We acknowledge support from the Structural and Computational Biology Unit and the Electron Microscopy Core Facility at the European Molecular Biology Laboratory in Heidelberg, Germany and from iNEXT-Discovery (project number 871037). We are extremely grateful for the excellent support from the author of the SerialEM software package, Professor David Mastronarde. We also thank Herman Fung for the critical reading of the manuscript.

The protocol described here is part of a more comprehensive document produced by the EMBL CryoEM Service Platform that includes thorough step-by-step instructions and screenshots illustrating the entire procedure of a typical cryoET session, including sample loading, grid mapping, microscope tuning, set up of acquisition points, and automated data collection. The full protocol can be downloaded at the following link: https://oc.embl.de/index.php/s/9OuTl8AazDkCNq0/download
1. Prerequisites
<ol>
	<li>Install SerialEM version 3.8 and set up to control the microscope and detector (http://bio3d.colorado.edu/SerialEM/betaHlp/html/setting_up_serialem.htm).</li>
	<li>Install a dummy instance of SerialEMversion 3.8 (https://sphinx-emdocs.readthedocs.io/en/latest/serialEM-note-setup-dummy.html).</li>
	<li>Install PyEM (https://git.embl.de/schorb/pyem).</li>
</ol>
2. Grid mapping
<ol>
	<li>Load a cassette with grids into the microscope autoloader.</li>
	<li>Set up imaging conditions suitable for mapping the entire grid. Do this at the lowest magnification possible taking into account the field of view on the detector used (EFTEM SA 2250x). Save the imaging conditions as a SerialEM Imaging State to make things convenient for later use.</li>
	<li>Set up full montage
	<ol>
		<li>Open the SerialEM Navigator menu.</li>
		<li>Select Montaging &#38; Grids.</li>
		<li>Select Set up Full Montage.</li>
	</ol>
	</li>
	<li>Start the script Grid_Mapping. Allow the script to wait for the autoloader to cool down; do an inventory and then map each grid that the inventory procedure found. Input an email via the Tilt Series Menu to allow the script to conveniently send an email when done.</li>
	<li>Save Navigator.</li>
	<li>Inspect all grid maps from the SerialEM Navigator and choose which grid to map further at higher magnification. 
	NOTE: Many TEMs equipped with an autoloader system will show a rotation of the grid when reloaded. It&#39;s best to remap any grid after reloading it. Alternative systems usually only suffer some shifts, which can be corrected in SerialEM with a Shift To Marker procedure.</li>
</ol>
3. Set up the SerialEM low dose
<ol>
	<li>Set the magnification of SerialEM low dose View and Preview modes (this is required for step 6).</li>
	<li>Acquire a View image, and save it as a map in the Navigator.</li>
	<li>Acquire a Preview image, and save it as a map in the Navigator.
	<ol>
		<li>Set both the modes to the same binning (binning 4 is suggested). This allows saving the two maps into one image stack.</li>
		<li>In the SerialEM Navigator window, change the label of the View map to View and the label of the Preview map to Preview.</li>
		<li>Save and close the navigator file. 
		NOTE: No target is needed for the initial View and Preview images, PyEM will merely use their imaging settings.</li>
	</ol>
	</li>
</ol>
4. Grid square mapping
<ol>
	<li>Set up the imaging conditions to map grid squares. It is of great importance to be able to see the sample of interest and the fiducial bead distribution. To ensure optimal contrast for grid square maps, perform the following steps.
	<ol>
		<li>Insert an objective aperture.</li>
		<li>If applicable, insert the energy filter slit.</li>
		<li>Use a defocus of -100 &#181;m.</li>
	</ol>
	</li>
	<li>Screen for good grid squares suitable for further mapping. After visual inspection of the squares from the grid map, take test images of the square with the imaging conditions to be used for grid square maps.</li>
	<li>When a good square is identified, mark its center in the grid map image using the Add Points feature of the SerialEM Navigator.</li>
	<li>Once all the points are added, in the SerialEM Navigator press Shift + A on the first point, then press Shift + A on the last point. 
	NOTE: All added points are now marked by an A, meaning they are all Acquisition Points.</li>
	<li>Press Shift + N (create a new file at item) on the first point and then again on the last point. In the dialog that comes up, select Montaged Images.</li>
	<li>When the montage dialog pops up, set up a montage size that covers one grid square. This depends on the magnification and the mesh size of the grids used and typically requires 2 x 2 to 4 x 4 montages. Give it a name with a number (e.g., squaremap_01.mrc) to allow the SerialEM to conveniently auto-number all the files per grid square.</li>
	<li>Start the grid-mapping by opening the SerialEM Navigator menu and click on Acquire At Items.</li>
	<li>In the pop-up menu, select the following options.
	<ol>
		<li>Select Rough Eucentricity.</li>
		<li>Select Acquire Map Image.</li>
		<li>Select Close Column Valves at End.</li>
		<li>Select Send Email at End.</li>
	</ol>
	</li>
</ol>
5. Selecting the targets
<ol>
	<li>Open a dummy SerialEM instance. This can be set up on the SerialEM PC that controls the microscope or on a different (support) PC if both computers share a network connection.</li>
