Development of an Algorithm for Reconstructing a Comprehensive Pathway Model: Application to Saccharomyces cerevisiae

Itaru Takeda^1,2, Masayuki Machida^1,3, Sachiyo Aburatani^2*

¹Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Naka-cho, Koganei, Tokyo, Japan.
²Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo Waterfront Bio-IT Research Building, Aomi, Koto-ku, Tokyo, Japan.
³Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Higashi-nijo, Tsukisamu, Sapporo, Japan.

DOI: 10.4236/jbise.2015.88047                

Abstract

The generation of bioactive products by microbial bioprocesses is important for drug discovery, functional food development, and other beneficial purposes. Many pathways contribute to the production of these bioactive compounds, but important knowledge for improving productivity still remains in hidden pathways. Recently, an abundance of knowledge about metabolic pathways has been accumulated in metabolic pathway databases, such as BioCyc and KEGG. Many by-products are chemically transformed and actually used in other enzymatic reactions. In this work, we developed an algorithm for the reconstruction of a comprehensive genetic pathway model from a known metabolic pathway database. This model considers the interactions of the by-products, in addition to the main products. Furthermore, we developed a method for the construction of a comprehensive pathway model in a specific organism. In this study, we reconstructed a Saccharomyces cerevisiae model. From this model, the pathways among enzymes that contributed to galactose metabolism were explored. Using S. cerevisiae DNA microarray data, the activated pathways were found among the explored pathways.

