Article

Phylogenetic distances are encoded in networks of interacting pathways.

Systems Biology Group, Institut Pasteur, 25 rue du Docteur Roux, 75015 Paris, France.
Bioinformatics (impact factor: 5.47). 10/2008; 24(22):2579-85. DOI:10.1093/bioinformatics/btn503 pp.2579-85
Source: PubMed

ABSTRACT Although metabolic reactions are unquestionably shaped by evolutionary processes, the degree to which the overall structure and complexity of their interconnections are linked to the phylogeny of species has not been evaluated in depth. Here, we apply an original metabolome representation, termed Network of Interacting Pathways or NIP, with a combination of graph theoretical and machine learning strategies, to address this question. NIPs compress the information of the metabolic network exhibited by a species into much smaller networks of overlapping metabolic pathways, where nodes are pathways and links are the metabolites they exchange.
Our analysis shows that a small set of descriptors of the structure and complexity of the NIPs combined into regression models reproduce very accurately reference phylogenetic distances derived from 16S rRNA sequences (10-fold cross-validation correlation coefficient higher than 0.9). Our method also showed better scores than previous work on metabolism-based phylogenetic reconstructions, as assessed by branch distances score, topological similarity and second cousins score. Thus, our metabolome representation as network of overlapping metabolic pathways captures sufficient information about the underlying evolutionary events leading to the formation of metabolic networks and species phylogeny. It is important to note that precise knowledge of all of the reactions in these pathways is not required for these reconstructions. These observations underscore the potential for the use of abstract, modular representations of metabolic reactions as tools in studying the evolution of species.
Supplementary data are available at Bioinformatics online.

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Keywords

10-fold cross-validation correlation coefficient higher
 
16S rRNA sequences
 
Bioinformatics online
 
evolutionary processes
 
graph theoretical
 
Interacting Pathways
 
metabolic network exhibited
 
metabolic networks
 
metabolic reactions
 
metabolism-based phylogenetic reconstructions
 
metabolome representation
 
original metabolome representation
 
overlapping metabolic pathways
 
overlapping metabolic pathways captures sufficient information
 
reactions
 
regression models reproduce
 
smaller networks
 
species phylogeny
 
topological similarity
 
underlying evolutionary events