We thank Bill Anderson, Charles Bowman, and Jean-Christophe Ducom (TSRI) for help with microscopy, Leginon installations, and data transfer infrastructure. We also thank Gordon Louie (Salk Institute) and Yong Zi Tan (National University of Singapore) for the critical reading of the manuscript. We thank Chris Russo (MRC Laboratory of Molecular Biology, Cambridge) for providing us with the plasmid for expression of DPS.&#160;This work was supported by grants from the US National Institutes of Health (U54AI150472,&#160;U54 AI170855, and R01AI136680 to DL), the National Science Foundation (NSF MCB-2048095 to DL), the Hearst Foundations (to DL), and Arthur and Julie Woodrow Chair (to J. P. N.). T.S. is supported by an F32 postdoctoral fellowship from the National Institutes of Health (GM148049).

1. Sample preparation
<ol>
	<li>Use grids containing gold foil and gold grid support16 (see Table of Materials) because tilted data collection can accentuate beam-induced motion17. 
	NOTE: For the present study, samples on grids were vitrified using the manual plunging and blotting technique18 in a humidified (greater than 80%) cold room (~4 &#176;C).</li>
	<li>Avoid using grids containing copper support and carbon foil or a continuous layer of amorphous carbon unless absolutely necessary, as these grids may lead to greater beam-induced motion16 when the specimen stage is tilted. 
	NOTE: Alternative support layers, such as graphene/graphene oxide, appear to reduce beam-induced movement compared to amorphous carbon19,20.</li>
	<li>Pre-screen grids and identify regions characterized by acceptable ice thickness and particle distribution. Grids containing too tightly packed particles will lead to particle overlap during tilted data collection, which may affect downstream data-processing steps. 
	NOTE: These steps are subjective since identifying good areas of ice is performed by visually inspecting defocused images for regions where particle contrast is clear. This may not be feasible for all samples since some samples will not distribute efficiently in areas of thin ice, leading to challenges during data collection (described in the Discussion section).</li>
	<li>Vitrify the grids containing your protein sample. Here, for demonstration purposes, we use DNA Protection during Starvation (DPS) protein (see Table of Materials) at a range from 0.1-0.5 mg/mL with gold foil and gold support grids. 
	&#8203;NOTE: The protein was purified as described previously, except no TEV protease cleavage was performed21. The protein concentration range for a sample of interest will have to be optimized individually, since it is hard to gauge an ideal range that is universally applicable and will almost certainly vary between different samples.</li>
</ol>
2. Setting up tilted data collection
<ol>
	<li>Align the microscope to ensure parallel illumination of the specimen and minimize coma aberrations22. 
	NOTE: The microscope must be well aligned for standard SPA data collection without stage tilt. No special alignments are necessary for tilted data collection, but a good alignment will ensure that targeting and imaging proceed smoothly. A general scheme comparing tilted and untilted data collection is provided in Figure 2.</li>
	<li>Record a grid atlas without stage tilt to identify squares suitable for data collection or manually inspect squares at the magnification used in Square Acquisition Node. Look for squares where the foil is intact, does not look dehydrated, and has ideal ice thickness. 
	NOTE: Square Acquisition Node is the low-magnification node used for multi-scale imaging in Leginon.
	<ol>
		<li>For typical untilted automated data collection, record a grid atlas, which provides an overview of the overall grid quality and an initial indication of suitable areas for data collection.</li>
		<li>Subsequently, select suitable squares through the atlas and submit them to the queue. Then, either through manual selection of holes or through the automated EM hole finder, queue and submit the hole targets.</li>
		<li>Finally, use the automated EM hole finder for submitting high magnification exposure targets. 
		NOTE: For tilted data collection, squares may need to be queued manually for consistent results, especially if the optimal tilt angle has not been pre-determined and is likely to be adjusted during data collection. The grid atlas could also be recorded using a pre-defined stage tilt if the tilt angle used for data collection had previously been established.</li>
	</ol>
	</li>
	<li>Move the specimen stage to a square of interest.</li>
	<li>Determine the eucentric height for the stage position using &#945;-wobbler at &#177; 15&#176; stage tilt. Adjust the Z-height to bring the stage to eucentric height using the keypad panel for the microscope. Ensure the image shift is minimal during the &#945;-wobble routine. 
