scholarly journals Live analysis and reconstruction of single-particle cryo-electron microscopy data with CryoFLARE

2019 ◽  
Author(s):  
Andreas D. Schenk ◽  
Simone Cavadini ◽  
Nicolas H. Thomä ◽  
Christel Genoud
Keyword(s):  
Electron Microscopy ◽  
Data Collection ◽  
Single Particle ◽  
Integrated Reporting ◽  
Seamless Integration ◽  
High Resolution Data ◽  
User Input ◽  
Cryo Electron Microscopy ◽  
New Processing ◽  
Set Up

AbstractEfficient, reproducible and accountable single-particle cryo-electron microscopy structure determination is tedious and often impeded by lack of a standardized procedure for data analysis and processing. To address this issue, we have developed the FMI Live Analysis and Reconstruction Engine (CryoFLARE). CryoFLARE is a modular open-source platform offering easy integration of new processing algorithms developed by the cryo-EM community. It provides a user-friendly interface that allows fast setup of standardized workflows, serving the need of pharmaceutical industry and academia alike who need to optimize throughput of their microscope. To consistently document how data is processed, CryoFLARE contains an integrated reporting facility to create reports.Live analysis and processing parallel to data acquisition are used to monitor and optimize data quality. Problems at the level of the sample preparation (heterogeneity, ice thickness, sparse particles, areas selected for acquisition, etc.) or misalignments of the microscope optics can quickly be detected and rectified before data collection is continued. Interfacing with automated data collection software for retrieval of acquisition metadata reduces user input needed for analysis, and with it minimizes potential sources of errors and workflow inconsistencies. Local and remote export support in Relion-compatible job and data format allows seamless integration into the refinement process. The support for non-linear workflows and fine-grained scheduling for mixed workflows with separate CPU and GPU based calculation steps ensures optimal use of processing hardware. CryoFLARE’s flexibility allows it to be used for all types of image acquisitions, ranging from sample screening to high-resolution data collection, and offers a new alternative for setting up image processing workflows. It can be used without modifications of the hardware/software delivered by the microscope supplier. As it is running on a server in parallel to the hardware used for acquisition, it can easily be set up for remote display connections and fast control of the acquisition status.

scholarly journals Real-time object locator for cryo-EM data collection --- You only navigate EM once ---

2021 ◽  
Author(s):  
Koji Yonekura ◽  
Saori Maki-Yonekura ◽  
Hisashi Naitow ◽  
Tasuku Hamaguchi ◽  
Kiyofumi Takaba
Keyword(s):  
Electron Microscopy ◽  
Machine Learning ◽  
Electron Diffraction ◽  
Data Collection ◽  
Real Time ◽  
Single Particle ◽  
Detection System ◽  
Target Object ◽  
Electron Crystallography ◽  
Cryo Electron Microscopy

In cryo-electron microscopy (cryo-EM) data collection, locating a target object is the most error-prone. Here, we present a machine learning-based approach with a real-time object locator named yoneoLocr using YOLO, a well-known object detection system. Implementation showed its effectiveness in rapidly and precisely locating carbon holes in single particle cryo-EM and for locating crystals and evaluating electron diffraction (ED) patterns in automated cryo-electron crystallography (cryo-EX) data collection.

scholarly journals High-resolution cryo-EM using beam-image shift at 200 keV

2020 ◽  
Author(s):  
Jennifer N. Cash ◽  
Sarah Kearns ◽  
Yilai Li ◽  
Michael A. Cianfrocco
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Data Collection ◽  
Data Quality ◽  
Single Particle ◽  
Aberration Correction ◽  
Cryo Electron Microscopy ◽  
Beam Image ◽  
Recent Advances ◽  
Shift Data

ABSTRACTRecent advances in single-particle cryo-electron microscopy (cryo-EM) data collection utilizes beam-image shift to improve throughput. Despite implementation on 300 keV cryo-EM instruments, it remains unknown how well beam-image shift data collection affects data quality on 200 keV instruments and how much aberrations can be computationally corrected. To test this, we collected and analyzed a cryo-EM dataset of aldolase at 200 keV using beam-image shift. This analysis shows that beam tilt on the instrument initially limited the resolution of aldolase to 4.9Å. After iterative rounds of aberration correction and particle polishing in RELION, we were able to obtain a 2.8Å structure. This analysis demonstrates that software correction of microscope aberrations can provide a significant improvement in resolution at 200 keV.

