Nelson Ashley C, Kariyawasam Gayan K, Wyatt Nathan A, Li Jinling, Haueisen Janine, Stukenbrock Eva H, Borowicz Pawel, Liu Zhaohui, Friesen Timothy L
Department of Plant Pathology, North Dakota State University, Fargo, ND 58102, U.S.A.
Department of Entomology and Plant Pathology, University of Tennessee, Knoxville, TN 37996, U.S.A.
Mol Plant Microbe Interact. 2024 Dec;37(12):804-813. doi: 10.1094/MPMI-08-24-0090-TA. Epub 2024 Dec 17.
The ability of laser scanning confocal microscopy to generate high-contrast 2D and 3D images has become essential in studying plant-fungal interactions. Techniques such as visualization of native fluorescence, fluorescent protein tagging of microbes, green fluorescent protein (GFP)/red fluorescent protein (RFP)-fusion proteins, and fluorescent labeling of plant and fungal proteins have been widely used to aid in these investigations. Use of fluorescent proteins has several pitfalls, including variability of expression in planta and the requirement of gene transformation. Here, we used the unlabeled pathogens , f. , and infecting wheat, barley, and sugar beet, respectively, to show the utility of a staining and imaging pipeline that uses propidium iodide (PI), which stains RNA and DNA, and wheat germ agglutinin labeled with fluorescein isothiocyanate (WGA-FITC), which stains chitin, to visualize fungal colonization of plants. This pipeline relies on the use of KOH to remove the cutin layer of the leaf, increasing its permeability, allowing the different stains to penetrate and effectively bind to their targets, resulting in a consistent visualization of cellular structures. To expand the utility of this pipeline, we used the staining techniques in conjunction with machine learning to analyze fungal biomass through volume analysis, as well as quantifying nuclear breakdown, an early indicator of programmed cell death (PCD). This pipeline is simple to use, robust, consistent across host and fungal species, and can be applied to most plant-fungal interactions. Therefore, this pipeline can be used to characterize model systems as well as nonmodel interactions where transformation is not routine. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.
激光扫描共聚焦显微镜生成高对比度二维和三维图像的能力在研究植物 - 真菌相互作用中变得至关重要。诸如天然荧光可视化、微生物的荧光蛋白标记、绿色荧光蛋白(GFP)/红色荧光蛋白(RFP)融合蛋白以及植物和真菌蛋白的荧光标记等技术已被广泛用于辅助这些研究。荧光蛋白的使用存在几个缺陷,包括在植物中的表达变异性以及基因转化的要求。在这里,我们分别使用未标记的病原体,即感染小麦、大麦和甜菜的[病原体名称未给出],来展示一种染色和成像流程的效用,该流程使用碘化丙啶(PI)(可对RNA和DNA进行染色)以及异硫氰酸荧光素标记的麦胚凝集素(WGA - FITC)(可对几丁质进行染色)来可视化植物中的真菌定殖。该流程依赖于使用氢氧化钾去除叶片的角质层,增加其通透性,使不同的染料能够渗透并有效结合到其靶点,从而实现细胞结构的一致可视化。为了扩展该流程的效用,我们将染色技术与机器学习相结合,通过体积分析来分析真菌生物量,以及对核解体进行定量,核解体是程序性细胞死亡(PCD)的早期指标。该流程易于使用、稳健,在宿主和真菌物种之间具有一致性,并且可应用于大多数植物 - 真菌相互作用。因此,该流程可用于表征模型系统以及转化不常规的非模型相互作用。[公式:见原文]作者已根据知识共享CC0“无权利保留”许可将作品奉献给公共领域,在法律允许的范围内,放弃其在全球范围内对该作品的所有版权,包括所有相关和相邻权利,2024年。