The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

Samuel M. D. Seaver, Filipe Liu, Qizhi Zhang, James Jeffryes, José P. Faria, Janaka N. Edirisinghe, Michael Mundy, Nicholas Chia, Elad Noor, Moritz E. Beber, Aaron A. Best, Matthew DeJongh, Jeffrey A. Kimbrel, Patrik D'haeseleer, Sean R. McCorkle, Jay R. Bolton, Erik Pearson, Shane Canon, Elisha M. Wood-Charlson, Robert W. CottinghamAdam P. Arkin, Christopher S. Henry*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical 'Rosetta Stone' to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org and KBase.
Original languageEnglish
JournalNucleic acids research
Volume49
Issue numberD1
Pages (from-to)D575–D588
ISSN0305-1048
DOIs
Publication statusPublished - 2021

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