	<li>Once the first grid square is mapped, use the SerialEM Navigator menu option Merge to see the montage in the dummy SerialEM instance.</li>
	<li>Double click on the Navigator window to open grid square map.</li>
	<li>Search the map and use the dummy SerialEM Navigator option Add Points to add image acquisition points on the target of interest.</li>
	<li>When done and after mapping the new squares, save the Navigator file and merge the Navigator again; continue until all grid squares are mapped.</li>
</ol>
6. Generate virtual maps
<ol>
	<li>Once again, merge the navigator file with the dummy SerialEM instance.</li>
	<li>Run PyEM Virtual maps script from dummy SerialEM menu, Tools and select Virtual Anchor Maps. This may take some time depending on the size and amount of the grid square maps and the binning of the View and Preview maps. 
	NOTE: PyEM starts a command window that automatically closes when done, then the new navigator file can be opened. Per montaged map that contains selected points, PyEM writes a single merged map and all its View and Preview maps. Finally, it writes a new Navigator file called &#60;navigatorfilename&#62;_automaps.nav.</li>
</ol>
7. Microscope tuning
<ol>
	<li>Check the microscope tuning. To assure proper microscope performance, use the same magnification and beam size setup for data acquisition, in the following order.
	<ol>
		<li>Run SeriaLEM Coma-free alignment by CTF (Zemlin tableau).</li>
		<li>Insert and center an objective aperture.</li>
		<li>Run SerialEM Correct Astigmatism by CTF (auto-stigmate).</li>
		<li>Run GIF Quick Tune (i.e., only slit focus). 
		&#8203;NOTE: As steps 7.1.1, 7.1.3, and 7.1.4 might require more dose rate, only the spot size should be changed; the beam size should not be changed as this causes beam tilt, which makes the tunings incorrect. Steps 7.1.1, 7.1.2, and 7.1.3&#160;are semi-automated in this publicly available script (https://serialemscripts.nexperion.net/script/47).</li>
	</ol>
	</li>
</ol>
8. Set up Navigator
<ol>
	<li>In SerialEM, open the new navigator file named &#60;navigatorfilename&#62;_automaps.nav. 
	NOTE: V_yyyy&#160;are the View maps and P_yyyy&#160;are the Preview maps. The preview maps are set as Acquisition Points.</li>
	<li>In the SerialEM Navigator window, deselect all A points, select the first V_yyyy&#160;map, select Collapse, click on A twice, and deselect Collapse.</li>
	<li>Select the first V_yyyy position, press Shift + T, then select the very last V_yyyy position, and press Shift + T again.</li>
	<li>Choose Single Frame Images in the properties of the file to open dialog.</li>
	<li>In the next File Properties dialog, select the desired parameters according to the imaging needs and the instrument setup.</li>
	<li>When prompted, give a name with a number (e.g., TS_001.mrc) and click on Save. 
	NOTE: SerialEM will auto-number the filenames for all tilt series.</li>
	<li>Set up the tilt series controller for the first TS position. When done, click on OK to set these parameters for all tilt series after this acquisition item. All Preview maps are now selected as TS (Tilt Series) with numbered file name TS_xxx.mrc. 
	NOTE: One can change the parameters manually later using the Navigator TSparams feature; changes will be applied for all items downwards on the list. The user has the option to run a custom script instead of the tilt series.</li>
</ol>
9. Set the focus/track positions
<ol>
	<li>Set the focus/track distance for each target if needed (make sure that SerialEM Low Dose is switched on).</li>
	<li>Double click on the View Map to load it.</li>
	<li>Select the Preview Map in the Navigator list.</li>
	<li>Select Edit Focus in the Navigator window.</li>
	<li>In the Low Dose Control panel, deselect Rotate inter-area axis to position Trial and Focus along the stage tilt axis.</li>
	<li>Click on the desired region in the loaded view map to set the focus/trial position for this tilt series.</li>
	<li>Ensure that the Navigator item has TSP set now; repeat the procedure for all the items. 
	&#8203;NOTE: Focus/track positions are automatically copied downwards in the Navigator. Therefore, if the focus/track position for the previous itemis on the correct side and of the correct distance, there is no need to change it for the current item.</li>
</ol>
10. Set up additional scripts
<ol>
	<li>Two scripts handle the Focus range: pretomo and duringtomo. The pretomo script runs before each tilt series and the duringtomo script during each tilt.</li>
	<li>Edit the focus range in the script pretomo.</li>
	<li>In the SerialEM Tilt Series menu, check Run Script in TS and select the script number of the duringtomo script.</li>
</ol>
11. Run
<ol>
	<li>Check the nitrogen tank level.</li>
	<li>Check whether the Autoloader turbo off is selected.</li>
	<li>Check the data storage free space.</li>
	<li>In the SerialEM file menu, deselect continuous saving for the log file and close any currently open logfile. Each tilt series will get its own log file.</li>
	<li>In the Navigator menu, click on Acquire at Items.</li>
	<li>Run the script PreTomo.</li>
	<li>Select Primary task Acquire tilt series.</li>
	<li>Select Run script after PostTomo.</li>
	<li>Select Close column valves at end.</li>
	<li>Select Send email at end.</li>
	<li>Click on GO. 
	NOTE: SerialEM will send an email per tilt series, either successful or error; error can, however, also mean the full tilt range was not reached.</li>
</ol>

