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iML1515, a knowledgebase that computes Escherichia coli traits
Open accessAbstract
VOLUME 35 NUMBER 10 OCTOBER 2017 NATURE BIOTECHNOLOGY To the Editor: Extracting knowledge from the many types of big data produced by highthroughput methods remains a challenge, even when data are from Escherichia coli, the best characterized bacterial species. Here, we present iML1515, the most complete genomescale reconstruction of the metabolic network in E. coli K-12 MG1655 to date, and we demonstrate how it can be used to address this challenge. Enabling analysis of several data types, including transcriptomes, proteomes, and metabolomes, iML1515 accounts for 1,515 open reading frames and 2,719 metabolic reactions involving 1,192 unique metabolites. The iML1515 knowledgebase is linked to 1,515 protein structures to provide an integrated modeling framework bridging systems and structural biology. We apply iML1515 to build metabolic models of E. coli human gut microbiome strains from metagenomic sequencing data. We then use iML1515 to build metabolic models for E. coli clinical isolates and predict their metabolic capabilities. Finally, we use iML1515 to carry out a comparative structural proteome analysis of 1,122 E. coli strains and identify multi-strain sequence variations. Genome-scale network reconstructions of metabolism (reviewed in ref. 1) are structured biochemical, genetic, and genomic (BiGG) knowledgebases for an organism1. Metabolic reconstructions aim to cover all metabolic reactions possible in a cell2 to be useful for data interpretation and physiological predictions. Inclusion of different data types can improve the explanatory and predictive capability of a reconstruction. (Fig. 1a). Although E. coli K-12 MG1655 is well-characterized, new functions and capabilities continue to be reported3–5. iML1515 includes the most up-to-date set of characterized genes and metabolic reactions for E. coli K-12 MG1655 (Supplementary Data set 1; http://bigg.ucsd. edu), most of which have been discovered since the last model iJO1366 was published in 2011: structural information for all proteins in the model with links to known protein domains, metabolism of reactive oxygen iML1515, a knowledgebase that computes Escherichia coli traits
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Reconstructing organisms in silico: genome-scale models and their emerging applications
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Heckmann, D., Lloyd, C. J., Mih, N., Ha, Y., Zielinski, D. C., Haiman, Z. B., Desouki, A. A., Lercher, M. J., & Palsson, B. O. (2018) · Nature Communications · doi:10.1038/s41467-018-07652-6 · Cited by 218
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Metadata
- Authors
- Monk, J. M., Lloyd, C. J., Brunk, E., Mih, N., Sastry, A., King, Z., Takeuchi, R., Nomura, W., Zhang, Z., Mori, H., Feist, A. M., & Palsson, B. O.
- Venue
- Nature Biotechnology
- Published
- 2017-10
- Volume
- 35
- Issue
- 10
- Pages
- 904-908
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2764202526
- Cited by
- 560
- References
- 30
- FWCI
- 12.81
- Type
- journal article
- Language
- en
- Open access
- green
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- Monk, J. M., Lloyd, C. J., Brunk, E., Mih, N., Sastry, A., King, Z., Takeuchi, R., Nomura, W., Zhang, Z., Mori, H., Feist, A. M., & Palsson, B. O. (2017). iML1515, a knowledgebase that computes Escherichia coli traits. Nature Biotechnology. https://doi.org/10.1038/nbt.3956
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