	NOTE: If the eucentric height is not properly identified, a large image shift will be observed upon tilting the stage at the square magnification. This can also happen if there are local deformations on the grid, for example, if the grid is broken or severely bent in the vicinity of the imaged area. Although it is best to avoid such regions for data collection, it is imperative to accurately estimate eucentric height if these represent one of the few promising regions for data collection. Figure 3 shows how targeting without properly identifying eucentric height can cause large image shifts in the square magnification.</li>
	<li>Find a more accurate Z-height, use the Focuser node, and press Simulate.
	<ol>
		<li>Typically, estimate the Z-height in the Focuser node at the magnification used in Square Acquisition Node. 
		NOTE: The Focuser node focus sequence can also include a fine Z focus estimation at the Hole Acquisition node (a tool in Leginon software) magnification during data collection.</li>
		<li>Adjust the settings for the Focuser node and enable/disable the fine Z focus option during the initial queuing of squares. 
		NOTE: It is important to ensure that eucentric height is accurately identified when automated data collection begins, which may require re-enabling fine Z focus (step 2.10).</li>
	</ol>
	</li>
	<li>Tilt the specimen stage to the desired tilt angle for data collection at the true eucentric height, and re-center the stage if necessary. 0&#176;, 30&#176;, and 60&#176; tilt angles were used for this study. Press Simulate in the Square Acquisition node to begin queuing targets for Hole Acquisition node exposures. 
	NOTE: As indicated in step 2.2.1, the grid atlas can be recorded using a pre-defined stage tilt, which would obviate the need to tilt the stage again at this step. This works well and speeds up the process if the tilt angle used for data collection is pre-defined. The current protocol is written with new specimens in mind, wherein the user may wish to test different tilt angles for data collection.</li>
	<li>Select a Z focus target and regions with holes suitable for high magnification exposures.</li>
	<li>Press Submit targets to queue for imaging. Do not press Submit Queued Targets until finished queuing up all squares.</li>
	<li>Bring the specimen stage back to its untilted state. Move to the next square and repeat steps 2.3-2.8 until an adequate number of hole exposures have been queued.</li>
	<li>Go to the Hole Targeting Node and press Submit Queued Targets once all squares are queued. 
	NOTE: If fine Z focus was disabled previously to save time (step 2.5), it needs to be re-enabled before submitting the queue.</li>
	<li>Manually inspect targets selected by the high magnification Exposure Acquisition node to test if the automated EM hole finder can accurately identify suitable regions for image acquisition when the specimen stage is tilted.
	<ol>
		<li>During this procedure, select &#39;Allow for user verification of selected targets&#39; in Exposure Acquisition node settings. Once the user is satisfied with targeting accuracy, deselect this option for automated data collection. 
		&#8203;NOTE: Targets in high magnification Exposure Acquisition node are typically imaged using a beam-tilt image shift strategy, which works equally well for both tilted and untilted data collection23,24,25,26. For accurate CTF estimation in downstream data processing steps, the lens-coma aberration calibration must be performed for the beam-tilt image shift data collection strategy.</li>
	</ol>
	</li>
</ol>
3. Data Processing
<ol>
	<li>Initiate on-the-fly data processing10,27,28,29 with motion-correction of recordedmovies, CTF estimation, particle selection, and generation of initial reconstructions during data collection. 
	NOTE: For the present study, cryoSPARC Live10 (see Table of Materials) has been utilized for pre-processing. On-the-fly data processing provides an initial cryo-EM reconstruction and an approximation for the angular distribution, which can inform the user about the extent of resolution anisotropy. These can, in turn, be used to guide the user as to whether or not the tilt angle used for data collection is sufficiently high.</li>
	<li>Visualize the reconstructed map and plot the Euler angle distribution to gauge the extent of preferred particle orientations. 
	NOTE: The Euler angle distributions can be converted directly into Fourier space sampling distributions to determine the potential extent of resolution anisotropy. A graphical user interface (GUI) has been developed to assist the user in evaluating the quality of an Euler angle distribution and determining an optimal tilt angle30,31. The tool can be obtained from the Github repository, https://github.com/LyumkisLab/SamplingGui.</li>
	<li>If necessary, adjust the stage tilt angle at which data is collected to overcome the effects of preferential orientation. The angle can be increased if the preferential orientation remains a problem, as evidenced by the map and Euler distribution in 3.2. Alternatively, the user may wish to split the data collection into groups and record using several different tilt angles, such as 20&#176;, 30&#176;, and 40&#176;. 
	NOTE: Although most TEMs must have the capability of tilting the stage to 70&#176;, common specimen stage tilts (that we have used) range from 20&#176;-40&#176;.</li>
</ol>