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The authors declare no conflicts of interest.

From a niche technique, cryoET has now matured into a widespread method to perform structural studies at the cellular and molecular level with unprecedented reachable resolution21,22. The ever-increasing demand for cryoEM imaging has put a strain on the limited resources available to access this technology. Despite the opening of a number of national cryoEM facilities and the efforts of scientific institutes to increase their TEM capacity to support the needs of the community worldwide, access to cryoEM instruments is still limited and the time available for data collection must therefore be efficiently used by the users to maximize the yield of each microscopy session. The need to acquire hundreds of tilt series combined with the limited time available for data collection called for novel image acquisition routines to achieve better throughput without compromising data quality. Recent developments in hardware and imaging workflows have considerably increased the speed of tilt series acquisition18,19, thus resulting in a dramatic shift of the ratio between time spent to set up an acquisition point and time needed for the actual tilt series acquisition. Altogether, the procedure for setting up acquisition points is becoming one of the major bottlenecks for the achievable throughput of cryoET sessions.
The optimized protocol presented here enabled us to set up, in off-line mode, 171 positions for automated tomographic acquisition within the first day of a cryoET session while the microscope was actively engaged in other operations (e.g., square mapping, tuning, and automated tilt series acquisition), thus without affecting the microscope time available for data collection. In addition to maximizing the throughput of a cryoET session, this pipeline drastically reduces the amount of time invested by the user in the preparatory phase of an automated data collection session. In the described protocol, the user is asked to browse the mapped grid squares to identify suitable regions of interest and add them to the Serial EM Navigator as acquisition points. All targets will then be automatically processed in batch within SerialEM by the PyEM tool for the production of the virtual maps16. The presented computational approach is therefore considerably faster than acquiring real anchoring maps by eliminating the waiting periods associated with stage movement, image acquisition, change of imaging conditions between View and Preview, and by the eventual reiteration of these steps while centering at high magnification. Additionally, as each acquired image leads to accumulation of electron dose on the object of interest23, the use of virtual maps for the precise realignment of the targets reduces the radiation damage introduced in the preparatory phase of a cryoET session before the actual tilt series acquisition. The protocol described here makes use of both intermediate and high magnification virtual maps (Preview and View, respectively) for realignment of the target before tilt series acquisition. This procedure can easily be modified to only use the intermediate magnification View image when alignment accuracy is of less importance, for instance, in the case of large structures where ultimate target accuracy is of less concern10 or for single particle analysis samples that are poorly spread on the cryo-grid requiring the user's manual selection of each acquisition point24,25. Finally, an approach based on the off-line use of a dummy SerialEM instance also facilitates the setup of acquisition points through remote connection by minimizing the need of the physical presence of the user at the microscope, thus enabling more flexibility in terms of operational organization of the facility.
The recent advances in technology and methods for cryoET have drastically improved the speed and reliability of automated data collection sessions. However, further developments are required to address the remaining rate-limiting steps of this method. Most notably, the initial step of grid and square mapping is now becoming one of the major bottlenecks of the session setup, thus generating the need for hardware improvements aimed at increasing the speed of microscope stage movements and of image acquisition by the direct electron detectors. Additionally, the development of machine learning approaches to fully automate the process of target identification will be crucial to eliminate the need of the users' visual inspection for selecting the regions of interest, a time-consuming procedure that relies on the users' expertise.

