To evaluate the specificity of long dsRNAs used in high-throughput RNA interference (RNAi) screens performed at the Drosophila RNAi Screening Center (DRSC), we performed a global analysis of their activity in 30 genome-wide screens completed at our facility. Notably, our analysis predicts that dsRNAs containing > or = 19-nucleotide perfect matches identified in silico to unintended targets may contribute to a significant false positive error rate arising from off-target effects. We confirmed experimentally that such sequences in dsRNAs lead to false positives and to efficient knockdown of a cross-hybridizing transcript, raising a cautionary note about interpreting results based on the use of a single dsRNA per gene. Although a full appreciation of all causes of false positive errors remains to be determined, we suggest simple guidelines to help ensure high-quality information from RNAi high-throughput screens.

Nearly 1.7 billion people are infected with Mycobacterium tuberculosis. Its ability to survive intracellularly is thought to be central to its success as a pathogen, but how it does this is poorly understood. Using a Drosophila model of infection, we identify three host cell activities, Rab7, CG8743, and the ESCRT machinery, that modulate the mycobacterial phagosome. In the absence of these factors the cell no longer restricts growth of the non-pathogen Mycobacterium smegmatis. Hence, we identify factors that represent unique vulnerabilities of the host cell, because manipulation of any one of them alone is sufficient to allow a nonpathogenic mycobacterial species to proliferate. Furthermore, we demonstrate that, in mammalian cells, the ESCRT machinery plays a conserved role in restricting bacterial growth.

BACKGROUND: Insights into how the Frizzled/LRP6 receptor complex receives, transduces and terminates Wnt signals will enhance our understanding of the control of the Wnt/ss-catenin pathway. METHODOLOGY/PRINCIPAL FINDINGS: In pursuit of such insights, we performed a genome-wide RNAi screen in Drosophila cells expressing an activated form of LRP6 and a beta-catenin-responsive reporter. This screen resulted in the identification of Bili, a Band4.1-domain containing protein, as a negative regulator of Wnt/beta-catenin signaling. We found that the expression of Bili in Drosophila embryos and larval imaginal discs significantly overlaps with the expression of Wingless (Wg), the Drosophila Wnt ortholog, which is consistent with a potential function for Bili in the Wg pathway. We then tested the functions of Bili in both invertebrate and vertebrate animal model systems. Loss-of-function studies in Drosophila and zebrafish embryos, as well as human cultured cells, demonstrate that Bili is an evolutionarily conserved antagonist of Wnt/beta-catenin signaling. Mechanistically, we found that Bili exerts its antagonistic effects by inhibiting the recruitment of AXIN to LRP6 required during pathway activation. CONCLUSIONS: These studies identify Bili as an evolutionarily conserved negative regulator of the Wnt/beta-catenin pathway.

Systems biology aims to describe the complex interplays between cellular building blocks which, in their concurrence, give rise to the emergent properties observed in cellular behaviors and responses. This approach tries to determine the molecular players and the architectural principles of their interactions within the genetic networks that control certain biological processes. Large-scale loss-of-function screens, applicable in various different model systems, have begun to systematically interrogate entire genomes to identify the genes that contribute to a certain cellular response. In particular, RNA interference (RNAi)-based high-throughput screens have been instrumental in determining the composition of regulatory systems and paired with integrative data analyses have begun to delineate the genetic networks that control cell biological and developmental processes. Through the creation of tools for both, in vitro and in vivo genome-wide RNAi screens, Drosophila melanogaster has emerged as one of the key model organisms in systems biology research and over the last years has massively contributed to and hence shaped this discipline. WIREs Syst Biol Med 2011 3 471-478 DOI: 10.1002/wsbm.127

Regulation of genes that initiate and amplify inflammatory programs of gene expression is achieved by signal-dependent exchange of coregulator complexes that function to read, write, and erase specific histone modifications linked to transcriptional activation or repression. Here, we provide evidence for the role of trimethylated histone H4 lysine 20 (H4K20me3) as a repression checkpoint that restricts expression of toll-like receptor 4 (TLR4) target genes in macrophages. H4K20me3 is deposited at the promoters of a subset of these genes by the SMYD5 histone methyltransferase through its association with NCoR corepressor complexes. Signal-dependent erasure of H4K20me3 is required for effective gene activation and is achieved by NF-κB-dependent delivery of the histone demethylase PHF2. Liver X receptors antagonize TLR4-dependent gene activation by maintaining NCoR/SMYD5-mediated repression. These findings reveal a histone H4K20 trimethylation/demethylation strategy that integrates positive and negative signaling inputs that control immunity and homeostasis.

