The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information
Open accessAbstract
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.
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Citations
Cites
Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection
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Energy conservation in chemotrophic anaerobic bacteria
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Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
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Self-citationEvolution Experiments with Microorganisms: The Dynamics and Genetic Bases of Adaptation
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The effects of alternate optimal solutions in constraint-based genome-scale metabolic models
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Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
Ibarra, R. U., Edwards, J. S., & Palsson, B. O. (2002) · Nature · doi:10.1038/nature01149 · Cited by 857 · cited 1×
“…in the context of generating maximal amounts of biomass precursors (i.e., simulated optimal growth) from available media substrates using FBA can generate results that are consistent with experimental data (Edwards et al, 2001; Covert and Palsson, 2002; Ibarra et al, 2002; Covert et al, 2004).”
ResultSelf-citationIntegrating high-throughput and computational data elucidates bacterial networks
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Self-citationChance and necessity in the evolution of minimal metabolic networks
Pál, C., Papp, B., Lercher, M. J., Csermely, P., Oliver, S. G., & Hurst, L. D. (2006) · Nature · doi:10.1038/nature04568 · Cited by 239 · cited 1×
“For studies of bacterial evolution, a reconstruction serves as a highly curated database and model to examine and simulate evolutionary hypotheses (Pal et al, 2005, 2006).”
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“The literature confirms that whereas import of these ions proceeds via diffusion through a regulated ion channel, export of these ions requires a separate mechanism that utilizes ATP hydrolysis or proton antiport as a source of energy to drive the reaction (Silver, 1996; Grass et al, 2005).”
BackgroundMathematical models in microbial systems biology
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Cited by
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903
Self-citationQuantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.308 · Cited by 1,835
Self-citationA protocol for generating a high-quality genome-scale metabolic reconstruction
Thiele, I., & Palsson, B. Ø. (2010) · Nature Protocols · doi:10.1038/nprot.2009.203 · Cited by 1,789
Self-citationModelling and analysis of gene regulatory networks
Karlebach, G., & Shamir, R. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2503 · Cited by 1,296
High-throughput generation, optimization and analysis of genome-scale metabolic models
Henry, C. S., DeJongh, M., Best, A. A., Frybarger, P. M., Linsay, B., & Stevens, R. L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1672 · Cited by 1,090
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Metadata
- Authors
- Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P. D., Broadbelt, L. J., Hatzimanikatis, V., & Palsson, B. Ø.
- Venue
- Molecular Systems Biology
- Published
- 2007-01
- Volume
- 3
- Issue
- 1
- Pages
- 121-121
- ISSN
- 1744-4292 (ISSN-L)
- OpenAlex
- W2170427655
- Cited by
- 1,383
- References
- 10
- FWCI
- 32.81
- Type
- journal article
- Language
- en
- Open access
- gold
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- Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P. D., Broadbelt, L. J., Hatzimanikatis, V., & Palsson, B. Ø. (2007). A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Molecular Systems Biology. https://doi.org/10.1038/msb4100155
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