Cryogenic electron microscopy (cryoEM) methods are based on the imaging of biological samples by means of a transmission electron microscope (TEM) after their rapid vitrification, a sample preparation process that preserves the molecular and cellular structures of specimens in a close-to-native and hydrated state1,2. In cryogenic electron tomography (cryoET) a 3D model of the vitrified sample is achieved by acquiring a number of images of the same region of interest from different orientations, the so-called tilt series, followed by the computational reconstruction of the tomographic volume3. This advanced imaging technique has matured into a powerful method for the structural investigation of biological processes in the context of their native cellular environments4,5,6.
In addition to the ultrastructural analysis of the vitrified sample, high-resolution reconstructions of macromolecular complexes that are present in multiple copies within the tomographic volume can be obtained by applying subtomogram averaging5. This reconstruction approach is based on the iterative alignment and averaging of sub-volumes containing the structure of interest and it is aimed at increasing the signal-to-noise ratio and the resolution of the final reconstruction7,8. Subtomogram averaging relies on the collection and processing of a large amount of data that often demands the acquisition of hundreds of tilt series by means of high-end TEMs with onerous operational running-costs.
Currently the setup of such automated cryoET sessions is a time-consuming process that usually relies on the user&#39;s manual input9,10,11. Typically, targets are identified by visual inspection of the mapped grid and subsequently set up for automated data collection. The user&#39;s efficiency in identifying acquisition points is often affected by the nature of the sample, becoming particularly challenging when analyzing purified macromolecules with suboptimal concentration or in the case of rare events within crowded cellular environments, implying the use of correlative approaches12. Furthermore, current workflows require the acquisition of images during set-up at various magnifications that will be later used for precise localization and centering of the target during automated acquisition11,13,14. These high-precision re-alignment steps are crucial for high-resolution applications, which demand the imaging to be performed at high magnification and require accurate centering steps for retaining the region of interest within the resulting small field of view. Altogether, several hours of each data collection session are committed for this time-consuming procedure during which the TEM is not engaged in tilt series acquisition. Therefore, depending on the amount of tilt series required, the identification and set-up of acquisition points can have a considerable impact on the microscope time available for data collection during a cryoET session.
Described here is an optimized protocol based on the SerialEM software package15 and the latest version the PyEM software16 to map grids, map grid squares, select targets, and set up automated data acquisition for large-scale tilt series collection. The key concept of this approach is to provide SerialEM with computationally generated images by PyEM for each acquisition item, termed virtual maps, for the accurate localization and centering of the target. To gain actual acquisition time, the selection of the targets as well as the creation of the virtual maps are performed off-line using a second dummy instance of SerialEM, decoupling the selection process of acquisition targets from TEM operations. While not addressing how to increase the data quality13,17 or the speed of tilt series acquisition18,19, this protocol is primarily focused on strategies to optimize the time-efficiency of large-scale automated cryoET sessions setup. Therefore, the implementation of the presented protocol is meant for those scientists establishing cryoET data collection workflows that desire to maximize the yield of automated data acquisition by increasing the microscope time available for tilt series acquisition.

<table><tbody><tr><td>Transmission Electron Microscope</td><td></td><td></td><td>Our protocol is only based on computational workflows. The user will only need acess to a TEM of any kind</td></tr></tbody></table>

strategies for optimization of cryogenic electron tomography data acquisition

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current state-of-the-art cryoET combined with subtomogram averaging analysis enables the high-resolution structural determination of macromolecular complexes that are present in multiple copies within tomographic reconstructions. Tomographic experiments usually require a vast amount of tilt series to be acquired by means of high-end transmission electron microscopes with important operational running-costs. Although the throughput and reliability of automated data acquisition routines have constantly improved over the recent years, the process of selecting regions of interest at which a tilt series will be acquired cannot be easily automated and it still relies on the user's manual input. Therefore, the set-up of a large-scale data collection session is a time-consuming procedure that can considerably reduce the remaining microscope time available for tilt series acquisition. Here, the protocol describes the recently developed implementations based on the SerialEM package and the PyEM software that significantly improve the time-efficiency of grid screening and large-scale tilt series data collection. The presented protocol illustrates how to use SerialEM scripting functionalities to fully automate grid mapping, grid square mapping, and tilt series acquisition. Furthermore, the protocol describes how to use PyEM to select additional acquisition targets in off-line mode after automated data collection is initiated. To illustrate this protocol, its application in the context of high-end data collection of Sars-Cov-2 tilt series is described. The presented pipeline is particularly suited to maximizing the time-efficiency of tomography experiments that require a careful selection of acquisition targets and at the same time a large amount of tilt series to be collected.

