A workflow for generating multi-strain genome-scale metabolic models of prokaryotes

Charles J. Norsigian, Xin Fang, Yara Seif, Jonathan M. Monk, Bernhard O. Palsson*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Genome-scale models (GEMs) of bacterial strains’ metabolism have been formulated and used over the past 20 years. Recently, with the number of genome sequences exponentially increasing, multi-strain GEMs have proved valuable to define the properties of a species. Here, through four major stages, we extend the original Protocol used to generate a GEM for a single strain to enable multi-strain GEMs: (i) obtain or generate a high-quality model of a reference strain; (ii) compare the genome sequence between a reference strain and target strains to generate a homology matrix; (iii) generate draft strain-specific models from the homology matrix; and (iv) manually curate draft models. These multi-strain GEMs can be used to study pan-metabolic capabilities and strain-specific differences across a species, thus providing insights into its range of lifestyles. Unlike the original Protocol, this procedure is scalable and can be partly automated with the Supplementary Jupyter notebook Tutorial. This Protocol Extension joins the ranks of other comparable methods for generating models such as CarveMe and KBase. This extension of the original Protocol takes on the order of weeks to multiple months to complete depending on the availability of a suitable reference model.

Original languageEnglish
JournalNature Protocols
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020

Bibliographical note

Funding Information:
This research was supported by NIH grant 1-U01-AI124316, and Novo Nordisk Foundation Center for Technical University of Denmark (grant NNF10CC1016517).

Publisher Copyright:
© 2019, The Author(s), under exclusive licence to Springer Nature Limited.

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