Aug;3(8):438-41.

Weiss WA, Taylor SS, Shokat KM. Recognizing and exploiting differences between RNAi and small-molecule inhibitors. Nat Chem Biol. 2007 Dec;3(12):739-44.

Buehler E, Chen YC, Martin S. C911: A bench-level control for sequence specific siRNA off-target effects. PLoS One. 2012;7(12):e51942.