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Gene silencing by RNA interference has become a powerful tool to help identify genes that regulate biological processes. However, the complexity of the biology probed and the incomplete validation of the reagents used make it difficult to interpret the results of genome-wide siRNA screens. To address this challenge and maximize the return on the efforts required for validating genomic screen hits, the screening strategy must be designed to increase the robustness of the primary screening hits and include assays that inform on the mechanism of action of the knocked-down transcripts. Here, we describe the implementation of a small interfering RNA (siRNA) screen to identify genes that sensitize the effect of poly-(ADP ribose)-polymerase (PARP) inhibitor on cell survival. In the strategy we designed for the primary screen, two biological activities, apoptosis and cell viability, were measured simultaneously at different time points in the presence and absence of a PARP inhibitor (PARPi). The multiplexed assay allowed us to identify PARPi sensitizers induced by both caspase-dependent and independent mechanisms. The multiplexed screening strategy yielded robust primary hits with significant enrichment for DNA repair genes, which were further validated using relevant high-content imaging assays and confirmation of transcript knockdown by real-time PCR (rtPCR).

Reducing circulating LDL-cholesterol (LDL-c) reduces the risk of cardiovascular disease in people with hypercholesterolemia. Current approaches to reduce circulating LDL-c include statins, which inhibit cholesterol synthesis, and ezetimibe, which blocks cholesterol absorption. Both elevate serum PCSK9 protein levels in patients, which could attenuate their efficacy by reducing the amount of cholesterol cleared from circulation. To determine whether PCSK9 inhibition could enhance LDL-c lowering of both statins and ezetimibe, we utilized small interfer­ing RNAs (siRNAs) to knock down Pcsk9, together with ezetimibe, rosuvastatin, and an ezetimibe/rosuvastatin combination in a mouse model with a human-like lipid profile. We found that ezetimibe, rosuvastatin, and ezetimibe/rosuvastatin combined lower serum cholesterol but induce the expression of Pcsk9 as well as the Srebp-2 hepatic cholesterol biosynthesis pathway. Pcsk9 knockdown in combination with either treatment led to greater reductions in serum non-HDL with a near-uniform reduction of all LDL-c subfractions. In addition to reducing serum cholesterol, the combined rosuvastatin/ezetimibe/Pcsk9 siRNA treatment exhibited a significant reduction in serum APOB protein and triglyceride levels. Taken together, these data provide evidence that PCSK9 inhibitors, in combination with current therapies, have the potential to achieve greater reductions in both serum cholesterol and triglycerides.

High-throughput screening (HTS) of large-scale RNA interference (RNAi) libraries has become an increasingly popular method of functional genomics in recent years. Cell-based assays used for RNAi screening often produce small dynamic ranges and significant variability because of the combination of cellular heterogeneity, transfection efficiency, and the intrinsic nature of the genes being targeted. These properties make reliable hit selection in the RNAi screen a difficult task. The use of robust methods based on median and median absolute deviation (MAD) has been suggested to improve hit selection in such cases, but mean and standard deviation (SD)-based methods are still predominantly used in many RNAi HTS. In an experimental approach to compare these 2 methods, a genome-scale small interfering RNA (siRNA) screen was performed, in which the identification of novel targets increasing the therapeutic index of the chemotherapeutic agent mitomycin C (MMC) was sought. MAD values were resistant to the presence of outliers, and the hits selected by the MAD-based method included all the hits that would be selected by SD-based method as well as a significant number of additional hits. When retested in triplicate, a similar percentage of these siRNAs were shown to genuinely sensitize cells to MMC compared with the hits shared between SD- and MAD-based methods. Confirmed hits were enriched with the genes involved in the DNA damage response and cell cycle regulation, validating the overall hit selection strategy. Finally, computer simulations showed the superiority and generality of the MAD-based method in various RNAi HTS data models. In conclusion, the authors demonstrate that the MAD-based hit selection method rescued physiologically relevant false negatives that would have been missed in the SD-based method, and they believe it to be the desirable 1st-choice hit selection method for RNAi screen results.

RNA interference (RNAi), combined with the availability of genome sequences, provides an unprecedented opportunity for the massive and parallel investigations of gene function. Small interfering RNA (siRNA) represents a popular and quick approach of RNAi for in vitro loss-of-function genetic screens. Efficient transfection of siRNA is critical for unambiguous interpretation of screen results and thus overall success of any siRNA screen. A high-throughput, lipid-based transfection method for siRNA was developed that can process eighty 384-well microplates in triplicate (for a total of 30,720 unique transfections) in 8 h. Transfection throughput was limited only by the speed of robotics, whereas the cost of screening was reduced. As a proof of principle, a genome-scale screen with a library of 22,108 siRNAs was performed to identify the genes sensitizing cells to mitomycin C at concentrations of 0, 20, and 60 nM. Transfection efficiency, performances of control siRNAs, and other quality metrics were monitored and demonstrated that the new, optimized transfection protocol produced high-quality results throughout the screen. (Journal of Biomolecular Screening XXXX:xx-xx)

Proteolysis of beta-amyloid precursor protein (APP) into amyloid beta peptide (Abeta) by beta- and gamma-secretases is a critical step in the pathogenesis of Alzheimer's Disease (AD), but the pathways regulating secretases are not fully characterized. Ubiquitinylation, which is dysregulated in AD, may affect APP processing. Here, we describe a screen for APP processing modulators using an siRNA library targeting 532 predicted ubiquitin ligases. Seven siRNA pools diminished Abeta production. Of these, siRNAs targeting PPIL2 (hCyp-60) suppressed beta-site cleavage. Knockdown of PPIL2 mRNA decreased BACE1 mRNA, while overexpression of PPIL2 cDNA enhanced BACE1 mRNA levels. Microarray analysis of PPIL2 or BACE1 knockdown indicated that genes affected by BACE1 knockdown are a subset of those dependent upon PPIL2; suggesting that BACE1 expression is downstream of PPIL2. The association of PPIL2 with BACE expression and its requirement for Abeta production suggests new approaches to discover disease modifying agents for AD.