Keywords

Bioinformatics, Metabolic Pathway

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Wiemann, P. and Keller, N.P. (2014) Strategies for Mining Fungal Natural Products. Journal of Industrial Microbiology & Biotechnology, 41, 301-313. http://dx.doi.org/10.1007/s10295-013-1366-3
[2]	Hwang, K.S., Kim, H.U., Charusanti, P., Palsson, B.O. and Lee, S.Y. (2014) Systems Biology and Biotechnology of Streptomyces Species for the Production of Secondary Metabolites. Biotechnology Advances, 32, 255-268. http://dx.doi.org/10.1016/j.biotechadv.2013.10.008
[3]	Bentley, R. (2006) From miso, saké and shoyu to Cosmetics: A Century of Science for Kojic Acid. Natural Product Reports, 23, 1046-1062. http://dx.doi.org/10.1039/b603758p
[4]	Saruno, R., Kato, F. and Ikeno, T. (1979) Kojic Acid, a Tyrosinase Inhibitor from Aspergillus albus. Agricultural and Biological Chemistry, 43, 1337-1338.
[5]	Cabanes, J., Charzarra, S. and Garcia-Carmona, F. (1994) Kojic Acid, a Cosmetic Skin Whitening Agent, Is a Slow-Binding Inhibitor of Catecholase Activity of Tyrosinase. Journal of Pharmacy and Pharmacology, 46, 982-985. http://dx.doi.org/10.1111/j.2042-7158.1994.tb03253.x
[6]	Terabayashi, Y., Sano, M., Yamane, N., Marui, J., Tamano, K., Sagara, J., Dohmoto, M., Oda, K., Ohshima, E., Tachibana, K., Higa, Y., Ohashi, S., Koike, H. and Machida, M. (2010) Identification and Characterization of Genes Responsible for Biosynthesis of Kojic Acid, an Industrially Important Compound from Aspergillus oryzae. Fungal Genetics and Biology, 47, 953-961. http://dx.doi.org/10.1016/j.fgb.2010.08.014
[7]	Liu, J., Farmer, J.D. Jr., Lane, W.S., Friedman, J., Weissman, I. and Schreiber, S.L. (1991) Calcineurin Is a Common Target of Cyclophilin-Cyclosporin A and FKBP-FK506 Complexes. Cell, 66, 807-815. http://dx.doi.org/10.1016/0092-8674(91)90124-H
[8]	Kunz, J. and Hall, M.N. (1993) Cyclosporin A, FK506 and Rapamycin: More than Just Immunosuppression. Trends in Biochemical Sciences, 18, 334-338. http://dx.doi.org/10.1016/0968-0004(93)90069-Y
[9]	Survase, S.A., Kagliwal, L.D., Annapure, U.S. and Singhal, R.S. (2011) Cyclosporin A—A Review on Fermentative Production, Downstream Processing and Pharmacological Applications. Biotechnology Advances, 29, 418-435. http://dx.doi.org/10.1016/j.biotechadv.2011.03.004
[10]	Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H. and Kanehisa, M. (1999) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research, 27, 29-34. http://dx.doi.org/10.1093/nar/27.1.29
[11]	Kanehisa, M. and Goto, S. (2000) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research, 28, 27-30.
[12]	Kanehisa, M., Goto, S., Sato, Y., Furumichi, M. and Tanabe, M. (2012) KEGG for Integration and Interpretation of Large-Scale Molecular Data Sets. Nucleic Acids Research, 40, 109-114. http://dx.doi.org/10.1093/nar/gkr988
[13]	Karp, P.D., Ouzounis, C.A., Moore-Kochlacs, C., Goldovsky, L., Kaipa, P., Ahrén, D., Tsoka, S., Darzentas, N., Kunin, V. and López-Bigas, N. (2005) Expansion of the BioCyc Collection of Pathway/Genome Databases to 160 Genomes. Nucleic Acids Research, 33, 6083-6089. http://dx.doi.org/10.1093/nar/gki892
[14]	Croft, D., O’Kelly, G., Wu, G., Haw, R., Gillespie, M., Matthews, L., Caudy, M., Garapati, P., Gopinath, G., Jassal, B., Jupe, S., Kalatskaya, I., Mahajan, S., May, B., Ndegwa, N., Schmidt, E., Shamovsky, V., Yung, C., Birney, E., Hermjakob, H., D’Eustachio, P. and Stein, L. (2011) Reactome: A Database of Reactions, Pathways and Biological Processes. Nucleic Acids Research, 39, 691-697. http://dx.doi.org/10.1093/nar/gkq1018
[15]	Karp, P.D. and Caspi, R. (2011) A Survey of Metabolic Databases Emphasizing the MetaCyc Family. Archives of Toxicology, 85, 1015-1033. http://dx.doi.org/10.1007/s00204-011-0705-2
[16]	Stobbe, M.D., Jansen, G.A., Moerland, P.D. and van Kampen, A.H. (2014) Knowledge Representation in Metabolic Pathway Databases. Briefings in Bioinformatics, 15, 455-470. http://dx.doi.org/10.1093/bib/bbs060
[17]	Kanehisa, M. (2013) Chemical and Genomic Evolution of Enzyme-Catalyzed Reaction Networks. Federation of European Biochemical Societies, 587, 2731-2737. http://dx.doi.org/10.1016/j.febslet.2013.06.026
[18]	Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y. and Hattori, M. (2004) The KEGG Resource for Deciphering the Genome. Nucleic Acids Research, 32, 277-280. http://dx.doi.org/10.1093/nar/gkh063
[19]	Barrett, T. and Edgar, R. (2006) Gene Expression Omnibus: Microarray Data Storage, Submission, Retrieval, and Analysis. Methods in Enzymology, 411, 352-369. http://dx.doi.org/10.1016/S0076-6879(06)11019-8
[20]	Gasch, A.P., Spellman, P.T., Kao, C.M., Carmel-Harel, O., Eisen, M.B., Storz, G., Botstein, D. and Brown, P.O. (2000) Genomic Expression Programs in the Response of Yeast Cells to Environmental Changes. Molecular Biology of the Cell, 11, 4241-4257. http://dx.doi.org/10.1091/mbc.11.12.4241
[21]	Umemura, M., Koyama, Y., Takeda, I., Hagiwara, H., Ikegami, T., Koike, H. and Machida, M. (2013) Fine de Novo Sequencing of a Fungal Genome Using Only SOLiD Short Read Data: Verification on Aspergillus oryzae RIB40. PLoS ONE, 8, e63673. http://dx.doi.org/10.1371/journal.pone.0063673
[22]	Takeda, I., Tamano, K., Yamane, N., Ishii, T., Miura, A., Umemura, M., Terai, G., Baker, S.E., Koike, H. and Machida, M. (2014) Genome Sequence of the Mucoromycotina Fungus Umbelopsis isabellina, an Effective Producer of Lipids. Genome Announcements, 2, e00071-14. http://dx.doi.org/10.1128/genomea.00071-14
[23]	Moriya, Y, Itoh, M., Okuda, S., Yoshizawa, A.C. and Kanehisa, M. (2007) KAAS: An Automatic Genome Annotation and Pathway Reconstruction Server. Nucleic Acids Research, 35, 182-185. http://dx.doi.org/10.1093/nar/gkm321
[24]	Sellick, C.A., Campbell, R.N. and Reece, R.J. (2008) Galactose Metabolism in Yeast-Structure and Regulation of the Leloir Pathway Enzymes and the Genes Encoding Them. International Review of Cell and Molecular Biology, 269, 111-150. http://dx.doi.org/10.1016/S1937-6448(08)01003-4
[25]	Conrad, M., Schothorst, J., Kankipati, H.N., Van Zeebroeck, G., Rubio-Texeira, M. and Thevelein, J.M. (2014) Nutrient Sensing and Signaling in the Yeast Saccharomyces cerevisiae. FEMS Microbiology Reviews, 38, 254-299. http://dx.doi.org/10.1111/1574-6976.12065
[26]	Johnston, M. (1987) A Model Fungal Gene Regulatory Mechanism: The GAL Genes of Saccharomyces cerevisiae. Microbiological Reviews, 51, 458-476.
[27]	Bro, C., Knudsen, S., Regenberg, B., Olsson, L. and Nielsen J. (2005) Improvement of Galactose Uptake in Saccharomyces cerevisiae through Overexpression of Phosphoglucomutase: Example of Transcript Analysis as a Tool in Inverse Metabolic Engineering. Applied and Environmental Microbiology, 71, 6465-6472. http://dx.doi.org/10.1128/AEM.71.11.6465-6472.2005