The authors would like to acknowledge economical support from: The Spanish Ministry of Science and Innovation through Grants: PID2019-104757RB-I00/AEI/10.13039/501100011033, the &#34;Comunidad Aut&#243;noma de Madrid&#34; through Grant: S2017/BMD-3817, Instituto de Salud Carlos III, PT17/0009/0010 (ISCIII-SGEFI/ERDF), European Union (EU) and Horizon 2020 through grant: INSTRUCT - ULTRA (INFRADEV-03-2016-2017, Proposal: 731005), EOSC Life (INFRAEOSC-04-2018, Proposal: 824087), iNEXT - Discovery (Proposal: 871037), and HighResCells (ERC - 2018 - SyG, Proposal: 810057). The project that gave rise to these results received the support of a fellowship from &#34;la Caixa&#34; Foundation (ID 100010434). The fellowship code is LCF/BQ/DI18/11660021. This project has received funding from the European Union&#39;s Horizon 2020 research and innovation programme under the Marie Sk&#322;odowska-Curie grant agreement No. 713673. The authors acknowledge the support and the use of resources of Instruct, a Landmark ESFRI project.

<ol>
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The authors have nothing to disclose.

Currently, cryo-EM is a key tool to reveal the 3D structure of biological samples. When good data is collected with the microscope, the available processing tools will allow us to obtain a 3D reconstruction of the macromolecule under study. Cryo-EM data processing is able to achieve near-atomic resolution, which is key to understanding the functional behavior of a macromolecule and is also crucial in drug discovery.
Scipion is a software that allows creating the whole workflow combining the most relevant image processing packages in an integrative way, which helps the traceability and reproducibility of the entire image-processing workflow. Scipion provides a very complete set of tools to carry out the processing; however, obtaining high resolutions reconstructions depends completely on the quality of the acquired data and how these data is processed. 
To get a high resolution 3D reconstruction, the first requirement is to obtain good movies from the microscope, which preserve structural information to high resolution. If this is not the case, the workflow will not be able to extract high definition information from the data. Then, a successful processing workflow should be able to extract particles that really correspond to the structure and to find the orientations of these particles in the 3D space. If any of the steps in the workflow fails, the quality of the reconstructed volume will be degraded. Scipion allows for using different packages in any of the processing steps, which helps to find the most adequate approach to process the data. Moreover, thanks to having many packages available, consensus tools, that boost the accuracy by finding an agreement in the estimated outputs of different methods, can be used. Also, it has been discussed in detail in the Representative Results section several validation tools and how to identify accurate and inaccurate results in every step of the workflow, to detect potential problems, and how to try to solve them. There are several checkpoints along the protocol that could help to realize if the protocol is running properly or not. Some of the most relevant are: picking, 2D classification, initial volume estimation, and 3D alignment. Checking the inputs, repeating the step with a different method, or using consensus, are options available in Scipion that the user can use to find solutions when issues appear. 
Regarding the previous approaches to package integration in the Cryo-EM field, Appion31 is the only one that allows real integration of different software packages. However, Appion is tightly connected with Leginon32, a system for automated collection of images from electron microscopes. The main difference with Scipion is that data model and storage are less coupled. In such a way, to create a new protocol in Scipion, only a Python script needs to be developed. However, in Appion, the developer must write the script and change the underlying database. In summary, Scipion was developed to simplify maintenance and extensibility.
We have presented in this manuscript a complete workflow for Cryo-EM processing, using the real case dataset of the Plasmodium falciparum 80S Ribosome (EMPIAR entry: 10028, EMDB entry: 2660). The steps covered and discussed here can be summarized as movie alignment, CTF estimation, particle picking, 2D classification, initial map estimation, 3D classification, 3D refinement, evaluation, and post-processing. Different packages have been used and consensus tools were applied in several of these steps. The final 3D reconstructed volume achieved a resolution of 3 &#197; and, in the post-processed volume, some secondary structures can be distinguished, like alpha-helices, which helps to describe how atoms are arranged in space.
The workflow presented in this manuscript shows how Scipion can be used to combine different Cryo-EM packages in a straightforward and integrative way to simplify the processing, and obtain more reliable result at the same time.
In the future, the development of new methods and packages will keep growing and software like Scipion to easily integrate all of them will be even more important for the researchers. Consensus approaches will be more relevant even then, when plenty of methods with different basis will be available, helping to obtain more accurate estimations of all the parameters involve in the reconstruction process in Cryo-EM. Tracking and reproducibility are key in the research process and easier to achieve with Scipion thanks to having a common framework for the execution of complete workflows.

