Micro-electron diffraction (MicroED) is an emerging technique to use cryo-electron microscope to study the crystal structures of macromolecule from its micro-/nano-crystals, which are not suitable for conventional X-ray crystallography. However, this technique has been prevented for its wide application by the limited availability of producing good micro-/nano-crystals and the inappropriate transfer of crystals. Here, we developed a complete workflow to prepare suitable crystals efficiently for MicroED experiment. This workflow includes in situ on-grid crystallization, single-side blotting, cryo-focus ion beam (cryo-FIB) fabrication, and cryo-electron diffraction of crystal cryo-lamella. This workflow enables us to apply MicroED to study many small macromolecular crystals with the size of 2–10 μm, which is too large for MicroED but quite small for conventional X-ray crystallography. We have applied this method to solve 2.5 Å crystal structure of lysozyme from its micro-crystal within the size of 10 × 10 × 10 μm³. Our work will greatly expand the availability space of crystals suitable for MicroED and fill up the gap between MicroED and X-ray crystallography.

Electron Tomography (ET) is an important method for studying cell ultrastructure in three-dimensional (3D) space. By combining cryo-electron tomography of frozen-hydrated samples (cryo-ET) and a sub-tomogram averaging approach, ET has recently reached sub-nanometer resolution, thereby realizing the capability for gaining direct insights into function and mechanism. To obtain a high-resolution 3D ET reconstruction, alignment and geometry determination of the ET tilt series are necessary. However, typical methods for determining geometry require human intervention, which is not only subjective and easily introduces errors, but is also labor intensive for high-throughput tomographic reconstructions. To overcome these problems, we have developed an automatic geometry-determination method, called AutoGDeterm. By taking advantage of the high-contrast re-projections of the Iterative Compressed-sensing Optimized Non-Uniform Fast Fourier Transform (NUFFT) reconstruction (ICON) and a series of numerical analysis methods, AutoGDeterm achieves high-precision fully automated geometry determination. Experimental results on simulated and resin-embedded datasets show that the accuracy of AutoGDeterm is high and comparable to that of the typical “manual positioning” method. We have made AutoGDeterm available as software, which can be freely downloaded from our website http://ear.ict.ac.cn.

Determining the cellular localization of proteins of interest at nanometer resolution is necessary for elucidating their functions. Besides super-resolution fluorescence microscopy, conventional electron microscopy (EM) combined with immunolabeling or clonable EM tags provides a unique approach to correlate protein localization information and cellular ultrastructural information. However, there are still rare cases of such correlation in three-dimensional (3D) spaces. Here, we developed an approach by combining the focus ion beam scanning electron microscopy (FIB-SEM) and a promising clonable EM tag APEX2 (an enhanced ascorbate peroxidase 2) to determine the target protein localization within 3D cellular ultrastructural context. We further utilized this approach to study the 3D localization of mitochondrial dynamics-related proteins (MiD49/51, Mff, Fis1, and Mfn2) in the cells where the target proteins were overexpressed. We found that all the target proteins were located at the surface of the mitochondrial outer membrane accompanying with mitochondrial clusters. Mid49/51, Mff, and hFis1 spread widely around the mitochondrial surface while Mfn2 only exists at the contact sites.

Electron tomography (ET) plays an important role in studying in situ cell ultrastructure in three-dimensional space. Due to limited tilt angles, ET reconstruction always suffers from the “missing wedge” problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction (ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units (GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON’s dependence on computing resource.

Correlative cryo-fluorescence and cryo-electron microscopy (cryo-CLEM) system has been fast becoming a powerful technique with the advantage to allow the fluorescent labeling and direct visualization of the close-to-physiologic ultrastructure in cells at the same time, offering unique insights into the ultrastructure with specific cellular function. There have been various engineered ways to achieve cryo-CLEM including the commercial FEI iCorr system that integrates fluorescence microscope into the column of transmission electron microscope. In this study, we applied the approach of the cryo-CLEM-based iCorr to image the syntaphilin-immobilized neuronal mitochondria in situ to test the performance of the FEI iCorr system and determine its correlation accuracy. Our study revealed the various morphologies of syntaphilin-immobilized neuronal mitochondria that interact with microtubules and suggested that the cryo-CLEM procedure by the FEI iCorr system is suitable with a half micron-meter correlation accuracy to study the cellular organelles that have a discrete distribution and large size, e.g. mitochondrion, Golgi complex, lysosome, etc.