Beyond transformation: Unleashing the secrets of plant-fungal interactions with a simple yet highly effective confocal staining technique

Authors: NELSON, ASHLEY - North Dakota State University; KARIYAWASAM, GAYAN - North Dakota State University; Wyatt, Nathan; LING, JI - North Dakota State University; HAUEISEN, JANINE - Max Planck Institute For Evolutionary Biology; STUKENBROCK, EVA - Max Planck Institute For Evolutionary Biology; BOROWICZ, PAWEL - North Dakota State University; Friesen, Timothy

Submitted to: Molecular Plant-Microbe Interactions
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/17/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Fungi account for around 85% of all crop losses caused by pathogens. Fluorescent microscopy is the best way to visualize how these fungal pathogens are penetrating and colonizing their respective hosts. However, the differentiation of plant and fungal material using fluorescent microscopy is not straightforward especially for non-model systems. Here we present a simple yet effective method for visualizing any plant-fungal interaction. This method does not require transformation with fluorescent protein genes but rather uses commonly available fluorescent stains that clearly differentiate plant and fungal material. Using this method we were also able to use machine learning to more accurately describe both the increase in fungal biomass (a proxy for pathogen health) and nuclear degradation (a hallmark of host controlled programmed cell death) to more effectively asses three plant- fungal pathogen interactions including net form net blotch on barley, septoria nodorum blotch on wheat, and Cercospora leaf blotch on sugar beet. This information is already being used by multiple researchers evaluating additional plant-fungal interactions.

Technical Abstract: Laser scanning confocal microscopy’s ability to generate high-contrast 3D images has become essential to studying plant-fungal interactions. Techniques such as visualization of native fluorescence, fluorescent protein tagging of microbes, GFP/RFP-fusion proteins, and fluorescent labelling of plant and fungal proteins have been widely used to aid in these investigations. Use of fluorescent proteins have several pitfalls including variability of expression in planta and the requirement of gene transformation. Here we used the unlabeled pathogens Parastagonospora nodorum, Pyrenophora teres f. teres, and Cercospora beticola infecting wheat, barley, and sugar beet respectively, to show the utility of a staining and imaging technique that uses propidium iodide (PI) and wheat germ agglutinin labeled with fluorescein isothiocyanate (WGA-FITC) to visualize fungal colonization of plants. This method relies on the use of KOH to remove the cutin layer of the leaf, increasing its permeability. This permeability allows the staining solution to penetrate and efficiently bind to its targets, resulting in a consistent visualization of cellular structures. We have also used this staining technique in conjunction with machine learning to analyze fungal volume (biomass), which indicates the fitness of the pathogen in planta, as well as quantifying nuclear breakdown, an early indicator of programmed cell death (PCD).This technique is simple to use, robust, consistent across host species, and can be applied to any plant-fungal interaction. Therefore, this technique can be used to characterize model systems as well as non-model interactions where transformation is not routine.