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Research Article
Lihong Chen*1,2, Zhuofan Fang*1,3, Qi Wen1, Chunling Wu4, Tongxin Niu4, Rensen Ran1,3, Jing Hang1,3
1Department of Obstetrics and Gynecology, Center for Reproductive Medicine, State Key Laboratory of Female Fertility Promotion,Peking University Third Hospital, 2Medical and Health Analysis Center,Peking University Health Science Center, 3Beijing Key Laboratory of Collaborative Innovation in Frontier Technologies for Population Quality, 4Institute of Biophysics,Chinese Academy of Sciences
Erratum Notice
Important: There has been an erratum issued for this article. View Erratum Notice
Retraction Notice
The article Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size (LEfSe) in Microbiome Data (10.3791/61715) has been retracted by the journal upon the authors' request due to a conflict regarding the data and methodology. View Retraction Notice
Electron tomography enables near-atomic-level imaging of organelles, cells, and macromolecules within tissues in cryo-biological samples. Achieving such resolution requires strictly controlled imaging conditions. Here, using a 200 kV transmission electron microscope with a two-stage condenser lens system as an example, we describe how to perform high-quality electron tomography data collection.
Cryo-electron tomography (cryo-ET) has emerged as a powerful technique for elucidating the structures of cellular organelles and large protein complexes in their native environments. Unlike conventional room-temperature electron microscopy, cryo-ET minimizes radiation-induced and preparation-induced damage to internal structures. Moreover, in contrast to single-particle analysis (SPA), cryo-ET reduces the need for repetitive purification, thereby preserving the most authentic structural information of the samples. To achieve high-resolution imaging, cryo-ET also imposes stringent requirements on the imaging conditions of the TEM. Despite the continuous improvement in cryo-ET data acquisition efficiency and the emergence of numerous software platforms, most solutions are proprietary, vendor-specific, and tightly coupled to certain electron microscope models, leading to high implementation costs. In this study, we installed the open-source software SerialEM on a 200 kV electron microscope (Glacios 2 cryo-TEM) with a dual condenser lens system and performed comprehensive calibrations to enable high-quality tomographic data acquisition. Using apoferritin as a model specimen, we describe the entire workflow-from cryo-sample preparation to automated cryo-ET data collection, followed by tomogram reconstruction and sub-tomogram analysis. This method offers a cost-effective and accessible solution for cryo-ET data collection, particularly for laboratories using Glacios microscopes without access to proprietary software.
Cryo-electron tomography (cryo-ET) has emerged as a powerful technique for studying the native structures of macromolecular complexes and cellular organelles in situ. A major advantage of cryo-ET over single-particle analysis (SPA) is its ability to avoid the excessive purification steps, thereby preserving the native state of the target biomolecules within their biological context. At present, a broad spectrum of specimens -- including purified organelles1,2,3,4, cell membrane sheets, macromolecular complexes5, viruses6, cellular lamellae7, and tissue sections8,9,10 -- can be investigated by cryo-ET. Given the diversity of sample types and experimental objectives, data collection strategies vary substantially and must be carefully tailored to both the specimen and the specific instrument configuration.
Data collection is a critical step in the cryo-ET workflow, as both data quality and acquisition efficiency directly impact downstream processing and the overall experimental success of the experiment. To meet the evolving experimental demands, several data-collection platforms have been developed. Among the most widely used are commercial Tomography and the open-source software SerialEM11,12,13. Tomography offers a highly integrated and user-friendly interface with a low learning curve, but it is less flexible and requires a commercial license. In contrast, SerialEM is a free, open-source package supporting both graphical user interface (GUI)-based and script-based workflows, providing greater flexibility and extensibility.
Tomographic data collection from cryo-lamellae poses unique challenges. High-quality lamellae are difficult to prepare, and their mechanical instability and high sensitivity to electron irradiation further complicate data collection. To address these challenges, Fabian Eisenstein developed the PACEtomo workflow14, an enhancement of SerialEM that introduces beam-image shift to acquire multiple tomograms per tilt series, thereby reducing the frequency of focus and tracking adjustments. This strategy maximizes the amount of usable data from each section while minimizing unnecessary electron exposure. Similar functionality is also available in the commercial Tomography5 software.
In contrast, data collection from cryo-fixed organelles or membrane sheets is generally more straightforward, as these samples are typically prepared on holey carbon grids, offering ample area for focusing and tracking15,16. In such cases, SerialEM's built-in cryo-ET acquisition workflows -- accessible directly via its GUI -- offer a convenient, scripting-free option, particularly suitable for beginners or smaller laboratories. Nevertheless, from the perspective of efficiency, we still recommend beam image shift-based strategies whenever feasible.
