ArticleBMC bioinformatics2007
A network perspective on the topological importance of enzymes and their phylogenetic conservation.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 40 citations in OpenAlex.
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- Tradeoff between robustness and elaboration in carotenoid networks produces cycles of avian color diversification.Biology direct · 2015Article
- High similarity of phylogenetic profiles of rate-limiting enzymes with inhibitory relation in Human, Mouse, Rat, budding Yeast and E. coli.BMC genomics · 2011Article
- Expression level, cellular compartment and metabolic network position all influence the average selective constraint on mammalian enzymes.BMC evolutionary biology · 2011Article
- Structural correlations in bacterial metabolic networks.BMC evolutionary biology · 2011Article
- A quantitative approach to study indirect effects among disease proteins in the human protein interaction network.BMC systems biology · 2010Article
- MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks.Nucleic acids research · 2010Article
- An interaction-motif-based scoring function for protein-ligand docking.BMC bioinformatics · 2010Article
- Evolutionary constraints permeate large metabolic networks.BMC evolutionary biology · 2009Article
- Article
- Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.BMC systems biology · 2009Article
- Optimized ancestral state reconstruction using Sankoff parsimony.BMC bioinformatics · 2009Article
- Evolutionary constraint and adaptation in the metabolic network of Drosophila.Molecular biology and evolution · 2008Article
- Phylogenetic distances are encoded in networks of interacting pathways.Bioinformatics (Oxford, England) · 2008Article
- The pairwise disconnectivity index as a new metric for the topological analysis of regulatory networks.BMC bioinformatics · 2008Article
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA metabolic network is the sum of all chemical transformations or reactions in the cell, with the metabolites being interconnected by enzyme-catalyzed reactions. Many enzymes exist in numerous species while others occur only in a few. We ask if there are relationships between the phylogenetic profile of an enzyme, or the number of different bacterial species that contain it, and its topological importance in the metabolic network. Our null hypothesis is that phylogenetic profile is independent of topological importance. To test our null hypothesis we constructed an enzyme network from the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We calculated three network indices of topological importance: the degree or the number of connections of a network node; closeness centrality, which measures how close a node is to others; and betweenness centrality measuring how frequently a node appears on all shortest paths between two other nodes.
resultsEnzyme phylogenetic profile correlates best with betweenness centrality and also quite closely with degree, but poorly with closeness centrality. Both betweenness and closeness centralities are non-local measures of topological importance and it is intriguing that they have contrasting power of predicting phylogenetic profile in bacterial species. We speculate that redundancy in an enzyme network may be reflected by betweenness centrality but not by closeness centrality. We also discuss factors influencing the correlation between phylogenetic profile and topological importance.
conclusionOur analysis falsifies the hypothesis that phylogenetic profile of enzymes is independent of enzyme network importance. Our results show that phylogenetic profile correlates better with degree and betweenness centrality, but less so with closeness centrality. Enzymes that occur in many bacterial species tend to be those that have high network importance. We speculate that this phenomenon originates in mechanisms driving network evolution. Closeness centrality reflects phylogenetic profile poorly. This is because metabolic networks often consist of distinct functional modules and some are not in the centre of the network. Enzymes in these peripheral parts of a network might be important for cell survival and should therefore occur in many bacterial species. They are, however, distant from other enzymes in the same network.
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