Automatic extraction of actin networks in plants.

Abstract

The actin cytoskeleton is essential in eukaryotes, not least in the plant kingdom where it plays key roles in cell expansion, cell division, environmental responses and pathogen defence. Yet, the precise structure-function relationships of properties of the actin network in plants are still to be unravelled, including details of how the network configuration depends upon cell type, tissue type and developmental stage. Part of the problem lies in the difficulty of extracting high-quality, quantitative measures of actin network features from microscopy data. To address this problem, we have developed DRAGoN, a novel image analysis algorithm that can automatically extract the actin network across a range of cell types, providing seventeen different quantitative measures that describe the network at a local level. Using this algorithm, we then studied a number of cases in Arabidopsis thaliana, including several different tissues, a variety of actin-affected mutants, and cells responding to powdery mildew. In many cases we found statistically-significant differences in actin network properties. In addition to these results, our algorithm is designed to be easily adaptable to other tissues, mutants and plants, and so will be a valuable asset for the study and future biological engineering of the actin cytoskeleton in globally-important crops.

Plant phenotyping relevance

植物画像からアクチンネットワークの定量的形質を自動抽出する画像解析アルゴリズムの開発が中心であり、植物組織・変異体・病害応答への適用も行っている。

Code and data availability

The paper's Data Availability statement explicitly deposits the complete DRAGoN analysis code (the computational tool that performs the paper's actin network extraction and phenotyping measurements) on a public GitHub repository, and the repository URL is also cited in the Results section.