Damage initiates a pleiotropic cellular response aimed at cellular survival when appropriate. To identify genes required for damage survival, we used a cell-based RNAi screen against the Drosophila genome and the alkylating agent methyl methanesulphonate (MMS). Similar studies performed in other model organisms report that damage response may involve pleiotropic cellular processes other than the central DNA repair components, yet an intuitive systems level view of the cellular components required for damage survival, their interrelationship, and contextual importance has been lacking. Further, by comparing data from different model organisms, identification of conserved and presumably core survival components should be forthcoming. We identified 307 genes, representing 13 signaling, metabolic, or enzymatic pathways, affecting cellular survival of MMS-induced damage. As expected, the majority of these pathways are involved in DNA repair; however, several pathways with more diverse biological functions were also identified, including the TOR pathway, transcription, translation, proteasome, glutathione synthesis, ATP synthesis, and Notch signaling, and these were equally important in damage survival. Comparison with genomic screen data from Saccharomyces cerevisiae revealed no overlap enrichment of individual genes between the species, but a conservation of the pathways. To demonstrate the functional conservation of pathways, five were tested in Drosophila and mouse cells, with each pathway responding to alkylation damage in both species. Using the protein interactome, a significant level of connectivity was observed between Drosophila MMS survival proteins, suggesting a higher order relationship. This connectivity was dramatically improved by incorporating the components of the 13 identified pathways within the network. Grouping proteins into "pathway nodes" qualitatively improved the interactome organization, revealing a highly organized "MMS survival network." We conclude that identification of pathways can facilitate comparative biology analysis when direct gene/orthologue comparisons fail. A biologically intuitive, highly interconnected MMS survival network was revealed after we incorporated pathway data in our interactome analysis.
BACKGROUND: The Notch signaling pathway regulates a diverse array of developmental processes, and aberrant Notch signaling can lead to diseases, including cancer. To obtain a more comprehensive understanding of the genetic network that integrates into Notch signaling, we performed a genome-wide RNAi screen in Drosophila cell culture to identify genes that modify Notch-dependent transcription. RESULTS: Employing complementary data analyses, we found 399 putative modifiers: 189 promoting and 210 antagonizing Notch activated transcription. These modifiers included several known Notch interactors, validating the robustness of the assay. Many novel modifiers were also identified, covering a range of cellular localizations from the extracellular matrix to the nucleus, as well as a large number of proteins with unknown function. Chromatin-modifying proteins represent a major class of genes identified, including histone deacetylase and demethylase complex components and other chromatin modifying, remodeling and replacement factors. A protein-protein interaction map of the Notch-dependent transcription modifiers revealed that a large number of the identified proteins interact physically with these core chromatin components. CONCLUSIONS: The genome-wide RNAi screen identified many genes that can modulate Notch transcriptional output. A protein interaction map of the identified genes highlighted a network of chromatin-modifying enzymes and remodelers that regulate Notch transcription. Our results open new avenues to explore the mechanisms of Notch signal regulation and the integration of this pathway into diverse cellular processes.
Reactive Oxygen Species (ROS) are a natural by-product of cellular growth and proliferation, and are required for fundamental processes such as protein-folding and signal transduction. However, ROS accumulation, and the onset of oxidative stress, can negatively impact cellular and genomic integrity. Signalling networks have evolved to respond to oxidative stress by engaging diverse enzymatic and non-enzymatic antioxidant mechanisms to restore redox homeostasis. The architecture of oxidative stress response networks during periods of normal growth, and how increased ROS levels dynamically reconfigure these networks are largely unknown. In order to gain insight into the structure of signalling networks that promote redox homeostasis we first performed genome-scale RNAi screens to identify novel suppressors of superoxide accumulation. We then infer relationships between redox regulators by hierarchical clustering of phenotypic signatures describing how gene inhibition affects superoxide levels, cellular viability, and morphology across different genetic backgrounds. Genes that cluster together are likely to act in the same signalling pathway/complex and thus make "functional interactions". Moreover we also calculate differential phenotypic signatures describing the difference in cellular phenotypes following RNAi between untreated cells and cells submitted to oxidative stress. Using both phenotypic signatures and differential signatures we construct a network model of functional interactions that occur between components of the redox homeostasis network, and how such interactions become rewired in the presence of oxidative stress. This network model predicts a functional interaction between the transcription factor Jun and the IRE1 kinase, which we validate in an orthogonal assay. We thus demonstrate the ability of systems-biology approaches to identify novel signalling events.
