Name: a robust single-particle cryo-electron microscopy (cryo-em) processing workflow with cryosparc, relion, and scipion
Uploaded: 2022-01-31T13:30:00
Description: Watch this Scientific Journal Video about A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion at JoVE.com

We thank Carlos Oscar Sorzano for help with Scipion3 installation and Kilian Schnelle and Arne Moeller for help with data transfer between different processing platforms. A portion of this research was supported by NIH grant U24GM129547 and performed at the PNCC at OHSU and accessed through EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research. This study was supported by a start-up grant from Rutgers University to Arek Kulczyk.

1. Creating a new cryoSPARC v3 project and importing data
NOTE: Data was acquired at Oregon Health and Science University (OHSU) in Portland using a 300 kV Titan Krios electron microscope equipped with a Falcon 3 direct electron detector. Images were collected in a counting mode with a total dose of 28.38 e&#8722;/&#197;2 fractioned across 129 frames, and a defocus range from -0.5 &#181;m to -2.5 &#181;m, at a pixel size of 1.045 &#197; using EPU. The sampl...

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In this article, we present a robust SPA workflow for cryo-EM data processing across various software platforms to achieve high-resolution 3D reconstructions (Figure 1). This workflow is applicable to a wide variety of biological macromolecules. The subsequent steps of the protocol are outlined in Figure 4, including movie pre-processing, particle picking and classification, and multiple methods for structure refinements (Table 1</strong...

Cryo-electron microscopy (cryo-EM) and single-particle analysis (SPA) enable structure determination of a wide variety of biomolecular assemblies in their hydrated state, helping to illuminate the roles of these macromolecules in atomic detail. Improvements in microscope optics, computer hardware, and image processing software have made it possible to determine structures of biomolecules at resolution reaching beyond 2 &#197;1,2,3. More than 2,300 cryo-EM structures were deposited in the Protein Data Bank (PDB) in 2020, compared to 192 structures in 20144, indicating that cryo-EM has become the method of choice for many structural biologists. Here, we describe a workflow combining three different SPA programs for high-resolution structure determination (Figure 1).
The goal of SPA is to reconstruct 3D volumes of a target specimen from noisy 2D images recorded by a microscope detector. Detectors collect images as movies with individual frames of the same field of view. In order to preserve the sample, frames are collected with a low electron dose and thus have a poor signal-to-noise ratio (SNR). Additionally, electron exposure can induce motion within the vitrified cryo-EM grids, resulting in image-blurring. To overcome these issues, frames are aligned to correct for beam-induced motion and averaged to yield a micrograph with an increased SNR. These micrographs then undergo Contrast Transfer Function (CTF) estimation to account for the effects of defocus and aberrations imposed by the microscope. From the CTF-corrected micrographs, individual particles are selected, extracted, and sorted into 2D class averages representing different orientations adopted by the specimen in vitreous ice. The resultant homogeneous set of particles is used as input for ab initio&#160;3D reconstruction to generate a coarse model or models, which are then iteratively refined to produce one or more high-resolution structures. After reconstruction, structural refinements are performed to further improve the quality and resolution of the cryo-EM map. Finally, either an atomic model is directly derived from the map, or the map is fitted with atomic coordinates obtained elsewhere.
Different software packages are available to accomplish the tasks outlined above, including Appion5, cisTEM6, cryoSPARC7, EMAN8, IMAGIC9, RELION10, Scipion11, SPIDER12, Xmipp13, and others. While these programs follow similar processing steps, they employ different algorithms, for example, to pick particles, generate initial models, and refine reconstructions. Additionally, these programs require a varying level of user knowledge and intervention to operate, as some depend on the fine-tuning of parameters that can act as a hurdle for new users. These discrepancies often result in maps with inconsistent quality and resolution across platforms14, prompting many researchers to use multiple software packages to refine and validate results. In this article, we highlight the use of cryoSPARC v3, RELION-3, and Scipion 3 to obtain a high-resolution 3D reconstruction of AAV, a widely used vector for gene therapy15. The aforementioned software packages are free to academic users; cryoSPARC v3 and Scipion 3 require licenses.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>CryoSPARC</td>
			<td>Structura Biotechnology Inc.</td>
			<td>https://cryosparc.com/</td>
			<td></td>
		</tr>
		<tr>
			<td>CTFFIND 4</td>
			<td>Howard Hughes Medical Institute, UMass Chan Medical School</td>
			<td>https://grigoriefflab.umassmed.edu/ctffind4</td>
			<td></td>
		</tr>
		<tr>
			<td>MotionCorr2</td>
			<td>UCSF Macromolecular Structure Group</td>
			<td>https://msg.ucsf.edu/software</td>
			<td></td>
		</tr>
		<tr>
			<td>Phenix</td>
			<td>Computational Tools for Macromolecular Neutron Crystallography (MNC)</td>
			<td>http://www.phenix-online.org/</td>
			<td></td>
		</tr>
		<tr>
			<td>PyEM</td>
			<td>Univerisity of California, San Francisco</td>
			<td>https://github.com/asarnow/pyem</td>
			<td></td>
		</tr>
		<tr>
			<td>RELION</td>
			<td>MRC Laboratory of Structural Biology</td>
			<td>https://www3.mrc-lmb.cam.ac.uk/relion/index.php/Main_Page</td>
			<td></td>
		</tr>
		<tr>
			<td>Scipion</td>
			<td>Instruct Image Processing Center (I2PC), SciLifeLab</td>
			<td>http://scipion.i2pc.es/</td>
			<td></td>
		</tr>
		<tr>
			<td>UCSF Chimera</td>
			<td>UCSF Resource for Biocomputing, Visualization, and Informatics</td>
			<td>https://www.cgl.ucsf.edu/chimera/</td>
			<td></td>
		</tr>
	</tbody>
</table>

