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A systematic assessment of current genome-scale metabolic reconstruction tools

BACKGROUND: Several genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial rel...

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Autores principales: Mendoza, Sebastián N., Olivier, Brett G., Molenaar, Douwe, Teusink, Bas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685185/
https://www.ncbi.nlm.nih.gov/pubmed/31391098
http://dx.doi.org/10.1186/s13059-019-1769-1
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author Mendoza, Sebastián N.
Olivier, Brett G.
Molenaar, Douwe
Teusink, Bas
author_facet Mendoza, Sebastián N.
Olivier, Brett G.
Molenaar, Douwe
Teusink, Bas
author_sort Mendoza, Sebastián N.
collection PubMed
description BACKGROUND: Several genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial relevance. However, these platforms, as yet, have not been systematically evaluated with respect to software quality, best potential uses and intrinsic capacity to generate high-quality, genome-scale metabolic models. It is therefore unclear for potential users which tool best fits the purpose of their research. RESULTS: In this work, we perform a systematic assessment of current genome-scale reconstruction software platforms. To meet our goal, we first define a list of features for assessing software quality related to genome-scale reconstruction. Subsequently, we use the feature list to evaluate the performance of each tool. To assess the similarity of the draft reconstructions to high-quality models, we compare each tool’s output networks with that of the high-quality, manually curated, models of Lactobacillus plantarum and Bordetella pertussis, representatives of gram-positive and gram-negative bacteria, respectively. We additionally compare draft reconstructions with a model of Pseudomonas putida to further confirm our findings. We show that none of the tools outperforms the others in all the defined features. CONCLUSIONS: Model builders should carefully choose a tool (or combinations of tools) depending on the intended use of the metabolic model. They can use this benchmark study as a guide to select the best tool for their research. Finally, developers can also benefit from this evaluation by getting feedback to improve their software. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1769-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-66851852019-08-12 A systematic assessment of current genome-scale metabolic reconstruction tools Mendoza, Sebastián N. Olivier, Brett G. Molenaar, Douwe Teusink, Bas Genome Biol Research BACKGROUND: Several genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial relevance. However, these platforms, as yet, have not been systematically evaluated with respect to software quality, best potential uses and intrinsic capacity to generate high-quality, genome-scale metabolic models. It is therefore unclear for potential users which tool best fits the purpose of their research. RESULTS: In this work, we perform a systematic assessment of current genome-scale reconstruction software platforms. To meet our goal, we first define a list of features for assessing software quality related to genome-scale reconstruction. Subsequently, we use the feature list to evaluate the performance of each tool. To assess the similarity of the draft reconstructions to high-quality models, we compare each tool’s output networks with that of the high-quality, manually curated, models of Lactobacillus plantarum and Bordetella pertussis, representatives of gram-positive and gram-negative bacteria, respectively. We additionally compare draft reconstructions with a model of Pseudomonas putida to further confirm our findings. We show that none of the tools outperforms the others in all the defined features. CONCLUSIONS: Model builders should carefully choose a tool (or combinations of tools) depending on the intended use of the metabolic model. They can use this benchmark study as a guide to select the best tool for their research. Finally, developers can also benefit from this evaluation by getting feedback to improve their software. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1769-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-07 /pmc/articles/PMC6685185/ /pubmed/31391098 http://dx.doi.org/10.1186/s13059-019-1769-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Mendoza, Sebastián N.
Olivier, Brett G.
Molenaar, Douwe
Teusink, Bas
A systematic assessment of current genome-scale metabolic reconstruction tools
title A systematic assessment of current genome-scale metabolic reconstruction tools
title_full A systematic assessment of current genome-scale metabolic reconstruction tools
title_fullStr A systematic assessment of current genome-scale metabolic reconstruction tools
title_full_unstemmed A systematic assessment of current genome-scale metabolic reconstruction tools
title_short A systematic assessment of current genome-scale metabolic reconstruction tools
title_sort systematic assessment of current genome-scale metabolic reconstruction tools
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685185/
https://www.ncbi.nlm.nih.gov/pubmed/31391098
http://dx.doi.org/10.1186/s13059-019-1769-1
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