In cryo-electron microscopy (cryo-EM), single particle analysis (SPA) of vitrified frozen-hydrated specimens is one of the most widely used and successful variants of imaging for biological macromolecules, as it allows to understand molecular interactions and the function of biological ensembles1. This is thanks to the recent advances in this imaging technique that gave rise to the "resolution revolution"2 and have allowed the successful determination of biological 3D structures with near-atomic resolution. Currently, the highest resolution achieved in SPA cryo-EM was 1.15 &#197; for apoferritin3 (EMDB entry: 11668). These technological advances comprise improvements in the sample preparation4, the image acquisition5, and the image processing methods6. This article is focused on this last point. 
Briefly, the goal of the image processing methods is to identify all the acquisition parameters to invert the imaging process of the microscope and recover the 3D structure of the biological specimen under study. These parameters are the gain of the camera, the beam-induced movement, the aberrations of the microscope (mainly the defocus), the 3D angular orientation and translation of each particle, and the conformational state in case of having a specimen with conformational changes. However, the number of parameters is very high and cryo-EM requires using low-dose images to avoid radiation damage, which significantly reduces the Signal-to-Noise Ratio (SNR) of the acquired images. Thus, the problem cannot be unequivocally solved and all the parameters to be calculated only can be estimations. Along the image processing workflow, the correct parameters should be identified, discarding the remaining ones to finally obtain a high-resolution 3D reconstruction.
The data generated by the microscope are gathered in frames. Simplifying, a frame contains the number of electrons that have arrived at a particular position (pixel) in the image, whenever electron-counting detectors are used. In a particular field of view, several frames are collected and this is called a movie. As low electron doses are used to avoid radiation damage that could destroy the sample, the SNR is very low and the frames corresponding to the same movie need to be averaged to obtain an image revealing structural information about the sample. However, not only a simple average is applied, the sample can suffer shifts and other kinds of movements during the imaging time due to the beam-induced movement that need to be compensated. The shift-compensated and averaged frames originate a micrograph.
Once the micrographs are obtained, we need to estimate the aberrations introduced by the microscope for each of them, called Contrast Transfer Function (CTF), which represents the changes in the contrast of the micrograph as a function of frequency. Then, the particles can be selected and extracted, which is called particle picking. Every particle should be a small image containing only one copy of the specimen under study. There are three families of algorithms for particle picking: 1) the ones that only use some basic parameterization of the appearance of the particle to find them in the whole set of micrographs (e.g., particle size), 2) the ones that learn how the particles look like from the user or a pretrained set, and 3) the ones that use image templates. Each family has different properties that will be shown later.
The extracted set of particles found in the micrographs will be used in a 2D classification process that has two goals: 1) cleaning the set of particles by discarding the subset containing pure noise images, overlapping particles, or other artifacts, and 2) the averaged particles representing each class could be used as initial information to calculate a 3D initial volume. 
The 3D initial volume calculation is the next crucial step. The problem of obtaining the 3D structure can be seen as an optimization problem in a multidimensional solution landscape, where the global minimum is the best 3D volume that represents the original structure, but several local minima representing suboptimal solutions can be found, and where it is very easy to get trapped. The initial volume represents the starting point for the searching process, so bad initial volume estimation could prevent us to find the global minimum. From the initial volume, a 3D classification step will help to discover different conformational states and to clean again the set of particles; the goal is to obtain a structurally homogeneous population of particles. After that, a 3D refinement step will be in charge of refining the angular and translation parameters for every particle to get the best 3D volume possible. 
Finally, in the last steps, the obtained 3D reconstruction can be sharpened and polished. Sharpening is a process of boosting the high frequencies of the reconstructed volume, and the polishing is a step to further refine some parameters, as CTF or beam-induced movement compensation, at the level of particles. Also, some validation procedures could be used to better understand the achieved resolution at the end of the workflow. 
After all these steps, the tracing and docking processes7 will help to give a biological meaning to the obtained 3D reconstruction, by building atomic models de novo or fitting existing models. If high resolution is achieved, these processes will tell us the positions of the biological structures, even of the different atoms, in our structure.
Scipion8 allows creating the whole workflow combining the most relevant image processing packages in an integrative way. Xmipp9, Relion10, CryoSPARC11, Eman12, Spider13, Cryolo14, Ctffind15, CCP416, Phenix17, and many more packages can be included in Scipion. Also, it incorporates all the necessary tools to benefit the integration, interoperability, traceability, and reproducibility to make a full tracking of the entire image-processing workflow8.
One of the most powerful tools that Scipion allows us to use is the consensus, which means to compare the results obtained with several methods in one step of the processing, making a combination of the information conveyed by different methods to generate a more accurate output. This could help to boost the performance and improve the achieved quality in the estimated parameters. Note that a simpler workflow can be build without the use of consensus methods; however, we have seen the power of this tool22,25 and the workflow presented in this manuscript will use it in several steps. 
All the steps that have been summarized in the previous paragraphs will be explained in detail in the following section and combined in a complete workflow using Scipion. Also, how to use the consensus tools to achieve a higher agreement in the generated outputs will be shown. To that end, the example dataset of the Plasmodium falciparum 80S Ribosome has been chosen (EMPIAR entry: 10028, EMDB entry: 2660). The dataset is formed by 600 movies of 16 frames of size 4096x4096 pixels at a pixel size of 1.34&#197; taken at an FEI POLARA 300 with an FEI FALCON II camera, with a reported resolution at EMDB is 3.2&#197;18 .