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The authors have nothing to disclose.

Preferred particle orientation caused by specimen adherence to the air-water interface is one of the last major bottlenecks to routine high-resolution structure determination using cryo-EM SPA4,5,6. The data collection scheme presented here provides an easy-to-implement strategy for improving the orientation distribution of particles within a dataset. We note that the protocol requires no additional equipment or software and doe...

The advent of direct electron detectors over the past decade1,2,3 has spurred an exponential increase in the number of high-resolution structures of macromolecules and macromolecular assemblies solved using single-particle cryo-EM4,5,6. Almost all purified macromolecular species are expected to be amenable to structure determination using cryo-EM, except for the smallest proteins ~10 kDa in size or below7. The amount of starting material needed for grid preparation and structure determination is at least an order of magnitude less than other structure determination techniques, such as nuclear magnetic resonance spectroscopy and X-ray crystallography4,5,6.
However, a principal challenge for structure determination by cryo-EM involves suitable grid preparation for imaging. An extensive study evaluating diverse samples using different vitrification strategies and grids suggested that most approaches for vitrifying samples on cryo-EM grids lead to preferential adherence of macromolecules to the air-water interface8. Such adherence can potentially cause four suboptimal outcomes: (1) the macromolecular sample completely denatures, in which case no successful data collection and processing is possible; (2) the sample partially denatures, in which case it may be possible to obtain structural insights from regions of the macromolecule that are not damaged; (3) the sample retains native structure, but only one set of particle orientations relative to the direction of the electron beam are represented in the images; (4) the sample retains native structure, and some but not all possible particle orientations relative to the direction of the electron beam are represented in the images. For cases (3) and (4), tilted data collection will help with minimizing directional resolution anisotropy affecting the reconstructed cryo-EM map and provides a generalizable solution for a wide variety of samples9. Technically, tilting can also benefit case (2), since the denaturation presumably occurs at the air-water interface and similarly limits the number of distinct orientations represented within the data. The extent of orientation bias in the dataset can potentially be altered by experimenting with solution additives, but a lack of broad applicability hampers these trial-and-error approaches. Tilting the specimen stage at a single optimized tilt angle is sufficient to improve the distribution of orientations by virtue of altering the geometry of the imaging experiment9 (Figure 1). Due to the geometric configuration of the preferentially-oriented sample with respect to the electron beam, for each cluster of preferential orientations, tilting the grid generates a cone of illumination angles with respect to the cluster centroid. Hence, this spreads out the views and consequently improves Fourier space sampling and the isotropy of directional resolution.
There are, in practice, some detriments to tilting the stage. Tilting the specimen stage introduces a focus gradient across the field of view, which may affect the accuracy of contrast transfer function (CTF) estimations. Tilted data collection may also lead to increased beam-induced particle movement caused by increased charging effects when imaging tilted specimens. Grid tilting also leads to an increase in apparent ice thickness, which in turn leads to noisier micrographs and may ultimately impact the resolution of reconstructions5,9,10. It may be possible to overcome these issues by applying advanced computational data-processing schemes that are briefly described in the protocol and discussion sections. Lastly, tilting can lead to increased particle overlap, hindering the subsequent image processing pipeline. Although this can be mitigated to some extent by optimizing on-grid particle concentration, it is nonetheless an important consideration. Here, a simple-to-implement protocol is described for tilted data collection using the Leginon software suite (an automated image acquisition software), available open access and compatible with a broad range of microscopes11,12,13,14. The method requires at least version 3.0 or higher, with versions 3.3 onward containing dedicated improvements to enable tilted data collection. No additional software or equipment is necessary for this protocol. Extensive instructions on computational infrastructure and installation guides are provided elsewhere15.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Cryosparc Live v3.1.0+210216</td>
			<td>Structura Biotechnology</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DPS protein</td>
			<td></td>
			<td></td>
			<td>Purification adapted from protocol described in K.Naydenova et al IUCrJ. 2019 Nov 1; 6(Pt 6): 1086&#8211;1098.</td>
		</tr>
		<tr>
			<td>K2 Summit Direct Electron Detector</td>
			<td>Gatan</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Leginon software suite</td>
			<td></td>
			<td></td>
			<td>C Suloway et al Journal of Structural Biology 151 (1): pp. 41-60.</td>
		</tr>
		<tr>
			<td>Manual plunging device</td>
			<td></td>
			<td></td>
			<td>Homemade guillotine-like device for vitrification of EM grids</td>
		</tr>
		<tr>
			<td>Talos Arctica</td>
			<td>FEI/Thermo Fisher</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>UltrAufoil R1.2/1.3 300 mesh grids</td>
			<td>Quantifoil</td>
			<td>N1-A14nAu30-01</td>
			<td></td>
		</tr>
	</tbody>
</table>

