In vivo fly RNAi

2011
Joost Schulte, Katharine J Sepp, Chaohong Wu, Pengyu Hong, and Troy J Littleton. 2011. “High-content chemical and RNAi screens for suppressors of neurotoxicity in a Huntington's disease model.” PLoS One, 6, 8, Pp. e23841.Abstract

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.

2011_PLOS One_Schulte.pdf Supplemental Files.zip
Adam A Friedman, George Tucker, Rohit Singh, Dong Yan, Arunachalam Vinayagam, Yanhui Hu, Richard Binari, Pengyu Hong, Xiaoyun Sun, Maura Porto, Svetlana Pacifico, Thilakam Murali, Russell L Finley, John M Asara, Bonnie Berger, and Norbert Perrimon. 2011. “Proteomic and functional genomic landscape of receptor tyrosine kinase and ras to extracellular signal-regulated kinase signaling.” Sci Signal, 4, 196, Pp. rs10.Abstract

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.

2011_Sci Sig_Friedman.pdf Supplemental Files.zip
Ralph A Neumüller and Norbert Perrimon. 2011. “Where gene discovery turns into systems biology: genome-scale RNAi screens in Drosophila.” Wiley Interdiscip Rev Syst Biol Med, 3, 4, Pp. 471-8.Abstract

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

2011_Wiley_Neumuller.pdf
2010
Sheng Zhang, Richard Binari, Rui Zhou, and Norbert Perrimon. 2010. “A genomewide RNA interference screen for modifiers of aggregates formation by mutant Huntingtin in Drosophila.” Genetics, 184, 4, Pp. 1165-79.Abstract

Protein aggregates are a common pathological feature of most neurodegenerative diseases (NDs). Understanding their formation and regulation will help clarify their controversial roles in disease pathogenesis. To date, there have been few systematic studies of aggregates formation in Drosophila, a model organism that has been applied extensively in modeling NDs and screening for toxicity modifiers. We generated transgenic fly lines that express enhanced-GFP-tagged mutant Huntingtin (Htt) fragments with different lengths of polyglutamine (polyQ) tract and showed that these Htt mutants develop protein aggregates in a polyQ-length- and age-dependent manner in Drosophila. To identify central regulators of protein aggregation, we further generated stable Drosophila cell lines expressing these Htt mutants and also established a cell-based quantitative assay that allows automated measurement of aggregates within cells. We then performed a genomewide RNA interference screen for regulators of mutant Htt aggregation and isolated 126 genes involved in diverse cellular processes. Interestingly, although our screen focused only on mutant Htt aggregation, several of the identified candidates were known previously as toxicity modifiers of NDs. Moreover, modulating the in vivo activity of hsp110 (CG6603) or tra1, two hits from the screen, affects neurodegeneration in a dose-dependent manner in a Drosophila model of Huntington's disease. Thus, other aggregates regulators isolated in our screen may identify additional genes involved in the protein-folding pathway and neurotoxicity.

2010_Genetics_Zhang.pdf Supplemental Files
Norbert Perrimon, Jian-Quan Ni, and Lizabeth Perkins. 2010. “In vivo RNAi: today and tomorrow.” Cold Spring Harb Perspect Biol, 2, 8, Pp. a003640.Abstract

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.

2010_CSHPerspect_Perrimon.pdf
2008
Jian-Quan Ni, Michele Markstein, Richard Binari, Barret Pfeiffer, Lu-Ping Liu, Christians Villalta, Matthew Booker, Lizabeth Perkins, and Norbert Perrimon. 2008. “Vector and parameters for targeted transgenic RNA interference in Drosophila melanogaster.” Nat Methods, 5, 1, Pp. 49-51.Abstract

The conditional expression of hairpin constructs in Drosophila melanogaster has emerged in recent years as a method of choice in functional genomic studies. To date, upstream activating site-driven RNA interference constructs have been inserted into the genome randomly using P-element-mediated transformation, which can result in false negatives due to variable expression. To avoid this problem, we have developed a transgenic RNA interference vector based on the phiC31 site-specific integration method.

2008_Nat Meth_Ni.pdf Supplement.pdf
2006
Meghana M Kulkarni, Matthew Booker, Serena J Silver, Adam Friedman, Pengyu Hong, Norbert Perrimon, and Bernard Mathey-Prevot. 2006. “Evidence of off-target effects associated with long dsRNAs in Drosophila melanogaster cell-based assays.” Nat Methods, 3, 10, Pp. 833-8.Abstract

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.

2006_Nat Meth_Kulkarni.pdf Supplemental Files.zip
Ian Flockhart, Matthew Booker, Amy Kiger, Michael Boutros, Susan Armknecht, Nadire Ramadan, Kris Richardson, Andrew Xu, Norbert Perrimon, and Bernard Mathey-Prevot. 2006. “FlyRNAi: the Drosophila RNAi screening center database.” Nucleic Acids Res, 34, Database issue, Pp. D489-94.Abstract

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.

2006_Nucl Acids Res_Flockhart.pdf

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