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RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor

RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii)...

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Autores principales: Wang, Hao, Marcišauskas, Simonas, Sánchez, Benjamín J., Domenzain, Iván, Hermansson, Daniel, Agren, Rasmus, Nielsen, Jens, Kerkhoven, Eduard J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207324/
https://www.ncbi.nlm.nih.gov/pubmed/30335785
http://dx.doi.org/10.1371/journal.pcbi.1006541
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author Wang, Hao
Marcišauskas, Simonas
Sánchez, Benjamín J.
Domenzain, Iván
Hermansson, Daniel
Agren, Rasmus
Nielsen, Jens
Kerkhoven, Eduard J.
author_facet Wang, Hao
Marcišauskas, Simonas
Sánchez, Benjamín J.
Domenzain, Iván
Hermansson, Daniel
Agren, Rasmus
Nielsen, Jens
Kerkhoven, Eduard J.
author_sort Wang, Hao
collection PubMed
description RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii) a redesigned KEGG-based reconstruction pipeline; (iii) convergence of reconstructions from various sources; (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community (https://github.com/SysBioChalmers/RAVEN and https://github.com/SysBioChalmers/Streptomyces_coelicolor-GEM).
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spelling pubmed-62073242018-11-19 RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor Wang, Hao Marcišauskas, Simonas Sánchez, Benjamín J. Domenzain, Iván Hermansson, Daniel Agren, Rasmus Nielsen, Jens Kerkhoven, Eduard J. PLoS Comput Biol Research Article RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii) a redesigned KEGG-based reconstruction pipeline; (iii) convergence of reconstructions from various sources; (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community (https://github.com/SysBioChalmers/RAVEN and https://github.com/SysBioChalmers/Streptomyces_coelicolor-GEM). Public Library of Science 2018-10-18 /pmc/articles/PMC6207324/ /pubmed/30335785 http://dx.doi.org/10.1371/journal.pcbi.1006541 Text en © 2018 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Hao
Marcišauskas, Simonas
Sánchez, Benjamín J.
Domenzain, Iván
Hermansson, Daniel
Agren, Rasmus
Nielsen, Jens
Kerkhoven, Eduard J.
RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
title RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
title_full RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
title_fullStr RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
title_full_unstemmed RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
title_short RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
title_sort raven 2.0: a versatile toolbox for metabolic network reconstruction and a case study on streptomyces coelicolor
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207324/
https://www.ncbi.nlm.nih.gov/pubmed/30335785
http://dx.doi.org/10.1371/journal.pcbi.1006541
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