Analysis of Nanosensor-Reported Waveforms for Plant Wounding

Using nanosensors in living plants allows the real-time detection of internal reactive oxygen species (e.g., hydrogen peroxide) signaling in response to environmental stressors. The time-dependent pulse of hydrogen peroxide (H₂O₂) constitutes a <i>signaling waveform</i>; however, standardized methods of extracting and analyzing such waveforms quantitatively remain elusive. Here, we develop a reference-less framework to extract stress-induced H₂O₂ waveforms <i>in</i> <i>planta</i> directly from active nanosensors for the first time. We show that waveforms extracted for 3-week-old spinach across different experimental configurations, including 2D nIR imaging and 1D spectroscopy, are identical. Using this standardized approach, we systematically validate an analytical waveform model based on H₂O₂ reaction-diffusion transport with a large waveform data set and extract the wave velocities and propagation rate constants from different waveforms. A wave-velocity-rate constant map is created for comparative studies. Results suggest that nanosensors can identify distinct waveforms associated with specific plant stressors with the proposed framework, providing opportunities for new diagnostic tools.