Papers to Review
Cryo-electron microscopy (cryo-EM) of single-particle specimens is used to determine the structure of proteins and macromolecular complexes without the need for crystals. Recent advances in detector technology and software algorithms now allow images of unprecedented quality to be recorded and structures to be determined at near-atomic resolution. However, compared with X-ray crystallography, cryo-EM is a young technique with distinct challenges. This primer explains the different steps and considerations involved in structure determination by single-particle cryo-EM to provide an overview for scientists wishing to understand more about this technique and the interpretation of data obtained with it, as well as a starting guide for new practitioners.
To fully understand biological processes from the metabolism of a bacterium to the operation of a human brain, it is necessary to know the three-dimensional (3D) spatial arrangement and dynamics of the constituent molecules, how they assemble into complex molecular machines, and how they form functional organelles, cells, and tissues. The methods of X-ray crystallography and NMR spectroscopy can provide detailed information on molecular structure and dynamics. At the cellular level, optical microscopy reveals the spatial distribution and dynamics of molecules tagged with fluorophores. Electron microscopy (EM) overlaps with these approaches, covering a broad range from atomic to cellular structures. The development of cryogenic methods has enabled EM imaging to provide snapshots of biological molecules and cells trapped in a close to native, hydrated state.
Cryo-electron microscopy techniques and computational 3-D reconstruction of macromolecular assemblies are tightly linked tools in modern structural biology. This symbiosis has produced vast amounts of detailed information on the structure and function of biological macromolecules. Typically, one of two fundamentally different strategies is used depending on the specimens and their environment. A: 3-D reconstruction based on repetitive and structurally identical unit cells that allow for averaging, and B: tomographic 3-D reconstructions where tilt-series between approximately ± 60 and ± 70° at small angular increments are collected from highly complex and flexible structures that are beyond averaging procedures, at least during the first round of 3-D reconstruction. Strategies of group A are averaging-based procedures and collect large number of 2-D projections at different angles that are computationally aligned, averaged together, and back-projected in 3-D space to reach a most complete 3-D dataset with high resolution, today often down to atomic detail. Evidently, success relies on structurally repetitive particles and an aligning procedure that unambiguously determines the angular relationship of all 2-D projections with respect to each other. The alignment procedure of small particles may rely on their packing into a regular array such as a 2-D crystal, an icosahedral (viral) particle, or a helical assembly. Critically important for cryo-methods, each particle will only be exposed once to the electron beam, making these procedures optimal for highest-resolution studies where beam-induced damage is a significant concern. In contrast, tomographic 3-D reconstruction procedures (group B) do not rely on averaging, but collect an entire dataset from the very same structure of interest. Data acquisition requires collecting a large series of tilted projections at angular increments of 1-2° or less and a tilt range of ± 60° or more. Accordingly, tomographic data collection exposes its specimens to a large electron dose, which is particularly problematic for frozen-hydrated samples. Currently, cryo-electron tomography is a rapidly emerging technology, on one end driven by the newest developments of hardware such as super-stabile microscopy stages as well as the latest generation of direct electron detectors and cameras. On the other end, success also strongly depends on new software developments on all kinds of fronts such as tilt-series alignment and back-projection procedures that are all adapted to the very low-dose and therefore very noisy primary data. Here, we will review the status quo of cryo-electron microscopy and discuss the future of cellular cryo-electron tomography from data collection to data analysis, CTF-correction of tilt-series, post-tomographic sub-volume averaging, and 3-D particle classification. We will also discuss the pros and cons of plunge freezing of cellular specimens to vitrified sectioning procedures and their suitability for post-tomographic volume averaging despite multiple artifacts that may distort specimens to some degree.
