High-throughput data analysis

2018 Apr 13

DRSC & TRiP Workshop at ADRC

1:45pm to 3:45pm

Location: 

Philadelphia, PA, USA
The DRSC & TRiP will be hosting a workshop at the Annual Drosophila Research Conference in Philadelphia, PA. The workshop is scheduled for Friday, April 13th from 1:45 to 3:45 PM. Come hear from DRSC & TRiP leaders Norbert Perrimon, Jonathan Zirin (organizer), Claire Yanhui Hu, and Stephanie Mohr. At the workshop, you will learn about new opportunities for community nomination and experiments using CRISPR knockout and activation, as well as learn what's new and popular among our online software and database tools. There will be something for everyone -- we will provide information... Read more about DRSC & TRiP Workshop at ADRC
Figure 2 from Housden et al 2017 PNAS

Variable Dose Analysis: a new DRSC-supported cell screen approach that leverages existing reagents to perform robust screens

December 1, 2017

We are excited to report the publication of a paper from Benjamin Housden and colleagues describing development and use of the Variable Dose Analysis (VDA) approach. Ben developed a way to use existing TRiP shRNA plasmids originally developed for fly stock production in a new, effective approach to high-throughput cell screening.

The VDA approach is particularly useful for combinatorial approaches that are acutely sensitive to assay robustness. The screen Ben and colleagues report focused on synthetic effects in Drosophila tumor model cells.  The...

Read more about Variable Dose Analysis: a new DRSC-supported cell screen approach that leverages existing reagents to perform robust screens
Screenshot of a 2015 Science paper from Payre and colleagues

Francois Payre's plenary talk at ADRC 2017 features results from DRSC cell-based screen

March 30, 2017

Those of us lucky enough to be at the Annual Drosophila Research Conference this morning saw a great talk by Francois Payre about regulation of Shavenbaby by small ORFs. A genome-wide cell-based screen done at the DRSC by Emilie Benrabah identified the mechanism of regulation. As this exemplifies, cell screens can help identify key pathways and factors that can then be followed up with in vivo studies.

J Zanet, E Benrabah, T Li, A Pélissier-Monier, H Chanut-Delalande, B Ronsin, HJ Bellen, F Payre, and S Plaza. 2015. “Pri sORF peptides induce selective proteasome-mediated protein processing.” Science, 349, 6254, Pp. 1356-8.Abstract

A wide variety of RNAs encode small open-reading-frame (smORF/sORF) peptides, but their functions are largely unknown. Here, we show that Drosophila polished-rice (pri) sORF peptides trigger proteasome-mediated protein processing, converting the Shavenbaby (Svb) transcription repressor into a shorter activator. A genome-wide RNA interference screen identifies an E2-E3 ubiquitin-conjugating complex, UbcD6-Ubr3, which targets Svb to the proteasome in a pri-dependent manner. Upon interaction with Ubr3, Pri peptides promote the binding of Ubr3 to Svb. Ubr3 can then ubiquitinate the Svb N terminus, which is degraded by the proteasome. The C-terminal domains protect Svb from complete degradation and ensure appropriate processing. Our data show that Pri peptides control selectivity of Ubr3 binding, which suggests that the family of sORF peptides may contain an extended repertoire of protein regulators.

Arunachalam Vinayagam, Meghana M Kulkarni, Richelle Sopko, Xiaoyun Sun, Yanhui Hu, Ankita Nand, Christians Villalta, Ahmadali Moghimi, Xuemei Yang, Stephanie E Mohr, Pengyu Hong, John M Asara, and Norbert Perrimon. 9/13/2016. “An Integrative Analysis of the InR/PI3K/Akt Network Identifies the Dynamic Response to Insulin Signaling.” Cell Reports, 16, 11, Pp. 3062-3074.Abstract

Insulin regulates an essential conserved signaling pathway affecting growth, proliferation, and meta- bolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic, and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network sur- rounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNAi screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and, using quantitative phospho- proteomics, we demonstrate that $10% of interact- ing proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes and validate our method by iden- tifying regulatory roles for the Protein Phosphatase 2A (PP2A) and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for the study of the evolutionary conserved insulin network. 

Ian T Flockhart, Matthew Booker, Yanhui Hu, Benjamin McElvany, Quentin Gilly, Bernard Mathey-Prevot, Norbert Perrimon, and Stephanie E Mohr. 2012. “FlyRNAi.org--the database of the Drosophila RNAi screening center: 2012 update.” Nucleic Acids Res, 40, Database issue, Pp. D715-9.Abstract

FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.

Marcelo Perez-Pepe, Victoria Slomiansky, Mariela Loschi, Luciana Luchelli, Maximiliano Neme, María Gabriela Thomas, and Graciela Lidia Boccaccio. 2012. “BUHO: a MATLAB script for the study of stress granules and processing bodies by high-throughput image analysis.” PLoS One, 7, 12, Pp. e51495.Abstract

The spontaneous and reversible formation of foci and filaments that contain proteins involved in different metabolic processes is common in both the nucleus and the cytoplasm. Stress granules (SGs) and processing bodies (PBs) belong to a novel family of cellular structures collectively known as mRNA silencing foci that harbour repressed mRNAs and their associated proteins. SGs and PBs are highly dynamic and they form upon stress and dissolve thus releasing the repressed mRNAs according to changes in cell physiology. In addition, aggregates containing abnormal proteins are frequent in neurodegenerative disorders. In spite of the growing relevance of these supramolecular aggregates to diverse cellular functions a reliable automated tool for their systematic analysis is lacking. Here we report a MATLAB Script termed BUHO for the high-throughput image analysis of cellular foci. We used BUHO to assess the number, size and distribution of distinct objects with minimal deviation from manually obtained parameters. BUHO successfully addressed the induction of both SGs and PBs in mammalian and insect cells exposed to different stress stimuli. We also used BUHO to assess the dynamics of specific mRNA-silencing foci termed Smaug 1 foci (S-foci) in primary neurons upon synaptic stimulation. Finally, we used BUHO to analyze the role of candidate genes on SG formation in an RNAi-based experiment. We found that FAK56D, GCN2 and PP1 govern SG formation. The role of PP1 is conserved in mammalian cells as judged by the effect of the PP1 inhibitor salubrinal, and involves dephosphorylation of the translation factor eIF2α. All these experiments were analyzed manually and by BUHO and the results differed in less than 5% of the average value. The automated analysis by this user-friendly method will allow high-throughput image processing in short times by providing a robust, flexible and reliable alternative to the laborious and sometimes unfeasible visual scrutiny.

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