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Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks

BACKGROUND: Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, various centrality metrics have been mostly applied to metabolite-centric graphs....

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Autores principales: Kim, Eun-Youn, Ashlock, Daniel, Yoon, Sung Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567475/
https://www.ncbi.nlm.nih.gov/pubmed/31195955
http://dx.doi.org/10.1186/s12859-019-2897-z
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author Kim, Eun-Youn
Ashlock, Daniel
Yoon, Sung Ho
author_facet Kim, Eun-Youn
Ashlock, Daniel
Yoon, Sung Ho
author_sort Kim, Eun-Youn
collection PubMed
description BACKGROUND: Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, various centrality metrics have been mostly applied to metabolite-centric graphs. However, centrality metrics including those not depending on high connections are largely unexplored for directed reaction-centric graphs. RESULTS: We applied directed versions of centrality metrics to directed reaction-centric graphs of microbial metabolic networks. To investigate the local role of a node, we developed a novel metric, cascade number, considering how many nodes are closed off from information flow when a particular node is removed. High modularity and scale-freeness were found in the directed reaction-centric graphs and betweenness centrality tended to belong to densely connected modules. Cascade number and bridging centrality identified cascade subnetworks controlling local information flow and irreplaceable bridging nodes between functional modules, respectively. Reactions highly ranked with bridging centrality and cascade number tended to be essential, compared to reactions that other central metrics detected. CONCLUSIONS: We demonstrate that cascade number and bridging centrality are useful to identify key reactions controlling local information flow in directed reaction-centric graphs of microbial metabolic networks. Knowledge about the local flow connectivity and connections between local modules will contribute to understand how metabolic pathways are assembled. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2897-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-65674752019-06-17 Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks Kim, Eun-Youn Ashlock, Daniel Yoon, Sung Ho BMC Bioinformatics Research Article BACKGROUND: Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, various centrality metrics have been mostly applied to metabolite-centric graphs. However, centrality metrics including those not depending on high connections are largely unexplored for directed reaction-centric graphs. RESULTS: We applied directed versions of centrality metrics to directed reaction-centric graphs of microbial metabolic networks. To investigate the local role of a node, we developed a novel metric, cascade number, considering how many nodes are closed off from information flow when a particular node is removed. High modularity and scale-freeness were found in the directed reaction-centric graphs and betweenness centrality tended to belong to densely connected modules. Cascade number and bridging centrality identified cascade subnetworks controlling local information flow and irreplaceable bridging nodes between functional modules, respectively. Reactions highly ranked with bridging centrality and cascade number tended to be essential, compared to reactions that other central metrics detected. CONCLUSIONS: We demonstrate that cascade number and bridging centrality are useful to identify key reactions controlling local information flow in directed reaction-centric graphs of microbial metabolic networks. Knowledge about the local flow connectivity and connections between local modules will contribute to understand how metabolic pathways are assembled. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2897-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-13 /pmc/articles/PMC6567475/ /pubmed/31195955 http://dx.doi.org/10.1186/s12859-019-2897-z 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 Article
Kim, Eun-Youn
Ashlock, Daniel
Yoon, Sung Ho
Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
title Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
title_full Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
title_fullStr Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
title_full_unstemmed Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
title_short Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
title_sort identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567475/
https://www.ncbi.nlm.nih.gov/pubmed/31195955
http://dx.doi.org/10.1186/s12859-019-2897-z
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