Presentation Information
[SS20-02]Network topology enables independent control of G2-M from G1-S checkpoints in the fission yeast cell cycle system
*Yuhei Yamauchi1, Hironori Sugiyama2, Yuhei Goto5,6, Kazuhiro Aoki3,4,5,6, Atsushi Mochizuki1 (1. Theoretical Biology Laboratory, Institute for Life and Medical Sciences, Kyoto University (Japan), 2. Department of Applied Chemistry, School of Engineering, The University of Tokyo (Japan), 3. Division of Quantitative Biology, National Institute for Basic Biology, National Institutes of Natural Sciences (Japan), 4. Quantitative Biology Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences (Japan), 5. Laboratory of Cell Cycle Regulation, Graduate School of Biostudies, Kyoto University (Japan), 6. Center for Living Systems Information Science, Graduate School of Biostudies, Kyoto University (Japan))
Keywords:
Chemical reaction network,Network topology,Cell cycle system
Physiological functions of cells arise from the dynamics of chemical reaction networks. The G1-S and G2-M checkpoints in the cell cycle of fission yeast are controlled by dynamical changes in the concentrations of two different cyclin-dependent kinase (CDK)-cyclin complexes: CDK-Cig2 and CDK-Cdc13, through a complicated reaction network. While the concentration of these two complexes should rise specifically at different stages, it is not yet fully understood how these complexes are controlled separately in a stage-specific manner.
Our group has developed a topology-based theory called structural sensitivity analysis (Mochizuki and Fidler, 2015). This method allows us to determine, solely from the network structure, the qualitative changes in the steady-state concentrations of chemicals resulting from the perturbations to parameters. Notably, if a subnetwork satisfies specific topological conditions, it is called a buffering structure, and the effects of perturbations to a parameter in a buffering structure are localized to it (Okada and Mochizuki, 2016, 2017). Using these tools, here, we theoretically predicted that independent control of CDK-Cdc13 from CDK-Cig2 is achieved through the topology of the cell cycle network, and experimentally verified this prediction, refining the network information by comparing predictions with experiments.
We analyzed a known cell cycle network and revealed that the two cyclin-CDK complexes are included in different buffering structures, suggesting that the concentration of each cyclin-CDK complex will be controlled independently from the other complex. Experimental validations confirmed that the concentration of CDK-Cdc13 is controlled by the Cdc13 synthesis rate, independently from CDK-Cig2, as theoretically predicted. In contrast, the Cig2 synthesis rate affected not only CDK-Cig2, but also CDK-Cdc13. This finding, however, indicates the need to update the network. We theoretically predicted the existence of unknown necessary reaction—a Cdc13 degradation pathway—and experimentally confirmed its existence. The prediction-verification approach using the topology-based theory proposes a new systems biology, which progresses by comparing network structures with manipulation experiments and refining network information.
Our group has developed a topology-based theory called structural sensitivity analysis (Mochizuki and Fidler, 2015). This method allows us to determine, solely from the network structure, the qualitative changes in the steady-state concentrations of chemicals resulting from the perturbations to parameters. Notably, if a subnetwork satisfies specific topological conditions, it is called a buffering structure, and the effects of perturbations to a parameter in a buffering structure are localized to it (Okada and Mochizuki, 2016, 2017). Using these tools, here, we theoretically predicted that independent control of CDK-Cdc13 from CDK-Cig2 is achieved through the topology of the cell cycle network, and experimentally verified this prediction, refining the network information by comparing predictions with experiments.
We analyzed a known cell cycle network and revealed that the two cyclin-CDK complexes are included in different buffering structures, suggesting that the concentration of each cyclin-CDK complex will be controlled independently from the other complex. Experimental validations confirmed that the concentration of CDK-Cdc13 is controlled by the Cdc13 synthesis rate, independently from CDK-Cig2, as theoretically predicted. In contrast, the Cig2 synthesis rate affected not only CDK-Cig2, but also CDK-Cdc13. This finding, however, indicates the need to update the network. We theoretically predicted the existence of unknown necessary reaction—a Cdc13 degradation pathway—and experimentally confirmed its existence. The prediction-verification approach using the topology-based theory proposes a new systems biology, which progresses by comparing network structures with manipulation experiments and refining network information.