This procedure was used to acquire the Sars-Cov-2 tilt series described in Turonova et al. 202020; the whole dataset was produced using three distinct grids over three microscopy sessions at EMBL Heidelberg. The current study will focus on and describe the first 3-day (~72 h) session run with the first grid.
After the entire grid was mapped at low magnification (~10 min, see step 2), 71 suitable squares were selected on the grid map, and medium magnification maps (square maps) were acquired with settings (magnification, exposure, defocus) that allow for the direct visualization and identification of the sample of interest, coronaviruses in this case (see step 4) (Figure 1A). The acquisition time was ~3 min per square, 3 h 45 min in total.
As soon as the first square map was created, a dummy SerialEM instance (without any control on camera or microscope) was opened on a separate computer to visualize the square map and to add points on targets suitable for tilt series acquisition (see step 5) (Figure 1B). Newly acquired square maps were retrieved by merging the current dummy SerialEM navigator with the navigator from the acquiring SerialEM instance. After ~2 h of grid square acquisition and selection, 50 initial targets could be identified.
After the square map acquisitions had finished, SerialEM low-dose was set up and reference View and Preview images were taken and saved as maps (see step 3). The latter maps could then be used immediately on the dummy SerialEM instance to generate, from the corresponding square map images, the Virtual View (Figure 1C) and Virtual Preview (Figure 1D) maps of the 50 selected targets with the PyEM software suite, for a processing time of ~30 min (see step 6). This processing time on the dummy SerialEM session was used to perform final preparations of the microscope for acquisition: energy filter tuning, new camera gain reference image acquisition, astigmatism- and coma-free alignment of the objective lens.
Once microscope tuning was completed and virtual maps from the 50 initial targets generated, the actual SerialEM navigator to be used for acquisition was set up (see step 8), focus and track positions were set (step 9), and tilt series acquisition could be started (see steps 10 and 11). The Virtual View maps (Figure 1C) were used for an initial centering of the target (Figure 1E) followed by a final centering performed at the actual tilt series acquisition magnification (Figure 1F) using the Virtual Preview map (Figure 1D).
Starting with grid mapping at 9:30 in the morning, the acquisition of the tilt series for the 50 initial targets commenced at roughly 15:00. With the settings used for tomographic acquisition (see the reference for details), a tilt series took ~20 min to acquire, with enough targets then to run through the entire night. While the acquisition was running, the rest of the square maps could be inspected and more targets added, still off-line via the dummy SerialEM instance. 121 more targets were selected among the remaining square maps and added to the acquisition SerialEM navigator after virtual maps had been created for these new targets, enough to run until completion of the 72 h session.
This procedure (summarized in Figure 2) allowed, in a single working day, the setup of 171 targets for automated tomographic acquisitions for a 72 h (3 days) microscope session.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62383/62383fig01.jpg" /> 
Figure 1: Example of square map with representative virtual maps and corresponding acquisitions after centering. (A) Representative square map of a Sars-Cov-2 cryoEM grid used in Turonova et al.20. Four regions of interest are marked with a red cross. Microscope magnification is 2,250x. (B) Crop out of the square map highlighting the areas that were used to generate the Virtual View (orange) and Virtual Preview (yellow) maps for the selected target (red cross) (C) Virtual View map. (D) Virtual Preview map. (E) Actual View acquisition after centering using the Virtual View map as a reference. Microscope magnification is 11,500x. (F) 0&#176; tilt acquisition from the tilt series after centering using the Virtual Preview map as a reference. Microscope magnification is 64,000x. <a href="https://www.jove.com/files/ftp_upload/62383/62383fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62383/62383fig02.jpg" /> 
Figure 2: CryoET session workflow using SerialEM with PyEM tools. <a href="https://www.jove.com/files/ftp_upload/62383/62383fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition at JoVE.com

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

The increasing demand for large-scale data collection in cryogenic electron tomography requires high-throughput image acquisition routines. Described here is a protocol that implements the recent developments of advanced acquisition strategies aimed at maximizing the time-efficiency and throughput of tomographic data collection.

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current ...

strategies-for-optimization-cryogenic-electron-tomography-data

Research

JoVE Journal

Biology

4.4K Views.  European Molecular Biology Laboratory. The increasing demand for large-scale data collection in cryogenic electron tomography requires high-throughput image acquisition routines. Described here is a protocol that implements the recent developments of advanced acquisition strategies aimed at maximizing the time-efficiency and throughput of tomographic data collection.

Video: Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, direct visualization of individual viral complexes in their host cellular environment with cryoET is challenging2, due to the infrequent and dynamic nature of viral entry, particularly in the case of HIV-1. While time-lapse live-cell imaging has yielded a great deal of information about many aspects of the life cycle of HIV-13-7, the resolution afforded by live-cell microscopy is limited (~ 200 nm). Our work was aimed at developing a correlation method that permits direct visualization of early events of HIV-1 infection by combining live-cell fluorescent light microscopy, cryo-fluorescent microscopy, and cryoET. In this manner, live-cell and cryo-fluorescent signals can be used to accurately guide the sampling in cryoET. Furthermore, structural information obtained from cryoET can be complemented with the dynamic functional data gained through live-cell imaging of fluorescent labeled target.
In this video article, we provide detailed methods and protocols for structural investigation of HIV-1 and host-cell interactions using 3D correlative high-speed live-cell imaging and high-resolution cryoET structural analysis. HeLa cells infected with HIV-1 particles were characterized first by confocal live-cell microscopy, and the region containing the same viral particle was then analyzed by cryo-electron tomography for 3D structural details. The correlation between two sets of imaging data, optical imaging and electron imaging, was achieved using a home-built cryo-fluorescence light microscopy stage. The approach detailed here will be valuable, not only for study of virus-host cell interactions, but also for broader applications in cell biology, such as cell signaling, membrane receptor trafficking, and many other dynamic cellular processes.

