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Journal article

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

From

University of California at San Diego1

Big Data 2 Knowledge, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark2

Network Reconstruction in Silico Biology, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark3

Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark4

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.

Language: English
Publisher: Nature Publishing Group UK
Year: 2020
Pages: 1-14
Journal subtitle: Recipes for Researchers
ISSN: 17502799 and 17542189
Types: Journal article
DOI: 10.1038/s41596-019-0254-3
ORCIDs: Palsson, Bernhard O. and 0000-0001-8813-5679

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