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

Nature Protocols volume 15, pages 1–14 (2020)Cite this article

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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.

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Fig. 1: Applications of multi-strain GEMs.
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Code availability statement

The source code is provided in the Supplementary Tutorial. The code in this Protocol Extension has been peer-reviewed.

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Acknowledgements

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

Author information

Author notes

  1. These authors contributed equally: Charles J. Norsigian, Xin Fang.

Authors and Affiliations

  1. Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA

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

  2. Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA

    Bernhard O. Palsson

  3. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark

    Bernhard O. Palsson

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Contributions

C.J.N. and X.F. prepared the manuscript. C.J.N. and J.M.M. prepared the supplementary tutorial. Y.S., J.M.M. and B.O.P. reviewed and edited the manuscript.

Corresponding author

Correspondence to Bernhard O. Palsson.

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The authors declare no competing interests.

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Related links

Key references using this protocol

Thiele, I. & Palsson, B. Ø. Nat. Protoc. 5, 93–121 (2010): https://doi.org/10.1038/nprot.2009.203

Monk, J. M. et al. Nat. Biotechnol. 35, 904–908 (2017): https://doi.org/10.1038/nbt.3956

Seif, Y. et al. Nat. Commun. 9, 3771 (2018): https://doi.org/10.1038/s41467-018-06112-5

Norsigian, C. J. et al. Front. Cell. Infect. Microbiol. 9, 161 (2019): https://doi.org/10.3389/fcimb.2019.00161

This protocol is an extension to: Nat. Protoc. doi: 10.1038/nprot.2009.203

Integrated supplementary information

Supplementary Fig. 1 Genes retained per strain at incrementing PID thresholds.

The number of genes retained in each strain-specific model is dependent on the threshold utilized for binarization of the homology matrix. The effect of the threshold will also be dependent on how closely related the target strains are to the reference strain. For example, within the strains in the Supplementary Tutorial notebooks, we see that CU651637.1 and CP002167.1 are more dissimilar to reference model iML1515, as the drop-off in retained genes occurs in a steeper fashion. We suggest using a threshold of 80% when comparing strains of the same species to ensure a sufficient similarity metric to include a gene in the draft models.

Supplementary Fig. 2 Resulting assembly statistics at various coverages.

To investigate the effect of coverage on overall assembly statistics of N50 and number of contigs, we randomly sampled reads of the BOP27 strain, which has been sequenced to extremely high coverage (400×), enabling this analysis. Analyzing the resulting assemblies at coverages ranging from 10× to 100×, we see from comparing the metrics that at 70×, the assembly quality mostly saturates, and as such, we recommend that included genomes have at least this much coverage.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Supplementary Tables 1 and 2, and Supplementary Methods.

Reporting Summary

Supplementary Tutorial

Three Jupyter notebooks detailing the entire Protocol Extension as laid out within the Procedure. The first details sequence comparison to generate homology matrix, the second details generation of multi-strain models from the homology matrix, and the third details the beginning investigation of strain-specific capabilities using the draft models.

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Norsigian, C.J., Fang, X., Seif, Y. et al. A workflow for generating multi-strain genome-scale metabolic models of prokaryotes. Nat Protoc 15, 1–14 (2020). https://doi.org/10.1038/s41596-019-0254-3

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