A systematic comparison of the MetaCyc and KEGG pathway databases

被引：106

作者：

Altman, Tomer ^{[1
]}

Travers, Michael ^{[1
]}

Kothari, Anamika ^{[1
]}

Caspi, Ron ^{[1
]}

Karp, Peter D. ^{[1
]}

机构：

[1] SRI Int, Bioinformat Res Grp, Menlo Pk, CA 94025 USA

来源：

BMC BIOINFORMATICS | 2013年 / 14卷

基金：

美国国家卫生研究院;

关键词：

Pathway databases; Database comparison; METABOLIC PATHWAYS; BIOCYC COLLECTION; MULTIORGANISM DATABASE; KYOTO ENCYCLOPEDIA; ENZYMES; GENES; RESOURCE;

D O I：

10.1186/1471-2105-14-112

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Background: The MetaCyc and KEGG projects have developed large metabolic pathway databases that are used for a variety of applications including genome analysis and metabolic engineering. We present a comparison of the compound, reaction, and pathway content of MetaCyc version 16.0 and a KEGG version downloaded on Feb-27-2012 to increase understanding of their relative sizes, their degree of overlap, and their scope. To assess their overlap, we must know the correspondences between compounds, reactions, and pathways in MetaCyc, and those in KEGG. We devoted significant effort to computational and manual matching of these entities, and we evaluated the accuracy of the correspondences. Results: KEGG contains 179 module pathways versus 1,846 base pathways in MetaCyc; KEGG contains 237 map pathways versus 296 super pathways in MetaCyc. KEGG pathways contain 3.3 times as many reactions on average as do MetaCyc pathways, and the databases employ different conceptualizations of metabolic pathways. KEGG contains 8,692 reactions versus 10,262 for MetaCyc. 6,174 KEGG reactions are components of KEGG pathways versus 6,348 for MetaCyc. KEGG contains 16,586 compounds versus 11,991 for MetaCyc. 6,912 KEGG compounds act as substrates in KEGG reactions versus 8,891 for MetaCyc. MetaCyc contains a broader set of database attributes than does KEGG, such as relationships from a compound to enzymes that it regulates, identification of spontaneous reactions, and the expected taxonomic range of metabolic pathways. MetaCyc contains many pathways not found in KEGG, from plants, fungi, metazoa, and actinobacteria; KEGG contains pathways not found in MetaCyc, for xenobiotic degradation, glycan metabolism, and metabolism of terpenoids and polyketides. MetaCyc contains fewer unbalanced reactions, which facilitates metabolic modeling such as using flux-balance analysis. MetaCyc includes generic reactions that may be instantiated computationally. Conclusions: KEGG contains significantly more compounds than does MetaCyc, whereas MetaCyc contains significantly more reactions and pathways than does KEGG, in particular KEGG modules are quite incomplete. The number of reactions occurring in pathways in the two DBs are quite similar.

引用

页数：15

共 44 条

[1] Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome [J].

Abubucker, Sahar ;

Segata, Nicola ;

Goll, Johannes ;

Schubert, Alyxandria M. ;

Izard, Jacques ;

Cantarel, Brandi L. ;

Rodriguez-Mueller, Beltran ;

Zucker, Jeremy ;

Thiagarajan, Mathangi ;

Henrissat, Bernard ;

White, Owen ;

Kelley, Scott T. ;

Methe, Barbara ;

Schloss, Patrick D. ;

Gevers, Dirk ;

Mitreva, Makedonka ;

Huttenhower, Curtis .

PLOS COMPUTATIONAL BIOLOGY, 2012, 8 (06)

[2] Rhea-a manually curated resource of biochemical reactions [J].

Alcantara, Rafael ;

Axelsen, Kristian B. ;

Morgat, Anne ;

Belda, Eugeni ;

Coudert, Elisabeth ;

Bridge, Alan ;

Cao, Hong ;

de Matos, Paula ;

Ennis, Marcus ;

Turner, Steve ;

Owen, Gareth ;

Bougueleret, Lydie ;

Xenarios, Ioannis ;

Steinbeck, Christoph .

NUCLEIC ACIDS RESEARCH, 2012, 40 (D1) :D754-D760

[3]

[Anonymous], 2006, Introduction to Data Mining

[4]

Arnaud M., 2005, CURATORS GUIDE PATHW

[5] The Universal Protein Resource (UniProt) 2009 [J].

Bairoch, Amos ;

Consortium, UniProt ;

Bougueleret, Lydie ;

Altairac, Severine ;

Amendolia, Valeria ;

Auchincloss, Andrea ;

Argoud-Puy, Ghislaine ;

Axelsen, Kristian ;

Baratin, Delphine ;

Blatter, Marie-Claude ;

Boeckmann, Brigitte ;

Bolleman, Jerven ;

Bollondi, Laurent ;

Boutet, Emmanuel ;

Quintaje, Silvia Braconi ;

Breuza, Lionel ;

Bridge, Alan ;

deCastro, Edouard ;

Ciapina, Luciane ;

Coral, Danielle ;

Coudert, Elisabeth ;

Cusin, Isabelle ;

Delbard, Gwennaelle ;

Dornevil, Dolnide ;

Roggli, Paula Duek ;

Duvaud, Severine ;

Estreicher, Anne ;

Famiglietti, Livia ;

Feuermann, Marc ;

Gehant, Sebastian ;

Farriol-Mathis, Nathalie ;

Ferro, Serenella ;

Gasteiger, Elisabeth ;

Gateau, Alain ;

Gerritsen, Vivienne ;

Gos, Arnaud ;

Gruaz-Gumowski, Nadine ;

Hinz, Ursula ;

Hulo, Chantal ;

Hulo, Nicolas ;

James, Janet ;

Jimenez, Silvia ;

Jungo, Florence ;

Junker, Vivien ;

Kappler, Thomas ;

Keller, Guillaume ;

Lachaize, Corinne ;

Lane-Guermonprez, Lydie ;

Langendijk-Genevaux, Petra ;

Lara, Vicente .

NUCLEIC ACIDS RESEARCH, 2009, 37 :D169-D174

[6]

Bernard Thomas., 2012, Briefings in bioinformatics, pbbs058

[7]

Bolton E., 2008, PUBCHEM INTEGRATED P, V4

[8]

Caspi R, 2008, NUCLEIC ACIDS RES, V36, pD623, DOI [10.1093/nar/gkm900, 10.1093/nar/gkt1103]

[9] MetaCyc: a multiorganism database of metabolic pathways and enzymes [J].

Caspi, Ron ;

Foerster, Hartmut ;

Fulcher, Carol A. ;

Hopkinson, Rebecca ;

Ingraham, John ;

Kaipa, Pallavi ;

Krummenacker, Markus ;

Paley, Suzanne ;

Pick, John ;

Rhee, Seung Y. ;

Tissier, Christophe ;

Zhang, Peifen ;

Karp, Peter D. .

NUCLEIC ACIDS RESEARCH, 2006, 34 :D511-D516

[10] The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases [J].

Caspi, Ron ;

Altman, Tomer ;

Dreher, Kate ;

Fulcher, Carol A. ;

Subhraveti, Pallavi ;

Keseler, Ingrid M. ;

Kothari, Anamika ;

Krummenacker, Markus ;

Latendresse, Mario ;

Mueller, Lukas A. ;

Ong, Quang ;

Paley, Suzanne ;

Pujar, Anuradha ;

Shearer, Alexander G. ;

Travers, Michael ;

Weerasinghe, Deepika ;

Zhang, Peifen ;

Karp, Peter D. .

NUCLEIC ACIDS RESEARCH, 2012, 40 (D1) :D742-D753

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