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