We describe a correlative microscopy method that combines high-speed 3D live-cell fluorescent light microscopy and high-resolution cryo-electron tomography. We demonstrate the capability of the correlative method by imaging dynamic, small HIV-1 particles interacting with host HeLa cells.

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, ...

Bioengineering

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

Cryo-electron tomography (Cryo-ET) is a powerful three-dimensional (3-D) imaging technique for visualizing macromolecular complexes in their native context at a molecular level. The technique involves initially preserving the sample in its native state by rapidly freezing the specimen in vitreous ice, then collecting a series of micrographs from different angles at high magnification, and finally computationally reconstructing a 3-D density map. The frozen-hydrated specimen is extremely sensitive to the electron beam and so micrographs are collected at very low electron doses to limit the radiation damage. As a result, the raw cryo-tomogram has a very low signal to noise ratio characterized by an intrinsically noisy image. To better visualize subjects of interest, conventional imaging analysis and sub-tomogram averaging in which sub-tomograms of the subject are extracted from the initial tomogram and aligned and averaged are utilized to improve both contrast and resolution. Large datasets of tilt-series are essential to understanding and resolving the complexes at different states, conditions, or mutations as well as obtaining a large enough collection of sub-tomograms for averaging and classification. Collecting and processing this data can be a major obstacle preventing further analysis. Here we describe a high-throughput cryo-ET protocol based on a computer-controlled 300kV cryo-electron microscope, a direct detection device (DDD) camera and a highly effective, semi-automated image-processing pipeline software wrapper library tomoauto developed in-house. This protocol has been effectively utilized to visualize the intact type III secretion system (T3SS) in Shigella flexneri minicells. It can be applicable to any project suitable for cryo-ET.

We present a protocol on how to utilize high-throughput cryo-electron tomography to determine high resolution in situ structures of molecular machines. The protocol permits large amounts of data to be processed, avoids common bottlenecks and reduces resource downtime, allowing the user to focus on important biological questions.

Cryo-electron tomography (Cryo-ET) is a powerful three-dimensional (3-D) imaging technique for visualizing macromolecular complexes in their native ...

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Cryo-electron microscopy (cryo-EM) has been established as a routine method for protein structure determination during the past decade, taking an ever-increasing share of published structural data. Recent advances in TEM technology and automation have boosted both the speed of data collection and quality of acquired images while simultaneously decreasing the required level of expertise for obtaining cryo-EM maps at sub-3 &#197; resolutions. While most of such high-resolution structures have been obtained using state-of-the-art 300 kV cryo-TEM systems, high-resolution structures can be also obtained with 200 kV cryo-TEM systems, especially when equipped with an energy filter. Additionally, automation of microscope alignments and data collection with real-time image quality assessment reduces system complexity and assures optimal microscope settings, resulting in increased yield of high-quality images and overall throughput of data collection. This protocol demonstrates the implementation of recent technological advances and automation features on a 200 kV cryo-transmission electron microscope and shows how to collect data for the reconstruction of 3D maps that are sufficient for de novo atomic model building. We focus on best practices, critical variables, and common issues that must be considered to enable the routine collection of such high-resolution cryo-EM datasets. Particularly the following essential topics are reviewed in detail: i) automation of microscope alignments, ii) selection of suitable areas for data acquisition, iii) optimal optical parameters for high-quality, high-throughput data collection, iv) energy filter tuning for zero-loss imaging, and v) data management and quality assessment. Application of the best practices and improvement of achievable resolution using an energy filter will be demonstrated on the example of apo-ferritin that was reconstructed to 1.6 &#197;, and Thermoplasma acidophilum 20S proteasome reconstructed to 2.1-&#197; resolution using a 200 kV TEM equipped with an energy filter and a direct electron detector.

High-resolution cryo-EM maps of macromolecules can be also achieved by using 200 kV TEM microscopes. This protocol shows the best practices for setting accurate optics alignments, data acquisition schemes, and selection of imaging areas that are all essential for the successful collection of high-resolution datasets using a 200 kV TEM.

Cryo-electron microscopy (cryo-EM) has been established as a routine method for protein structure determination during the past decade, taking an ...