Given the high cost of cryo-electron microscopes, optimizing data collection strategies to maximize instrument utilization is essential. A 200 kV TEM equipped with a two-stage condenser lens system offers slightly lower electron penetration for thick samples than a 300 kV instrument, but it remains fully viable for cryo-ET when properly calibrated. However, its relatively narrow range of parallel beam conditions and fixed spot size across magnifications makes it generally less suitable for high-resolution cryo-ET unless the system is precisely optimized.
Our electron microscopy setup is equipped with a Falcon 4i direct electron detection camera, which provides substantial advantages in single-electron counting capability and high-speed continuous imaging. To fully exploit the performance of this detector, the TEM must be operated under well-optimized imaging conditions. For TEMs employing a two-stage condenser system, precise calibration of the illumination conditions for parallel light is an important factor in improving imaging quality17,18. In modern two-stage condenser systems, the focal point of the second-stage condenser lens must coincide with the front focal plane of the upper objective lens to ensure that the optical path intersecting with the sample plane is parallel. Accurately established parallel light conditions are crucial for ensuring that the under-focus values and magnification remain consistent at local positions in the collected images.
In this study, we focused on establishing a high-quality cryo-ET workflow using apoferritin as a model sample. Since the 200 kV transmission electron microscope system is not licensed for the commercial tomography software, we installed and calibrated the open-source SerialEM platform instead. By carefully optimizing the parallel beam parameters for the microscope's two-stage condenser lens system, we achieved automated tomographic data collection through the SerialEM graphical interface-without the need for Python scripts or complex configuration. This approach provides a user-friendly and cost-effective solution for efficient cryo-ET data acquisition on 200 kV instruments such as Glacios.
1. Preparation and loading of cryo-samples
2. Determining the parallel light conditions for electron microscopy
3. High-quality electron tomography data collection for apoferritin samples
NOTE: This section outlines a standardized procedure for high-throughput tomographic data acquisition, suitable for both experienced users and new researchers.
4. Subtomogram averaging of apoferritin
After precise parallel beam alignment, we conducted tomography data collection for apoferritin using the graphical interface function of SerialEM. Subsequent processing with Warp, AreTomo, PyTom, RELION, and other relevant software yielded a final structure at a resolution of 2.8 Å. This resolution sufficiently demonstrates the high quality of our data, reaching a level currently achievable by subtomogram averaging at relatively high resolution. As shown in Figure 4, the aligned and reconstructed results (Figure 4A) clearly demonstrate the overall architecture and spatial distribution of apoferritin. Subtomogram averaging was performed on particles extracted from eight aligned and reconstructed tilt series, yielding a structure at a resolution of 2.8 Å (Figure 4B). The corresponding Fourier shell correlation (FSC) curve is presented in Figure 4C.

Figure 1: Determination of parallel illumination condition using the second condenser lens system. (A) Diffraction pattern in Diffraction Mode without an aperture. (B) Diffraction pattern after insertion of a 100 µm objective aperture. (C) Aperture offset from diffraction center to better visualize edge sharpness. (D) Focused aperture edge and optimized diffraction rings by adjusting objective and C2 lens currents. (E) Elliptical central diffraction spot requiring correction via the Stigmator panel. (F) Circular and minimized central diffraction spot indicating optimized parallel illumination. Please click here to view a larger version of this figure.

Figure 2: High-to-low magnification alignment process from Search (115×) to View (2600×). (A) Search mode image with the marker (red arrow) positioned at the edge of the hole. (B) View mode image with the marker (red arrow) positioned at the same object location as in (A). The Shift to Marker option is clicked in the navigator. (C) In the pop-up window, the beam shifts from both magnifications are assigned to all markers in the Search map, and the shift values are saved. Please click here to view a larger version of this figure.

Figure 3: High-to-low magnification alignment process from View (2600×) to Record (120k×). (A) In Record mode, the target object is positioned at the center of the field of view (red dashed circle highlights the target object). (B) Image captured in View mode, where the target object does not align with the red crosshair (red dashed circle highlights the target object and the red crosshair). (C) The target object is dragged to the center of the red crosshair by right-clicking and moving it, followed by pressing the Set button located beside the Shift button (red dashed box highlights the button). Please click here to view a larger version of this figure.

Figure 4: Structure determination of apoferritin. (A) Structural imaging.Local resolution map of the final subtomogram average. The texture appears uniform, with closely arranged, repeating nanoscale features across the entire field of view. (B) Spatially resolved quantitative mapping. A false-color, circular map of the same or a related nanostructured region. Colors range from blue/green to yellow/red, corresponding to numerical values shown on the color scale below (approximately 2.5 to 3.5 in arbitrary units). The heterogeneous color distribution indicates spatial variation in a measured property (for example, height, thickness, refractive index, or mechanical/optical response) across the sample. (C) Global spectral or functional characterization. Fourier shell correlation (FSC) curve used for resolution estimation. The final resolution of 2.8 Å is indicated by the dashed line at FSC = 0.143. Please click here to view a larger version of this figure.
