Bioinformatics Analysis for Interactive Proteomics
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Abstract
High?throughput protein?protein interaction data are becoming a foundation for new biological discoveries. A major challenge is to manage, analyze, and model these data. In this unit several databases are described that are used to store, query, and visualize protein?protein interaction data. Comparison between experimental techniques reveals that each high?throughput technique has its limitations in detecting certain types of interactions; however, the techniques are generally complementary. In silico prediction methods for protein?protein interactions can expand the scope of experimental data and increase the confidence of certain interactions. Use of protein?protein interaction networks, preferably integrating them with other types of data, allows assignment of cellular functions to novel proteins and derivation of new biological pathways. As demonstrated in this unit, bioinformatics can be used to transform protein?protein interaction data from noisy information into knowledge of cellular mechanisms.
Keywords: protein?protein interaction; high?throughput data; yeast two hybrid; protein complex; proteome; bioinformatics
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Figure 25.1.1 (A ) Visualization of 8286 protein‐protein interactions from the BIND database generated with the Pajek visualization tool (http://vlado.fmf.uni‐lj.si/pub/networks/pajek/). (B ) Cytoscape (http://www.cytoscape.org/) graphic output for 359 protein‐protein interactions in yeast detected by two‐hybrid assays. View Image -
Figure 25.1.2 The protein interaction map in yeast around Nup100p from PathCalling (http://curatools.curagen.com/pathcalling_portal/). A gene is represented as a node and a protein‐protein interaction is indicated as an edge. View Image -
Figure 25.1.3 Three Cmd1p related protein complexes identified by mass spectrometry. The annotated Cmd1p interacting partners (i.e., proteins with known functions), shown in dark color, are derived from experimental results reviewed in Cyert (). View Image -
Figure 25.1.4 Output generated by GENFAS (http://digbio.missouri.edu/genefas/) to predict the function of the hypothetical gene YER079W . “Index” indicates the gene ontology (GO) hierarchical level. “Reliability Score” is used to rank the predicted functions. “Probability” gives the likelihood of prediction accuracy. “GO identifier” is the entry ID for GO. View Image -
Figure 25.1.5 Relationship between biological pathway and protein‐protein interaction data. (A ) The MAPK signaling pathway for filamentation (i.e., the connections between genes) taken from KEGG. (B ) A MAPK signal transduction pathway constructed using protein interaction data. View Image -
Figure 25.1.6 Output generated by the Web server http://digbio.missouri.edu/genepath showing a predicted biological pathway using products of YBL062W and YNL119W as the two terminal proteins. “GO MF ID” indicates GO molecular function identification codes. The numbers in the Function row indicate GO hierarchical levels. View Image
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Literature Cited
| Literature Cited | |
| Bader, G.D., Donaldson, I., Wolting, C., Ouellette, B.F., Pawson, T., and Hogue, C.W. 2001. BIND–The Biomolecular Interaction Network Database. Nucl. Acids Res. 29:242‐245. | |
| Bartel, P.L., Roecklein, J.A., SenGupta, D., and Fields, S. 1996. A protein linkage map of Escherichia coli bacteriophage T7. Nature Genet. 12:72‐77. | |
| Broder, Y.C., Katz, S., and Aronheim, A. 1998. The ras recruitment system, a novel approach to the study of protein‐protein interactions. Curr. Biol. 8:1121‐1124. | |
| Chen, Y. and Xu, D. 2003. Computational analyses of high‐throughput protein‐protein interaction data. Curr. Protein Pept. Sci. 4:159‐181. | |