Biochemistry

Preparation of Electron Microscopy Grids for In Situ Cellular Cryotomography

Sample Preparation for In Situ Cryotomography of Mammalian Cells

In situ cellular cryotomography is a powerful technique for studying complex objects in their native frozen-hydrated cellular context, making it highly relevant to cellular biology and virology. The potential of combining cryotomography with other microscopy modalities makes it a perfect technique for integrative and correlative imaging. However, sample preparation for in situ cellular tomography is not straightforward, as cells do not readily attach and stretch over the electron microscopy grid. Additionally, the grids themselves are fragile and can break if handled too forcefully, resulting in the loss of imageable areas. The geometry of tissue culture dishes can also pose a challenge when manipulating the grids with tweezers. Here, we describe the tips and tricks to overcome these (and other) challenges and prepare good-quality samples for in situ cellular cryotomography and correlative imaging of adherent mammalian cells. With continued advances in cryomicroscopy technology, this technique holds enormous promise for advancing our understanding of complex biological systems.

Author Spotlight: Optimizing Grid Preparation for Enhanced Cryoelectron Tomography 

This method provides an accessible and flexible protocol for the preparation of electron microscopy (EM) grids for in situ cellular cryotomography and correlative light and electron microscopy (CLEM).

In situ cellular cryotomography is a powerful technique for studying complex objects in their native frozen-hydrated cellular context, making it highly ...

Optimizing Sample Preparation for Cryogenic Electron Microscopy

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology by enabling the study of macromolecular structures in near-native conditions, suspended in vitreous ice. This technique allows for the high-resolution visualization of proteins and other biomolecules without the need for crystallization, offering significant insights into their function and mechanism. Recent advancements in single-particle analysis, coupled with improved computational data processing, have made cryo-EM an indispensable tool in modern structural biology. Despite its growing adoption, cryo-EM faces persistent challenges that can limit its effectiveness, particularly uneven particle distribution. This issue often leads to poor resolution and reduced accuracy in reconstructed protein structures. This article outlines a simple, practical approach to address this challenge, using the small heat-shock protein from Methanocaldococcus jannaschii (MjsHSP16.5) as an example. The method optimizes sample preparation to minimize preferential adsorption, ensuring more homogeneous particle distribution and higher-quality protein cryo-EM structures. This technique offers valuable guidance for researchers aiming to overcome similar challenges in structural studies.

This protocol presents a practical method using Methanocaldococcus jannaschii (MjsHSP16.5) as an example to address uneven particle distribution through sample preparation optimization, providing a reference for researchers to efficiently elucidate macromolecular structures using cryogenic electron microscopy (cryo-EM).

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology by enabling the study of macromolecular structures in near-native ...

User-friendly, High-throughput, and Fully Automated Data Acquisition Software for Single-particle Cryo-electron Microscopy

In the past several years, technological and methodological advancements in single-particle cryo-electron microscopy (cryo-EM) have paved a new avenue for the high-resolution structure determination of biological macromolecules. Despite the remarkable advances in cryo-EM, there is still scope for improvement in various aspects of the single-particle analysis workflow. Single-particle analysis demands a suitable software package for high-throughput automatic data acquisition. Several automatic data acquisition software packages were developed for automatic imaging for single-particle cryo-EM in the last eight years. This paper presents an application of a fully automated image acquisition pipeline for vitrified biomolecules under low-dose conditions. 
It demonstrates a software package, which can collect cryo-EM data fully, automatically, and precisely. Additionally, various microscopic parameters are easily controlled by this software package. This protocol demonstrates the potential of this software package in automated imaging of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) spike protein with a 200 keV cryo-electron microscope equipped with a direct electron detector (DED). Around 3,000 cryo-EM movie images were acquired in a single session (48 h) of data collection, yielding an atomic-resolution structure of the spike protein of SARS-CoV-2. Furthermore, this structural study indicates that the spike protein adopts two major conformations, 1-RBD (receptor-binding domain) up open and all RBD down closed conformations.

Single-particle cryo-electron microscopy demands a suitable software package and user-friendly pipeline for high-throughput automatic data acquisition. Here, we present the application of a fully automated image acquisition software package, Latitude-S, and a practical pipeline for data collection of vitrified biomolecules under low-dose conditions.

In the past several years, technological and methodological advancements in single-particle cryo-electron microscopy (cryo-EM) have paved a new avenue for ...

Immunology and Infection

Do's and Don'ts of Cryo-electron Microscopy: A Primer on Sample Preparation and High Quality Data Collection for Macromolecular 3D Reconstruction

Cryo-electron microscopy (cryoEM) entails flash-freezing a thin layer of sample on a support, and then visualizing the sample in its frozen hydrated state by transmission electron microscopy (TEM). This can be achieved with very low quantity of protein and in the buffer of choice, without the use of any stain, which is very useful to determine structure-function correlations of macromolecules. When combined with single-particle image processing, the technique has found widespread usefulness for 3D structural determination of purified macromolecules. 
The protocol presented here explains how to perform cryoEM and examines the causes of most commonly encountered problems for rational troubleshooting; following all these steps should lead to acquisition of high quality cryoEM images. The technique requires access to the electron microscope instrument and to a vitrification device. Knowledge of the 3D reconstruction concepts and software is also needed for computerized image processing. Importantly, high quality results depend on finding the right purification conditions leading to a uniform population of structurally intact macromolecules. 
The ability of cryoEM to visualize macromolecules combined with the versatility of single particle image processing has proven very successful for structural determination of large proteins and macromolecular machines in their near-native state, identification of their multiple components by 3D difference mapping, and creation of pseudo-atomic structures by docking of x-ray structures. The relentless development of cryoEM instrumentation and image processing techniques for the last 30 years has resulted in the possibility to generate de novo 3D reconstructions at atomic resolution level.