scholarly journals High-resolution cryo-EM using beam-image shift at 200 keV

IUCrJ ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 1179-1187 ◽  
Author(s):  
Jennifer N. Cash ◽  
Sarah Kearns ◽  
Yilai Li ◽  
Michael A. Cianfrocco
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Data Collection ◽  
Single Particle ◽  
Particle Motion ◽  
Data Set ◽  
Cryo Electron Microscopy ◽  
Beam Image ◽  
Shift Data ◽  
Resolution Structure

Recent advances in single-particle cryo-electron microscopy (cryo-EM) data collection utilize beam-image shift to improve throughput. Despite implementation on 300 keV cryo-EM instruments, it remains unknown how well beam-image-shift data collection affects data quality on 200 keV instruments and the extent to which aberrations can be computationally corrected. To test this, a cryo-EM data set for aldolase was collected at 200 keV using beam-image shift and analyzed. This analysis shows that the instrument beam tilt and particle motion initially limited the resolution to 4.9 Å. After particle polishing and iterative rounds of aberration correction in RELION, a 2.8 Å resolution structure could be obtained. This analysis demonstrates that software correction of microscope aberrations can provide a significant improvement in resolution at 200 keV.

scholarly journals Approaches to altering particle distributions in cryo-electron microscopy sample preparation

2018 ◽  
Vol 74 (6) ◽  
pp. 560-571 ◽  
Author(s):  
Ieva Drulyte ◽  
Rachel M. Johnson ◽  
Emma L. Hesketh ◽  
Daniel L. Hurdiss ◽  
Charlotte A. Scarff ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Sample Preparation ◽  
Single Particle ◽  
Structural Information ◽  
Particle Analysis ◽  
Diverse Range ◽  
Sample Distribution ◽  
High Resolution Data ◽  
Cryo Electron Microscopy

Cryo-electron microscopy (cryo-EM) can now be used to determine high-resolution structural information on a diverse range of biological specimens. Recent advances have been driven primarily by developments in microscopes and detectors, and through advances in image-processing software. However, for many single-particle cryo-EM projects, major bottlenecks currently remain at the sample-preparation stage; obtaining cryo-EM grids of sufficient quality for high-resolution single-particle analysis can require the careful optimization of many variables. Common hurdles to overcome include problems associated with the sample itself (buffer components, labile complexes), sample distribution (obtaining the correct concentration, affinity for the support film), preferred orientation, and poor reproducibility of the grid-making process within and between batches. This review outlines a number of methodologies used within the electron-microscopy community to address these challenges, providing a range of approaches which may aid in obtaining optimal grids for high-resolution data collection.

scholarly journals Combining high throughput and high quality for cryo-electron microscopy data collection

2020 ◽  
Vol 76 (8) ◽  
pp. 724-728
Author(s):  
Felix Weis ◽  
Wim J. H. Hagen
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Data Collection ◽  
Electron Tomography ◽  
3D Structure ◽  
Particle Analysis ◽  
High Resolution Data ◽  
Cryo Electron Microscopy ◽  
Microscopy Data ◽  
Subtomogram Averaging

Cryo-electron microscopy (cryo-EM) can be used to elucidate the 3D structure of macromolecular complexes. Driven by technological breakthroughs in electron-microscope and electron-detector development, coupled with improved image-processing procedures, it is now possible to reach high resolution both in single-particle analysis and in cryo-electron tomography and subtomogram-averaging approaches. As a consequence, the way in which cryo-EM data are collected has changed and new challenges have arisen in terms of microscope alignment, aberration correction and imaging parameters. This review describes how high-end data collection is performed at the EMBL Heidelberg cryo-EM platform, presenting recent microscope implementations that allow an increase in throughput while maintaining aberration-free imaging and the optimization of acquisition parameters to collect high-resolution data.

scholarly journals Optimized data acquisition workflow by sample thickness determination

2020 ◽  
Author(s):  
Jan Rheinberger ◽  
Gert Oostergetel ◽  
Guenter P Resch ◽  
Cristina Paulino
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Data Collection ◽  
Data Acquisition ◽  
Data Storage ◽  
Single Particle ◽  
Collection Efficiency ◽  
Sample Thickness ◽  
Cryo Electron Microscopy ◽  
Key Parameter