| Chen, Y., Joshi, T., Xu, Y., and Xu, D. 2003a. Automated derivation of biological pathways using yeast high‐throughput data In Proceedings of the 3rd IEEE Symposium on Bioinformatics and Bioengineering, pp. 3‐10. IEEE/CS Press, Los Alamitos, Ca. | |
| Chen, Y., Liu, Y., Goldstein, K., Becker, J.M., Xu, Y., and Xu, D. 2003b. A computational study on the signal transduction pathway for amino acid transport yeast: bridging the gap between high‐throughput data and traditional biology. Applied Genomics and Proteomics 4:159‐181. | |
| Cyert, M.S. 2001. Genetic analysis of calmodulin and its targets in Saccharomyces cerevisiae. Annu. Rev. Genet. 35:647‐672. | |
| Drees, B.L. 1999. Progress and variations in two‐hybrid and three‐hybrid technologies. Curr. Opin. Chem. Biol. 3:64‐70. | |
| Duan, X.J., Xenarios, I., and Eisenberg, D. 2002. Describing biological protein interactions in terms of protein states and state transitions: The LiveDIP database. Mol. Cell. Proteomics 1:104‐116. | |
| Ehrhard, K.N., Jacoby, J.J., Fu, X.Y., Jahn, R., and Dohlman, H.G. 2000. Use of G‐protein fusions to monitor integral membrane protein‐protein interactions in yeast. Nat. Biotechnol. 18:1075‐1079. | |
| Field, S. and Song, O. 1989. A novel genetic system to detect protein–protein interactions Nature 340:245‐246. | |
| Flajolet, M., Rotondo, G., Daviet, L., Bergametti, F., Inchauspe, G., Tiollais, P., Transy, C., and Legrain, P. 2000. A genomic approach of the hepatitis C virus generates a protein interaction map. Gene 241:369‐379. | |
| Gavin, A.C., Bosche, M., Krause, R., Grandi, P., Marzioch, M., Bauer, A., Schultz, J., Rick, J.M., Michon, A.M., Cruciat, C.M., Remor, M., Hofert, C., Schelder, M., Brajenovic, M., Ruffner, H., Merino, A., Klein, K., Hudak, M., Dickson, D., Rudi, T., Gnau, V., Bauch, A., Bastuck, S., Huhse, B., Leutwein, C., Heurtier, M.A., Copley, R.R, Edelmann, A., Querfurth, E., Rybin, V., Drewes, G., Raida, M., Bouwmeester, T., Bork, P., Seraphin, B., Kuster, B., Neubauer, G., and Superti‐Furga, G. 2002. Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415:141‐147. | |
| Ho, Y., Gruhler, A., Heilbut, A., Bader, G.D., Moore, L., Adams, S.L., Millar, A., Taylor, P., Bennett, K., Boutilier, K., Yang, L., Wolting, C., Donaldson, I., Schandorff, S., Shewnarane, J., Vo, M., Taggart, J., Goudreault, M., Muskat, B., Alfarano, C., Dewar, D., Lin, Z., Michalickova, K., Willems, A.R., Sassi, H., Nielsen, P.A., Rasmussen, K.J, Andersen, J.R., Johansen, L.E., Hansen, L.H., Jespersen, H., Podtelejnikov, A., Nielsen, E., Crawford, J., Poulsen, V., Sorensen, B.D., Matthiesen, J., Hendrickson, R.C., Gleeson, F., Pawson, T., Moran, M.F, Durocher, D., Mann, M., Hogue, C.W., Figeys, D., and Tyers, M. 2002. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415:180‐183. | |
| Holstege, F.C., Jennings, E.G., Wyrick, J.J., Lee, T.I., Hengartner, C.J., Green, M.R., Golub, T.R., Lander, E.S., and Young, R.A. 1998. Chromosomal landscape of nucleosome‐dependent gene expression and silencing in yeast. Cell 95:717‐728. | |
| Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M., and Sakaki, Y. 2001. A comprehensive two‐hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. U.S.A. 98:4569‐4574. | |
| Johnsson, N. and Varshavsky, A. 1994. Split ubiquitin as a sensor of protein interactions in vivo. Proc. Natl. Acad. Sci. U.S.A. 91:10340‐10344. | |
| Kanehisa, M., Goto, S., Kawashima, S., and Nakaya, A. 2002. The KEGG databases at GenomeNet. Nucl. Acids Res. 30:42‐46. | |
| Kumar, A. and Snyder, M. 2001. Emerging technologies in yeast genomics. Nat. Rev. Genet. 2:302‐312. | |
| Legrain, P., Wojcik, J., and Gauthier, J.M. 2001. Protein‐protein interaction maps: A lead towards cellular functions. Trends Genet. 7:346‐352. | |
