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3 Janelia Publications
Showing 1-3 of 3 resultsUnderstanding cellular architecture is essential for understanding biology. Electron microscopy (EM) uniquely visualizes cellular structures with nanometre resolution. However, traditional methods, such as thin-section EM or EM tomography, have limitations in that they visualize only a single slice or a relatively small volume of the cell, respectively. Focused ion beam-scanning electron microscopy (FIB-SEM) has demonstrated the ability to image small volumes of cellular samples with 4-nm isotropic voxels. Owing to advances in the precision and stability of FIB milling, together with enhanced signal detection and faster SEM scanning, we have increased the volume that can be imaged with 4-nm voxels by two orders of magnitude. Here we present a volume EM atlas at such resolution comprising ten three-dimensional datasets for whole cells and tissues, including cancer cells, immune cells, mouse pancreatic islets and Drosophila neural tissues. These open access data (via OpenOrganelle) represent the foundation of a field of high-resolution whole-cell volume EM and subsequent analyses, and we invite researchers to explore this atlas and pose questions.
Cells contain hundreds of organelles and macromolecular assemblies. Obtaining a complete understanding of their intricate organization requires the nanometre-level, three-dimensional reconstruction of whole cells, which is only feasible with robust and scalable automatic methods. Here, to support the development of such methods, we annotated up to 35 different cellular organelle classes-ranging from endoplasmic reticulum to microtubules to ribosomes-in diverse sample volumes from multiple cell types imaged at a near-isotropic resolution of 4 nm per voxel with focused ion beam scanning electron microscopy (FIB-SEM). We trained deep learning architectures to segment these structures in 4 nm and 8 nm per voxel FIB-SEM volumes, validated their performance and showed that automatic reconstructions can be used to directly quantify previously inaccessible metrics including spatial interactions between cellular components. We also show that such reconstructions can be used to automatically register light and electron microscopy images for correlative studies. We have created an open data and open-source web repository, 'OpenOrganelle', to share the data, computer code and trained models, which will enable scientists everywhere to query and further improve automatic reconstruction of these datasets.
Cellular versatility depends on accurate trafficking of diverse proteins to their organellar destinations. For the secretory pathway (followed by approximately 30% of all proteins), the physical nature of the vessel conducting the first portage (endoplasmic reticulum [ER] to Golgi apparatus) is unclear. We provide a dynamic 3D view of early secretory compartments in mammalian cells with isotropic resolution and precise protein localization using whole-cell, focused ion beam scanning electron microscopy with cryo-structured illumination microscopy and live-cell synchronized cargo release approaches. Rather than vesicles alone, the ER spawns an elaborate, interwoven tubular network of contiguous lipid bilayers (ER exit site) for protein export. This receptacle is capable of extending microns along microtubules while still connected to the ER by a thin neck. COPII localizes to this neck region and dynamically regulates cargo entry from the ER, while COPI acts more distally, escorting the detached, accelerating tubular entity on its way to joining the Golgi apparatus through microtubule-directed movement.