User-friendly electron microscopy protocols for the visualization of biological macromolecular complexes in three dimensions: Visualization of planta clathrin-coated vesicles at ultrastructural resolution

Abstract

Biological systems are the sum of their dynamic 3-dimensional (3D) parts. Therefore, it is critical to study biological structures in 3D and at high resolutions to gain insights into their physiological functions. Electron microscopy of metal replicas of unroofed cells and isolated organelles has been a key technique to visualize intracellular structures at nanometer resolution. However, many of these protocols require specialized equipment and personnel to complete them. Here we present novel accessible protocols to analyze biological structures in unroofed cells and biochemically isolated organelles in 3D and at nanometer resolutions, focusing on Arabidopsis clathrin-coated vesicles (CCVs) - an essential trafficking organelle lacking detailed structural characterization due to their low preservation in classical electron microscopy techniques. First, we establish a protocol to visualize CCVs in unroofed cells using scanning-transmission electron microscopy (STEM) tomography, providing sufficient resolution to define the clathrin coat arrangements. Critically, the samples are prepared directly on electron microscopy grids, removing the requirement to use extremely corrosive acids, thereby enabling the use of this protocol in any electron microscopy lab. Secondly, we demonstrate this standardized sample preparation allows the direct comparison of isolated CCV samples with those visualized in cells. Finally, to facilitate the high-throughput and robust screening of metal replicated samples, we provide a deep learning analysis workflow to screen the ‘pseudo 3D’ morphology of CCVs imaged with 2D modalities. Overall, we present accessible ways to examine the 3D structure of biological samples and provide novel insights into the structure of plant CCVs.

Plant phenotyping relevance

植物細胞内オルガネラの3D形態を取得・解析する電子顕微鏡プロトコルと深層学習ワークフローが研究の中心であり、植物CCV形態の技術的スクリーニング手法を提供している。

Code and data availability

The paper's Data Availability statement explicitly deposits example data (SEM replica images, training image pairs) and the analysis code (Cellpose-based CCV segmentation workflow) generated in this study at a public Zenodo DOI, making it a paper-specific, publicly actionable asset. The temography.com URLs are vendor/m