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Title: Semi-automated confocal imaging of fungal pathogenesis on plants: microscopic analysis of macroscopic specimens

Author
item MINKER, KATHARINE - University Of Delaware
item BIEDRZYCKI, MEREDITH - University Of Delaware
item KOLAGUNDA, ABHISEK - University Of Delaware
item RHEIN, STEPHEN - University Of Delaware
item PERINA, FABIANO - Embrapa
item JACOBS, SCOTT - Delaware Biotechnology Institute
item MOORE, MIKE - Delaware Biotechnology Institute
item JAMANN, TIFFANY - Cornell University
item NELSON, REBECCA - Cornell University
item YANG, QIN - North Carolina State University
item Balint-Kurti, Peter
item KAMBHAMETTU, CHANDRA - University Of Delaware
item WISSER, RANDALL - University Of Delaware
item CAPLAN, JEFFREY - University Of Delaware

Submitted to: Microscopy Research and Technique
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/10/2015
Publication Date: 7/1/2016
Citation: Minker, K., Biedrzycki, M., Kolagunda, A., Rhein, S., Perina, F.J., Jacobs, S., Moore, M., Jamann, T.M., Nelson, R., Yang, Q., Balint Kurti, P.J., Kambhamettu, C., Wisser, R.J., Caplan, J.L. 2016. Semi-automated confocal imaging of fungal pathogenesis on plants: microscopic analysis of macroscopic specimens. Microscopy Research and Technique. DOI: 10.1002/jemt.22709.

Interpretive Summary: We described a way of sampling a maize leaf infected with a fungal pathogen and fixing , clearing, staining and imaging the sample and processing those images so that the fungal hyphae can be visualized in the leaf tissue in unprecedented detail.

Technical Abstract: Contextualizing natural genetic variation in plant disease resistance in terms of pathogenesis can provide information about the function of causal genes. Cellular mechanisms associated with pathogenesis can be elucidated with confocal microscopy, but systematic phenotyping platforms—from sample processing to image analysis—to investigate this do not exist or provide limited information. We have developed a platform for 3D phenotyping of cellular features underlying variation in disease development by fluorescence-specific resolution of host and pathogen interactions across time (4D). A confocal microscopy phenotyping platform compatible with different maize-fungal pathosystems (fungi: Setoshpaeria turcica and Bipolaris maydis) was developed. Protocols and techniques were standardized for sample fixation, optical clearing, species-specific combinatorial fluorescence staining, multi-sample imaging, and image processing for investigation at the macro scale. The sample preparation methods presented here overcome challenges to fluorescence imaging such as specimen thickness and topography as well as physiological characteristics of the samples such as tissue autofluorescence and presence of cuticle. The resulting imaging techniques provide interesting qualitative information as well correlation and quantification methods not possible with conventional light or electron 2D imaging.