Cargando…

MANET 3.0: Hierarchy and modularity in evolving metabolic networks

Enzyme recruitment is a fundamental evolutionary driver of modern metabolism. We see evidence of recruitment at work in the metabolic Molecular Ancestry Networks (MANET) database, an online resource that integrates data from KEGG, SCOP and structural phylogenomic reconstruction. The database, which...

Descripción completa

Detalles Bibliográficos
Autores principales: Mughal, Fizza, Caetano-Anollés, Gustavo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6812854/
https://www.ncbi.nlm.nih.gov/pubmed/31648227
http://dx.doi.org/10.1371/journal.pone.0224201
_version_ 1783462726283034624
author Mughal, Fizza
Caetano-Anollés, Gustavo
author_facet Mughal, Fizza
Caetano-Anollés, Gustavo
author_sort Mughal, Fizza
collection PubMed
description Enzyme recruitment is a fundamental evolutionary driver of modern metabolism. We see evidence of recruitment at work in the metabolic Molecular Ancestry Networks (MANET) database, an online resource that integrates data from KEGG, SCOP and structural phylogenomic reconstruction. The database, which was introduced in 2006, traces the deep history of the structural domains of enzymes in metabolic pathways. Here we release version 3.0 of MANET, which updates data from KEGG and SCOP, links enzyme and PDB information with PDBsum, and traces evolutionary information of domains defined at fold family level of SCOP classification in metabolic subnetwork diagrams. Compared to SCOP folds used in the previous versions, fold families are cohesive units of functional similarity that are highly conserved at sequence level and offer a 10-fold increase of data entries. We surveyed enzymatic, functional and catalytic site distributions among superkingdoms showing that ancient enzymatic innovations followed a biphasic temporal pattern of diversification typical of module innovation. We grouped enzymatic activities of MANET into a hierarchical system of subnetworks and mesonetworks matching KEGG classification. The evolutionary growth of these modules of metabolic activity was studied using bipartite networks and their one-mode projections at enzyme, subnetwork and mesonetwork levels of organization. Evolving metabolic networks revealed patterns of enzyme sharing that transcended mesonetwork boundaries and supported the patchwork model of metabolic evolution. We also explored the scale-freeness, randomness and small-world properties of evolving networks as possible organizing principles of network growth and diversification. The network structure shows an increase in hierarchical modularity and scale-free behavior as metabolic networks unfold in evolutionary time. Remarkably, this evolutionary constraint on structure was stronger at lower levels of metabolic organization. Evolving metabolic structure reveals a ‘principle of granularity’, an evolutionary increase of the cohesiveness of lower-level parts of a hierarchical system. MANET is available at http://manet.illinois.edu.
format Online
Article
Text
id pubmed-6812854
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-68128542019-11-02 MANET 3.0: Hierarchy and modularity in evolving metabolic networks Mughal, Fizza Caetano-Anollés, Gustavo PLoS One Research Article Enzyme recruitment is a fundamental evolutionary driver of modern metabolism. We see evidence of recruitment at work in the metabolic Molecular Ancestry Networks (MANET) database, an online resource that integrates data from KEGG, SCOP and structural phylogenomic reconstruction. The database, which was introduced in 2006, traces the deep history of the structural domains of enzymes in metabolic pathways. Here we release version 3.0 of MANET, which updates data from KEGG and SCOP, links enzyme and PDB information with PDBsum, and traces evolutionary information of domains defined at fold family level of SCOP classification in metabolic subnetwork diagrams. Compared to SCOP folds used in the previous versions, fold families are cohesive units of functional similarity that are highly conserved at sequence level and offer a 10-fold increase of data entries. We surveyed enzymatic, functional and catalytic site distributions among superkingdoms showing that ancient enzymatic innovations followed a biphasic temporal pattern of diversification typical of module innovation. We grouped enzymatic activities of MANET into a hierarchical system of subnetworks and mesonetworks matching KEGG classification. The evolutionary growth of these modules of metabolic activity was studied using bipartite networks and their one-mode projections at enzyme, subnetwork and mesonetwork levels of organization. Evolving metabolic networks revealed patterns of enzyme sharing that transcended mesonetwork boundaries and supported the patchwork model of metabolic evolution. We also explored the scale-freeness, randomness and small-world properties of evolving networks as possible organizing principles of network growth and diversification. The network structure shows an increase in hierarchical modularity and scale-free behavior as metabolic networks unfold in evolutionary time. Remarkably, this evolutionary constraint on structure was stronger at lower levels of metabolic organization. Evolving metabolic structure reveals a ‘principle of granularity’, an evolutionary increase of the cohesiveness of lower-level parts of a hierarchical system. MANET is available at http://manet.illinois.edu. Public Library of Science 2019-10-24 /pmc/articles/PMC6812854/ /pubmed/31648227 http://dx.doi.org/10.1371/journal.pone.0224201 Text en © 2019 Mughal, Caetano-Anollés 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
Mughal, Fizza
Caetano-Anollés, Gustavo
MANET 3.0: Hierarchy and modularity in evolving metabolic networks
title MANET 3.0: Hierarchy and modularity in evolving metabolic networks
title_full MANET 3.0: Hierarchy and modularity in evolving metabolic networks
title_fullStr MANET 3.0: Hierarchy and modularity in evolving metabolic networks
title_full_unstemmed MANET 3.0: Hierarchy and modularity in evolving metabolic networks
title_short MANET 3.0: Hierarchy and modularity in evolving metabolic networks
title_sort manet 3.0: hierarchy and modularity in evolving metabolic networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6812854/
https://www.ncbi.nlm.nih.gov/pubmed/31648227
http://dx.doi.org/10.1371/journal.pone.0224201
work_keys_str_mv AT mughalfizza manet30hierarchyandmodularityinevolvingmetabolicnetworks
AT caetanoanollesgustavo manet30hierarchyandmodularityinevolvingmetabolicnetworks