Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks

Nature Biotechnology

Volumn 23, Issue 3, 2005, Pages 377-383

  Bernardo, Diego Di ^a   Thompson, Michael J ^b   Gardner, Timothy S ^b   Chobot, Sarah E ^c   Eastwood, Erin L ^c,d   Wojtovich, Andrew P ^c   Elliott, Scan J ^c   Schaus, Scott E ^c,d   Collins, James J ^b  

^a TELETHON INSTITUTE OF GENETICS AND MEDICINE TIGEM   (Italy)

^b Boston University   (United States)

^c Boston University   (United States)

^d BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL CULTURE; DRUG DOSAGE; ENZYME INHIBITION; ENZYME KINETICS; RNA;

CHEMOGENOMIC PROFILING; GENE REGULATORY NETWORK; THIOREDOXIN REDUCTASE;

GENES;

1 PHENYL 1H TETRAZOL 5 YLSULFONYL BUTANENITRILE; AMITROLE; CHITIN; CYCLOHEXIMIDE; DNA; DYCLONINE; ERGOSTEROL; HISTIDINE; HYDROXYUREA; ITRACONAZOLE; MESSENGER RNA; MEVINOLIN; NIKKOMYCIN; REACTIVE OXYGEN METABOLITE; TERBINAFINE; TETRAZOLE DERIVATIVE; THIOREDOXIN; THIOREDOXIN REDUCTASE; TUNICAMYCIN; UNCLASSIFIED DRUG; SACCHAROMYCES CEREVISIAE PROTEIN;

ARTICLE; BIOSYNTHESIS; CANCER CELL CULTURE; CELL GROWTH; DNA DAMAGE; DNA MICROARRAY; DNA REPLICATION; DRUG RESEARCH; DRUG TARGETING; ENZYME ASSAY; FUNGUS GROWTH; GROWTH INHIBITION; HUMAN; HUMAN CELL; LUNG SMALL CELL CANCER; NONHUMAN; OXIDATION REDUCTION REACTION; PHARMACOGENOMICS; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE; STEROID METABOLISM; STEROL SYNTHESIS; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; COMPUTER SIMULATION; DRUG DELIVERY SYSTEM; DRUG DESIGN; DRUG EFFECT; EVALUATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; METHODOLOGY; PHYSIOLOGY; PROTEIN ANALYSIS; PROTEIN ENGINEERING; SIGNAL TRANSDUCTION; STATISTICAL MODEL;

FUNGI; SACCHAROMYCES CEREVISIAE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DRUG DELIVERY SYSTEMS; DRUG DESIGN; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PROTEIN ENGINEERING; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SIGNAL TRANSDUCTION; THIOREDOXIN; THIOREDOXIN REDUCTASE (NADPH);

EID: 21444452397     PISSN: 10870156     EISSN: None     Source Type: Journal    
DOI: 10.1038/nbt1075     Document Type: Article

References (48)

