A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information

By Adam M. Feist, Christopher S. Henry, Jennifer L. Reed, Markus Krummenacker, Andrew R. Joyce, Peter D. Karp, Linda J. Broadbelt, Vassily Hatzimanikatis, Bernhard O. Palsson. Molecular Systems Biology, 2007

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An updated genome‐scale reconstruction of the metabolic network in Escherichia coli K‐12 MG1655 is presented. This updated metabolic reconstruction includes: (1) an alignment with the latest genome annotation and the metabolic content of EcoCyc leading to the inclusion of the activities of 1260 ORFs, (2) characterization and quantification of the biomass components and maintenance requirements associated with growth of E. coli and (3) thermodynamic information for the included chemical reactions. The conversion of this metabolic network reconstruction into an in silico model is detailed. A new step in the metabolic reconstruction process, termed thermodynamic consistency analysis, is introduced, in which reactions were checked for consistency with thermodynamic reversibility estimates. Applications demonstrating the capabilities of the genome‐scale metabolic model to predict high‐throughput experimental growth and gene deletion phenotypic screens are presented. The increased scope and computational capability using this new reconstruction is expected to broaden the spectrum of both basic biology and applied systems biology studies of E. coli metabolism.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0b9193580334b1529287aed6a91d1221f09126dd

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Citations in the corpus

Metabolic-network-driven analysis of bacterial ecological strategies (2009, methodology): “Computing the environmental viability matrix, environmental scope index and co-habitation score As a measure for species viability we constructed a list of 65 compounds termed 'target metabolites' (Additional data file 5), which are most likely essential for growth in most species [36-38].”
Environments that Induce Synthetic Microbial Ecosystems (2010, methodology): “The genome scale metabolic models for 5 of the organisms used have been published and are publicly available (Escherichia coli [59], Bacillus subtilis [60], Helicobacter pylori [61], Salmonella typhimurium [62], Methanosarcina barkeri [63]).”
Chapter 1. General introduction (2015, neutral): “…books Built by scientists, for scientists 12.2% 117,000 130M TOP 1%154 4,400 Chapter 1 General Introduction: Advances in Hepatic Surgery J.H.M.B. Stoot, R.J.S. Coelen, J.L.A. van Vugt and C.H.C. Dejong Additional information is available at the end of the chapter http://dx.doi.org/10.5772/54710”
Genome-scale models of bacterial metabolism: reconstruction and applications (2008, methodology): “For instance, the most complete bacterial model available to date – namely iAF1260, the latest model of Escherichia coli metabolism – includes references to more than 320 articles (Feist et al ., 2007).”
High-throughput generation, optimization and analysis of genome-scale metabolic models (2010, neutral): “Auto-completion reactions Inactive reactions 800 800 1,200 1,200 1,600 1,600 Dehalococcoides (1) 600/381/105 α-proteobacteria (18) 944/705/64 ε-proteobacteria (6) 788/471/61 Bacilli (21) 1,051/757/47”
Consistent Estimation of Gibbs Energy Using Component Contributions (2013, background): “coli reconstruction iAF1260 [5], and a human reconstruction Recon 1 [29].”
Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism (2014, methodology): “The simulations for the E. coli and S. cerevisiae case studies were performed using, respectively, the iAF1260 and iTO977 genome-scale models [43,45].”
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions (2010, background): “The E. coli metabolic network reconstruction has gone through several iterations and has become more complete [35].”
Efficient searching and annotation of metabolic networks using chemical similarity (2015, background): “Native metabolic networks, such as that of iAF1260, are composed of (cid:2) 10 3 compound nodes, with an additional 10 3 reaction nodes (Feist et al. , 2007).”