Patterns of change in regulatory modules of chemical reaction systems induced by network modification

Author:

Hishida AtsukiORCID,Okada TakashiORCID,Mochizuki AtsushiORCID

Abstract

AbstractCellular functions are realized through the dynamics of chemical reaction networks formed by thousands of chemical reactions. Numerical studies have empirically demonstrated that small differences in network structures among species or tissues can cause substantial changes in dynamics. However, the existence of a general principle for behavior changes in response to network structure modifications is not known. The chemical reaction system possesses substructures called buffering structures, which are characterized by a certain topological index being zero. It was proven that the steady-state response to modulation of reaction parameters inside a buffering structure is localized in the buffering structure [1, 2, 3]. In this study, we developed a method to systematically identify the loss or creation of buffering structures induced by the addition of a single degradation reaction from network structure alone. This makes it possible to predict the qualitative and macroscopic changes in regulation that will be caused by the network modification. This method was applied to two reaction systems: the central metabolic system and the mitogen-activated protein kinases (MAPK) signal transduction system. Our method enables identification of reactions that are important for biological functions in living systems.Significance StatementDynamics of complex biological systems have been understood using mathematical models[4, 5, 6, 7]; however, various assumptions are necessary to construct models for large networks such as those found in the life sciences, and discussing the relation between the network structure and its behavior is difficult. Our study using structural sensitivity analysis [1, 2, 3] shows that directly discussing changes in the structure and behavior of a reaction network without making assumptions about kinetics is possible. This enabled the prediction of changes in behavior depending on whether a reaction is present or not and identify reactions that are essentially important for biological behavior.

Publisher

Cold Spring Harbor Laboratory

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