The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Omic data from evolved E. coli are consistent with computed optimal growth from genome‐scale models
Open accessAbstract
After hundreds of generations of adaptive evolution at exponential growth, Escherichia coli grows as predicted using flux balance analysis (FBA) on genome‐scale metabolic models (GEMs). However, it is not known whether the predicted pathway usage in FBA solutions is consistent with gene and protein expression in the wild‐type and evolved strains. Here, we report that >98% of active reactions from FBA optimal growth solutions are supported by transcriptomic and proteomic data. Moreover, when E. coli adapts to growth rate selective pressure, the evolved strains upregulate genes within the optimal growth predictions, and downregulate genes outside of the optimal growth solutions. In addition, bottlenecks from dosage limitations of computationally predicted essential genes are overcome in the evolved strains. We also identify regulatory processes that may contribute to the development of the optimal growth phenotype in the evolved strains, such as the downregulation of known regulons and stringent response suppression. Thus, differential gene and protein expression from wild‐type and adaptively evolved strains supports observed growth phenotype changes, and is consistent with GEM‐computed optimal growth states.
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Citations
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 6×
“In addition, the measured growth rates of evolved strains were shown to be consistent with most growth rate predictions from an in silico genome-scale metabolic model (GEM) of Escherichia coli (Ibarra et al , 2002; Fong and Palsson, 2004).”
InfluentialSelf-citationOptimality and evolutionary tuning of the expression level of a protein
Dekel, E., & Alon, U. (2005) · Nature · doi:10.1038/nature03842 · Cited by 766
Growth Rate-Dependent Global Effects on Gene Expression in Bacteria
Klumpp, S., Zhang, Z., & Hwa, T. (2009) · Cell · doi:10.1016/j.cell.2009.12.001 · Cited by 703
Shifts in growth strategies reflect tradeoffs in cellular economics
Molenaar, D., van Berlo, R., de Ridder, D., & Teusink, B. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.82 · Cited by 653
The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli
Feist, A. M., & Palsson, B. Ø. (2008) · Nature Biotechnology · doi:10.1038/nbt1401 · Cited by 545 · cited 1×
“To begin to address these questions, we use constraint-based modeling of E. coli K-12 metabolism (Feist and Palsson, 2008; Lewis et al , 2009b) to analyze a compendium of ‘omics’ data obtained from adaptive evolution experiments.”
Self-citationBeg, Q. K., Vazquez, A., Ernst, J., de Menezes, M. A., Bar-Joseph, Z., Barabási, A.-L., & Oltvai, Z. N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609845104 · Cited by 368
Fong, S. S., Joyce, A. R., & Palsson, B. Ø. (2005) · Genome Research · doi:10.1101/gr.3832305 · Cited by 265 · cited 11×
“Growth rates and substrate uptake rates were determined and reported earlier (Fong et al , 2005, 2006).”
InfluentialSelf-citationThiele, I., Jamshidi, N., Fleming, R. M. T., & Palsson, B. Ø. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000312 · Cited by 182 · cited 1×
“Thus, it is anticipated that genome-scale models of transcription and translation (Thiele et al , 2009) will be useful in evaluating the functional consequences of changes in these systems.”
Self-citationMetabolic Characterization of Escherichia coli Strains Adapted to Growth on Lactate
Hua, Q., Joyce, A. R., Palsson, B. Ø., & Fong, S. S. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.00527-07 · Cited by 67
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Quantitative 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-citationConstraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods
Lewis, N. E., Nagarajan, H., & Palsson, B. O. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2737 · Cited by 779
Self-citationMetabolic modeling of single Th17 cells reveals regulators of autoimmunity
Wagner, A., Wang, C., Fessler, J., DeTomaso, D., Avila-Pacheco, J., Kaminski, J., Zaghouani, S., Christian, E., Thakore, P., Schellhaass, B., et al. (2021) · Cell · doi:10.1016/j.cell.2021.05.045 · Cited by 524
Paxdb, a database of protein abundance averages across all three domains of life
Wang, M., Weiss, M., Simonovic, M., Haertinger, G., Schrimpf, S. P., Hengartner, M. O., & von Mering, C. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.014704 · Cited by 466
Sánchez, B. J., Zhang, C., Nilsson, A., Lahtvee, P., Kerkhoven, E. J., & Nielsen, J. (2017) · Molecular Systems Biology · doi:10.15252/msb.20167411 · Cited by 466
Metadata
- Authors
- Lewis, N. E., Hixson, K. K., Conrad, T. M., Lerman, J. A., Charusanti, P., Polpitiya, A. D., Adkins, J. N., Schramm, G., Purvine, S. O., Lopez‐Ferrer, D., Weitz, K. K., Eils, R., König, R., Smith, R. D., & Palsson, B. Ø.
- Venue
- Molecular Systems Biology
- Published
- 2010-01
- Volume
- 6
- Issue
- 1
- Pages
- 390-390
- ISSN
- 1744-4292 (ISSN-L)
- OpenAlex
- W2160541874
- Cited by
- 753
- References
- 9
- FWCI
- 8.27
- Type
- journal article
- Language
- en
- Open access
- gold
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- Lewis, N. E., Hixson, K. K., Conrad, T. M., Lerman, J. A., Charusanti, P., Polpitiya, A. D., Adkins, J. N., Schramm, G., Purvine, S. O., Lopez‐Ferrer, D., Weitz, K. K., Eils, R., König, R., Smith, R. D., & Palsson, B. Ø. (2010). Omic data from evolved E. coli are consistent with computed optimal growth from genome‐scale models. Molecular Systems Biology. https://doi.org/10.1038/msb.2010.47
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