Abstract
Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores.
Highlights
Organisms have evolved so that their networks are robust against the effects of mutations, but evolvable in response to environmental changes [1,2,3,4]
Biological systems are known to be robust and evolvable to internal mutations and external environmental changes. What causes these apparently contradictory properties? This study shows that the human signaling network can be decomposed into two structurally distinct subgroups of links that provide both evolvability to environmental changes and robustness against internal mutations
Based on the Boolean network model, we first identified an attractor landscape of the model, and we decomposed the network into two subgroups of interactions: the evolvable core, which preserves the basin of the primary attractor in state space, and the robust neighbor, which has no influence on the basin of the primary attractor
Summary
Organisms have evolved so that their networks are robust against the effects of mutations, but evolvable in response to environmental changes [1,2,3,4]. Biological systems have evolved to possess modular structures [10,11,12], critical regime [2,13], hub nodes [14,15], and hierarchical structures [15] so as to simultaneously increase mutational robustness and evolvability. These investigations mainly focused on either revealing the relationship between mutational robustness and evolvability or unraveling the structural characteristics of biomolecular regulatory networks which have evolved to increase robustness and evolvability
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