Selective pressure on metabolic network structures as measured from the random blind-watchmaker network

TL;DR

This study compares metabolic network structures to a random null model, revealing evolutionary pressures on properties like clustering and assortativity, and suggesting a more flexible null model for detecting selection.

Contribution

It introduces an analysis of how metabolic network properties are shaped by evolutionary pressures using the Blind Watchmaker null model, highlighting the importance of flexible degree distributions.

Findings

Metabolic networks' clustering and assortativity are close to the null model.

Evolutionary pressure favors low assortativity, especially in larger networks.

Degree distribution deviations suggest a need for flexible null models.

Abstract

A random null model termed the Blind Watchmaker network (BW) has been shown to reproduce the degree distribution found in metabolic networks. This might suggest that natural selection has had little influence on this particular network property. We here investigate to what extent other structural network properties have evolved under selective pressure from the corresponding ones of the random null model: The clustering coefficient and the assortativity measures are chosen and it is found that these measures for the metabolic network structure are close enough to the BW-network so as to fit inside its reachable random phase space. It is furthermore shown that the use of this null model indicates an evolutionary pressure towards low assortativity and that this pressure is stronger for larger networks. It is also shown that selecting for BW networks with low assortativity causes the BW degree distribution to slightly deviate from its power-law shape in the same way as the metabolic networks. This implies that an equilibrium model with fluctuating degree distribution is more suitable as a null model, when identifying selective pressures, than a randomized counterpart with fixed degree sequence, since the overall degree sequence itself can change under selective pressure on other global network properties.