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.

We have presented a comprehensive SPA pipeline to obtain a high-resolution structure using three different processing platforms: cryoSPARC v3, RELION-3, and Scipion 3. Figure 1 and Figure 4 summarize the general processing workflow, and Table 1 details refinement protocols. These protocols were used during refinements of a 2.3 &#197; structure of AAV, achieving near Nyquist resolution.
Movies were first imported to cr...

Watch this Scientific Journal Video about A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion at JoVE.com

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.

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 ...

Single-particle cryo-electron microscopy is the method for structured determinations of macromolecules at near atomic resolution. Multiple software packages are available for image processing and structure calculations, yet the result on 3D maps often vary in quality and resolution due to the differences in algorithms applied during calculations. Thus, using a combination of different programs is often beneficial to achieve the optimal results.This protocol guides users to navigate workflow across three different cryo-EM processing platforms:CryoSPARC, RELION, and Scipion. We will demonstrate how to use this pipeline to obtain a high-resolution structure of the adeno-associated virus which is a widely used vector for gene therapy. After opening CryoSPARC v3 in a web browser and creating the workspace for the project, navigate to the new workspace and open the job builder on the right panel.Click on import movies and provide the movies path and gain reference file path. Then set the acquisition parameters. Next, click on queue, select a lane to run the job and a workspace and click on create.Open patch motion correction and the import movies job card. Then drag the imported_movies output to the movies placeholder on the new job and queue the job. To perform the contrast transfer function or CTF estimation, open patch CTF estimation.Input the generated micrographs and queue the job. To inspect the averaged and CTF corrected micrographs and select a subset for further processing, open curate exposures, input the exposures obtained from the previous step and queue the job. After the job enters waiting mode, click on the interactive tab on the job card.Adjust the parameter thresholds and accept or reject individual micrographs for further processing. While processing the current data, set the upper threshold of astigmatism to 400 angstroms, CTF fit resolution to five angstroms and relative ice thickness to two. Then click on done to select the micrographs for downstream processing.For manual-based picking, open the manual picker. Input the accepted exposures and queue the job. Then click on the interactive tab, set the box size to 300 pixels and click on a few hundred particles across multiple micrographs, avoiding overlapping particles.Once finished with the selection, click on done picking extract particles. Next, to generate templates for automated particle picking, click on 2D classification and input the generated particle picks. Then change the number of 2D classes to 10 and queue the job.Next, open select 2D classes and input the particles and class averages obtained in the previous step. Then click on the interactive tab, select representative 2D classes with a good signal-to-noise ratio and click on done. For template-based particle picking, open template picker and input the selected 2D classes and micrographs.Then set the particle diameter to 220 angstroms and queue the job. Finally, open extract from micrographs and input the micrographs and particles obtained from inspecting particle picks. Then set the extracted box size to 300 pixels and queue the job.For 2D classification, click on 2D classification and input the extracted particles. Then set the number of 2D classes to 50 and queue the job. Next, open select 2D classes and input the obtained particles and class averages.Click on the interactive tab. Choose 2D classes based upon the resolution and the number of particles in the class and click on done. To generate an initial 3D volume, open ab-initio reconstruction and input the particles from the final 2D classification.Then adjust symmetry to icosahedral and queue the job. Next, open homogenous refinement, input the volume from the previous step and particles from the final 2D classification. Then change the symmetry and queue the job.When the job is finished, inspect the Fourier shell correlation or FSC curve and download the volume to examine in UCSF Chimera. In CryoSPARC v3, open the job card of the select 2D class job from the final 2D classification. Then on the details tab, click on export job.Using PyEM, convert the particles_exported. cs file to star format by executing the indicated command. After clicking on particle extraction, in the I/O tab, input the CTF corrected micrographs and coordinates.Then click on the extract tab, change the particle box size to 300 pixels and run the job. For 3D refinement, use the map generated in CryoSPARC v3 as an initial model in RELION-3. Select the import method