Ashley C Nelson, Gayan Kariyawasam, Nathan A Wyatt, Jinling Li, Janine Haueisen, Eva H Stukenbrock, Pawel Borowicz, Zhaohui Liu, Timothy L Friesen
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Here we used the unlabeled pathogens <i>Parastagonospora nodorum</i>, <i>Pyrenophora teres</i> f. <i>teres</i>, and <i>Cercospora beticola</i> 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. 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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. 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引用次数: 0
摘要
激光扫描共聚焦显微镜能够生成高对比度的二维和三维图像,这对研究植物与真菌的相互作用至关重要。原生荧光可视化、微生物荧光蛋白标记、GFP/RFP 融合蛋白以及植物和真菌蛋白荧光标记等技术已被广泛用于辅助这些研究。使用荧光蛋白有几个缺陷,包括在植物体内表达的可变性和基因转化的要求。在这里,我们使用了未标记的病原体 Parastagonospora nodorum、Pyrenophora teres f. teres 和 Cercospora。在这里,我们利用分别感染小麦、大麦和甜菜的未标记病原体 Parastagonospora nodorum、Pyrenophora teres f. teres 和 Cercospora beticola 来展示染色和成像流水线的实用性,该流水线使用碘化丙啶(可对 RNA 和 DNA 进行染色)和用异硫氰酸荧光素标记的小麦胚芽凝集素(WGA-FITC)(可对几丁质进行染色)来观察植物的真菌定殖。该方法利用 KOH 去除叶片的角质层,增加其通透性,使不同的染色剂能够渗透并有效地与目标结合,从而实现细胞结构的一致可视化。为了扩大该管道的实用性,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的生物量,并量化细胞核破坏,这是程序性细胞死亡(PCD)的早期指标。该方法简单易用、功能强大、跨宿主和真菌物种,可用于大多数植物与真菌的相互作用。因此,该管道可用于描述模型系统以及非模型相互作用的特征,在这些系统中,转化并非常规。
Assembly and evaluation of a confocal microscopy image analysis pipeline useful in revealing the secrets of plant-fungal interactions.
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, 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 has 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 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 non-model interactions where transformation is not routine.