AbstractSample thickness is a known key parameter in cryo-electron microscopy (cryo-EM) and can affect the amount of high-resolution information retained in the image. Yet, common data acquisition approaches in single particle cryo-EM do not take it into account. Here, we demonstrate how the sample thickness can be determined before data acquisition, allowing to identify optimal regions and restrict data collection to images with preserved high-resolution details. This quality over quantity approach, almost entirely eliminates the time- and storage-consuming collection of suboptimal images, which are discarded after a recorded session or during early image processing due to lack of high-resolution information. It maximizes data collection efficiency and lowers the electron microscopy time required per dataset. This strategy is especially useful, if the speed of data collection is restricted by the microscope hardware and software, or if data transfer, data storage and computational power are a bottleneck.SynopsisDetermining sample thickness, a key parameter in single particle cryo-electron microscopy, before data acquisition, and targeting only optimal areas, maximizes the data output from a single particle cryo-electron microscopy session. Scripts and optimized workflows for EPU and SerialEM are presented utilizing this concept.

scholarly journals Practical Experience with Hole-Free Phase Plates for Cryo Electron Microscopy

2016 ◽  
Vol 22 (6) ◽  
pp. 1316-1328 ◽  
Author(s):  
Michael Marko ◽  
Chyongere Hsieh ◽  
Eric Leith ◽  
David Mastronarde ◽  
Sohei Motoki
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Practical Experience ◽  
Phase Plate ◽  
Native State ◽  
Automated Data Collection ◽  
Cryo Electron Microscopy ◽  
Transmission Electron ◽  
Phase Plates ◽  
Set Up

AbstractPhase plate (PP) imaging has proven to be valuable in transmission cryo electron microscopy of unstained, native-state biological specimens. Many PP types have been described, however until the recent implementation of the “hole-free” phase plate (HFPP), imaging has been challenging. We found the HFPP to be simple to construct and to set up in the transmission electron microscopy, but care in implementing automated data collection is needed. Performance may be variable, both initially and over time, thus it is important to monitor and evaluate image quality by observing the power spectrum. We found that while some HFPPs gave transfer to high resolution without CTF oscillation, most reached high resolution when operated with modest defocus.

scholarly journals Single-particle cryo-EM—How did it get here and where will it go

Science ◽  
2018 ◽  
Vol 361 (6405) ◽  
pp. 876-880 ◽  
Author(s):  
Yifan Cheng
Keyword(s):  
Electron Microscopy ◽  
Structural Biology ◽  
Single Particle ◽  
Electron Crystallography ◽  
The Past ◽  
Cryo Electron Microscopy ◽  
Technological Advances ◽  
The Future ◽  
Electron Cryotomography

Cryo–electron microscopy, or simply cryo-EM, refers mainly to three very different yet closely related techniques: electron crystallography, single-particle cryo-EM, and electron cryotomography. In the past few years, single-particle cryo-EM in particular has triggered a revolution in structural biology and has become a newly dominant discipline. This Review examines the fascinating story of its start and evolution over the past 40-plus years, delves into how and why the recent technological advances have been so groundbreaking, and briefly considers where the technique may be headed in the future.

scholarly journals In situ structure determination using single particle cryo-electron microscopy images

2020 ◽  
Author(s):  
Jing Cheng ◽  
Bufan Li ◽  
Long Si ◽  
Xinzheng Zhang
Keyword(s):  
Electron Microscopy ◽  
Structure Determination ◽  
Single Particle ◽  
Structure Refinement ◽  
Target Function ◽  
Target Protein ◽  
Particle Analysis ◽  
Cryo Electron Microscopy ◽  
Tilt Series

AbstractCryo-electron microscopy (cryo-EM) tomography is a powerful tool for in situ structure determination. However, this method requires the acquisition of tilt series, and its time consuming throughput of acquiring tilt series severely slows determination of in situ structures. By treating the electron densities of non-target protein as non-Gaussian distributed noise, we developed a new target function that greatly improves the efficiency of the recognition of the target protein in a single cryo-EM image without acquiring tilt series. Moreover, we developed a sorting function that effectively eliminates the false positive detection, which not only improves the resolution during the subsequent structure refinement procedure but also allows using homolog proteins as models to recognize the target protein. Together, we developed an in situ single particle analysis (isSPA) method. Our isSPA method was successfully applied to solve structures of glycoproteins on the surface of a non-icosahedral virus and Rubisco inside the carboxysome. The cryo-EM data from both samples were collected within 24 hours, thus allowing fast and simple structural determination in situ.

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