Fabrication of carbon films with ∼500 nm holes for cryo-EM with a direct detector device

Single particle electron cryomicroscopy (cryo-EM) is often performed using EM grids coated with a perforated or holey layer of amorphous carbon. Regular arrays of holes enable efficient cryo-EM data collection and several methods for the production of micropatterned holey-carbon film coated grids have been described. However, a new generation of direct detector device (DDD) electron microscope cameras can benefit from hole diameters that are smaller than currently available. Here we extend a previously proposed method involving soft lithography with a poly(dimethylsiloxane) (PDMS) stamp for the production of holey-carbon film coated EM grids. By incorporating electron-beam (e-beam) lithography and modifying the procedure, we are able to produce low-cost high-quality holey-carbon film coated EM grids with ∼500 nm holes spaced 4 μm apart centre-to-centre. We demonstrate that these grids can be used for cryo-EM. Furthermore, we show that by applying image shifts to obtain movies of the carbon regions beside the holes after imaging the holes, the contrast transfer function (CTF) parameters needed for calculation of high-resolution cryo-EM maps with a DDD can be obtained efficiently.     

Two-dimensional crystallization of streptavidin by nonspecific binding to a surface film: study with a scanning electron microscope.

A two-dimensional (2D) crystal of streptavidin has been obtained by a nonspecific binding method. The protein molecules were bound and formed a dense packing on the film of poly(1-benzyl-L-histidine) spread at the surface of protein solution. The surface film was moderately heated to stimulate crystallization of bound streptavidin. A potential of this method for obtaining 2D crystals of soluble proteins is demonstrated. The present 2D crystal structure of streptavidin resembles that previously obtained by specific binding to biotinylated lipid. We show in addition that the 2D array of protein with usual size approximately 50 A can be imaged using a high resolution scanning electron microscope (HR-SEM) and subject to structural analysis at low resolution. Various limitations in HR-SEM degrade considerably the image quality. However, the usability of a bulk plate as specimen support would make HR-SEM a convenient tool, when such a substrate must be considered in application of protein arrays, and if an intrinsic low resolution is acceptable.     

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.     

Two-dimensional crystallization of streptavidin: in pursuit of the molecular origins of structure, morphology, and thermodynamics

The streptavidin two-dimensional (2D) crystallization model has served as a paradigm for molecular self-assembly at interfaces. We have developed quantitative Brewster angle microscopy for the in situ measurement of spatially resolved relative protein surface densities. This allows investigation of both the thermodynamics and morphologies of 2D crystal growth. For crystal structure analysis, we employ TEM on grown crystals transferred to solid substrates. Comparison of results between commercially available streptavidin, recombinant streptavidin, and site-directed streptavidin mutants has provided insight into the protein protein and protein-lipid interactions that underlie 2D crystallization.     

Automatic particle pickup method using a neural network has high accuracy by applying an initial weight derived from eigenimages: a new reference free method for single-particle analysis

The single-particle analysis is a structure-determining method for electron microscope (EM) images which does not require crystal. In this method, the projections are picked up and averaged by the images of similar Euler angles to improve the signal to noise ratio, and then create a 3-D reconstruction. The selection of a large number of particles from the cryo-EM micrographs is a pre-requisite for obtaining a high resolution. To pickup a low-contrast cryo-EM protein image, we have recently found that a three-layer pyramidal-type neural network is successful in detecting such a faint image, which had been difficult to detect by other methods. The connection weights between the input and hidden layers, which work as a matching filter, have revealed that they reflect characters of the particle projections in the training data. The images stored in terms of the connection weights were complex, more similar to the eigenimages which are created by the principal component analysis of the learning images rather than to the averages of the particle projections. When we set the initial learning weights according to the eigenimages in advance, the learning period was able to be shortened to less than half the time of the NN whose initial weights had been set randomly. Further, the pickup accuracy increased from 90 to 98%, and a combination of the matching filters were found to work as an integrated matching filter there. The integrated filters were amazingly similar to averaged projections and can be used directly as references for further two-dimensional averaging. Therefore, this research also presents a brand-new reference-free method for single-particle analysis.     

Robust filtering and particle picking in micrograph images towards 3D reconstruction of purified proteins with cryo-electron microscopy

In order to make a high resolution model of macromolecular structures from cryo-electron microscope (cryo-EM) raw images one has to be precise at every processing step from particle picking to 3D image reconstruction. In this paper we propose a collection of novel methods for filtering cryo-EM images and for automatic picking of particles. These methods have been developed for two cases: (1) when particles can be identified and (2) when particle are not distinguishable. The advantages of these methods are demonstrated in standard purified protein samples and to generalize them we do not use any ad hoc presumption of the geometry of the particle projections. We have also suggested a filtering method to increase the signal-to-noise (S/N) ratio which has proved to be useful for other levels of reconstruction, i.e., finding orientations and 3D model reconstruction.     