and set the indicated parameters in the I/O tab.Then on the others tab, select the CryoSPARC v3 map as the input file, change node type to 3D reference and run the job. Next, select the 3D auto-refine and on the I/O tab, set input images as the particles. star file from the last selection job.Use the CryoSPARC v3 reconstruction as the reference map, click on the reference tab and change initial low-pass filter to 50 angstroms and symmetry to icosahedral. Then on the optimization tab, change the mask diameter to 280 angstroms and run the job. For post processing, click on post-processing.And on the I/O tab, input the created half maps and mask and set the calibrated pixel size to 1.045 angstroms. Then on the sharpen tab, for estimate B-factor automatically, input yes. For lowest resolution for auto-B fit, input 10.And for use your own B-factor, input no. Finally, on the filter tab, set skip FSC-weighting to no and run the job. For polishing training, open Bayesian polishing.And on the I/O tab, input the motion corrected micrographs, particles, and PostProcess. star file obtained previously. Click the training tab and set train optimal parameters to yes, fraction of Fourier pixels for testing to 0.5 and use this many particles to 5, 000.Then run the job. Once the training job is finished, click on Bayesian polishing. Then in the training tab, set train optimal parameters to no.Select the polish tab and in optimized parameter file, specify the path to the opt_params_all_groups. txt file from the previous step and click on run. To estimate higher order aberrations, open CTF refinement.And on the I/O tab under particles, select the path to the star file containing polished particles from the recent refined 3D job. Then under postprocess STAR file, set the path to the output from the latest post-processing job. Next, select the fit tab and set estimate anisotropic magnification to no.Perform CTF parameter fitting to no. Estimate beamtilt to yes. Also estimate trefoil to yes.And estimate fourth order aberrations to yes. Then run the job. To further refine and validate the RELION-3 map, launch Scipion 3 and create a new project.On the left protocols panel, select the imports dropdown and click on import particles. Change the parameters import from to RELION-3 and star file to postprocess.star. Then specify the acquisition parameters as demonstrated earlier and click on execute.Next, click on the imports dropdown and select import volumes. Under import from, give the path to the RELION-3 map, change pixel size sampling rate to 1.045 angstroms per pixel and execute. To perform a global alignment, select the refine dropdown menu from the protocols panel and click on xmipp3-highres.Input the imported particles and volumes from the previous steps as full size images and initial volumes respectively and set the symmetry group to icosahedral. Then on the image alignment tab under angular assignment, choose global, set the max target resolution to three angstroms and run the job. To perform a local alignment, select xmipp3-highres global, change continue from previous run to yes and select the previous job.Then on the angular assignment tab, change image alignment to local and set the max target resolution to 2.1 angstroms. After finishing, in the xmipp3-highres results window, click on display resolution plots to see how the FSC has changed after the refinement and click on plot histogram with angular changes to see if the Euler angle assignments have changed. Inspect the volume in UCSF Chimera.Zoom in and look for high-resolution features. Micrographs with good CTF fit and low astigmatism were selected for further processing, while those with high astigmatism and forfeit were discarded. 2D class averages containing well-defined classes were selected, and those with low resolution, noise, and partial particles were rejected.Regions of the cryo-electron microscopy map fitted with atomic coordinates of an adeno-associated virus are shown here. Well-defined EM densities allow for fitting side chains of individual amino acids, water molecules and magnesium ions. FSC curves calculated using CryoSPARC v3, RELION-3, and Scipion indicate increasing resolution across the workflow, resolution estimates at four different slices through the structures and resolution histograms demonstrate the incremental improvement in local resolution between the maps throughout the workflow.Combining cryo-EM processing algorithms of CryoSPARC, RELION-3, Scipion, and Phoenix resulted in a resolution increase of the adeno-associated virus structures from 2.9 to 2.3 angstroms across the processing pipeline. It is important to remember that the parameters specified in each step are sample and microscope-dependent. Additionally, the ability to reach high resolution greatly depends upon the quality of the sample and of the raw data.In this video, we present the robust SP workflow for processing of cryo-EM data across various software platforms. By using this approach, one can implement algorithms for multiple programs to refine and validate cryo structures. This workflow can be applied to structure calculations of a wide variety of macromolecular assemblies.

