Metabolic robustness and network modularity: A model study

TL;DR

This study investigates how network modularity influences metabolic robustness, revealing that increased modularity enhances robustness to concentration changes but reduces it for enzyme expression variations, indicating a nuanced role of modularity.

Contribution

The paper provides a model-based analysis showing that network modularity's effect on robustness varies depending on the type of perturbation in metabolic systems.

Findings

Robustness to metabolite concentration changes increases with modularity.

Robustness to enzyme expression changes decreases with modularity.

Relaxation speed after perturbations scales with network modularity.

Abstract

[Background] Several studies have mentioned network modularity -- that a network can easily be decomposed into subgraphs that are densely connected within and weakly connected between each other -- as a factor affecting metabolic robustness. In this paper we measure the relation between network modularity and several aspects of robustness directly in a model system of metabolism. [Methodology/Principal Findings] By using a model for generating chemical reaction systems where one can tune the network modularity, we find that robustness increases with modularity for changes in the concentrations of metabolites, whereas it decreases with changes in the expression of enzymes. The same modularity scaling is true for the speed of relaxation after the perturbations. [Conclusions/Significance] Modularity is not a general principle for making metabolism either more or less robust; this question needs to be addressed specifically for different types of perturbations of the system.