iML1515, a knowledgebase that computes Escherichia coli traits

Jonathan M. Monk, Colton J. Lloyd, Elizabeth Brunk, Nathan Mih, Anand Sastry, Zachary King, Rikiya Takeuchi, Wataru Nomura, Zhen Zhang, Hirotada Mori, Adam M. Feist, Bernhard O. Palsson

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To the Editor:
Extracting knowledge from the many types of big data produced by high-throughput methods remains a challenge, even when data are from Escherichia coli, the best characterized bacterial species. Here, we present iML1515, the most complete genome-scale 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.
Original languageEnglish
JournalNature Biotechnology
Issue number10
Pages (from-to)904-908
Publication statusPublished - 2017

Cite this

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, 35(10), 904-908.