Quantification of Immunohistochemistry Fluorescence of Plant Cell Wall Glycan Epitopes – A Semiautomated Workflow Design
Miguel Moreira (Portugal)1; Maria João Ferreira (Portugal)1; Martin Vojtek (Portugal)2; Carmen Diniz (Portugal)2; Ieva Lelenaite (UK)3; William G. T. Willats (UK)3; Sílvia Coimbra (Portugal)1; Ricardo M. F. da Costa (Portugal)4 5;
1 - LAQV/REQUIMTE, Biology Department, Faculty of Sciences, University of Porto, Porto, Portugal; 2 - LAQV/REQUIMTE, Laboratory of Pharmacology, Department of Drug Sciences, Faculty of Pharmacy, University of Porto, Porto, Portugal; 3 - School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; 4 - University of Coimbra, Molecular Physical-Chemistry R&D Unit, Department of Chemistry, LAQV/REQUIMTE, Coimbra, Portugal; 5 - Centre for Functional Ecology – Science for People and the Planet (CFE), Department of Life Sciences, University of Coimbra, Coimbra, Portugal;
Keywords: plant cell wall glycans; immunohistochemistry; semiautomated fluorescence quantification;
Abstract Topics: Theme 10: Tools, Imaging, and Omics for Cell Wall Research
Type of Presentation: Poster

Abstract text: Automating plant cell wall (CW) glycan epitope quantification in immunohistochemistry is hindered by plant growth plasticity, glycan dynamics and monoclonal antibody (mAb) cross-reactivity. To address this, we designed an experimental pipeline to compare labeling patterns and fluorescence intensities across: (1) mAbs targeting different CW glycans in the same tissues, (2) KOH-treated vs. untreated sections, (3) plant species with distinct CW compositions/structures – Arabidopsis thaliana (dicot), Zea mays (commelinid monocot), and Pinus pinaster (conifer). Thin LR-White resin cross-sections were incubated with mAbs against CW matrix glycans: xyloglucan (LM15), xylan (CCRC-M144, LM10), and pectin (JIM7). Some sections were pretreated with 0.1M KOH and all were stained with 0.01% (w/v) calcofluor-white. Specimens were imaged using a Lionheart FX automated fluorescence microscope for uniform acquisition. DAPI and GFP channels were captured and analyzed with a custom Fiji (ImageJ) macro, which pairs images, defines regions of interest via DAPI thresholding, and transfers them to the GFP channel for fluorescence quantification. The produced distinct immunolabelling patterns and signal intensities allowed reliable detection of differences based on recognized epitope, KOH-treatment, and plant species. The dataset generated during the developed workflow allows semiautomated, computer-assisted image analysis of bulk immunolabelling data with reduced bias and increased speed.