(586b) Analysis of Stress-Induced H2O2 Signaling Waveforms in Planta | AIChE

(586b) Analysis of Stress-Induced H2O2 Signaling Waveforms in Planta


Porter, T. - Presenter, The Ohio State University
Heinz, M. N., University of California, Berkeley
Lundberg, D. J., Massachusetts Institute of Technology
Brooks, A., Massachusetts Institute of Technology
Lew, T. T. S., Massachusetts Institute of Technology
Silmore, K., Massachusetts Institute of Technology
Koman, V., MIT
Ang, M., Singapore-Mit Alliance For Research and Technology
Khong, D. T., Singapore-Mit Alliance For Research and Technology
Singh, G. P., Singapore-MIT Alliance for Research and Technology
Swan, J., Massachusetts Institute of Technology
Sarojam, R., Temasek Life Sciences Laboratory
Chua, N. H., Temasek Life Sciences Laboratory
Strano, M., Massachusetts Institute of Technology
Decoding stress signaling in plants is critical for understanding various aspects of plant sciences, from pest resistance to secondary metabolite and phytohormone biosynthesis. As sessile organisms lacking mobile immune cells, plants adapt to their everchanging environments via rapid cell-to-cell signaling. Under abiotic and biotic stresses, one such rapid signaling mechanism occurs at the onset of stress via the autocatalytic production and diffusion of H2O2 in a cascade known as the H­2O2 wave. Real-time spatiotemporal monitoring of the H­2O2 wave generated after mechanical wounding in planta using single-walled carbon nanotube (SWNT) optical sensors has revealed a conserved traveling waveform across different plant species. Herein, we develop a quantitative theory describing the mechanical stress-induced H2O2 signaling waveform based on a soliton solution to the nonlinear reaction-diffusion process occurring within the plant. The spatial and temporal waveform is modeled by partial differential equations describing the autocatalytic production and Fickian diffusion of H2O2 followed by its first-order decay. We develop an approximate solution from a single-term logistic function ansatz using a traveling wave coordinate combining space and time to convert the model into a system of ordinary differential equations. The application of our theory to experimental data describes H2O2 production and degradation dynamics and links species-dependent dimensionless wave velocities to subtle changes in higher moments of the waveform. Notably, H2O2 waveforms generated from other stresses such as high light, high heat, and pathogen-associated molecular pattern (PAMP)-induced stresses appear to be distinct from the mechanical wound-induced waveform, suggesting that stress specificity may be encoded within the spatiotemporal dynamics of the H­2O2 wave. Our theory should greatly advance the analysis of stress-induced H2O2 waveforms, aiding interpretation of encoded information within the H2O2 signal and its connections to concurrent and downstream signaling pathways.