Clément Carré, Caroline Jacquier, Anne-Laure Bougé, Fabrice de Chaumont, Corinne Besnard-Guerin, Hélène Thomassin, Josette Pidoux, Bruno Da Silva, Eleftheria Chalatsi, Sarah Zahra, Jean-Christophe Olivo-Marin, Hélène Munier-Lehmann, and Christophe Antoniewski. 2013. “
AutomiG, a biosensor to detect alterations in miRNA biogenesis and in small RNA silencing guided by perfect target complementarity.” PLoS One, 8, 9, Pp. e74296.
AbstractDefects 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.
2013_PLOS One_Carre.pdf Supplemental Files.zip Yong Miao, Cathrine Miner, Lei Zhang, Phyllis I Hanson, Adish Dani, and Monika Vig. 2013. “
An essential and NSF independent role for α-SNAP in store-operated calcium entry.” Elife, 2, Pp. e00802.
AbstractStore-operated calcium entry (SOCE) by calcium release activated calcium (CRAC) channels constitutes a primary route of calcium entry in most cells. Orai1 forms the pore subunit of CRAC channels and Stim1 is the endoplasmic reticulum (ER) resident Ca(2+) sensor. Upon store-depletion, Stim1 translocates to domains of ER adjacent to the plasma membrane where it interacts with and clusters Orai1 hexamers to form the CRAC channel complex. Molecular steps enabling activation of SOCE via CRAC channel clusters remain incompletely defined. Here we identify an essential role of α-SNAP in mediating functional coupling of Stim1 and Orai1 molecules to activate SOCE. This role for α-SNAP is direct and independent of its known activity in NSF dependent SNARE complex disassembly. Importantly, Stim1-Orai1 clustering still occurs in the absence of α-SNAP but its inability to support SOCE reveals that a previously unsuspected molecular re-arrangement within CRAC channel clusters is necessary for SOCE. DOI:http://dx.doi.org/10.7554/eLife.00802.001.
2013_eLife_Miao.pdf Keren Imberg-Kazdan, Susan Ha, Alex Greenfield, Christopher S Poultney, Richard Bonneau, Susan K Logan, and Michael J Garabedian. 2013. “
A genome-wide RNA interference screen identifies new regulators of androgen receptor function in prostate cancer cells.” Genome Res, 23, 4, Pp. 581-91.
AbstractThe androgen receptor (AR) is a mediator of both androgen-dependent and castration-resistant prostate cancers. Identification of cellular factors affecting AR transcriptional activity could in principle yield new targets that reduce AR activity and combat prostate cancer, yet a comprehensive analysis of the genes required for AR-dependent transcriptional activity has not been determined. Using an unbiased genetic approach that takes advantage of the evolutionary conservation of AR signaling, we have conducted a genome-wide RNAi screen in Drosophila cells for genes required for AR transcriptional activity and applied the results to human prostate cancer cells. We identified 45 AR-regulators, which include known pathway components and genes with functions not previously linked to AR regulation, such as HIPK2 (a protein kinase) and MED19 (a subunit of the Mediator complex). Depletion of HIPK2 and MED19 in human prostate cancer cells decreased AR target gene expression and, importantly, reduced the proliferation of androgen-dependent and castration-resistant prostate cancer cells. We also systematically analyzed additional Mediator subunits and uncovered a small subset of Mediator subunits that interpret AR signaling and affect AR-dependent transcription and prostate cancer cell proliferation. Importantly, targeting of HIPK2 by an FDA-approved kinase inhibitor phenocopied the effect of depletion by RNAi and reduced the growth of AR-positive, but not AR-negative, treatment-resistant prostate cancer cells. Thus, our screen has yielded new AR regulators including drugable targets that reduce the proliferation of castration-resistant prostate cancer cells.
2013_Genome Res_Imberg-Kazdan.pdf Supplement.pdf Arunachalam Vinayagam, Yanhui Hu, Meghana Kulkarni, Charles Roesel, Richelle Sopko, Stephanie E Mohr, and Norbert Perrimon. 2013. “
Protein complex-based analysis framework for high-throughput data sets.” Sci Signal, 6, 264, Pp. rs5.
AbstractAnalysis of high-throughput data increasingly relies on pathway annotation and functional information derived from Gene Ontology. This approach has limitations, in particular for the analysis of network dynamics over time or under different experimental conditions, in which modules within a network rather than complete pathways might respond and change. We report an analysis framework based on protein complexes, which are at the core of network reorganization. We generated a protein complex resource for human, Drosophila, and yeast from the literature and databases of protein-protein interaction networks, with each species having thousands of complexes. We developed COMPLEAT (http://www.flyrnai.org/compleat), a tool for data mining and visualization for complex-based analysis of high-throughput data sets, as well as analysis and integration of heterogeneous proteomics and gene expression data sets. With COMPLEAT, we identified dynamically regulated protein complexes among genome-wide RNA interference data sets that used the abundance of phosphorylated extracellular signal-regulated kinase in cells stimulated with either insulin or epidermal growth factor as the output. The analysis predicted that the Brahma complex participated in the insulin response.
2013_Sci Sig_Vinayagam.pdf Supplemental Files.zip Zheng Yin, Amine Sadok, Heba Sailem, Afshan McCarthy, Xiaofeng Xia, Fuhai Li, Mar Arias Garcia, Louise Evans, Alexis R Barr, Norbert Perrimon, Christopher J Marshall, Stephen TC Wong, and Chris Bakal. 2013. “
A screen for morphological complexity identifies regulators of switch-like transitions between discrete cell shapes.” Nat Cell Biol, 15, 7, Pp. 860-71.
AbstractThe 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.
2013_Nat Cell Bio_Yin.pdf Supplemental Files.zip Yanhui Hu, Charles Roesel, Ian Flockhart, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 2013. “
UP-TORR: online tool for accurate and Up-to-Date annotation of RNAi Reagents.” Genetics, 195, 1, Pp. 37-45.
AbstractRNA interference (RNAi) is a widely adopted tool for loss-of-function studies but RNAi results only have biological relevance if the reagents are appropriately mapped to genes. Several groups have designed and generated RNAi reagent libraries for studies in cells or in vivo for Drosophila and other species. At first glance, matching RNAi reagents to genes appears to be a simple problem, as each reagent is typically designed to target a single gene. In practice, however, the reagent-gene relationship is complex. Although the sequences of oligonucleotides used to generate most types of RNAi reagents are static, the reference genome and gene annotations are regularly updated. Thus, at the time a researcher chooses an RNAi reagent or analyzes RNAi data, the most current interpretation of the RNAi reagent-gene relationship, as well as related information regarding specificity (e.g., predicted off-target effects), can be different from the original interpretation. Here, we describe a set of strategies and an accompanying online tool, UP-TORR (for Updated Targets of RNAi Reagents; www.flyrnai.org/up-torr), useful for accurate and up-to-date annotation of cell-based and in vivo RNAi reagents. Importantly, UP-TORR automatically synchronizes with gene annotations daily, retrieving the most current information available, and for Drosophila, also synchronizes with the major reagent collections. Thus, UP-TORR allows users to choose the most appropriate RNAi reagents at the onset of a study, as well as to perform the most appropriate analyses of results of RNAi-based studies.
2013_Genetics_Hu.pdf Supplement.pdf