EcoSal Plus
Domain 10: Bioinformatics and Systems Biology
The EcoCyc Database
- Authors: Peter D. Karp1, Wai Kit Ong2, Suzanne Paley3, Richard Billington4, Ron Caspi5, Carol Fulcher6, Anamika Kothari7, Markus Krummenacker8, Mario Latendresse9, Peter E. Midford10, Pallavi Subhraveti11, Socorro Gama-Castro12, Luis Muñiz-Rascado13, César Bonavides-Martinez14, Alberto Santos-Zavaleta15, Amanda Mackie16, Julio Collado-Vides17, Ingrid M. Keseler18, and Ian Paulsen19
- Editor: Susan T. Lovett20
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VIEW AFFILIATIONS HIDE AFFILIATIONSAffiliations: 1: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 2: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 3: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 4: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 5: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 6: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 7: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 8: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 9: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 10: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 11: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 12: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, México; 13: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, México; 14: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, México; 15: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, México; 16: Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109, Australia; 17: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, A.P. 565-A, Cuernavaca, Morelos 62100, México; 18: Bioinformatics Research Group, SRI International, Menlo Park, CA 94025; 19: Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109, Australia; 20: Department of Biology, Brandeis University, Waltham, MA
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Received 05 June 2018 Accepted 18 September 2018 Published 12 November 2018
- Address correspondence to Peter D. Karp, [email protected]

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Abstract:
EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed via EcoCyc.org. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.
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Citation: Karp P, Ong W, Paley S, Billington R, Caspi R, Fulcher C, Kothari A, Krummenacker M, Latendresse M, Midford P, Subhraveti P, Gama-Castro S, Muñiz-Rascado L, Bonavides-Martinez C, Santos-Zavaleta A, Mackie A, Collado-Vides J, Keseler I, Paulsen I. 2018. The EcoCyc Database, EcoSal Plus 2018; doi:10.1128/ecosalplus.ESP-0006-2018




The EcoCyc Database, Page 1 of 2
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Abstract:
EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed via EcoCyc.org. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.

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Tables

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Table 1
Genes and gene products in EcoCyc

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Table 2
Gene annotation status in EcoCyc

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Table 3
Reactions, compounds, and pathways in EcoCyc

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Table 4
Regulation-related objects and interactions in EcoCyc

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Table 5
Comparison of the number of biomass metabolites and the number of reactions carrying flux for EcoCyc-17.5, EcoCyc-18.0, and EcoCyc-22.05 under glucose aerobic and anaerobic conditions

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Table 6
Comparison of experimental aerobic glucose-limited chemostat growth data with EcoCyc-17.5, EcoCyc-22.05, and iML1515 model predictions

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Table 7
Comparison of experimental anaerobic glucose-limited chemostat growth data with EcoCyc-17.5, EcoCyc-22.05, and iML1515 model predictions

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Table 8
Comparison of experimental gene essentiality results with computational EcoCyc-22.05_BW results for aerobic growth on MOPS medium with 0.4% glucose

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Table 9
Comparison of experimental gene essentiality results with computational EcoCyc-22.05_BW results for aerobic growth on MOPS medium with 1% glycerol
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