Structural controllability of dynamic transcriptional regulatory networks for Saccharomyces cerevisiae

Biological networks can dynamically change their structures to adapt to various biotic and abiotic stimuli. However, state-of-the-art studies on large-scale biological networks mainly focus on static networks. Here, we applied the sophisticated structural controllability tool to analyze one static and five dynamic transcriptional regulatory networks (TRNs) for Saccharomyces cerevisiae (S. cerevisiae), the five dynamic networks include two endogenous and three exogenous ones. Structural controllability allows us to classify nodes into different categories according to their control roles, and we clarify their topological features. Our results reveal that biological networks are rather difficult to be fully controlled. However, the dynamic networks are relatively easier to be controlled than the static one, and one needs relatively more external inputs to control the exogenous networks than the endogenous ones. Moreover, we found that nodes consisting of the single input module (SIM) and multiple input module (MIM) tend to be critical driver nodes, and those consisting of the feed-forward loop (FFL) in dynamic networks are prone to be critical drivers in comparison with those in the static network. Furthermore, GO enrichment analysis reveals that driver nodes but not critical driver nodes contribute to functional differences between the static and dynamic networks. Critical drivers, indispensable and neutral nodes are all enriched with transcriptional factors (TFs). On the contrary, essential genes tend to be enriched as driver nodes and dispensable nodes. The obtained results have certain robustness against perturbations. We declare that control roles of TFs and essential genes facilitate the identification of them via structural controllability theory. Our investigations provide some insights into real-world control of biological networks.