single-particle cryo-em data collection with stage tilt using leginon

Single-particle analysis (SPA) by cryo-electron microscopy (cryo-EM) is now a mainstream technique for high-resolution structural biology. Structure determination by SPA relies upon obtaining multiple distinct views of a macromolecular object vitrified within a thin layer of ice. Ideally, a collection of uniformly distributed random projection orientations would amount to all possible views of the object, giving rise to reconstructions characterized by isotropic directional resolution. However, in reality, many samples suffer from preferentially oriented particles adhering to the air-water interface. This leads to non-uniform angular orientation distributions in the dataset and inhomogeneous Fourier-space sampling in the reconstruction, translating into maps characterized by anisotropic resolution. Tilting the specimen stage provides a generalizable solution to overcoming resolution anisotropy by virtue of improving the uniformity of orientation distributions, and thus the isotropy of Fourier space sampling. The present protocol describes a tilted-stage automated data collection strategy using Leginon, a software for automated image acquisition. The procedure is simple to implement, does not require any additional equipment or software, and is compatible with most standard transmission electron microscopes (TEMs) used for imaging biological macromolecules.

DPS at 0.3 mg/mL was used to demonstrate imaging at 0&#176;, 30&#176;, and 60&#176; tilts. Data from different tilt angles were collected on the same grid at different grid regions. CTF resolution fits for higher angle tilts tend to be poorer, as was the case when comparing the three datasets in this study. Figure 4 demonstrates comparative representative images and 2D classification averages. Although the protein concentration is unchanged across the different tilt angles, a higher tilt ang...

Watch this Scientific Journal Video about Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon at JoVE.com

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

The present protocol describes a generalized and easy-to-implement scheme for tilted single-particle data collection in cryo-EM experiments. Such a procedure is especially useful for obtaining a high-quality EM map for samples suffering from preferential orientation bias due to adherence to the air-water interface.

Single-particle analysis (SPA) by cryo-electron microscopy (cryo-EM) is now a mainstream technique for high-resolution structural biology. Structure ...

single-particle-cryo-em-data-collection-with-stage-tilt-using-leginon

Research

JoVE Journal

Biochemistry

2.2K Views.  The Salk Institute for Biological Studies. The present protocol describes a generalized and easy-to-implement scheme for tilted single-particle data collection in cryo-EM experiments. Such a procedure is especially useful for obtaining a high-quality EM map for samples suffering from preferential orientation bias due to adherence to the air-water interface.