Defects in miRNA biogenesis or activity are associated to development abnormalities and diseases. In Drosophila, miRNAs are predominantly loaded in Argonaute-1, which they guide for silencing of target RNAs. The miRNA pathway overlaps the RNAi pathway in this organism, as miRNAs may also associate with Argonaute-2, the mediator of RNAi. We set up a gene construct in which a single inducible promoter directs the expression of the GFP protein as well as two miRNAs perfectly matching the GFP sequences. We show that self-silencing of the resulting automiG gene requires Drosha, Pasha, Dicer-1, Dicer-2 and Argonaute-2 loaded with the anti-GFP miRNAs. In contrast, self-silencing of the automiG gene does not involve Argonaute-1. Thus, automiG reports in vivo for both miRNA biogenesis and Ago-2 mediated silencing, providing a powerful biosensor to identify situations where miRNA or siRNA pathways are impaired. As a proof of concept, we used automiG as a biosensor to screen a chemical library and identified 29 molecules that strongly inhibit miRNA silencing, out of which 5 also inhibit RNAi triggered by long double-stranded RNA. Finally, the automiG sensor is also self-silenced by the anti-GFP miRNAs in HeLa cells and might be easily used to identify factors involved in miRNA biogenesis and silencing guided by perfect target complementarity in mammals.
We present a resource of high quality lists of functionally related Drosophila genes, e.g. based on protein domains (kinases, transcription factors, etc.) or cellular function (e.g. autophagy, signal transduction). To establish these lists, we relied on different inputs, including curation from databases or the literature and mapping from other species. Moreover, as an added curation and quality control step, we asked experts in relevant fields to review many of the lists. The resource is available online for scientists to search and view, and is editable based on community input. Annotation of gene groups is an ongoing effort and scientific need will typically drive decisions regarding which gene lists to pursue. We anticipate that the number of lists will increase over time; that the composition of some lists will grow and/or change over time as new information becomes available; and that the lists will benefit the scientific community, e.g. at experimental design and data analysis stages. Based on this, we present an easily updatable online database, available at www.flyrnai.org/glad, at which gene group lists can be viewed, searched and downloaded.
The cytokine-activated Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway plays an important role in the control of a wide variety of biological processes. When misregulated, JAK/STAT signaling is associated with various human diseases, such as immune disorders and tumorigenesis. To gain insights into the mechanisms by which JAK/STAT signaling participates in these diverse biological responses, we carried out a genome-wide RNA interference (RNAi) screen in cultured Drosophila cells. We identified 121 genes whose double-stranded RNA (dsRNA)-mediated knockdowns affected STAT92E activity. Of the 29 positive regulators, 13 are required for the tyrosine phosphorylation of STAT92E. Furthermore, we found that the Drosophila homologs of RanBP3 and RanBP10 are negative regulators of JAK/STAT signaling through their control of nucleocytoplasmic transport of STAT92E. In addition, we identified a key negative regulator of Drosophila JAK/STAT signaling, protein tyrosine phosphatase PTP61F, and showed that it is a transcriptional target of JAK/STAT signaling, thus revealing a novel negative feedback loop. Our study has uncovered many uncharacterized genes required for different steps of the JAK/STAT signaling pathway.
Nuclear translocation of Smad proteins is a critical step in signal transduction of transforming growth factor beta (TGF-beta) and bone morphogenetic proteins (BMPs). Using nuclear accumulation of the Drosophila Smad Mothers against Decapentaplegic (Mad) as the readout, we carried out a whole-genome RNAi screening in Drosophila cells. The screen identified moleskin (msk) as important for the nuclear import of phosphorylated Mad. Genetic evidence in the developing eye imaginal discs also demonstrates the critical functions of msk in regulating phospho-Mad. Moreover, knockdown of importin 7 and 8 (Imp7 and 8), the mammalian orthologues of Msk, markedly impaired nuclear accumulation of Smad1 in response to BMP2 and of Smad2/3 in response to TGF-beta. Biochemical studies further suggest that Smads are novel nuclear import substrates of Imp7 and 8. We have thus identified new evolutionarily conserved proteins that are important in the signal transduction of TGF-beta and BMP into the nucleus.
Cellular signaling networks have evolved to enable swift and accurate responses, even in the face of genetic or environmental perturbation. Thus, genetic screens may not identify all the genes that regulate different biological processes. Moreover, although classical screening approaches have succeeded in providing parts lists of the essential components of signaling networks, they typically do not provide much insight into the hierarchical and functional relations that exist among these components. We describe a high-throughput screen in which we used RNA interference to systematically inhibit two genes simultaneously in 17,724 combinations to identify regulators of Drosophila JUN NH(2)-terminal kinase (JNK). Using both genetic and phosphoproteomics data, we then implemented an integrative network algorithm to construct a JNK phosphorylation network, which provides structural and mechanistic insights into the systems architecture of JNK signaling.
RNA interference (RNAi) is an effective tool for genome-scale, high-throughput analysis of gene function. In the past five years, a number of genome-scale RNAi high-throughput screens (HTSs) have been done in both Drosophila and mammalian cultured cells to study diverse biological processes, including signal transduction, cancer biology, and host cell responses to infection. Results from these screens have led to the identification of new components of these processes and, importantly, have also provided insights into the complexity of biological systems, forcing new and innovative approaches to understanding functional networks in cells. Here, we review the main findings that have emerged from RNAi HTS and discuss technical issues that remain to be improved, in particular the verification of RNAi results and validation of their biological relevance. Furthermore, we discuss the importance of multiplexed and integrated experimental data analysis pipelines to RNAi HTS.
