ArticleScientific reports2017
EColiCore2: a reference network model of the central metabolism of Escherichia coli and relationships to its genome-scale parent model.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- On the conditions for shifts in metabolic strategies.PLoS computational biology · 2026Review
- The return of metabolism: biochemistry and physiology of glycolysis.Biological reviews of the Cambridge Philosophical Society · 2026Review
- A compact model of Escherichia coli core and biosynthetic metabolism.PLoS computational biology · 2025Article
- Minimal cut sets in metabolic networks: from conceptual foundations to applications in metabolic engineering and biomedicine.Briefings in bioinformatics · 2025Review
- Efficiency of acetate-based isopropanol synthesis in Escherichia coli W is controlled by ATP demand.Biotechnology for biofuels and bioproducts · 2024Article
- Genome scale metabolic network modelling for metabolic profile predictions.PLoS computational biology · 2024Article
- Microbiome modeling: a beginner's guide.Frontiers in microbiology · 2024Review
- Balancing biomass reaction stoichiometry and measured fluxes in flux balance analysis.Bioinformatics (Oxford, England) · 2023Article
- Growth-coupled anaerobic production of isobutanol from glucose in minimal medium with Escherichia coli.Biotechnology for biofuels and bioproducts · 2023Article
- Chaos in synthetic microbial communities.PLoS computational biology · 2022Article
- Rapid-SL identifies synthetic lethal sets with an arbitrary cardinality.Scientific reports · 2022Article
- Analyzing and Resolving Infeasibility in Flux Balance Analysis of Metabolic Networks.Metabolites · 2022Article
- Deciphering the physiological response of Escherichia coli under high ATP demand.Molecular systems biology · 2021Article
- EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search.BMC bioinformatics · 2021Article
- Designing microbial communities to maximize the thermodynamic driving force for the production of chemicals.PLoS computational biology · 2021Article
- Atlas: automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages.Bioinformatics (Oxford, England) · 2021Article
- Opening a Novel Biosynthetic Pathway to Dihydroxyacetone and Glycerol inInternational journal of molecular sciences · 2020Article
- An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets.PLoS computational biology · 2020Article
- A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks.PLoS computational biology · 2020Article
- Characterizing and ranking computed metabolic engineering strategies.Bioinformatics (Oxford, England) · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-scale metabolic modeling has become an invaluable tool to analyze properties and capabilities of metabolic networks and has been particularly successful for the model organism Escherichia coli. However, for several applications, smaller metabolic (core) models are needed. Using a recently introduced reduction algorithm and the latest E. coli genome-scale reconstruction iJO1366, we derived EColiCore2, a model of the central metabolism of E. coli. EColiCore2 is a subnetwork of iJO1366 and preserves predefined phenotypes including optimal growth on different substrates. The network comprises 486 metabolites and 499 reactions, is accessible for elementary-modes analysis and can, if required, be further compressed to a network with 82 reactions and 54 metabolites having an identical solution space as EColiCore2. A systematic comparison of EColiCore2 with its genome-scale parent model iJO1366 reveals that several key properties (flux ranges, reaction essentialities, production envelopes) of the central metabolism are preserved in EColiCore2 while it neglects redundancies along biosynthetic routes. We also compare calculated metabolic engineering strategies in both models and demonstrate, as a general result, how intervention strategies found in a core model allow the identification of valid strategies in a genome-scale model. Overall, EColiCore2 holds promise to become a reference model of E. coli's central metabolism.
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