Conformational heterogeneity and probability distributions from single-particle cryo-electron microscopy

Single-particle cryo-electron microscopy (cryo-EM) is a technique that takes projection images of biomolecules frozen at cryogenic temperatures. A major advantage of this technique is its ability to image single biomolecules in heterogeneous conformations. While this poses a challenge for data analysis, recent algorithmic advances have enabled the recovery of heterogeneous conformations from the noisy imaging data. Here, we review methods for the reconstruction and heterogeneity analysis of cryo-EM images, ranging from linear-transformation-based methods to nonlinear deep generative models. We overview the dimensionality-reduction techniques used in heterogeneous 3D reconstruction methods and specify what information each method can infer from the data. Then, we review the methods that use cryo-EM images to estimate probability distributions over conformations in reduced subspaces or predefined by atomistic simulations. We conclude with the ongoing challenges for the cryo-EM community.     

Two-dimensional streptavidin crystals: macropatterns and micro-organization

Two dimensional crystals of streptavidin grown on lipid monolayers can be viewed as model systems for the study of phase transitions and morphology. These crystals form a variety of macroscopic morphologies associated with different microscopic crystal structures. Observed morphologies are similar to those found in two-dimensional lipid systems, and growth of the protein arrays is somewhat analogous. Such solid state physical processes as nucleation, transformation between crystal phases, crystal phase coexistence, and roughening have been observed in the streptavidin system. In this review, we highlight observations that cause streptavidin to remain an interesting model system exhibiting a variety of intriguing phenomena.     

Electron crystallography of macromolecular periodic arrays on phospholipid monolayers

Electron crystallography has the potential of yielding structural information equivalent to x-ray diffraction. The major difficulty has been preparing specimens with the required structural order and size for diffraction and imaging in the electron microscope. 2D crystallization on phospholipid monolayers is capable of fulfilling both of these requirements. Crystals can form as a result of specific interactions with a protein's ligand or an analog, suitably linked to a lipid tail; or on a surface of complementary head-group charge. With such choices, the availability of a suitable lipid is limited only by synthetic chemistry. Ultimately, it is the quality and regularity of the protein-protein interactions that determine the crystalline order, as it is with any protein crystal. In the case of streptavidin, the monolayer crystal diffracts beyond 2.5 Å. A 3 Å projection map reconstructed from electron diffraction amplitudes and phases from images shows density which can be interpreted as β-sheets and clusters of side chains. It remains to be shown that the monolayer crystals are flat and diffract as well at high tilt angle as untilted. Technological issues such as charging must be resolved. With parallel advances in data collection and processing, electron crystallography of monolayer macromolecular crystals will eventually take its place beside x-ray crystallography and NMR as a routine and efficient structural technique.     

Structure of HIV-1 Capsid Assemblies by Cryo-electron Microscopy and Iterative Helical Real-space Reconstruction

Cryo-electron microscopy (cryo-EM), combined with image processing, is an increasingly powerful tool for structure determination of macromolecular protein complexes and assemblies. In fact, single particle electron microscopy¹ and two-dimensional (2D) electron crystallography² have become relatively routine methodologies and a large number of structures have been solved using these methods. At the same time, image processing and three-dimensional (3D) reconstruction of helical objects has rapidly developed, especially, the iterative helical real-space reconstruction (IHRSR) method³, which uses single particle analysis tools in conjunction with helical symmetry. Many biological entities function in filamentous or helical forms, including actin filaments⁴, microtubules⁵, amyloid fibers⁶, tobacco mosaic viruses⁷, and bacteria flagella⁸, and, because a 3D density map of a helical entity can be attained from a single projection image, compared to the many images required for 3D reconstruction of a non-helical object, with the IHRSR method, structural analysis of such flexible and disordered helical assemblies is now attainable.In this video article, we provide detailed protocols for obtaining a 3D density map of a helical protein assembly (HIV-1 capsid⁹ is our example), including protocols for cryo-EM specimen preparation, low dose data collection by cryo-EM, indexing of helical diffraction patterns, and image processing and 3D reconstruction using IHRSR. Compared to other techniques, cryo-EM offers optimal specimen preservation under near native conditions. Samples are embedded in a thin layer of vitreous ice, by rapid freezing, and imaged in electron microscopes at liquid nitrogen temperature, under low dose conditions to minimize the radiation damage. Sample images are obtained under near native conditions at the expense of low signal and low contrast in the recorded micrographs. Fortunately, the process of helical reconstruction has largely been automated, with the exception of indexing the helical diffraction pattern. Here, we describe an approach to index helical structure and determine helical symmetries (helical parameters) from digitized micrographs, an essential step for 3D helical reconstruction. Briefly, we obtain an initial 3D density map by applying the IHRSR method. This initial map is then iteratively refined by introducing constraints for the alignment parameters of each segment, thus controlling their degrees of freedom. Further improvement is achieved by correcting for the contrast transfer function (CTF) of the electron microscope (amplitude and phase correction) and by optimizing the helical symmetry of the assembly.     

