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Computational tools for serial block EM reveal differences in plasmodesmata distributions and wall environments

31 Mar 2020 · 10.1101/2020.03.31.005991

Abstract

Plasmodesmata are small channels that connect plant cells. While recent technological advances have facilitated the analysis of the ultrastructure of these channels, there are limitations to efficiently addressing their presence over an entire cellular interface. Here, we highlight the value of serial block electron microscopy for this purpose. We developed a computational pipeline to study plasmodesmata distributions and we detect presence/absence of plasmodesmata clusters, pit fields, at the phloem unloading interfaces of Arabidopsis thaliana roots. Pit fields can be visualised and quantified. As the wall environment of plasmodesmata is highly specialised we also designed a tool to extract the thickness of the extracellular matrix at and outside plasmodesmata positions. We show and quantify clear wall thinning around plasmodesmata with differences between genotypes, namely in the recently published plm-2 sphingolipid mutant. Our tools open new avenues for quantitative approaches in the analysis of symplastic trafficking. Sentence summary We developed computational tools for serial block electron microscopy datasets to extract information on the spatial distribution of plasmodesmata over an entire cellular interface and on the wall environment the plasmodesmata are in.

Plant phenotyping relevance

植物組織の電子顕微鏡画像から原形質連絡の分布や細胞壁厚を定量抽出する計算ツールとパイプラインが研究の中心であり、植物形態状態の測定法に該当する。

abstractWe developed a computational pipeline to study plasmodesmata distributions
abstractwe also designed a tool to extract the thickness of the extracellular matrix at and outside plasmodesmata positions
abstractOur tools open new avenues for quantitative approaches in the analysis of symplastic trafficking.

Code and data availability

The paper publicly releases its authors' MIB plugins for plasmodesmata distribution and wall-thickness analysis (GitHub), a guided R analysis tutorial/pipeline (GitHub Pages), and the Col-0 SB-EM datasets with segmented wall models and PD annotations (Google Drive), all with explicit availability statements and URLs.

Codepublic

A guided tutorial with all the necessary code for this analysis is available at https://andreapaterlini.github.io/Plasmodesmata_dist_wall/

Open resource ↗pdf-page:6 lines:1-49
Datasetpublic

The Col-0 datasets used in this paper, with corresponding models and annotation are available from https://drive.google.com/file/d/1g-

Open resource ↗pdf-page:6 lines:1-49

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