a-robust-single-particle-cryo-electron-microscopy-cryo-em-processing

Research

JoVE Journal

Biochemistry

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 ...

Expression and Purification of the Human Lipid-sensitive Cation Channel TRPC3 for Structural Determination by Single-particle Cryo-electron Microscopy

Transient receptor potential channels (TRPCs) of the canonical TRP subfamily are nonselective cation channels that play an essential role in calcium homeostasis, particularly store-operated calcium entry, which is critical to maintaining proper function of synaptic vesicle release and intracellular signaling pathways. Accordingly, TRPC channels have been implicated in a variety of human diseases including cardiovascular disorders such as cardiac hypertrophy, neurodegenerative disorders such as Parkinson&#39;s disease, and neurologic disorders such as spinocerebellar ataxia. Therefore, TRPC channels represent a potential pharmacologic target in human diseases. However, the molecular mechanisms of gating in these channels are still unclear. The difficulty in obtaining large quantities of stable, homogeneous, and purified protein has been a limiting factor in structure determination studies, particularly for mammalian membrane proteins such as the TRPC ion channels. Here, we present a protocol for the large-scale expression of mammalian ion channel membrane proteins using a modified baculovirus gene transfer system and the purification of these proteins by affinity and size-exclusion chromatography. We further present a protocol to collect single-particle cryo-electron microscopy images from purified protein and to use these images to determine the protein structure. Structure determination is a powerful method for understanding the mechanisms of gating and function in ion channels.

This protocol describes techniques used to determine ion channel structures by cryo-electron microscopy, including a baculovirus system used to efficiently express genes in mammalian cells with minimum effort and toxicity, protein extraction, purification, and quality checking, sample grid preparation and screening, as well as data collection and processing.

Transient receptor potential channels (TRPCs) of the canonical TRP subfamily are nonselective cation channels that play an essential role in calcium ...

Fast Grid Preparation for Time-Resolved Cryo-Electron Microscopy

The field of cryo-electron microscopy (cryo-EM) is rapidly developing with new hardware and processing algorithms, producing higher resolution structures and information on more challenging systems. Sample preparation for cryo-EM is undergoing a similar revolution with new approaches being developed to supersede the traditional blotting systems. These include the use of piezo-electric dispensers, pin printing and direct spraying. As a result of these developments, the speed of grid preparation is going from seconds to milliseconds, providing new opportunities, especially in the field of time-resolved cryo-EM where proteins and substrates can be rapidly mixed before plunge freezing, trapping short lived intermediate states. Here we describe, in detail, a standard protocol for making grids on our in-house time-resolved EM device both for standard fast grid preparation and also for time-resolved experiments. The protocol requires a minimum of about 50 &#181;L sample at concentrations of &#8805; 2 mg/mL for the preparation of 4 grids. The delay between sample application and freezing can be as low as 10 ms. One limitation is increased ice thickness at faster speeds and compared to the blotting method. We hope this protocol will aid others in designing their own grid making devices and those interested in designing time-resolved experiments.

Here, we provide a detailed protocol for the use of a rapid grid making device for both fast grid-making and for rapid mixing and freezing to conduct time-resolved experiments.

The field of cryo-electron microscopy (cryo-EM) is rapidly developing with new hardware and processing algorithms, producing higher resolution structures ...

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 ...