An adaptation of the Wiener filter suitable for analyzing images of isolated single particles

The Wiener filter is a standard means of optimizing the signal in sums of aligned, noisy images obtained by electron cryo-microscopy (cryo-EM). However, estimation of the resolution-dependent (“spectral”) signal-to-noise ratio (SSNR) from the input data has remained problematic, and error reduction due to specific application of the SSNR term within a Wiener filter has not been reported. Here we describe an adjustment to the Wiener filter for optimal summation of images of isolated particles surrounded by large regions of featureless background, as is typically the case in single-particle cryo-EM applications. We show that the density within the particle area can be optimized, in the least-squares sense, by scaling the SSNR term found in the conventional Wiener filter by a factor that reflects the fraction of the image field occupied by the particle. We also give related expressions that allow the SSNR to be computed for application in this new filter, by incorporating a masking step into a Fourier Ring Correlation (FRC), a standard resolution measure. Furthermore, we show that this masked FRC estimation scheme substantially improves on the accuracy of conventional SSNR estimation methods. We demonstrate the validity of our new approach in numeric tests with simulated data corresponding to realistic cryo-EM imaging conditions. This variation of the Wiener filter and accompanying derivation should prove useful for a variety of single-particle cryo-EM applications, including 3D reconstruction.     

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography

Electron crystallography has evolved as a method that can be used either alternatively or in combination with three-dimensional crystallization and X-ray crystallography to study structure-function questions of membrane proteins, as well as soluble proteins. Screening for two-dimensional (2D) crystals by transmission electron microscopy (EM) is the critical step in finding, optimizing, and selecting samples for high-resolution data collection by cryo-EM. Here we describe the fundamental steps in identifying both large and ordered, as well as small 2D arrays, that can potentially supply critical information for optimization of crystallization conditions.By working with different magnifications at the EM, data on a range of critical parameters is obtained. Lower magnification supplies valuable data on the morphology and membrane size. At higher magnifications, possible order and 2D crystal dimensions are determined. In this context, it is described how CCD cameras and online-Fourier Transforms are used at higher magnifications to assess proteoliposomes for order and size.While 2D crystals of membrane proteins are most commonly grown by reconstitution by dialysis, the screening technique is equally applicable for crystals produced with the help of monolayers, native 2D crystals, and ordered arrays of soluble proteins. In addition, the methods described here are applicable to the screening for 2D crystals of even smaller as well as larger membrane proteins, where smaller proteins require the same amount of care in identification as our examples and the lattice of larger proteins might be more easily identifiable at earlier stages of the screening.Download video file.^{(59M, mov)}     

3D structure of the CD26-ADA complex obtained by cryo-EM and single particle analysis

The specific binding of adenosine deaminase to the multifunctional membrane glycoprotein dipeptidyl peptidase IV is thought to be immunologically relevant for certain regulatory and co-stimulatory processes. In this study we present the 3D structure of the complete CD26-ADA complex obtained by single particle cryo-EM at 22A resolution. ADA binding occurs at the outer edges of the beta-propeller of CD26. Docking calculations of available CD26 and ADA crystal data into the obtained EM density map revealed that the ADA-binding site is stretched across CD26 beta-propeller blades 4 and 5 involving the outermost distal hydrophobic amino acids L294 and V341 but not T440 and K441 as suggested by antibody binding. Though the docking of the ADA orientation appears less significant due to the lack of distinct surface features, non-ambiguous conclusions can be drawn in the combination with earlier indirect non-imaging methods affirming the crucial role of the ADA alpha2-helix for binding.     

Single particle 3D reconstruction for 2D crystal images of membrane proteins

In cases where ultra-flat cryo-preparations of well-ordered two-dimensional (2D) crystals are available, electron crystallography is a powerful method for the determination of the high-resolution structures of membrane and soluble proteins. However, crystal unbending and Fourier-filtering methods in electron crystallography three-dimensional (3D) image processing are generally limited in their performance for 2D crystals that are badly ordered or non-flat. Here we present a single particle image processing approach, which is implemented as an extension of the 2D crystallographic pipeline realized in the 2dx software package, for the determination of high-resolution 3D structures of membrane proteins. The algorithm presented, addresses the low single-to-noise ratio (SNR) of 2D crystal images by exploiting neighborhood correlation between adjacent proteins in the 2D crystal. Compared with conventional single particle processing for randomly oriented particles, the computational costs are greatly reduced due to the crystal-induced limited search space, which allows a much finer search space compared to classical single particle processing. To reduce the considerable computational costs, our software features a hybrid parallelization scheme for multi-CPU clusters and computer with high-end graphic processing units (GPUs). We successfully apply the new refinement method to the structure of the potassium channel MloK1. The calculated 3D reconstruction shows more structural details and contains less noise than the map obtained by conventional Fourier-filtering based processing of the same 2D crystal images.     

