Evolution of Regulatory Complexity for Cell-Cycle Control

Abstract

How complexity arises is a fundamental evolutionary question. Complex gene regulation is thought to arise by the interplay between adaptive and non-adaptive forces at multiple organizational levels. Using a computational model, we investigate how complexity arises in cell-cycle regulation. Starting from the well-known Caulobacter crescentus network, we study how cells adapt their cell-cycle behaviour to a gradient of limited nutrient conditions using 10 replicate in silico evolution experiments. We find adaptive expansion of the gene regulatory network: improvement of cell-cycle behaviour allows cells to overcome the inherent cost of complexity. Replicates traverse different evolutionary trajectories leading to distinct eco-evolutionary strategies. In four replicates, cells evolve a generalist strategy to cope with a variety of nutrient levels; in two replicates, different specialist cells evolve for specific nutrient levels; in the remaining four replicates, an intermediate strategy evolves. The generalist and specialist strategies are contingent on the regulatory mechanisms that arise early in evolution, but they are not directly linked to network expansion and overall fitness. This study shows that functionality of cells depends on the combination of gene regulatory network topology and genome structure. For example, the positions of dosage-sensitive genes are exploited to signal to the regulatory network when replication is completed, forming a de novo evolved cell-cycle checkpoint. Complex gene regulation can arise adaptively both from expansion of the regulatory network and from the genomic organization of the elements in this network, demonstrating that to understand complex gene regulation and its evolution, it is necessary to integrate systems that are often studied separately.