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MetNet: A two-level approach to reconstructing and comparing metabolic networks

Metabolic pathway comparison and interaction between different species can detect important information for drug engineering and medical science. In the literature, proposals for reconstructing and comparing metabolic networks present two main problems: network reconstruction requires usually human...

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Autores principales: Cocco, Nicoletta, Llabrés, Mercè, Reyes-Prieto, Mariana, Simeoni, Marta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880445/
https://www.ncbi.nlm.nih.gov/pubmed/33577575
http://dx.doi.org/10.1371/journal.pone.0246962
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author Cocco, Nicoletta
Llabrés, Mercè
Reyes-Prieto, Mariana
Simeoni, Marta
author_facet Cocco, Nicoletta
Llabrés, Mercè
Reyes-Prieto, Mariana
Simeoni, Marta
author_sort Cocco, Nicoletta
collection PubMed
description Metabolic pathway comparison and interaction between different species can detect important information for drug engineering and medical science. In the literature, proposals for reconstructing and comparing metabolic networks present two main problems: network reconstruction requires usually human intervention to integrate information from different sources and, in metabolic comparison, the size of the networks leads to a challenging computational problem. We propose to automatically reconstruct a metabolic network on the basis of KEGG database information. Our proposal relies on a two-level representation of the huge metabolic network: the first level is graph-based and depicts pathways as nodes and relations between pathways as edges; the second level represents each metabolic pathway in terms of its reactions content. The two-level representation complies with the KEGG database, which decomposes the metabolism of all the different organisms into “reference” pathways in a standardised way. On the basis of this two-level representation, we introduce some similarity measures for both levels. They allow for both a local comparison, pathway by pathway, and a global comparison of the entire metabolism. We developed a tool, MetNet, that implements the proposed methodology. MetNet makes it possible to automatically reconstruct the metabolic network of two organisms selected in KEGG and to compare their two networks both quantitatively and visually. We validate our methodology by presenting some experiments performed with MetNet.
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spelling pubmed-78804452021-02-19 MetNet: A two-level approach to reconstructing and comparing metabolic networks Cocco, Nicoletta Llabrés, Mercè Reyes-Prieto, Mariana Simeoni, Marta PLoS One Research Article Metabolic pathway comparison and interaction between different species can detect important information for drug engineering and medical science. In the literature, proposals for reconstructing and comparing metabolic networks present two main problems: network reconstruction requires usually human intervention to integrate information from different sources and, in metabolic comparison, the size of the networks leads to a challenging computational problem. We propose to automatically reconstruct a metabolic network on the basis of KEGG database information. Our proposal relies on a two-level representation of the huge metabolic network: the first level is graph-based and depicts pathways as nodes and relations between pathways as edges; the second level represents each metabolic pathway in terms of its reactions content. The two-level representation complies with the KEGG database, which decomposes the metabolism of all the different organisms into “reference” pathways in a standardised way. On the basis of this two-level representation, we introduce some similarity measures for both levels. They allow for both a local comparison, pathway by pathway, and a global comparison of the entire metabolism. We developed a tool, MetNet, that implements the proposed methodology. MetNet makes it possible to automatically reconstruct the metabolic network of two organisms selected in KEGG and to compare their two networks both quantitatively and visually. We validate our methodology by presenting some experiments performed with MetNet. Public Library of Science 2021-02-12 /pmc/articles/PMC7880445/ /pubmed/33577575 http://dx.doi.org/10.1371/journal.pone.0246962 Text en © 2021 Cocco 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
Cocco, Nicoletta
Llabrés, Mercè
Reyes-Prieto, Mariana
Simeoni, Marta
MetNet: A two-level approach to reconstructing and comparing metabolic networks
title MetNet: A two-level approach to reconstructing and comparing metabolic networks
title_full MetNet: A two-level approach to reconstructing and comparing metabolic networks
title_fullStr MetNet: A two-level approach to reconstructing and comparing metabolic networks
title_full_unstemmed MetNet: A two-level approach to reconstructing and comparing metabolic networks
title_short MetNet: A two-level approach to reconstructing and comparing metabolic networks
title_sort metnet: a two-level approach to reconstructing and comparing metabolic networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880445/
https://www.ncbi.nlm.nih.gov/pubmed/33577575
http://dx.doi.org/10.1371/journal.pone.0246962
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