| Marcotte, E.M., Pellegrini, M., Ng, H.L., Rice, D.W., Yeates, T.O., and Eisenberg, D. 1999. Detecting protein function and protein‐protein interactions from genome sequences. Science 285:751‐753. | |
| Martzen, M.R., McCraith, S.M., Spinelli, S.L., Torres, F.M., Fields, S., Grayhack, E.J., and Phizicky, E.M. 1999. A biochemical genomics approach for identifying genes by the activity of their products. Science 286:1153‐1155. | |
| Mewes, H.W., Frishman, D., Gruber, C., Geier, B., Haase, D., Kaps, A., Lemcke, K., Mannhaupt, G., Pfeiffer, F., Schuller, C., Stocker, S., and Weil, B. 2000. MIPS: A database for genomes and protein sequences. Nucl. Acids Res. 28:37‐40. | |
| Mullaney, B.P. and Pallavicini, M.G. 2001. Protein‐protein interactions in hematology and phage display. Exp. Hematol. 29:1136‐1146. | |
| Ono, T., Hishigaki, H., Tanigami, A., and Takagi, T. 2001. Automated extraction of information on protein‐protein interactions from the biological literature. Bioinformatics 17:155‐161. | |
| Overbeek, R., Fonstein, M., D'Souza, M., Pusch, G.D., and Maltsev, N. 1999. The use of gene clusters to infer functional coupling. Proc. Natl. Acad. Sci. U.S.A. 96:2896‐2901. | |
| Pellegrini, M., Marcotte, E.M., Thompson, M.J., Eisenberg, D., and Yeates, T.O. 1999. Assigning protein functions by comparative genome analysis: Protein phylogenetic profiles. Proc. Natl. Acad. Sci. U.S.A. 96:4285‐4288. | |
| Pelletier, J. and Sidhu, S. 2001. Mapping protein‐protein interactions with combinatorial biology methods. Curr. Opin. Biotechnol. 12:340‐347. | |
| Phizicky, E.M. and Field, S. 1995. Protein‐protein interactions: Methods for detection and analysis. Microbiol. Rev. 59:94‐123. | |
| Rain, J.C., Selig, L., De Reuse, H., Battaglia, V., Reverdy, C., Simon, S., Lenzen, G., Petel, F., Wojcik, J., Schachter, V., Chemama, Y., Labigne, A., and Legrain, P. 2001. The protein‐protein interaction map of Helicobacter pylori. Nature 409:211‐215. | |
| Schachter, V. 2002. Protein‐interaction networks: From experiments to analysis. Drug Discov. Today 7:S48‐S54. | |
| Schwikowski, B., Uetz, P., and Fields, S. 2000. A network of protein‐protein interactions in yeast. Nat. Biotechnol. 18:1257‐1261. | |
| Suzuki, H., Fukunishi, Y., Kagawa, I., Saito, R., Oda, H., Endo, T., Kondo, S., Bono, H., Okazaki, Y., and Hayashizaki, Y. 2001. Protein‐protein interaction panel using mouse full‐length cDNAs. Genome Res. 11:1758‐1765. | |
| Uetz, P. and Hughes, R.E. 2000. Systematic and large‐scale two‐hybrid screens. Curr. Opin. Microbiol. 3:303‐308. | |
| Uetz, P., Giot, L., Cagney, G., Mansfield, T.A., Judson, R.S., Knight, J.R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., Qureshi‐Emili, A., Li, Y., Godwin, B., Conover, D., Kalbfleisch, T., Vijayadamodar, G., Yang, M., Johnston, M., Fields, S., and Rothberg, J.M. 2000. A comprehensive analysis of protein‐protein interactions in Saccharomyces cerevisiae. Nature 403:623‐627. | |
| Walhout, A.J., Soredella, R., Lu, X., Hartley, J.L., Temple, G.F., Brasch, M.A., Thierry‐Mieg, N., and Vidal, M. 2000. Protein interaction mapping in C. elegans using proteins involved in vulval development. Science 287:116‐122. | |
| Xenarios, I., Salwinski, L., Duan, X.J., Higney, P., Kim, S., and Eisenberg, D. 2002. DIP, the Database of Interacting Proteins: A research tool for studying cellular networks of protein interactions. Nucl. Acids Res. 30:303‐305. | |
| Zanzoni, A., Montechi‐Palazzi, L., Quondam, M., Ausiello, G., Helmer‐Citterich, M., and Cesareni, G. 2002. MINT: A Molecular INTeraction database. FEBS Lett. 513:135‐140. | |
| Zhu, H., Klemic, J.F., Chang, S., Bertone, P., Casamayor, A., Klemic, K.G., Smith, D., Gerstein, M., Reed, M.A., and Snyder, M. 2000. Analysis of yeast protein kinases using protein chips. Nat. Genet. 26:283‐289. |
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