<table><tbody><tr><td>&lt;em&gt;no material is used in this article&lt;/em&gt;</td><td>-</td><td>-</td><td>-</td></tr></tbody></table>

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.

Watch this Scientific Journal Video about Cryo-EM and Single-Particle Analysis with Scipion at JoVE.com

Cryo-EM and Single-Particle Analysis with Scipion

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 ...

cryo-em-and-single-particle-analysis-with-scipion

Research

JoVE Journal

Biochemistry

3.7K Views.  Campus Universidad Autónoma de Madrid. Scipion biedt de tools om de hele verwerkingsworkflow op een integratieve manier te creëren voor een enkele deeltjesanalyse in cryo-EM om een hoge resolutie reconstructie van het biologische monster te bereiken. Dit raamwerk maakt het mogelijk om de verwerkingsworkflow te creëren met behulp van verschillende beeldverwerkingspakketten, waarbij interoperabiliteit, traceerbaarheid, reproduceerbaarheid en de combinatie van informatie die door verschillende methoden wordt overgebracht, worden be...

Video: Cryo-EM and Single-Particle Analysis with Scipion

A Protein Preparation Method for the High-throughput Identification of Proteins Interacting with a Nuclear Cofactor Using LC-MS/MS Analysis

Transcriptional coregulators are vital to the efficient transcriptional regulation of nuclear chromatin structure. Coregulators play a variety of roles in regulating transcription. These include the direct interaction with transcription factors, the covalent modification of histones and other proteins, and the occasional chromatin conformation alteration. Accordingly, establishing relatively quick methods for identifying proteins that interact within this network is crucial to enhancing our understanding of the underlying regulatory mechanisms. LC-MS/MS-mediated protein binding partner identification is a validated technique used to analyze protein-protein interactions. By immunoprecipitating a previously-identified member of a protein complex with an antibody (occasionally with an antibody for a tagged protein), it is possible to identify its unknown protein interactions via mass spectrometry analysis. Here, we present a method of protein preparation for the LC-MS/MS-mediated high-throughput identification of protein interactions involving nuclear cofactors and their binding partners. This method allows for a better understanding of the transcriptional regulatory mechanisms of the targeted nuclear factors.

We have established a method for the purification of coregulatory interaction proteins using the LC-MS/MS system.

