ABSTRACT
Influenza virus encodes only 11 viral proteins but replicates in a broad range of avian and mammalian species by exploiting host cell functions. Genome-wide RNA interference (RNAi) has proven to be a powerful tool for identifying the host molecules that participate in each step of virus replication. Meta-analysis of findings from genome-wide RNAi screens has shown influenza virus to be dependent on functional nodes in host cell pathways, requiring a wide variety of molecules and cellular proteins for replication. Because rapid evolution of the influenza A viruses persistently complicates the effectiveness of vaccines and therapeutics, a further understanding of the complex host cell pathways coopted by influenza virus for replication may provide new targets and strategies for antiviral therapy. RNAi genome screening technologies together with bioinformatics can provide the ability to rapidly identify specific host factors involved in resistance and susceptibility to influenza virus, allowing for novel disease intervention strategies.
Subject(s)
High-Throughput Screening Assays/methods , Influenza A virus/genetics , Influenza, Human/therapy , RNA Interference , Viral Proteins/genetics , Animals , Humans , Meta-Analysis as Topic , MicroRNAs/genetics , MicroRNAs/metabolism , NF-kappa B/metabolism , Protein Kinase C/metabolism , RNA, Small Interfering/genetics , RNA, Small Interfering/metabolism , Signal Transduction/physiologyABSTRACT
RNA interference (RNAi) has become a powerful technique for reverse genetics and drug discovery, and in both of these areas large-scale high-throughput RNAi screens are commonly performed. The statistical techniques used to analyze these screens are frequently borrowed directly from small-molecule screening; however, small-molecule and RNAi data characteristics differ in meaningful ways. We examine the similarities and differences between RNAi and small-molecule screens, highlighting particular characteristics of RNAi screen data that must be addressed during analysis. Additionally, we provide guidance on selection of analysis techniques in the context of a sample workflow.
Subject(s)
RNA Interference , RNA, Small Interfering/chemistry , RNA, Small Interfering/genetics , Research Design/statistics & numerical data , Small Molecule Libraries , Animals , Computer Simulation , Models, StatisticalABSTRACT
BACKGROUND: Mesenchymal stem (MS) cells are excellent candidates for cell-based therapeutic strategies to regenerate injured tissue. Although human MS cells can be isolated from bone marrow and directed to differentiate by means of an osteogenic pathway, the regulation of cell-fate determination is not well understood. Recent reports identify critical roles for microRNAs (miRNAs), regulators of gene expression either by inhibiting the translation or by stimulating the degradation of target mRNAs. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we employed a library of miRNA inhibitors to evaluate the role of miRNAs in early osteogenic differentiation of human MS cells. We discovered that miR-148b, -27a and -489 are essential for the regulation of osteogenesis: miR-27a and miR-489 down-regulate while miR-148b up-regulates differentiation. Modulation of these miRNAs induced osteogenesis in the absence of other external differentiation cues and restored osteogenic potential in high passage number human MS cells. CONCLUSIONS/SIGNIFICANCE: Overall, we have demonstrated the utility of the functional profiling strategy for unraveling complex miRNA pathways. Our findings indicate that miRNAs regulate early osteogenic differentiation in human MS cells: miR-148b, -27a, and -489 were found to play a critical role in osteogenesis.