Abstract
Recent progress in nanotechnology-enabled sensors that can be placed inside of living plants has shown that it is possible to relay and record real-time chemical signaling stimulated by various abiotic and biotic stresses. The mathematical form of the resulting local reactive oxygen species (ROS) wave released upon mechanical perturbation of plant leaves appears to be conserved across a large number of species, and produces a distinct waveform from other stresses including light, heat and pathogen-associated molecular pattern (PAMP)-induced stresses. Herein, we develop a quantitative theory of the local ROS signaling waveform resulting from mechanical stress in planta. We show that nonlinear, autocatalytic production and Fickian diffusion of H2O2 followed by first order decay well describes the spatial and temporal properties of the waveform. The reaction–diffusion system is analyzed in terms of a new approximate solution that we introduce for such problems based on a single term logistic function ansatz. The theory is able to describe experimental ROS waveforms and degradation dynamics such that species-dependent dimensionless wave velocities are revealed, corresponding to subtle changes in higher moments of the waveform through an apparently conserved signaling mechanism overall. This theory has utility in potentially decoding other stress signaling waveforms for light, heat and PAMP-induced stresses that are similarly under investigation. The approximate solution may also find use in applied agricultural sensing, facilitating the connection between measured waveform and plant physiology.
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Acknowledgements
The mathematical and analytical work is supported by Nanotechnology for Agricultural and Food Systems (A1511) [Grant No. 2021-67021-33999/Project Accession No. 1025638] from the USDA National Institute of Food and Agriculture. The extension of the theory to plant signaling data was supported by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) program. The Disruptive & Sustainable Technology for Agricultural Precision (DiSTAP) is an interdisciplinary research group of the Singapore MIT Alliance for Research and Technology (SMART) Centre. DJL and TKP are grateful for support from the National Science Foundation Graduate Research Fellowship Program under Grant No. 1745302. TTSL acknowledges a graduate fellowship by the Agency of Science, Research and Technology, Singapore. KSS was supported by the Department of Energy Computational Science Graduate Fellowship program under Grant DE-FG02-97ER25308. Professor Per-Olof Persson is acknowledged for helpful insights during the development of the approximate solutions.
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TKP: Data Curation, Formal analysis, Methodology, Software, Visualization, Writing—Original Draft (main text), Writing—Review & Editing. MNH: Formal analysis, Methodology, Software, Writing—Original Draft (Supplementary Information), Writing—Review & Editing. DJL: Formal analysis, Methodology, Writing—Review & Editing. AMB: Formal analysis, Methodology, Writing—Review & Editing. TTSL: Data Curation, Formal analysis, Investigation, Methodology, Software, Writing—Review & Editing. KSS: Formal analysis, Methodology, Software, Writing—Review & Editing. VBK: Formal analysis, Methodology, Writing—Review & Editing. MCYA: Investigation, Validation, Writing—Review & Editing. DTK: Investigation, Validation, Writing—Review & Editing. GPS: Conceptualization, Funding acquisition, Supervision, Writing—Review & Editing. JWS: Conceptualization, Formal analysis, Methodology, Supervision. RS: Conceptualization, Funding acquisition, Supervision, Writing—Reviewing & Editing. NHC: Conceptualization, Funding acquisition, Supervision, Writing—Review & Editing. MSS: Conceptualization, Formal analysis, Funding acquisition, Methodology, Supervision, Writing—Review & Editing.
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This paper is dedicated, with appreciation, to our colleague and co-author Professor James W. Swan, who died suddenly on Nov. 5th, 2021.
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Porter, T.K., Heinz, M.N., Lundberg, D.J. et al. A theory of mechanical stress-induced H2O2 signaling waveforms in Planta. J. Math. Biol. 86, 11 (2023). https://doi.org/10.1007/s00285-022-01835-y
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DOI: https://doi.org/10.1007/s00285-022-01835-y