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.
References
[1]
Altieri F, Grillo C, Maceroni M, Chichiarelli S (2008) DNA damage and repair: from molecular mechanisms to health implications. Antioxid Redox Signal 10: 891–937.
[2]
Shimada M, Nakanishi M (2006) DNA damage checkpoints and cancer. J Mol Histol 37: 253–260.
[3]
Begley TJ, Rosenbach AS, Ideker T, Samson LD (2004) Hot spots for modulating toxicity identified by genomic phenotyping and localization mapping. Mol Cell 16: 117–125.
[4]
Matsuoka S, Ballif BA, Smogorzewska A, McDonald ER 3rd, Hurov KE, et al. (2007) ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage. Science 316: 1160–1166.
[5]
Workman CT, Mak HC, McCuine S, Tagne JB, Agarwal M, et al. (2006) A systems approach to mapping DNA damage response pathways. Science 312: 1054–1059.
[6]
Kelley R, Ideker T (2005) Systematic interpretation of genetic interactions using protein networks. Nat Biotechnol 23: 561–566.
[7]
Ng A, Bursteinas B, Gao Q, Mollison E, Zvelebil M (2006) Resources for integrative systems biology: from data through databases to networks and dynamic system models. Brief Bioinform 7: 318–330.
[8]
Ramadan N, Flockhart I, Booker M, Perrimon N, Mathey-Prevot B (2007) Design and implementation of high-throughput RNAi screens in cultured Drosophila cells. Nat Protoc 2: 2245–2264.
[9]
Drablos F, Feyzi E, Aas PA, Vaagbo CB, Kavli B, et al. (2004) Alkylation damage in DNA and RNA–repair mechanisms and medical significance. DNA Repair (Amst) 3: 1389–1407.
[10]
Rydberg B, Lindahl T (1982) Nonenzymatic methylation of DNA by the intracellular methyl group donor S-adenosyl-L-methionine is a potentially mutagenic reaction. Embo J 1: 211–216.
[11]
Hecht SS (1999) DNA adduct formation from tobacco-specific N-nitrosamines. Mutat Res 424: 127–142.
[12]
Liu L, Taverna P, Whitacre CM, Chatterjee S, Gerson SL (1999) Pharmacologic disruption of base excision repair sensitizes mismatch repair-deficient and -proficient colon cancer cells to methylating agents. Clin Cancer Res 5: 2908–2917.
[13]
Malet-Martino M, Gilard V, Martino R (1999) The analysis of cyclophosphamide and its metabolites. Curr Pharm Des 5: 561–586.
[14]
Begley TJ, Rosenbach AS, Ideker T, Samson LD (2002) Damage recovery pathways in Saccharomyces cerevisiae revealed by genomic phenotyping and interactome mapping. Mol Cancer Res 1: 103–112.
[15]
Jelinsky SA, Samson LD (1999) Global response of Saccharomyces cerevisiae to an alkylating agent. Proc Natl Acad Sci U S A 96: 1486–1491.
[16]
Lee MW, Kim BJ, Choi HK, Ryu MJ, Kim SB, et al. (2007) Global protein expression profiling of budding yeast in response to DNA damage. Yeast 24: 145–154.
[17]
Murray JI, Whitfield ML, Trinklein ND, Myers RM, Brown PO, et al. (2004) Diverse and specific gene expression responses to stresses in cultured human cells. Mol Biol Cell 15: 2361–2374.
[18]
Wiles AM, Ravi D, Bhavani S, Bishop AJ (2008) An analysis of normalization methods for Drosophila RNAi genomic screens and development of a robust validation scheme. J Biomol Screen 13: 777–784.
[19]
Burgis NE, Samson LD (2007) The protein degradation response of Saccharomyces cerevisiae to classical DNA-damaging agents. Chem Res Toxicol 20: 1843–1853.
[20]
Shen C, Lancaster CS, Shi B, Guo H, Thimmaiah P, et al. (2007) TOR signaling is a determinant of cell survival in response to DNA damage. Mol Cell Biol 27: 7007–7017.
[21]
Rusyn I, Fry RC, Begley TJ, Klapacz J, Svensson JP, et al. (2007) Transcriptional networks in S. cerevisiae linked to an accumulation of base excision repair intermediates. PLoS ONE 2: e1252. doi:10.1371/journal.pone.0001252.
[22]
Dickinson DA, Levonen AL, Moellering DR, Arnold EK, Zhang H, et al. (2004) Human glutamate cysteine ligase gene regulation through the electrophile response element. Free Radic Biol Med 37: 1152–1159.
[23]
Dann SG, Thomas G (2006) The amino acid sensitive TOR pathway from yeast to mammals. FEBS Lett 580: 2821–2829.
[24]
Ou YH, Chung PH, Sun TP, Shieh SY (2005) p53 C-terminal phosphorylation by CHK1 and CHK2 participates in the regulation of DNA-damage-induced C-terminal acetylation. Mol Biol Cell 16: 1684–1695.
[25]
Sinnberg T, Lasithiotakis K, Niessner H, Schittek B, Flaherty KT, et al. (2008) Inhibition of PI3K-AKT-mTOR Signaling Sensitizes Melanoma Cells to Cisplatin and Temozolomide. J Invest Dermatol.
