Phylogeny of Metabolic Networks: A Spectral Graph Theoretical Approach

TL;DR

This paper introduces a spectral graph theoretical method to compare metabolic network structures of 79 organisms, revealing phylogenetic relationships and evolutionary insights based on network eigenvalues.

Contribution

It applies spectral density analysis of normalized Laplacian matrices to metabolic networks, providing a novel approach for phylogenetic comparison beyond traditional methods.

Findings

Spectral densities reflect global and local network architecture.

Phylogenetic relationships correlate with environmental and life history similarities.

The method uncovers unexpected relatedness among different species.

Abstract

Many methods have been developed for finding the commonalities between different organisms to study their phylogeny. The structure of metabolic networks also reveal valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyze the phylogeny from these distances. In our analysis, we focus on the species, which belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.