Transcriptional coregulators are vital to the efficient transcriptional regulation of nuclear chromatin structure. Coregulators play a variety of roles in ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

Cryo-Electron Microscopic Grid Preparation for Time-Resolved Studies using a Novel Robotic System, Spotiton

The capture of short-lived molecular states triggered by the early encounter of two or more interacting particles continues to be an experimental challenge of great interest to the field of cryo-electron microscopy (cryo-EM). A few methodological strategies have been developed that support these &#34;time-resolved&#34; studies, one of which, Spotiton-a novel robotic system-combines the dispensing of picoliter-sized sample droplets with precise temporal and spatial control. The time-resolved Spotiton workflow offers a uniquely efficient approach to interrogate early structural rearrangements from minimal sample volume. Fired from independently controlled piezoelectric dispensers, two samples land and rapidly mix on a nanowire EM grid as it plunges toward the cryogen. Potentially hundreds of grids can be prepared in rapid succession from only a few microliters of a sample. Here, a detailed step-by-step protocol of the operation of the Spotiton system is presented with a focus on troubleshooting specific problems that arise during grid preparation.

The protocol presented here describes the use of Spotiton, a novel robotic system, to deliver two samples of interest onto a self-wicking, nanowire grid that mix for a minimum of 90 ms prior to vitrification in liquid cryogen.

The capture of short-lived molecular states triggered by the early encounter of two or more interacting particles continues to be an experimental ...

Biology

Cryo-Structured Illumination Microscopic Data Collection from Cryogenically Preserved Cells

Three-dimensional (3D) structured illumination microscopy (SIM) allows imaging of fluorescently labelled cellular structures at higher resolution than conventional fluorescence microscopy. This super-resolution (SR) technique enables visualization of molecular processes in whole cells and has the potential to be used in conjunction with electron microscopy and X-ray tomography to correlate structural and functional information. A SIM microscope for cryogenically preserved samples (cryoSIM) has recently been commissioned at the correlative cryo-imaging beamline B24 at the UK synchrotron. 
It was designed specifically for 3D imaging of biological samples at cryogenic temperatures in a manner compatible with subsequent imaging of the same samples by X-ray microscopy methods such as cryo-soft X-ray tomography. This video article provides detailed methods and protocols for successful imaging using the cryoSIM. In addition to instructions on the operation of the cryoSIM microscope, recommendations have been included regarding the choice of samples, fluorophores, and parameter settings. The protocol is demonstrated in U2OS cell samples whose mitochondria and tubulin have been fluorescently labelled.

This protocol demonstrates how to image biological cryo-preserved samples using cryo-structured illumination microscopy. We demonstrate the methodology by imaging the cytoskeleton of U2OS cells.

Three-dimensional (3D) structured illumination microscopy (SIM) allows imaging of fluorescently labelled cellular structures at higher resolution than ...

Enhancing Cryo-EM Map Quality with CryoSieve Particle Selection

Enhancing Density Maps by Removing the Majority of Particles in Single Particle Cryogenic Electron Microscopy Final Stacks

Over the past decade, advancements in technology and methodology within the field of cryogenic electron microscopy (cryo-EM) single-particle analysis (SPA) have substantially improved our capacity for high-resolution structural examination of biological macromolecules. This advancement has ushered in a new era of molecular insights, replacing X-ray crystallography as the dominant method and providing answers to longstanding questions in biology. Since cryo-EM does not depend on crystallization, which is a significant limitation of X-ray crystallography, it captures particles of varying quality. Consequently, the selection of particles is crucial, as the quality of the selected particles directly influences the resolution of the reconstructed density map. An innovative iterative approach for particle selection, termed CryoSieve, significantly improves the quality of reconstructed density maps by effectively reducing the number of particles in the final stack. Experimental evidence shows that this method can eliminate the majority of particles in final stacks, resulting in a notable enhancement in the quality of density maps. This article outlines the detailed workflow of this approach and showcases its application on a real-world dataset.

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

An advanced particle selection method for cryo-EM, namely CryoSieve, improves density map resolution by removing a majority of particles in final stacks, as demonstrated through its application on a real-world dataset.

Over the past decade, advancements in technology and methodology within the field of cryogenic electron microscopy (cryo-EM) single-particle analysis ...

Cryo-EM and Single-Particle Analysis with Scipion

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