Communication in Plants: Comparison of Multiple Action Potential and Mechanosensitive Signals with Experiments

TL;DR

This paper investigates how action potentials and mechanosensitive signals propagate in plants, analyzing their information transfer capacity over multiple cells through theoretical models and experimental validation, revealing optimal ranges for signal efficiency.

Contribution

It introduces a combined theoretical and experimental framework for analyzing plant signaling, specifically comparing action potentials and mechanosensitive signals in terms of information transfer.

Findings

Mutual information per cell increases then decreases beyond 10-12 cells.

Propagation speed peaks at a certain number of cells.

Experimental data aligns with theoretical predictions.

Abstract

Both action potentials and mechanosensitive signalling are an important communication mechanisms in plants. Considering an information theoretic framework, this paper explores the effective range of multiple action potentials for a long chain of cells (i.e., up to 100) in different configurations, and introduces the study of multiple mechanosensitive activation signals (generated due to a mechanical stimulus) in plants. For both these signals, we find that the mutual information per cell and information propagation speed tends to increase up to a certain number of receiver cells. However, as the number of cells increase beyond 10 to 12, the mutual information per cell starts to decrease. To validate our model and results, we include an experimental verification of the theoretical model, using a PhytlSigns biosignal amplifier, allowing us to measure the magnitude of the voltage associated with the multiple AP and mechanosensitive activation signals induced by different stimulus in plants. Experimental data is used to calculate the mutual information and information propagation speed, which is compared with corresponding numerical results. Since these signals are used for a variety of important tasks within the plant, understanding them may lead to new bioengineering methods for plants.