Video: Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

SPHIRE (SPARX for High-Resolution Electron Microscopy) is a novel open-source, user-friendly software suite for the semi-automated processing of single particle electron cryo-microscopy (cryo-EM) data. The protocol presented here describes in detail how to obtain a near-atomic resolution structure starting from cryo-EM micrograph movies by guiding users through all steps of the single particle structure determination pipeline. These steps are controlled from the new SPHIRE graphical user interface and require minimum user intervention. Using this protocol, a 3.5 &#197; structure of TcdA1, a Tc toxin complex from Photorhabdus luminescens, was derived from only 9500 single particles. This streamlined approach will help novice users without extensive processing experience and a priori structural information, to obtain noise-free and unbiased atomic models of their purified macromolecular complexes in their native state.

This paper presents a protocol for processing cryo-EM images using the software suite SPHIRE. The present protocol can be applied for nearly all single particle EM projects that target near-atomic resolution.

SPHIRE (SPARX for High-Resolution Electron Microscopy) is a novel open-source, user-friendly software suite for the semi-automated processing of single ...

Fixed Target Serial Data Collection at Diamond Light Source

Serial data collection is a relatively new technique for synchrotron users. A user manual for fixed target data collection at I24, Diamond Light Source is presented with detailed step-by-step instructions, figures, and videos for smooth data collection.

We present a comprehensive guide to fixed target sample preparation, data collection, and data processing for serial synchrotron crystallography at Diamond beamline I24.

Serial data collection is a relatively new technique for synchrotron users. A user manual for fixed target data collection at I24, Diamond Light Source is ...

Cryo-EM and Single-Particle Analysis with Scipion

Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at near-atomic resolution. In single-particle analysis, the vitrified sample is imaged by an electron beam and the detectors at the end of the microscope column produce movies of that sample. These movies contain thousands of images of identical particles in random orientations. The data need to go through an image processing workflow with multiple steps to obtain the final 3D reconstructed volume. The goal of the image processing workflow is to identify the acquisition parameters to be able to reconstruct the specimen under study. Scipion provides all the tools to create this workflow using several image processing packages in an integrative framework, also allowing the traceability of the results. In this article the whole image processing workflow in Scipion is presented and discussed with data coming from a real test case, giving all the details necessary to go from the movies obtained by the microscope to a high resolution final 3D reconstruction. Also, the power of using consensus tools that allow combining methods, and confirming results along every step of the workflow, improving the accuracy of the obtained results, is discussed.

Single-particle analysis in cryo-electron microscopy is one of the main techniques used to determine the structure of biological ensembles at high resolution. Scipion provides the tools to create the whole pipeline to process the information acquired by the microscope and achieve a 3D reconstruction of the biological specimen.

Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at ...

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Cryo-electron microscopy (cryoEM) is a powerful technique for structure determination of macromolecular complexes, via single particle analysis (SPA). The overall process involves i) vitrifying the specimen in a thin film supported on a cryoEM grid; ii) screening the specimen to assess particle distribution and ice quality; iii) if the grid is suitable, collecting a single particle dataset for analysis; and iv) image processing to yield an EM density map. In this protocol, an overview for each of these steps is provided, with a focus on the variables which a user can modify during the workflow and the troubleshooting of common issues. With remote microscope operation becoming standard in many facilities, variations on imaging protocols to assist users in efficient operation and imaging when physical access to the microscope is limited will be described.

Structure determination of macromolecular complexes using cryoEM has become routine for certain classes of proteins and complexes. Here, this pipeline is summarized (sample preparation, screening, data acquisition and processing) and readers are directed towards further detailed resources and variables that may be altered in the case of more challenging specimens.

Cryo-electron microscopy (cryoEM) is a powerful technique for structure determination of macromolecular complexes, via single particle analysis (SPA). The ...