1. Hughes, T.R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109-126 (2000).
2. Courcelle, J., Khodursky, A., Peter, B., Brown, P.O. & Hanawalt, P.C. Comparative gene expression profiles following UV exposure in wild-type and SOS-deficient Escherichia coli. Genetics 158, 41-64 (2001).
3. Bredel, M. & Jacoby, E. Chemogenomics: an emerging strategy for rapid target and drug discovery. Nat. Rev. Genet. 5, 262-275 (2004).
4. Miklos, G.L.G. & Maleszka, R. Microarray reality checks in the context of a complex disease. Nat. Biotechnol. 22, 615-621 (2004).
5. Giaever, G. et al. Genomic profiling of drug sensitivities via induced haploinsufficiency. Nat. Genet 21, 278-283 (1999).
6. Giaever, G. et al. Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. Proc. Natl. Acad. Sci. USA 101, 793-798 (2004).
7. Lum, P.Y. et al. Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes. Cell 116, 121-137 (2004).
8. Parsons, A.B. et al. Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways. Nat. Biotechnol. 22, 62-69 (2004).
9. Marton, M.J. et al. Drug target validation and identification of secondary drug target effects using DNA microarrays. Nat. Med. 4, 1293-1301 (1998).
10. Stoughton, R. & Friend, S.H. Methods for identifying pathways of drug action. US Patent No. 5,965,352 (2003).
11. Bar-Joseph, Z. et al. Computational discovery of gene modules and regulatory networks. Nat. Biotechnol. 21, 1337-1342 (2003).
12. Beer, M.A. & Tavazoie, S. Predicting gene expression from sequence. Cell 117, 185-198 (2004).
13. Covert, M.W., Knight, E.M., Reed, J.L., Herrgard, M.J. & Palsson, B.O. Integrating high-throughput and computational data elucidates bacterial networks. Nature 429, 92-96 (2004).
14. de la Fuente, A., Brazhnik, P. & Mendes, P. Linking the genes: inferring quantitative gene networks from microarray data. Trends Genet. 18, 395-398 (2002).
15. Gardner, T.S., di Bernardo, D., Lorenz, D. & Collins, J.J. Inferring genetic networks and identifying compound mode of action via expression profiling. Science 301, 102-105 (2003).
16. Gasch, A.P. et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 11, 4241-4257 (2000).
17. Herrgard, M.J., Covert, M.W. & Palsson, B.O. Reconstruction of microbial transcriptional regulatory networks. Curr. Opin. Biotechnol. 15, 70-77 (2004).
18. Ideker, T. et al. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929-934 (2001).
19. Liao, J.C. et al. Network component analysis: reconstruction of regulatory signals in biological systems. Proc. Natl. Acad. Sci. USA 100, 15522-15527 (2003).
20. Rice, J. & Stolovitzky, G. Making the most of it: pathway reconstruction and integrative simulation using the data at hand. Drug Discov. Today: BioSilico 2, 70-77 (2004).
21. Ronen, M., Rosenberg, R., Shraiman, B.I. & Alon, U. Assigning numbers to the arrows: parameterizing a gene regulation network by using accurate expression kinetics. Proc. Natl. Acad. Sci. USA 99, 10555-10560 (2002).
22. Tegner, J., Yeung, M.K., Hasty, J. & Collins, J.J. Reverse engineering gene networks: integrating genetic perturbations with dynamical modeling. Proc. Natl. Acad. Sci. USA 100, 5944-5949 (2003).
23. Yeung, M.K.S., Tegner, J. & Collins, J.J. Reverse engineering gene networks using singular value decomposition and robust regression. Proc. Natl. Acad. Sci. USA 99, 6163-6168 (2002).
24. Kholodenko, B.N. et al. Untangling the wires: a strategy to trace functional interactions in signaling and gene networks. Proc. Natl. Acad. Sci. USA 99, 12841-12846 (2002).
25. Hartemink, A.J., Gifford, O.K., Jaakkola, T.S. & Young, R.A. Combining location and expression data for principled discovery of genetic regulatory network. Proc. Pacific. Symp. Biocomp. 7, 437-449 (2002).
26. Kalir, S. & Alon, U. Using a quantitative blueprint to reprogram the dynamics of the flagella gene network. Cell 117, 713-720 (2004).
27. Schmitt, W.A.J., Raab, R.M. & Stephanopoulos, G. Elucidation of gene interaction networks through time-lagged correlation analysis of transcriptional data. Genome Res. 14, 1654-1663 (2004).
28. Dempster, A., Laird, N. & Rubin, D. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. [Ser. B] 139, 1-38 (1977).
29. Mnaimneh, S. et al. Exploration of essential gene functions via titratable promoter alleles. Cell 118, 31-44 (2004).
30. Ueda, M. et al. Effect of catalase-specific inhibitor 3-amino-1,2,4-triazole on yeast peroxisomal catalase in vivo. FEMS Microbiol. Lett. 219, 93-98 (2003).
31. Chabes, A. et al. Survival of DNA damage in yeast directly depends on increased dNTP levels allowed by relaxes feedback inhibition of ribonucleotide reductase. Cell 112, 391-401 (2003).
32. Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000).
33. Bennett, C. et al. Genes required for ionizing radiation resistance in yeast. Nat. Genet. 29, 426-434 (2001).
34. Hand, R.A., Jia, N., Bard, M. & Craven, R.J. Saccharomyces cerevisiae Dap1p, a novel DNA damage response protein related to the mammalian membrane-associated progesterone receptor. Eukaryot. Cell 2, 306-317 (2003).
35. Holmgren, A. & Reichard, P. Thioredoxin 2: cleavage with cyanogen bromide. Eur. J. Biochem. 2, 187-196 (1967).
36. NCBI Gene Expression Omnibus: http://www.ncbi.nlm.nih.gov/geo.
37. Stanford Microarray Database: http://genome-www5.stanford.edu.
38. The Alliance for Cellular Signaling: http://www.signaling-gateway.org/.
39. Eisen, M.B. & Brown, P.O. DNA arrays for analysis of gene expression. Meth. Enzymol. 303, 179-205 (1999).
40. Hastie, T., Tibshirani, R. & Friedman, J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer, New York, 2001).
41. Klobucnikova, V. et al. Terbinafine resistance in a pleiotropic yeast mutant is caused by a single point mutation in the ERG1 gene. Biochem. Biophys. Res. Commun. 309, 666-671 (2003).
42. Rine, J., Hansen, W., Hardeman, E. & Davis, R.W. Targeted selection of recombinant clones through gene dosage effects. Proc. Natl. Acad. Sci. USA 80, 6750-6754 (1983).
43. Daum, G., Lees, N.D., Bard, M. & Dickson, R. Biochemistry, cell biology and molecular biology of lipids of Saccharomyces cerevisiae. Yeast 14, 1471-1510 (1998).
44. Rittberg, D.A. & Wright, J.A. Relationships between sensitivity to hydroxyurea and 4-methyl-5-amino-1-formylisoquinoline thiosemicarbazone (MAIO) and ribonucleotide reductase RNR2 mRNA levels in strains of Saccharomyces cerevisiae. Biochem. Cell Biol. 67, 352-357 (1989).
45. Stocklein, W. & Piepersberg, W. Binding of cycloheximide to ribosomes from wild-type and mutant strains of Saccharomyces cerevisiae. Antimicrob. Agents Chemother. 18, 863-867 (1980).
46. Barnes, G., Hansen, W.J., Holcomb, C.L. & Rine, J. Asparagine-linked glycosylation in Saccharomyces cerevisiae: genetic analysis of an early step. Mol. Cell Biol. 4, 2381-2388 (1984).
47. Gaughran, J.P., Lai, M.H., Kirsch, D.R. & Silverman, S.J. Nikkomycin Z is a specific inhibitor of Saccharomyces cerevisiae chitin synthase isozyme Chs3 in vitro and in vivo. J. Bacteriol. 175, 5857-5860 (1994).
48. Anderson, R.M. et al. Yeast life-span extension by calorie restriction is independent of NAD fluctuation. Science 302, 2124-2126(2003).