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.

Genome-wide RNA interference (RNAi) screening allows investigation of the role of individual genes in a process of choice. Most RNAi screens identify a large number of genes with a continuous gradient in the assessed phenotype. Screeners must decide whether to examine genes with the most robust phenotype or the full gradient of genes that cause an effect and how to identify candidate genes. The authors have used RNAi in Drosophila cells to examine viability in a 384-well plate format and compare 2 screens, untreated control and treatment. They compare multiple normalization methods, which take advantage of different features within the data, including quantile normalization, background subtraction, scaling, cellHTS2 (Boutros et al. 2006), and interquartile range measurement. Considering the false-positive potential that arises from RNAi technology, a robust validation method was designed for the purpose of gene selection for future investigations. In a retrospective analysis, the authors describe the use of validation data to evaluate each normalization method. Although no method worked ideally, a combination of 2 methods, background subtraction followed by quantile normalization and cellHTS2, at different thresholds, captures the most dependable and diverse candidate genes. Thresholds are suggested depending on whether a few candidate genes are desired or a more extensive systems-level analysis is sought. The normalization approaches and experimental design to perform validation experiments are likely to apply to those high-throughput screening systems attempting to identify genes for systems-level analysis. 1 Its compatibility with high-throughput technology 2 has revolutionized the quest for identification of novel genes in signal transduction pathways, human diseases, and drug targets. 1,3,4 Publications from analysis of these types of screens are constantly being added to the literature, with relatively few publications addressing experimental design and data analysis. Although publications have addressed general protocols and logical approaches for gene selection 5 or have introduced novel methods of data analysis and criteria for assessment of quality , 6 there is a lack of data in the literature to compare and contrast data analysis methods and a lack of design of rigorous validation methods. Because RNAi-based screening is a labor-intensive technology involving complex experimental setup, because there is a deficiency of appropriate standards and the current analytical tools are relatively limited, we address some of the deficiencies related to appropriate experimental design for Drosophila RNAi genomic screening, examine the available analytical methods, and develop a rigorous validation scheme. METHODS Tissue cultureKc 167 cells were grown in Schneider medium (Invitrogen, Carlsbad, CA) supplemented with 10% heat-inactivated fetal bovine serum (FBS; 65 °C, 10 min), 100 U/mL penicillin, and 100 μg/mL streptomycin, at 24 °C in a humidified chamber. One hour at 24 °C allowed phagocytic uptake of the dsR...

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Transfection of transgenes into Drosophila cultured cells is a standard approach for studying gene function. However, the number of transgenes present in the cell following transient transfection or stable random integration varies, and the resulting differences in expression level affect interpretation. Here we developed a system for Drosophila cell lines that allows selection of cells with a single-copy transgene inserted at a specific genomic site using recombination-mediated cassette exchange (RMCE). We used the fC31 integrase and its target sites attP and attB for RMCE. Cell lines with an attP-flanked genomic cassette were transfected with donor plasmids containing a transgene of interest (UAS-x), a dihydrofolate reductase (UAS-DHFR) gene flanked by attB sequences, and a thymidine kinase (UAS-TK) gene in the plasmid backbone outside the attB sequences. In cells undergoing RMCE, UAS-x and UAS-DHFR were exchanged for the attP-flanked genomic cassette, and UAS-TK was excluded. These cells were selected using methotrexate, which requires DHFR expression, and ganciclovir, which causes death in cells expressing TK. Pure populations of cells with one copy of a stably integrated transgene were efficiently selected by cloning or mass culture in $6 weeks. Our results show that RMCE avoids the problems associated with current methods, where transgene number is not controlled, and facilitates the rapid generation of Drosophila cell lines in which expression from a single transgene can be studied. KEYWORDS RMCE; Drosophila; cell line; single-transgene expression M AMMALIAN cultured cells can be genetically modified by site-specific insertion of transgenes using homologous recombination and various recombinase systems (Branda and Dymecki 2004;Sorrell and Kolb 2005). In contrast, transgenes are introduced into Drosophila cultured cells either by transient transfection or by stable transformation following random integration of transgenes together with a selectable marker (Eschalier 1997;Cherbas and Cherbas 2007). These methods fail to provide control of transgene expression because the number of transgene copies in the cells varies greatly. Moreover, in stably transformed lines, the sites of insertion vary, and each will be subject to position effects on gene expression (Spradling and Rubin 1983). For these reasons, methods that involve site-specific introduction of single transgenes into Drosophila tissue culture cells would be a significant improvement.Homologous recombination has been attempted in Drosophila cell culture, but the levels of nonspecific recombination observed make the approach unsatisfactory (Cherbas and Cherbas 1997). Several site-specific recombination systems have been used successfully in whole flies, including uC31, which mediates recombination between two heterotypic target sites referred to as attP and attB (Groth et al. 2004;Venken et al. 2006;Bischof et al. 2007). Insertion results in two new sites (attL and attR) that are not targets of the integrase, thus producing an irreversible cha...

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