Preparation of High-Temperature Sample Grids for Cryo-EM

The sample grids for cryo-electron microscopy (cryo-EM) experiments are usually prepared at a temperature optimal for the storage of biological samples, mostly at 4 &#176;C and occasionally at room temperature. Recently, we discovered that the protein structure solved at low temperature may not be functionally relevant, particularly for proteins from thermophilic archaea. A procedure was developed to prepare protein samples at higher temperatures (up to 70 &#176;C) for cryo-EM analysis. We showed that the structures from samples prepared at higher temperatures are functionally relevant and temperature dependent. Here we describe a detailed protocol for preparing sample grids at high temperature, using 55 &#176;C as an example. The experiment made use of a vitrification apparatus modified using an additional centrifuge tube, and samples were incubated at 55 &#176;C. The detailed procedures were fine-tuned to minimize vapor condensation and obtain a thin layer of ice on the grid. Examples of successful and unsuccessful experiments are provided.

This paper provides a detailed protocol for preparing sample grids at temperatures as high as 70 &#176;C, prior to plunge freezing for cryo-EM experiments.

The sample grids for cryo-electron microscopy (cryo-EM) experiments are usually prepared at a temperature optimal for the storage of biological samples, ...

A Robust Single-Particle Cryo-Electron Microscopy (cryo-EM) Processing Workflow with cryoSPARC, RELION, and Scipion

Recent advances in both instrumentation and image processing software have made single-particle cryo-electron microscopy (cryo-EM) the preferred method for structural biologists to determine high-resolution structures of a wide variety of macromolecules. Multiple software suites are available to new and expert users for image processing and structure calculation, which streamline the same basic workflow: movies acquired by the microscope detectors undergo correction for beam-induced motion and contrast transfer function (CTF) estimation. Next, particle images are selected and extracted from averaged movie frames for iterative 2D and 3D classification, followed by 3D reconstruction, refinement, and validation. Because various software packages employ different algorithms and require varying levels of expertise to operate, the 3D maps they generate often differ in quality and resolution. Thus, users regularly transfer data between a variety of programs for optimal results. This paper provides a guide for users to navigate a workflow across the popular software packages: cryoSPARC v3, RELION-3, and Scipion 3 to obtain a near-atomic resolution structure of the adeno-associated virus (AAV). We first detail an image processing pipeline with cryoSPARC v3, as its efficient algorithms and easy-to-use GUI allow users to quickly arrive at a 3D map. In the next step, we use PyEM and in-house scripts to convert and transfer particle coordinates from the best quality 3D reconstruction obtained in cryoSPARC v3 to RELION-3 and Scipion 3 and recalculate 3D maps. Finally, we outline steps for further refinement and validation of the resultant structures by integrating algorithms from RELION-3 and Scipion 3. In this article, we describe how to effectively utilize three processing platforms to create a single and robust workflow applicable to a variety of data sets for high-resolution structure determination.

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

This article describes how to effectively utilize three cryo-EM processing platforms, i.e., cryoSPARC v3, RELION-3, and Scipion 3, to create a single and robust workflow applicable to a variety of single-particle data sets for high-resolution structure determination.

Recent advances in both instrumentation and image processing software have made single-particle cryo-electron microscopy (cryo-EM) the preferred method ...

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 ...

The Peel-Blot Technique: A Cryo-EM Sample Preparation Method to Separate Single Layers From Multi-Layered or Concentrated Biological Samples

The peel-blot cryo-EM grid preparation technique is a significantly modified back-injection method with the objective of achieving a reduction in layers of multi-layered samples. This removal of layers prior to plunge freezing can aid in reducing sample thickness to a level suitable for cryo-EM data collection, improving sample flatness, and facilitating image processing. The peel-blot technique allows for the separation of multilamellar membranes into single layers, of layered 2D crystals into individual crystals, and of stacked, sheet-like structures of soluble proteins to likewise be separated into single layers. The high sample thickness of these types of samples frequently poses insurmountable problems for cryo-EM data collection and cryo-EM image processing, especially when the microscope stage must be tilted for data collection. Furthermore, grids of high concentrations of any of these samples can be prepared for efficient data collection since sample concentration prior to grid preparation can be increased and the peel-blot technique adjusted to result in a dense distribution of single-layered specimen.

The peel-blot technique is a cryo-EM grid preparation method that allows for the separation of multilayered and concentrated biological samples into single layers to reduce thickness, increase sample concentration, and facilitate image processing.