The way in which cells adopt different morphologies is not fully understood. Cell shape could be a continuous variable or restricted to a set of discrete forms. We developed quantitative methods to describe cell shape and show that Drosophila haemocytes in culture are a heterogeneous mixture of five discrete morphologies. In an RNAi screen of genes affecting the morphological complexity of heterogeneous cell populations, we found that most genes regulate the transition between discrete shapes rather than generating new morphologies. In particular, we identified a subset of genes, including the tumour suppressor PTEN, that decrease the heterogeneity of the population, leading to populations enriched in rounded or elongated forms. We show that these genes have a highly conserved function as regulators of cell shape in both mouse and human metastatic melanoma cells.

Chromatin insulators of higher eukaryotes functionally divide the genome into active and inactive domains. Furthermore, insulators regulate enhancer/promoter communication, which is evident from the Drosophila bithorax locus in which a multitude of regulatory elements control segment specific gene activity. Centrosomal protein 190 (CP190) is targeted to insulators by CTCF or other insulator DNA-binding factors. Chromatin analyses revealed that insulators are characterized by open and nucleosome depleted regions. Here, we wanted to identify chromatin modification and remodelling factors required for an enhancer blocking function. We used the well-studied Fab-8 insulator of the bithorax locus to apply a genome-wide RNAi screen for factors that contribute to the enhancer blocking function of CTCF and CP190. Among 78 genes required for optimal Fab-8 mediated enhancer blocking, all four components of the NURF complex as well as several subunits of the dREAM complex were most evident. Mass spectrometric analyses of CTCF or CP190 bound proteins as well as immune precipitation confirmed NURF and dREAM binding. Both co-localise with most CP190 binding sites in the genome and chromatin immune precipitation showed that CP190 recruits NURF and dREAM. Nucleosome occupancy and histone H3 binding analyses revealed that CP190 mediated NURF binding results in nucleosomal depletion at CP190 binding sites. Thus, we conclude that CP190 binding to CTCF or to other DNA binding insulator factors mediates recruitment of NURF and dREAM. Furthermore, the enhancer blocking function of insulators is associated with nucleosomal depletion and requires NURF and dREAM.

RNA interference (RNAi) has become a powerful tool for genetic screening in Drosophila. At the Drosophila RNAi Screening Center (DRSC), we are using a library of over 21,000 double-stranded RNAs targeting known and predicted genes in Drosophila. This library is available for the use of visiting scientists wishing to perform full-genome RNAi screens. The data generated from these screens are collected in the DRSC database (http://flyRNAi.org/cgi-bin/RNAi_screens.pl) in a flexible format for the convenience of the scientist and for archiving data. The long-term goal of this database is to provide annotations for as many of the uncharacterized genes in Drosophila as possible. Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.

Off-target effects have been demonstrated to be a major source of false-positives in RNA interference (RNAi) high-throughput screens. In this study, we re-assess the previously published transcriptional reporter-based whole-genome RNAi screens for the Wingless and Hedgehog signaling pathways using second generation double-stranded RNA libraries. Furthermore, we investigate other factors that may influence the outcome of such screens, including cell-type specificity, robustness of reporters, and assay normalization, which determine the efficacy of RNAi-knockdown of target genes.

The specificity of RNAi pathways is determined by several classes of small RNAs, which include siRNAs, piRNAs, endo-siRNAs, and microRNAs (miRNAs). These small RNAs are invariably incorporated into large Argonaute (Ago)-containing effector complexes known as RNA-induced silencing complexes (RISCs), which they guide to silencing targets. Both genetic and biochemical strategies have yielded conserved molecular components of small RNA biogenesis and effector machineries. However, given the complexity of these pathways, there are likely to be additional components and regulators that remain to be uncovered. We have undertaken a comparative and comprehensive RNAi screen to identify genes that impact three major Ago-dependent small RNA pathways that operate in Drosophila S2 cells. We identify subsets of candidates that act positively or negatively in siRNA, endo-siRNA, and miRNA pathways. Our studies indicate that many components are shared among all three Argonaute-dependent silencing pathways, though each is also impacted by discrete sets of genes.