[26]
Kao HY, Ordentlich P, Koyano-Nakagawa N, Tang Z, Downes M, et al. (1998) A histone deacetylase corepressor complex regulates the Notch signal transduction pathway. Genes Dev 12: 2269–2277.
[27]
Kerrien S, Alam-Faruque Y, Aranda B, Bancarz I, Bridge A, et al. (2007) IntAct–open source resource for molecular interaction data. Nucleic Acids Res 35: D561–565.
[28]
Salwinski L, Miller CS, Smith AJ, Pettit FK, Bowie JU, et al. (2004) The Database of Interacting Proteins: 2004 update. Nucleic Acids Res 32: D449–451.
[29]
Alfarano C, Andrade CE, Anthony K, Bahroos N, Bajec M, et al. (2005) The Biomolecular Interaction Network Database and related tools 2005 update. Nucleic Acids Res 33: D418–424.
[30]
Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393: 440–442.
[31]
Begley TJ, Samson LD (2004) Network responses to DNA damaging agents. DNA Repair (Amst) 3: 1123–1132.
[32]
Lynn S, Yew FH, Hwang JW, Tseng MJ, Jan KY (1994) Glutathione can rescue the inhibitory effects of nickel on DNA ligation and repair synthesis. Carcinogenesis 15: 2811–2816.
[33]
Mizumoto K, Glascott PA Jr, Farber JL (1993) Roles for oxidative stress and poly(ADP-ribosyl)ation in the killing of cultured hepatocytes by methyl methanesulfonate. Biochem Pharmacol 46: 1811–1818.
[34]
Harper JW, Elledge SJ (2007) The DNA damage response: ten years after. Mol Cell 28: 739–745.
[35]
Baudot A, Angelelli JB, Guenoche A, Jacq B, Brun C (2008) Defining a modular signalling network from the fly interactome. BMC Syst Biol 2: 45.
[36]
Barrios-Rodiles M, Brown KR, Ozdamar B, Bose R, Liu Z, et al. (2005) High-throughput mapping of a dynamic signaling network in mammalian cells. Science 307: 1621–1625.
[37]
Hwang D, Smith JJ, Leslie DM, Weston AD, Rust AG, et al. (2005) A data integration methodology for systems biology: experimental verification. Proc Natl Acad Sci U S A 102: 17302–17307.
[38]
Vidal M (2005) Interactome modeling. FEBS Lett 579: 1834–1838.
[39]
Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ, et al. (2008) Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321: 1801–1806.
[40]
Lin J, Gan CM, Zhang X, Jones S, Sjoblom T, et al. (2007) A multidimensional analysis of genes mutated in breast and colorectal cancers. Genome Res 17: 1304–1318.
[41]
Ghobrial IM, Witzig TE, Adjei AA (2005) Targeting apoptosis pathways in cancer therapy. CA Cancer J Clin 55: 178–194.
[42]
Rizzo P, Osipo C, Foreman K, Golde T, Osborne B, et al. (2008) Rational targeting of Notch signaling in cancer. Oncogene 27: 5124–5131.
[43]
McConnell JL, Gomez RJ, McCorvey LR, Law BK, Wadzinski BE (2007) Identification of a PP2A-interacting protein that functions as a negative regulator of phosphatase activity in the ATM/ATR signaling pathway. Oncogene 26: 6021–6030.
[44]
Chou WC, Wang HC, Wong FH, Ding SL, Wu PE, et al. (2008) Chk2-dependent phosphorylation of XRCC1 in the DNA damage response promotes base excision repair. Embo J 27: 3140–3150.
[45]
Zhao Y, Katzman RB, Delmolino LM, Bhat I, Zhang Y, et al. (2007) The notch regulator MAML1 interacts with p53 and functions as a coactivator. J Biol Chem 282: 11969–11981.
[46]
Langie SA, Knaapen AM, Houben JM, van Kempen FC, de Hoon JP, et al. (2007) The role of glutathione in the regulation of nucleotide excision repair during oxidative stress. Toxicol Lett 168: 302–309.
[47]
Jelinsky SA, Estep P, Church GM, Samson LD (2000) Regulatory networks revealed by transcriptional profiling of damaged Saccharomyces cerevisiae cells: Rpn4 links base excision repair with proteasomes. Mol Cell Biol 20: 8157–8167.
[48]
Barlow C, Hirotsune S, Paylor R, Liyanage M, Eckhaus M, et al. (1996) Atm-deficient mice: a paradigm of ataxia telangiectasia. Cell 86: 159–171.
[49]
Boutros M, Kiger AA, Armknecht S, Kerr K, Hild M, et al. (2004) Genome-wide RNAi analysis of growth and viability in Drosophila cells. Science 303: 832–835.
[50]
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(？Delta Delta C(T)) Method. Methods 25: 402–408.
[51]
Costa LdF, Rodrigues FA, Travieso G, Boas PRV (2007) Characterization of complex networks: A survey of measurements. Advances in Physics 56: 167–242.
[52]
Sokal RR, Rohlf FJ (1969) Biometrics. San Francisco: W. H. Freeman. pp. 575–585.
[53]
Fisher R (1922) On the interpretation of χ2 from contingency tables, and the calculation of P. Journal of the Royal Statistical Society 85: 87–94.