Manual Blot-and-Plunge Freezing of Biological Specimens for Single-Particle Cryogenic Electron Microscopy

Imaging biological specimens with electrons for high-resolution structure determination by single-particle cryogenic electron microscopy (cryoEM) requires a thin layer of vitreous ice containing the biomolecules of interest. Despite numerous technological advances in recent years that have propelled single-particle cryoEM to the forefront of structural biology, the methods by which specimens are vitrified for high-resolution imaging often remain the rate-limiting step. Although numerous recent efforts have provided means to overcome hurdles frequently encountered during specimen vitrification, including the development of novel sample supports and innovative vitrification instrumentation, the traditional manually operated plunger remains a staple in the cryoEM community due to the low cost to purchase and ease of operation. Here, we provide detailed methods for using a standard, guillotine-style manually operated blot-and-plunge device for the vitrification of biological specimens for high-resolution imaging by single-particle cryoEM. Additionally, commonly encountered issues and troubleshooting recommendations for when a standard preparation fails to yield a suitable specimen are also described.

This manuscript outlines the blot-and-plunge method to manually freeze biological specimens for single-particle cryogenic electron microscopy.

Imaging biological specimens with electrons for high-resolution structure determination by single-particle cryogenic electron microscopy (cryoEM) requires ...

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, ...

Micropatterning Transmission Electron Microscopy Grids to Direct Cell Positioning within Whole-Cell Cryo-Electron Tomography Workflows

Whole-cell cryo-electron tomography (cryo-ET) is a powerful technology that is used to produce nanometer-level resolution structures of macromolecules present in the cellular context and preserved in a near-native frozen-hydrated state. However, there are challenges associated with culturing and/or adhering cells onto TEM grids in a manner that is suitable for tomography while retaining the cells in their physiological state. Here, a detailed step-by-step protocol is presented on the use of micropatterning to direct and promote eukaryotic cell growth on TEM grids. During micropatterning, cell growth is directed by depositing extra-cellular matrix (ECM) proteins within specified patterns and positions on the foil of the TEM grid while the other areas remain coated with an anti-fouling layer. Flexibility in the choice of surface coating and pattern design makes micropatterning broadly applicable for a wide range of cell types. Micropatterning is useful for studies of structures within individual cells as well as more complex experimental systems such as host-pathogen interactions or differentiated multi-cellular communities. Micropatterning may also be integrated into many downstream whole-cell cryo-ET workflows, including correlative light and electron microscopy (cryo-CLEM) and focused-ion beam milling (cryo-FIB).

The goal of this protocol is to direct cell adhesion and growth to targeted areas of grids for cryo-electron microscopy. This is achieved by applying an anti-fouling layer that is ablated in user-specified patterns followed by deposition of extra-cellular matrix proteins in the patterned areas prior to cell seeding.

Whole-cell cryo-electron tomography (cryo-ET) is a powerful technology that is used to produce nanometer-level resolution structures of macromolecules ...

Preparation of Nucleosome Core Particles Complexed with DNA Repair Factors for Cryo-Electron Microscopy Structural Determination

DNA repair in the context of chromatin is poorly understood. Biochemical studies using nucleosome core particles, the fundamental repeating unit of chromatin, show most DNA repair enzymes remove DNA damage at reduced rates as compared to free DNA. The molecular details on how base excision repair (BER) enzymes recognize and remove DNA damage in nucleosomes have not been elucidated. However, biochemical BER data of nucleosomal substrates suggest the nucleosome presents different structural barriers dependent on the location of the DNA lesion and the enzyme. This indicates the mechanisms employed by these enzymes to remove DNA damage in free DNA may be different than those employed in nucleosomes. Given that the majority of genomic DNA is assembled into nucleosomes, structural information of these complexes is needed. To date, the scientific community lacks detailed protocols to perform technically feasible structural studies of these complexes. Here, we provide two methods to prepare a complex of two genetically fused BER enzymes (Polymerase &#946; and AP Endonuclease1) bound to a single-nucleotide gap near the entry-exit of the nucleosome for cryo-electron microscopy (cryo-EM) structural determination. Both methods of sample preparation are compatible for vitrifying quality grids via plunge freezing. This protocol can be used as a starting point to prepare other nucleosomal complexes with different BER factors, pioneer transcription factors, and chromatin-modifying enzymes.

This protocol outlines in detail the preparation of nucleosomal complexes using two methods of sample preparation for freezing TEM grids.

DNA repair in the context of chromatin is poorly understood. Biochemical studies using nucleosome core particles, the fundamental repeating unit of ...

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.

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 ...