This paper describes the cryo-electron microscopy methodology, which is used to obtain high quality microscopic images of macromolecules in their near-native state. The method yields images suitable for further computerized processing using the single particle approach, devised to generate the 3D reconstruction of a macromolecule.

Cryo-electron microscopy (cryoEM) entails flash-freezing a thin layer of sample on a support, and then visualizing the sample in its frozen hydrated state ...

Visualization of DNA Compaction in Cyanobacteria by High-voltage Cryo-electron Tomography

This protocol describes how to visualize the transient DNA compaction in cyanobacteria. DNA compaction is a dramatic cytoplasmic event recently found to occur in some cyanobacteria before cell division. However, due to the large cell size and the transient character, it is difficult to investigate the structure in detail. To overcome the difficulties, first, DNA compaction is reproducibly produced in the cyanobacterium Synechococcus elongatus PCC 7942 by synchronous culture using 12 h each light/dark cycle. Second, DNA compaction is monitored by fluorescence microscopy and captured by rapid freezing. Third, the detailed structure of DNA compacted cells is visualized in three dimensions (3D) by high voltage cryo-electron tomography. This set of methods is widely applicable to investigate transient structures in bacteria, e.g. cell division, chromosome segregation, phage infection etc., which are monitored by fluorescence microscopy and directly visualized by cryo-electron tomography at appropriate time points.

This protocol describes how to visualize the transient DNA compaction in cyanobacteria. Synchronous cultivation, monitoring by fluorescence microscopy, rapid freezing, and high voltage cryo-electron tomography are used. A protocol for these methodologies is presented, and future applications and developments are discussed.

This protocol describes how to visualize the transient DNA compaction in cyanobacteria. DNA compaction is a dramatic cytoplasmic event recently found to ...

Sample Preparation by 3D-Correlative Focused Ion Beam Milling for High-Resolution Cryo-Electron Tomography

Cryo-electron tomography (cryo-ET) has become the method of choice for investigating cellular ultrastructure and molecular complexes in their native, frozen-hydrated state. However, cryo-ET requires that samples are thin enough to not scatter or block the incident electron beam. For thick cellular samples, this can be achieved by cryo-focused ion beam (FIB) milling. This protocol describes how to target specific cellular sites during FIB milling using a 3D-correlative approach, which combines three-dimensional fluorescence microscopy data with information from the FIB-scanning electron microscope. Using this technique, rare cellular events and structures can be targeted with high accuracy and visualized at molecular resolution using cryo-transmission electron microscopy (cryo-TEM).

Here, we present a pipeline for 3D-correlative focused ion beam milling on guiding the preparation of cellular samples for cryo-electron tomography. The 3D position of fluorescently tagged proteins of interest is first determined by cryo-fluorescence microscopy, and then targeted for milling. The protocol is suitable for mammalian, yeast, and bacterial cells.

Cryo-electron tomography (cryo-ET) has become the method of choice for investigating cellular ultrastructure and molecular complexes in their native, ...

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved automated acquisition strategies, preparative techniques that expand the possibilities of what the electron microscope can image at high-resolution using cryo-ET and new subtomogram averaging software. Additionally, data acquisition has become increasingly streamlined, making it more accessible to many users. The SARS-CoV-2 pandemic has further accelerated remote cryo-electron microscopy (cryo-EM) data collection, especially for single-particle cryo-EM, in many facilities globally, providing uninterrupted user access to state-of-the-art instruments during the pandemic. With the recent advances in Tomo5 (software for 3D electron tomography), remote cryo-ET data collection has become robust and easy to handle from anywhere in the world. This article aims to provide a detailed walk-through, starting from the data collection setup in the tomography software for the process of a (remote) cryo-ET data collection session with detailed troubleshooting. The (remote) data collection protocol is further complemented with the workflow for structure determination at near-atomic resolution by subtomogram averaging with emClarity, using apoferritin as an example.

The present protocol describes high-resolution cryo-electron tomography remote data acquisition using Tomo5 and subsequent data processing and subtomogram averaging using emClarity. Apoferritin is used as an example to illustrate detailed step-by-step processes to achieve a cryo-ET structure at 2.86 &#197; resolution.

Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved ...