Project description:Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved automated acquisition strategies, preparative techniques that expand the possibilities of what the electron microscope can image at high-resolution using cryo-ET and new subtomogram averaging software. Additionally, data acquisition has become increasingly streamlined, making it more accessible to many users. The SARS-CoV-2 pandemic has further accelerated remote cryo-electron microscopy (cryo-EM) data collection, especially for single-particle cryo-EM, in many facilities globally, providing uninterrupted user access to state-of-the-art instruments during the pandemic. With the recent advances in Tomo5 (software for 3D electron tomography), remote cryo-ET data collection has become robust and easy to handle from anywhere in the world. This article aims to provide a detailed walk-through, starting from the data collection setup in the tomography software for the process of a (remote) cryo-ET data collection session with detailed troubleshooting. The (remote) data collection protocol is further complemented with the workflow for structure determination at near-atomic resolution by subtomogram averaging with emClarity, using apoferritin as an example.
Project description:Macromolecular complexes are intrinsically flexible and often challenging to purify for structure determination by single-particle cryo-electron microscopy (cryo-EM). Such complexes can be studied by cryo-electron tomography (cryo-ET) combined with subtomogram alignment and classification, which in exceptional cases achieves subnanometer resolution, yielding insight into structure-function relationships. However, it remains challenging to apply this approach to specimens that exhibit conformational or compositional heterogeneity or are present in low abundance. To address this, we developed emClarity ( https://github.com/bHimes/emClarity/wiki ), a GPU-accelerated image-processing package featuring an iterative tomographic tilt-series refinement algorithm that uses subtomograms as fiducial markers and a 3D-sampling-function-compensated, multi-scale principal component analysis classification method. We demonstrate that our approach offers substantial improvement in the resolution of maps and in the separation of different functional states of macromolecular complexes compared with current state-of-the-art software.
Project description:Structures of macromolecules in their native state provide unique unambiguous insights into their functions. Cryo-electron tomography combined with subtomogram averaging demonstrated the power to solve such structures in situ at resolutions in the range of 3 Angstrom for some macromolecules. In order to be applicable to the structural determination of the majority of macromolecules observable in cells in limited amounts, processing of tomographic data has to be performed in a high-throughput manner. Here we present TomoBEAR-a modular configurable workflow engine for streamlined processing of cryo-electron tomographic data for subtomogram averaging. TomoBEAR combines commonly used cryo-EM packages with reasonable presets to provide a transparent ("white box") approach for data management and processing. We demonstrate applications of TomoBEAR to two data sets of purified macromolecular targets, to an ion channel RyR1 in a membrane, and the tomograms of plasma FIB-milled lamellae and demonstrate the ability to produce high-resolution structures. TomoBEAR speeds up data processing, minimizes human interventions, and will help accelerate the adoption of in situ structural biology by cryo-ET. The source code and the documentation are freely available.
Project description:Electron cryo-tomography (cryo-ET) is a technique that is used to produce 3D pictures (tomograms) of complex objects such as asymmetric viruses, cellular organelles or whole cells from a series of tilted electron cryo-microscopy (cryo-EM) images. Averaging of macromolecular complexes found within tomograms is known as subtomogram averaging, and this technique allows structure determination of macromolecular complexes in situ. Subtomogram averaging is also gaining in popularity for the calculation of initial models for single-particle analysis. We describe herein a protocol for subtomogram averaging from cryo-ET data using the RELION software (http://www2.mrc-lmb.cam.ac.uk/relion). RELION was originally developed for cryo-EM single-particle analysis, and the subtomogram averaging approach presented in this protocol has been implemented in the existing workflow for single-particle analysis so that users may conveniently tap into existing capabilities of the RELION software. We describe how to calculate 3D models for the contrast transfer function (CTF) that describe the transfer of information in the imaging process, and we illustrate the results of classification and subtomogram averaging refinement for cryo-ET data of purified hepatitis B capsid particles and Saccharomyces cerevisiae 80S ribosomes. Using the steps described in this protocol, along with the troubleshooting and optimization guidelines, high-resolution maps can be obtained in which secondary structure elements are resolved subtomogram.
Project description:Cryo-electron tomography and subtomogram averaging (STA) has developed rapidly in recent years. It provides structures of macromolecular complexes in situ and in cellular context at or below subnanometer resolution and has led to unprecedented insights into the inner working of molecular machines in their native environment, as well as their functional relevant conformations and spatial distribution within biological cells or tissues. Given the tremendous potential of cryo-electron tomography STA in in situ structural cell biology, we previously developed emClarity, a graphics processing unit-accelerated image-processing software that offers STA and classification of macromolecular complexes at high resolution. However, the workflow remains challenging, especially for newcomers to the field. In this protocol, we describe a detailed workflow, processing and parameters associated with each step, from initial tomography tilt-series data to the final 3D density map, with several features unique to emClarity. We use four different samples, including human immunodeficiency virus type 1 Gag assemblies, ribosome and apoferritin, to illustrate the procedure and results of STA and classification. Following the processing steps described in this protocol, along with a comprehensive tutorial and guidelines for troubleshooting and parameter optimization, one can obtain density maps up to 2.8 Å resolution from six tilt series by cryo-electron tomography STA.
Project description:Cryo-electron tomography (cryo-ET) allows cellular ultrastructures and macromolecular complexes to be imaged in three-dimensions in their native environments. Cryo-electron tomograms are reconstructed from projection images taken at defined tilt-angles. In order to recover high-resolution information from cryo-electron tomograms, it is necessary to measure and correct for the contrast transfer function (CTF) of the microscope. Most commonly, this is performed using protocols that approximate the sample as a two-dimensional (2D) plane. This approximation accounts for differences in defocus and therefore CTF across the tilted sample. It does not account for differences in defocus of objects at different heights within the sample; instead, a 3D approach is required. Currently available approaches for 3D-CTF correction are computationally expensive and have not been widely implemented. Here we simulate the benefits of 3D-CTF correction for high-resolution subtomogram averaging, and present a user-friendly, computationally-efficient 3D-CTF correction tool, NovaCTF, that is compatible with standard tomogram reconstruction workflows in IMOD. We validate the approach on synthetic data and test it using subtomogram averaging of real data. Consistent with our simulations, we find that 3D-CTF correction allows high-resolution structures to be obtained with much smaller subtomogram averaging datasets than are required using 2D-CTF. We also show that using equivalent dataset sizes, 3D-CTF correction can be used to obtain higher-resolution structures. We present a 3.4Å resolution structure determined by subtomogram averaging.
Project description:Human infectious disease is classified into five etiologies: bacterial, viral, parasitic, fungal, and prion. Viral infections are unique in that they recruit human cellular machinery to replicate themselves and spread infection. The number of viruses causing human disease is vast, and viruses can be broadly categorized by their structures. Many viruses, such as influenza, appear to be amorphous particles, whereas others, such as herpes simplex virus, rhinovirus, dengue virus, and adenovirus, have roughly symmetric structural components. Icosahedral viruses have been a target of electron microscopists for years, and they were some of the first objects to be reconstructed three-dimensionally from electron micrographs. The ease with which highly purified and conformationally uniform virus samples can be produced makes them an ideal target structural studies. Apart from their biological significance, these virus samples have played a pivotal role in the development of new methodologies in the field of molecular biology as well as in cryo-electron microscopy and cryo-electron tomography.
Project description:Subtomogram averaging (STA) is a powerful image processing technique in electron tomography used to determine the 3D structure of macromolecular complexes in their native environments. It is a fast growing technique with increasing importance in structural biology. The computational aspect of STA is very complex and depends on a large number of variables. We noticed a lack of detailed guides for STA processing. Also, current publications in this field often lack a documentation that is practical enough to reproduce the results with reasonable effort, which is necessary for the scientific community to grow. We therefore provide a complete, detailed, and fully reproducible processing protocol that covers all aspects of particle picking and particle alignment in STA. The command line-based workflow is fully based on the popular Dynamo software for STA. Within this workflow, we also demonstrate how large parts of the processing pipeline can be streamlined and automatized for increased throughput. This protocol is aimed at users on all levels. It can be used for training purposes, or it can serve as basis to design user-specific projects by taking advantage of the flexibility of Dynamo by modifying and expanding the given pipeline. The protocol is successfully validated using the Electron Microscopy Public Image Archive (EMPIAR) database entry 10164 from immature HIV-1 virus-like particles (VLPs) that describe a geometry often seen in electron tomography.
Project description:Cryo-electron tomography (cryo-ET) with subtomogram averaging (STA) has emerged as a key tool for determining macromolecular structure(s) in vitro and in situ. However, processing cryo-ET data with STA currently requires significant user expertise. Recent efforts have streamlined several steps in STA workflows; however, particle picking remains a time-consuming bottleneck for many projects and requires considerable user input. Here, we present several strategies for the time-efficient and accurate picking of membrane-associated particles using the COPII inner coat as a case study. We also discuss a range of particle cleaning solutions to remove both poor quality and false-positive particles from STA datasets. We provide a step-by-step guide and the necessary scripts for users to independently carry out the particle picking and cleaning strategies discussed.