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Red light imaging for programmed cell death visualization and quantification in plant–pathogen interactions

Sergio Landeo Villanueva · Michele C. Malvestiti · Wim van Ieperen · Matthieu H. A. J. Joosten · Jan A. L. van Kan

Molecular Plant Pathology · 26 Jan 2021 · 10.1111/mpp.13027

Abstract

Abstract Studies on plant–pathogen interactions often involve monitoring disease symptoms or responses of the host plant to pathogen‐derived immunogenic patterns, either visually or by staining the plant tissue. Both these methods have limitations with respect to resolution, reproducibility, and the ability to quantify the results. In this study we show that red light detection by the red fluorescent protein (RFP) channel of a multipurpose fluorescence imaging system that is probably available in many laboratories can be used to visualize plant tissue undergoing cell death. Red light emission is the result of chlorophyll fluorescence on thylakoid membrane disassembly during the development of a programmed cell death process. The activation of programmed cell death can occur during either a hypersensitive response to a biotrophic pathogen or an apoptotic cell death triggered by a necrotrophic pathogen. Quantifying the intensity of the red light signal enables the magnitude of programmed cell death to be evaluated and provides a readout of the plant immune response in a faster, safer, and nondestructive manner when compared to previously developed chemical staining methodologies. This application can be implemented to screen for differences in symptom severity in plant–pathogen interactions, and to visualize and quantify in a more sensitive and objective manner the intensity of the plant response on perception of a given immunological pattern. We illustrate the utility and versatility of the method using diverse immunogenic patterns and pathogens.

Code and data availability

The paper's red light imaging measurements and quantification data are not publicly deposited; the authors state data are available from the corresponding author upon reasonable request. No public dataset, image, or code repository URL is provided in the supplied blocks.

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