A Phenotype-Based RNAi Screening for Ras-ERK/MAPK Signaling-Associated Stem Cell Regulators in C. elegans.

Stem cells have the ability to self-renew and to generate differentiated cell types. A regulatory network that controls this balance is critical for stem cell homeostasis and normal animal development. Particularly, Ras-ERK/MAPK signaling pathway is critical for stem cell self-renewal and differentiation in mammals, including humans. Aberrant regulation of Ras-ERK/MAPK signaling pathway results in either stem cell or overproliferation. Therefore, the identification of Ras-ERK/MAPK signaling pathway-associated regulators is critical to understand the mechanism of stem cell (possibly cancer stem cell) control. In this report, using the nematode C. elegans mutants, we developed a methodology for a phenotype-based RNAi screening that identifies stem cell regulator genes associated with Ras-ERK/MAPK signaling within the context of a whole organism. Importantly, this phenotype-based RNAi screening can be applied for other stem cell-associated signaling pathways such as Wnt/ß-catenin and Notch using the C. elegans.

High-Throughput RNAi Screening Identifies a Role for the Osteopontin Pathway in Proliferation and Migration of Human Aortic Smooth Muscle Cells.

PURPOSE: Understanding of the mechanisms of vascular smooth muscle cells (VSMCs) phenotypic regulation is critically important to identify novel candidates for future therapeutic intervention. While HTS approaches have recently been used to identify novel regulators in many cell lines, such as cancer cells and hematopoietic stem cells, no studies have so far systematically investigated the effect of gene inactivation on VSMCs with respect to cell survival and growth response. METHODS AND RESULTS: 257 out of 2000 genes tested resulted in an inhibition of cell proliferation in HaoSMCs. After pathway analysis, 38 significant genes were selected for further study. 23 genes were confirmed to inhibit proliferation, and 13 genes found to induce apoptosis in the synthetic phenotype. 11 genes led to an aberrant nuclear phenotype indicating a central role in cell mitosis. 4 genes affected the cell migration in synthetic HaoSMCs. Using computational biological network analysis, 11 genes were identified to have an indirect or direct interaction with the Osteopontin pathway. For 10 of those genes, levels of proteins downstream of the Osteopontin pathway were found to be down-regulated, using RNAi methodology. CONCLUSIONS: A phenotypic high-throughput siRNA screen could be applied to identify genes relevant for the cell biology of HaoSMCs. Novel genes were identified which play a role in proliferation, apoptosis, mitosis and migration of HaoSMCs. These may represent potential drug candidates in the future.

Specific inhibition of diverse pathogens in human cells by synthetic microRNA-like oligonucleotides inferred from RNAi screens.

Systematic genetic perturbation screening in human cells remains technically challenging. Typically, large libraries of chemically synthesized siRNA oligonucleotides are used, each designed to degrade a specific cellular mRNA via the RNA interference (RNAi) mechanism. Here, we report on data from three genome-wide siRNA screens, conducted to uncover host factors required for infection of human cells by two bacterial and one viral pathogen. We find that the majority of phenotypic effects of siRNAs are unrelated to the intended "on-target" mechanism, defined by full complementarity of the 21-nt siRNA sequence to a target mRNA. Instead, phenotypes are largely dictated by "off-target" effects resulting from partial complementarity of siRNAs to multiple mRNAs via the "seed" region (i.e., nucleotides 2-8), reminiscent of the way specificity is determined for endogenous microRNAs. Quantitative analysis enabled the prediction of seeds that strongly and specifically block infection, independent of the intended on-target effect. This prediction was confirmed experimentally by designing oligos that do not have any on-target sequence match at all, yet can strongly reproduce the predicted phenotypes. Our results suggest that published RNAi screens have primarily, and unintentionally, screened the sequence space of microRNA seeds instead of the intended on-target space of protein-coding genes. This helps to explain why previously published RNAi screens have exhibited relatively little overlap. Our analysis suggests a possible way of identifying "seed reagents" for controlling phenotypes of interest and establishes a general strategy for extracting valuable untapped information from past and future RNAi screens.