To identify Huntington's Disease therapeutics, we conducted high-content small molecule and RNAi suppressor screens using a Drosophila primary neural culture Huntingtin model. Drosophila primary neurons offer a sensitive readout for neurotoxicty, as their neurites develop dysmorphic features in the presence of mutant polyglutamine-expanded Huntingtin compared to nonpathogenic Huntingtin. By tracking the subcellular distribution of mRFP-tagged pathogenic Huntingtin and assaying neurite branch morphology via live-imaging, we identified suppressors that could reduce Huntingtin aggregation and/or prevent the formation of dystrophic neurites. The custom algorithms we used to quantify neurite morphologies in complex cultures provide a useful tool for future high-content screening approaches focused on neurodegenerative disease models. Compounds previously found to be effective aggregation inhibitors in mammalian systems were also effective in Drosophila primary cultures, suggesting translational capacity between these models. However, we did not observe a direct correlation between the ability of a compound or gene knockdown to suppress aggregate formation and its ability to rescue dysmorphic neurites. Only a subset of aggregation inhibitors could revert dysmorphic cellular profiles. We identified lkb1, an upstream kinase in the mTOR/Insulin pathway, and four novel drugs, Camptothecin, OH-Camptothecin, 18β-Glycyrrhetinic acid, and Carbenoxolone, that were strong suppressors of mutant Huntingtin-induced neurotoxicity. Huntingtin neurotoxicity suppressors identified through our screen also restored viability in an in vivo Drosophila Huntington's Disease model, making them attractive candidates for further therapeutic evaluation.
Lipid droplets (LDs) are specialized cell organelles for the storage of energy-rich lipids. Although lipid storage is a conserved feature of all cells and organisms, little is known about fundamental aspects of the cell biology of LDs, including their biogenesis, structural assembly and subcellular positioning, and the regulation of organismic energy homeostasis. We identified a novel LD-associated protein family, represented by the Drosophila protein CG9186 and its murine homolog MGI:1916082. In the absence of LDs, both proteins localize at the endoplasmic reticulum (ER). Upon lipid storage induction, they translocate to LDs using an evolutionarily conserved targeting mechanism that acts through a 60-amino-acid targeting motif in the center of the CG9186 protein. Overexpression of CG9186, and MGI:1916082, causes clustering of LDs in both tissue culture and salivary gland cells, whereas RNAi knockdown of CG9186 results in a reduction of LDs. Organismal RNAi knockdown of CG9186 results in a reduction in lipid storage levels of the fly. The results indicate that we identified the first members of a novel and evolutionarily conserved family of lipid storage regulators, which are also required to properly position LDs within cells.
BACKGROUND: RNA interference (RNAi) is an effective and important tool used to study gene function. For large-scale screens, RNAi is used to systematically down-regulate genes of interest and analyze their roles in a biological process. However, RNAi is associated with off-target effects (OTEs), including microRNA (miRNA)-like OTEs. The contribution of reagent-specific OTEs to RNAi screen data sets can be significant. In addition, the post-screen validation process is time and labor intensive. Thus, the availability of robust approaches to identify candidate off-targeted transcripts would be beneficial. RESULTS: Significant efforts have been made to eliminate false positive results attributable to sequence-specific OTEs associated with RNAi. These approaches have included improved algorithms for RNAi reagent design, incorporation of chemical modifications into siRNAs, and the use of various bioinformatics strategies to identify possible OTEs in screen results. Genome-wide Enrichment of Seed Sequence matches (GESS) was developed to identify potential off-targeted transcripts in large-scale screen data by seed-region analysis. Here, we introduce a user-friendly web application that provides researchers a relatively quick and easy way to perform GESS analysis on data from human or mouse cell-based screens using short interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), as well as for Drosophila screens using shRNAs. Online GESS relies on up-to-date transcript sequence annotations for human and mouse genes extracted from NCBI Reference Sequence (RefSeq) and Drosophila genes from FlyBase. The tool also accommodates analysis with user-provided reference sequence files. CONCLUSION: Online GESS provides a straightforward user interface for genome-wide seed region analysis for human, mouse and Drosophila RNAi screen data. With the tool, users can either use a built-in database or provide a database of transcripts for analysis. This makes it possible to analyze RNAi data from any organism for which the user can provide transcript sequences.
A crucial aim upon completion of whole genome sequences is the functional analysis of all predicted genes. We have applied a high-throughput RNA-interference (RNAi) screen of 19,470 double-stranded (ds) RNAs in cultured cells to characterize the function of nearly all (91%) predicted Drosophila genes in cell growth and viability. We found 438 dsRNAs that identified essential genes, among which 80% lacked mutant alleles. A quantitative assay of cell number was applied to identify genes of known and uncharacterized functions. In particular, we demonstrate a role for the homolog of a mammalian acute myeloid leukemia gene (AML1) in cell survival. Such a systematic screen for cell phenotypes, such as cell viability, can thus be effective in characterizing functionally related genes on a genome-wide scale.
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.