RNA interference (RNAi) provides a powerful reverse genetics approach to analyze gene functions both in tissue culture and in vivo. Because of its widespread applicability and effectiveness it has become an essential part of the tool box kits of model organisms such as Caenorhabditis elegans, Drosophila, and the mouse. In addition, the use of RNAi in animals in which genetic tools are either poorly developed or nonexistent enables a myriad of fundamental questions to be asked. Here, we review the methods and applications of in vivo RNAi to characterize gene functions in model organisms and discuss their impact to the study of developmental as well as evolutionary questions. Further, we discuss the applications of RNAi technologies to crop improvement, pest control and RNAi therapeutics, thus providing an appreciation of the potential for phenomenal applications of RNAi to agriculture and medicine.

Characterizing the extent and logic of signaling networks is essential to understanding specificity in such physiological and pathophysiological contexts as cell fate decisions and mechanisms of oncogenesis and resistance to chemotherapy. Cell-based RNA interference (RNAi) screens enable the inference of large numbers of genes that regulate signaling pathways, but these screens cannot provide network structure directly. We describe an integrated network around the canonical receptor tyrosine kinase (RTK)-Ras-extracellular signal-regulated kinase (ERK) signaling pathway, generated by combining parallel genome-wide RNAi screens with protein-protein interaction (PPI) mapping by tandem affinity purification-mass spectrometry. We found that only a small fraction of the total number of PPI or RNAi screen hits was isolated under all conditions tested and that most of these represented the known canonical pathway components, suggesting that much of the core canonical ERK pathway is known. Because most of the newly identified regulators are likely cell type- and RTK-specific, our analysis provides a resource for understanding how output through this clinically relevant pathway is regulated in different contexts. We report in vivo roles for several of the previously unknown regulators, including CG10289 and PpV, the Drosophila orthologs of two components of the serine/threonine-protein phosphatase 6 complex; the Drosophila ortholog of TepIV, a glycophosphatidylinositol-linked protein mutated in human cancers; CG6453, a noncatalytic subunit of glucosidase II; and Rtf1, a histone methyltransferase.

In a developing Drosophila melanogaster embryo, mRNAs have a maternal origin, a zygotic origin, or both. During the maternal-zygotic transition, maternal products are degraded and gene expression comes under the control of the zygotic genome. To interrogate the function of mRNAs that are both maternally and zygotically expressed, it is common to examine the embryonic phenotypes derived from female germline mosaics. Recently, the development of RNAi vectors based on short hairpin RNAs (shRNAs) effective during oogenesis has provided an alternative to producing germline clones. Here, we evaluate the efficacies of: (1) maternally loaded shRNAs to knockdown zygotic transcripts and (2) maternally loaded Gal4 protein to drive zygotic shRNA expression. We show that, while Gal4-driven shRNAs in the female germline very effectively generate phenotypes for genes expressed maternally, maternally loaded shRNAs are not very effective at generating phenotypes for early zygotic genes. However, maternally loaded Gal4 protein is very efficient at generating phenotypes for zygotic genes expressed during mid-embryogenesis. We apply this powerful and simple method to unravel the embryonic functions of a number of pleiotropic genes.

A major objective of systems biology is to organize molecular interactions as networks and to characterize information flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the 'signs' of interactions (i.e., activation-inhibition relationships). We constructed a Drosophila melanogaster signed PPI network consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes enolase and aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation-inhibition relationships between physically interacting proteins within signaling pathways will affect our understanding of many biological functions, including signal transduction and mechanisms of disease.

The tuberous sclerosis complex (TSC) family of tumor suppressors, TSC1 and TSC2, function together in an evolutionarily conserved protein complex that is a point of convergence for major cell signaling pathways that regulate mTOR complex 1 (mTORC1). Mutation or aberrant inhibition of the TSC complex is common in various human tumor syndromes and cancers. The discovery of novel therapeutic strategies to selectively target cells with functional loss of this complex is therefore of clinical relevance to patients with nonmalignant TSC and those with sporadic cancers. We developed a CRISPR-based method to generate homogeneous mutant Drosophila cell lines. By combining TSC1 or TSC2 mutant cell lines with RNAi screens against all kinases and phosphatases, we identified synthetic interactions with TSC1 and TSC2. Individual knockdown of three candidate genes (mRNA-cap, Pitslre, and CycT; orthologs of RNGTT, CDK11, and CCNT1 in humans) reduced the population growth rate of Drosophila cells lacking either TSC1 or TSC2 but not that of wild-type cells. Moreover, individual knockdown of these three genes had similar growth-inhibiting effects in mammalian TSC2-deficient cell lines, including human tumor-derived cells, illustrating the power of this cross-species screening strategy to identify potential drug targets.