The procedures for cryo-sample preparation and electron tomography data collection must be adapted to the specific specimen type. The experimental strategy described here is well-suited for biological macromolecules, protein complexes, and small organelles. These specimens can be directly vitrified onto EM grids, and their relatively small thickness ensures efficient electron transmission and the acquisition of high-contrast images. Ideally, sample thickness should not exceed 200 nm.
For plunge-frozen samples, a lateral dimension of less than 10 µm is generally preferred to minimize crystalline ice formation, which can compromise structural integrity. For larger samples, high-pressure freezing or the inclusion of cryoprotectants, such as glycerol, in the buffer can delay ice nucleation23. However, to satisfy the thickness requirements for TEM, further thinning is often necessary. Among the available thinning approaches, focused ion beam (FIB) milling24is the most widely adopted due to its precision and minimal damage, producing lamellae suitable for high-resolution cryo-ET.
During lamella data collection, it is critical to maximize lamella utilization. The implementation of beam-image shift acquisition can reduce the need for repetitive focus and tracking steps, thereby increasing data collection throughput. Although not described in detail here, this technique has been extensively described in the PACEtomo methodology.
Currently, popular software options for tomographic data collection include Tomography (Thermo Fisher Scientific) and SerialEM. Tomography is a commercial solution with limited flexibility for customization, whereas SerialEM, developed by David Mastronarde at the University of Colorado Boulder, is an open-source software that supports script-based automation. However, fully exploiting SerialEM's capabilities requires a substantial learning curve. In this study, we present a streamlined workflow that leverages SerialEM's GUI, eliminating the need for scripting or Python-based configurations while enabling unattended overnight data acquisition.
A frequent challenge encountered during tomographic data acquisition using this method is inaccurate tracking, which can lead to incomplete tilt-series with missing angles or complicate subsequent alignment. To mitigate these issues, tracking parameters must be optimized based on the sample's contrast and the tilt-stage stability. Effective strategies include adjusting the exposure time at tracking positions to ensure image clarity, physically separating the tracking and focusing positions to reduce cumulative radiation damage, and reducing the tracking magnification when stage stability is poor to facilitate reliable pattern matching. Collectively, these adjustments are essential for achieving robust tracking performance across diverse experimental conditions. In this work, we use apoferritin as a model specimen. Under the premise of testing and correcting parallel light, we utilize the built-in functions of SerialEM to collect high-quality data for cryo-ET and perform subtomogram calculations on the ferritin samples, ultimately obtaining the final structure at 2.8 Å.
This method was developed to extend the applicability of 200 kV electron microscopes for high-resolution cryo-ET. Achieving such a resolution fundamentally depends on obtaining high-quality imaging data, which in turn requires precise illumination conditions. To this end, we performed accurate parallel illumination alignment as a critical preparatory step. The alignment procedure described here is specifically designed for TEMs equipped with a two-condenser lens system, such as the Thermo Fisher Scientific Talos Arctica and Glacios. Unlike instruments with a third condenser lens (C3), these systems restrict the condition for parallel illumination to a single, specific excitation value of the C2 lens. This inherent constraint necessitates exceptionally precise alignment of the electron beam to position the source image at the front focal plane of the upper objective lens-a prerequisite for optimal imaging performance. Our subsequent data processing results demonstrate that, following this alignment, the data acquisition quality achieved with this 200 kV microscope for the tested samples is nearly comparable to that typically expected from a 300 kV instrument.
The authors declare no competing interests.
We are thankful to the Cryo-EM Facility at Peking University Health Science Center for providing the instrumentation. This work was supported by the National Key Research and Development Program of China (2023YFC2705902), National Natural Science Foundation of the P. R. of China (32470880, 32500722, and 32500737), Beijing Natural Science Foundation (7262143), Key Clinical Projects of Peking University Third Hospital (BYSYZD2023033), Clinical Medicine Plus X-Young Scholars Project, Peking University (PKU2025PKULCXQ037), and National Clinical Research Center for Obstetrics and Gynecology (Peking University Third Hospital (BYSYSZKF2023019).
| ANTCryoTM niti grid | Najingdingxin | M04240922A | used for cryo-sample preparation |
| apoferritin | Biortus | BP17854-00A | used for cryo-sample preparation |
| cross-grating grid | Agar Scientific | AGS106 | used for determining the parallel light conditions |
| Glacios2 | thermo fisher | 9959084 | used for tomo data collection |
| Number 2 filter paper, 55 mm | Whatman | 10311807 | Blotting paper |
| PELCO easiGLOW | TED PELLA | 91000-01020 | used for glow discharge |
| Quantifoil Cu grid | quantifoil | N1-C14nCu30-01 | used for cryo-sample preparation |
| Vitrobot Mark IV | thermo fisher | 230101164 | used for cryo-sample preparation |