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An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR)
Open accessAbstract
BACKGROUND: Diverse datasets, including genomic, transcriptomic, proteomic and metabolomic data, are becoming readily available for specific organisms. There is currently a need to integrate these datasets within an in silico modeling framework. Constraint-based models of Escherichia coli K-12 MG1655 have been developed and used to study the bacterium's metabolism and phenotypic behavior. The most comprehensive E. coli model to date (E. coli iJE660a GSM) accounts for 660 genes and includes 627 unique biochemical reactions. RESULTS: An expanded genome-scale metabolic model of E. coli (iJR904 GSM/GPR) has been reconstructed which includes 904 genes and 931 unique biochemical reactions. The reactions in the expanded model are both elementally and charge balanced. Network gap analysis led to putative assignments for 55 open reading frames (ORFs). Gene to protein to reaction associations (GPR) are now directly included in the model. Comparisons between predictions made by iJR904 and iJE660a models show that they are generally similar but differ under certain circumstances. Analysis of genome-scale proton balancing shows how the flux of protons into and out of the medium is important for maximizing cellular growth. CONCLUSIONS: E. coli iJR904 has improved capabilities over iJE660a. iJR904 is a more complete and chemically accurate description of E. coli metabolism than iJE660a. Perhaps most importantly, iJR904 can be used for analyzing and integrating the diverse datasets. iJR904 will help to outline the genotype-phenotype relationship for E. coli K-12, as it can account for genomic, transcriptomic, proteomic and fluxomic data simultaneously.
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Cites
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 2×
“An objective function with a combination of the metabolic precursors, energy and redox potential required for the production of biomass has proven useful in predicting in vivo cellular behavior [9,10,25,26].”
BackgroundMethodSelf-citationMetabolic modelling of microbes: the flux‐balance approach
Edwards, J. S., Covert, M., & Palsson, B. (2002) · Environmental Microbiology · doi:10.1046/j.1462-2920.2002.00282.x · Cited by 365
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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-citationGlobal reconstruction of the human metabolic network based on genomic and bibliomic data
Duarte, N. C., Becker, S. A., Jamshidi, N., Thiele, I., Mo, M. L., Vo, T. D., Srivas, R., & Palsson, B. Ø. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610772104 · Cited by 1,374
Self-citationThe effects of alternate optimal solutions in constraint-based genome-scale metabolic models
Mahadevan, R., & Schilling, C. H. (2003) · Metabolic Engineering · doi:10.1016/j.ymben.2003.09.002 · Cited by 1,203
Self-citationHigh-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
Metadata
- Authors
- Reed, J. L., Vo, T. D., Schilling, C. H., & Palsson, B. O.
- Venue
- Genome Biology
- Published
- 2003-08-28
- Volume
- 4
- Issue
- 9
- Pages
- R54-R54
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- OpenAlex
- W2096245011
- Cited by
- 999
- References
- 2
- FWCI
- 13.73
- Type
- journal article
- Language
- en
- Open access
- gold
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- Reed, J. L., Vo, T. D., Schilling, C. H., & Palsson, B. O. (2003). An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biology. https://doi.org/10.1186/gb-2003-4-9-r54
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