The peel-blot cryo-EM grid preparation technique is a significantly modified back-injection method with the objective of achieving a reduction in layers ...

Accelerating Macromolecular Structural Analysis Using Smart Leginon Autoscreen

Cryo-Electron Microscopy Screening Automation Across Multiple Grids Using Smart Leginon

Advancements in cryo-electron microscopy (cryoEM) techniques over the past decade have allowed structural biologists to routinely resolve macromolecular protein complexes to near-atomic resolution. The general workflow of the entire cryoEM pipeline involves iterating between sample preparation, cryoEM grid preparation, and sample/grid screening before moving on to high-resolution data collection. Iterating between sample/grid preparation and screening is typically a major bottleneck for researchers, as every iterative experiment must optimize for sample concentration, buffer conditions, grid material, grid hole size, ice thickness, and protein particle behavior in the ice, amongst other variables. Furthermore, once these variables are satisfactorily determined, grids prepared under identical conditions vary widely in whether they are ready for data collection, so additional screening sessions prior to selecting optimal grids for high-resolution data collection are recommended. This sample/grid preparation and screening process often consumes several dozen grids and days of operator time at the microscope. Furthermore, the screening process is limited to operator/microscope availability and microscope accessibility. Here, we demonstrate how to use Leginon and Smart Leginon Autoscreen to automate the majority of cryoEM grid screening. Autoscreen combines machine learning, computer vision algorithms, and microscope-handling algorithms to remove the need for constant manual operator input. Autoscreen can autonomously load and image grids with multi-scale imaging using an automated specimen-exchange cassette system, resulting in unattended grid screening for an entire cassette. As a result, operator time for screening 12 grids may be reduced to ~10 min with Autoscreen compared to ~6 h using previous methods which are hampered by their inability to account for high variability between grids. This protocol first introduces basic Leginon setup and functionality, then demonstrates Autoscreen functionality step-by-step from the creation of a template session to the end of a 12-grid automated screening session.

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques

Cryo-electron microscopy (cryoEM) multi-grid screening is often a tedious process that demands hours of attention. This protocol shows how to set up a standard Leginon collection and Smart Leginon Autoscreen to automate this process. This protocol can be applied to the majority of cryoEM holey foil grids.

Advancements in cryo-electron microscopy (cryoEM) techniques over the past decade have allowed structural biologists to routinely resolve macromolecular ...

Fabrication of Streptavidin Affinity Grids for Cryo-EM Structural Studies

Streptavidin-Affinity Grid Fabrication for Cryo-Electron Microscopy Sample Preparation

Streptavidin affinity grids provide strategies to overcome many commonly encountered cryo-electron microscopy (cryo-EM) sample preparation challenges, including sample denaturation and preferential orientations that can occur due to the air-water interface. Streptavidin affinity grids, however, are currently utilized by few cryo-EM labs because they are not commercially available and require a careful fabrication process. Two-dimensional streptavidin crystals are grown onto a biotinylated lipid monolayer that is applied directly to standard holey-carbon cryo-EM grids. The high-affinity interaction between streptavidin and biotin allows for the subsequent binding of biotinylated samples that are protected from the air-water interface during cryo-EM sample preparation. Additionally, these grids provide a strategy for concentrating samples available in limited quantities and purifying protein complexes of interest directly on the grids. Here, a step-by-step, optimized protocol is provided for the robust fabrication of streptavidin affinity grids for use in cryo-EM and negative-stain experiments. Additionally, a trouble-shooting guide is included for commonly experienced challenges to make the use of streptavidin affinity grids more accessible to the larger cryo-EM community.

Author Spotlight: Enhancing Cryo-EM Sample Preparation with Streptavidin-Biotin Approach

A step-by-step protocol for fabricating streptavidin affinity grids is provided for use in structural studies of challenging macromolecular samples by cryo-electron microscopy.

Streptavidin affinity grids provide strategies to overcome many commonly encountered cryo-electron microscopy (cryo-EM) sample preparation challenges, ...