Quantitative Analysis of Ligand-Induced Endocytosis of FLAGELLIN-SENSING 2 Using Automated Image Segmentation.

Abstract

Plants are equipped with a suite of plant pattern recognition receptors (PRRs) that must be properly trafficked to and from the plasma membrane (PM), which serves as the host-pathogen interface, for robust detection of invading pathogenic microbes. Recognition of bacterial flagellin, or the derived peptide flg22, is facilitated by the PM-localized PRR, FLAGELLIN SENSING 2 (FLS2). Upon flg22 binding, FLS2 is rapidly internalized from the PM into endosomal compartments and subsequently degraded. To understand better the integration of FLS2 endocytosis and signaling outputs, we developed methods for the quantitative analysis of FLS2 trafficking using freely available bioimage informatic tools. Emphasis was placed on robust recognition of features and ease of access for users. Using the free and open-source software Fiji (Fiji is just ImageJ) and Trainable Weka Segmentation (TWS) plug-in, we developed a workflow for the automated identification of green fluorescent protein (GFP)-tagged FLS2 in endosomal puncta. Fiji-TWS methods can be adapted with ease for the analysis of FLS2 trafficking in various genetic backgrounds as well as for the endocytic regulation of diverse plant PRRs.

Plant phenotyping relevance

植物受容体の細胞内局在・エンドサイトーシスを画像から定量する自動セグメンテーション手法と再利用可能な解析ワークフローを開発しており、表現型取得・抽出法が中心である。

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