Structural analysis of macromolecular assemblies in their physiological environment is a challenging task that is instrumental in answering fundamental questions in cellular and molecular structural biology. The continuous development of computational and analytical tools for cryo-electron tomography (cryo-ET) enables the study of these assemblies at a resolution of a few nanometers. Through the implementation of thinning procedures, cryo-ET can now be applied to the reconstruction of macromolecular structures located inside thick regions of vitrified cells and tissues, thus becoming a central tool for structural determinations in various biological disciplines. Here, we focus on the successful in situ applications of cryo-ET to reveal structures of macromolecular complexes within eukaryotic cells.
Single particle electron microscopy (EM), of both negative stained or frozen hydrated biological samples, has become a versatile tool in structural biology. In recent years, this method has achieved great success in studying structures of proteins and macromolecular complexes. Compared with electron cryomicroscopy (cryoEM), in which frozen hydrated protein samples are embedded in a thin layer of vitreous ice, negative staining is a simpler sample preparation method in which protein samples are embedded in a thin layer of dried heavy metal salt to increase specimen contrast. The enhanced contrast of negative stain EM allows examination of relatively small biological samples. In addition to determining three-dimensional (3D) structure of purified proteins or protein complexes, this method can be used for much broader purposes. For example, negative stain EM can be easily used to visualize purified protein samples, obtaining information such as homogeneity/heterogeneity of the sample, formation of protein complexes or large assemblies, or simply to evaluate the quality of a protein preparation. In this video article, we present a complete protocol for using an EM to observe negatively stained protein sample, from preparing carbon coated grids for negative stain EM to acquiring images of negatively stained sample in an electron microscope operated at 120kV accelerating voltage. These protocols have been used in our laboratory routinely and can be easily followed by novice users.
Many of the electron microscopy (EM) samples that are analyzed by single-particle reconstruction are flexible macromolecular assemblies that adopt multiple structural states in their functioning. Consequently, EM samples often contain a mixture of different structural states. This structural variability has long been regarded as a severe hindrance for single-particle analysis because the combination of projections from different structures into a single reconstruction may cause severe artifacts. This chapter reviews recent developments in image processing that may turn structural variability from an obstacle into an advantage. Modern algorithms now allow classifying projection images according to their underlying three-dimensional (3D) structures, so that multiple reconstructions may be obtained from a single data set. This places 3D-EM in a unique position to study the intricate dynamics of functioning molecular assemblies.
Online Video Courses
- SRAMM Workshops
- Jensen Lab Lectures
- Besides the previously advertised FTP site (see #2 above) the recorded lectures and slides of our 2017 cryo-EM course are now also available from LMB’s new scientific training website. We hope that these resources will be useful in the training of newcomers to the field. Lectures on other topics (e.g. X-ray crystallography) will be added to this site at a later date.
Automation Tools
- Automation in single-particle electron microscopy connecting the pieces. Throughout the history of single-particle electron microscopy (EM), automated technologies have seen varying degrees of emphasis and development, usually depending upon the contemporary demands of the field. We are currently faced with increasingly sophisticated devices for specimen preparation, vast increases in the size of collected data sets, comprehensive algorithms for image processing, sophisticated tools for quality assessment, and an influx of interested scientists from outside the field who might lack the skills of experienced microscopists. This situation places automated techniques in high demand. In this chapter, we provide a generic definition of and discuss some of the most important advances in automated approaches to specimen preparation, grid handling, robotic screening, microscope calibrations, data acquisition, image processing, and computational infrastructure. Each section describes the general problem and then provides examples of how that problem has been addressed through automation, highlighting available processing packages, and sometimes describing the particular approach at the National Resource for Automated Molecular Microscopy (NRAMM). We contrast the more familiar manual procedures with automated approaches, emphasizing breakthroughs as well as current limitations. Finally, we speculate on future directions and improvements in automated technologies. Our overall goal is to present automation as more than simply a tool to save time. Rather, we aim to illustrate that automation is a comprehensive and versatile strategy that can deliver biological information on an unprecedented scale beyond the scope available with classical manual approaches.
- Leginon Wiki
- Appion Wiki
- An Introduction to Appion