The survival of plants in a changing environment requires the activity of numerous signaling systems which regulate physiological processes and participate in adaptation to stressors. Signaling processes include increases of calcium concentration in cytoplasm and nucleus, production of reactive oxygen species (ROS, especially hydrogen peroxide), changes in pH in cytoplasm, organelles, and apoplast, induction of electrical responses on the plasma membrane and tonoplast, propagation of hydraulic waves, etc. Often, these signals interact with each other and their combined action on physiological processes is connected through a complex network of regulatory events. Plant signalling systems, therefore, require the integration of various signals. Such systems frequently exhibit complex behavior for which intuition often breaks down, necessitating simulation-based approaches to help unravel and understand the experimental observations.

The development of mathematical models of signaling and regulatory systems is the efficient way of providing insights, aiding data analysis and interpretation, generating and evaluating hypotheses, as well as making predictions to guide future experiments. In particular, in the fields of plant physiology and predictive crop breeding this approach provides a key component towards a systems-level understanding.

Simulation of signaling and regulation in plants is often focused on specific process and at different spatial and temporal scales. Some processes can be described on the level of organelles, with examples including the simulation of the regulation of photosynthetic processes by light intensity; modelling of changes in ions concentrations and pH for processes of signaling and regulation. Often processes need to include more than one organelle and account for intracellular signaling, for instance models of calcium signal networks and Ca²⁺-dependent regulation of gene expression or the electrical activity in plant cells. The connection between the electrical activity and physiological processes (e.g. photosynthesis) is an important direction of simulation of intracellular signaling. Simulation of the propagation of intercellular signals is key for dissecting systemic signals and whole plant physiological responses. Various models are based on the description of plant body as a system of electrically-coupled elements or on alternative descriptions (e.g. diffusion of regulatory agents, propagation of the hydraulic signal, etc). To gain an in-depth, integrated view of signaling and physiological regulation all levels must be considered.

Mathematical modelling and computational simulation of signaling and physiological regulation is an important, growing and actively-developing field of plant science. There are many outstanding problems which require investigations, including the interaction between different types of signals, signals propagation through the non-homogeneous plant body, and connection of signals with physiological processes. One more important problem is integration of individual mathematical models into complex models aimed at addressing various specific questions. New models of signaling and regulatory processes will be key for unraveling the complex nature of plant signaling and adaptation as well as for the applied plant science.

The goal of this Research Topic is to collect a series of reviews and original research articles, which focus on the development and comparison of mathematical models of signaling and physiological regulation in plants across different levels of their organization.

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Frontiers in Plant Science

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