Assessing the significance of knockout cascades in metabolic networks

TL;DR

This paper investigates how metabolic networks balance robustness and regulation by analyzing the impact of reaction removals and cascades, revealing evolutionary tradeoffs between efficiency and vulnerability.

Contribution

It introduces a cascading failure algorithm to assess reaction removal impacts and compares null models, highlighting evolutionary pressures shaping metabolic network robustness.

Findings

Larger cascades of non-viable reactions are favored by evolution.

Metabolic regulation efficiency increases vulnerability to cascades.

Evolution promotes tradeoffs between robustness and regulation.

Abstract

Complex networks have been shown to be robust against random structural perturbations, but vulnerable against targeted attacks. Robustness analysis usually simulates the removal of individual or sets of nodes, followed by the assessment of the inflicted damage. For complex metabolic networks, it has been suggested that evolutionary pressure may favor robustness against reaction removal. However, the removal of a reaction and its impact on the network may as well be interpreted as selective regulation of pathway activities, suggesting a tradeoff between the efficiency of regulation and vulnerability. Here, we employ a cascading failure algorithm to simulate the removal of single and pairs of reactions from the metabolic networks of two organisms, and estimate the significance of the results using two different null models: degree preserving and mass-balanced randomization. Our analysis suggests that evolutionary pressure promotes larger cascades of non-viable reactions, and thus favors the ability of efficient metabolic regulation at the expense of robustness.