Screening for Gene Candidates Using shRNAs
While these technological advances in siRNA synthesis and delivery have optimized the effectiveness of siRNAs in RNAi-mediated therapeutics, shRNAs are also important tools for RNAi research that can overcome some of the difficulties presented by using siRNAs.
By exploiting the cell’s endogenous RNAi processing machinery, shRNA constructs allow for potent, sustainable knockdown using low copy numbers that can result in fewer off-target effects. siRNA molecules must overcome barriers like circulating nucleases and endosome acidity, but lentiviral transduction of shRNA vectors removes these potential hindrances.
Another advantage of shRNA libraries is efficient transduction of nontransfectable cell types, which can be a limitation for siRNA libraries. Additionally, shRNAs can be integrated into the host genome and are only administered once, while siRNAs remain in the cytosol and usually have a more transient effect.
Annaleen Vermeulen, Ph.D., senior scientist and R&D manager at Thermo Fisher Scientific, explains that to set up a successful shRNA screen, a pooled library is used containing multiple shRNAs, which are then packaged into lentiviral particles and transduced into the control and experimental populations such that there is one shRNA per cell on average. For example, the experimental sample may be treated with a cancer drug in order to look for enrichment in cell death in the presence of the drug and the shRNA, identifying genes that are responsible for cell death sensitization.
In the past, Thermo Fisher Scientific has created genome-wide libraries with multiple shRNAs targeting each gene, but they now have also made smaller libraries that target gene families, such as the kinase library, while still maintaining high shRNA coverage. These smaller libraries require fewer cells to be transduced, which can be particularly useful when working with rare cell lines that are hard to isolate.
“From publications and from internal work, we noticed that researchers often identify only a few strong hits from these screens that are really useful for understanding their biology. We decided that if reproducibility of these screens could be improved, we could increase the dynamic range of these screens, so that there would be more candidate genes to follow up on,” Dr. Vermeulen states.
She and colleagues systematically examined the pooled shRNA screen reproducibility for different experimental parameters, including shRNA representation at the transduction step, the PCR amplification step, and data analysis by microarray or next-generation sequencing (NGS).
With one shRNA per cell on average, it was essential to have at least 500 to 1,000 cells representing each shRNA to provide reproducible data and confidence in the hits that were identified. Furthermore, maintaining shRNA representation during amplification also proved to be critical in obtaining reproducible data. While there was overlap between the results obtained using an NGS or microarray readout, NGS had a much greater dynamic range, the hits were inherently more reproducible, and there were fewer false positives.
“We have shown that to have high reproducibility and confidence in the significance of your hits from a pooled shRNA screen, it is critical to have the highest fold shRNA representation that is reasonable for your experiment, as well as optimal amplification conditions,” Dr. Vermeulen concludes. By optimizing these factors, Thermo Fisher Scientific has developed a complete workflow for pooled shRNA screening combined with NGS analysis.
Cellecta is developing RNAi dropout viability and rescue screens, says Paul Diehl, Ph.D., director of marketing and business development. Dropout viability screens identify essential genes for cell viability, such as genes required for cancer cell proliferation, or genes that increase cell sensitivity to a particular drug. Rescue screens, on the other hand, identify genes required for apoptosis or for cell sensitivity to a drug.
Dr. Diehl explains that Cellecta uses a synthesized pool of oligonucleotides to make a library of shRNA-expression constructs instead of making individual plasmids. This approach allows them to generate an entire library within three months. The screening process utilizes a complex library of 27,000–55,000 barcoded shRNA constructs per pool with typically 5–10 shRNAs per gene. The barcodes enable each shRNA construct to be identified by PCR and high-throughput screening.
In a dropout viability screen, by comparing the barcodes present in the surviving cell population with the original library’s barcode distribution, shRNAs interfering with or slowing down cell growth can be identified, since they are depleted in the final population. It is the gene targets of these deleted shRNAs that are likely essential for cell viability. Conversely, in a rescue screen, shRNAs that are enriched in the final population compared to the original library interfere with genes that produce the lethal response in the presence of the apoptosis inducer.
Dr. Diehl also notes that while shRNA-specific library barcoding identifies the particular shRNAs present in the cell population, Cellecta has developed a new approach that includes a second barcode on the lentiviral vector, called a clonal barcode. This variation provides an additional layer of specificity.
“When you assess the shRNAs in surviving cells, you can not only identify the total distribution of shRNAs but also look at how many separated clones produced the population with a specific shRNA. Basically, you can actually track the fate of each individual cell from the original population in which the library was introduced,” Dr. Diehl says.
“This can help identify if all the cells with a specific shRNA grew or if there was one weird clone skewing the results, so you can separate external and spurious effects that alter growth rates from those produced by the presence of the shRNA itself.” Cellecta has moved this technology into a xenograft model to identify, for example, which genes are required for tumor growth in vivo.
Dr. Diehl has worked with a dropout screen identifying genes essential for viability in leukemic cells, as well as a rescue screen identifying genes essential for Fas-induced apoptosis. The results from the dropout screen identified many general viability genes, but there were no major hits common across different blood lines, he says.
The rescue screen identified canonical genes like Fas, Fadd, and Bid, as well as genes not normally associated with Fas-induced apoptosis. With collaborators at Roswell Park Cancer Center, Cellecta’s research team treated mice with the Fas ligand to induce apoptosis of hepatic cells, and they were able to validate that synthetic siRNA genes identified in the in vitro screen, as well as chemical inhibitors targeting the corresponding proteins, were both able to protect the mice from Fas-induced hepatic failure.
According to Dr. Diehl, “Cellecta is continuing to develop both our shRNA and high-throughput barcode tracking technologies with a plan to move into applications with more direct clinical and diagnostic relevance.”