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

Hamdan Awan, Kareem Zeid, Raviraj S. Adve, Nigel Wallbridge, Carrol Plummer, Andrew W. Eckford

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

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's 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.

Original languageEnglish
Article number8890624
Pages (from-to)213-223
Number of pages11
JournalIEEE Transactions on Nanobioscience
Volume19
Issue number2
DOIs
Publication statusPublished - Apr 2020
Externally publishedYes

Keywords

  • biological information theory
  • molecular biophysics
  • Molecular communication
  • mutual information

Fingerprint

Dive into the research topics of 'Communication in Plants: Comparison of Multiple Action Potential and Mechanosensitive Signals with Experiments'. Together they form a unique fingerprint.

Cite this