TMaCS: A hybrid template matching and classification system for partially-automated particle selection

Selection of particle images from electron micrographs presents a bottleneck in determining the structures of macromolecular assemblies by single particle electron cryomicroscopy (cryo-EM). The problem is particularly important when an experimentalist wants to improve the resolution of a 3D map by increasing by tens or hundreds of thousands of images the size of the dataset used for calculating the map. Although several existing methods for automatic particle image selection work well for large protein complexes that produce high-contrast images, it is well known in the cryo-EM community that small complexes that give low-contrast images are often refractory to existing automated particle image selection schemes. Here we develop a method for partially-automated particle image selection when an initial 3D map of the protein under investigation is already available. Candidate particle images are selected from micrographs by template matching with template images derived from projections of the existing 3D map. The candidate particle images are then used to train a support vector machine, which classifies the candidates as particle images or non-particle images. In a final step in the analysis, the selected particle images are subjected to projection matching against the initial 3D map, with the correlation coefficient between the particle image and the best matching map projection used to assess the reliability of the particle image. We show that this approach is able to rapidly select particle images from micrographs of a rotary ATPase, a type of membrane protein complex involved in many aspects of biology.     

A maximum likelihood approach to two-dimensional crystals

Maximum likelihood (ML) processing of transmission electron microscopy images of protein particles can produce reconstructions of superior resolution due to a reduced reference bias. We have investigated a ML processing approach to images centered on the unit cells of two-dimensional (2D) crystal images. The implemented software makes use of the predictive lattice node tracking in the MRC software, which is used to window particle stacks. These are then noise-whitened and subjected to ML processing. Resulting ML maps are translated into amplitudes and phases for further processing within the 2dx software package. Compared with ML processing for randomly oriented single particles, the required computational costs are greatly reduced as the 2D crystals restrict the parameter search space. The software was applied to images of negatively stained or frozen hydrated 2D crystals of different crystal order. We find that the ML algorithm is not free from reference bias, even though its sensitivity to noise correlation is lower than for pure cross-correlation alignment. Compared with crystallographic processing, the newly developed software yields better resolution for 2D crystal images of lower crystal quality, and it performs equally well for well-ordered crystal images.     

Bacteriophage lambda stabilization by auxiliary protein gpD: timing, location, and mechanism of attachment determined by cryo-EM

We report the cryo-EM structure of bacteriophage lambda and the mechanism for stabilizing the 20-A-thick capsid containing the dsDNA genome. The crystal structure of the HK97 bacteriophage capsid fits most of the T = 7 lambda particle density with only minor adjustment. A prominent surface feature at the 3-fold axes corresponds to the cementing protein gpD, which is necessary for stabilization of the capsid shell. Its position coincides with the location of the covalent cross-link formed in the docked HK97 crystal structure, suggesting an evolutionary replacement of this gene product in lambda by autocatalytic chemistry in HK97. The crystal structure of the trimeric gpD, in which the 14 N-terminal residues required for capsid binding are disordered, fits precisely into the corresponding EM density. The N-terminal residues of gpD are well ordered in the cryo-EM density, adding a strand to a beta-sheet formed by the capsid proteins and explaining the mechanism of particle stabilization.     

Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of natural proteins have a molecular mass between 40 - 200 kDa^1,2, a robust and high-throughput method with a nanometer resolution capability is needed. Negative staining (NS) electron microscopy (EM) is an easy, rapid, and qualitative approach which has frequently been used in research laboratories to examine protein structure and protein-protein interactions. Unfortunately, conventional NS protocols often generate structural artifacts on proteins, especially with lipoproteins that usually form presenting rouleaux artifacts. By using images of lipoproteins from cryo-electron microscopy (cryo-EM) as a standard, the key parameters in NS specimen preparation conditions were recently screened and reported as the optimized NS protocol (OpNS), a modified conventional NS protocol ³ . Artifacts like rouleaux can be greatly limited by OpNS, additionally providing high contrast along with reasonably high‐resolution (near 1 nm) images of small and asymmetric proteins. These high-resolution and high contrast images are even favorable for an individual protein (a single object, no average) 3D reconstruction, such as a 160 kDa antibody, through the method of electron tomography^4,5. Moreover, OpNS can be a high‐throughput tool to examine hundreds of samples of small proteins. For example, the previously published mechanism of 53 kDa cholesteryl ester transfer protein (CETP) involved the screening and imaging of hundreds of samples ⁶. Considering cryo-EM rarely successfully images proteins less than 200 kDa has yet to publish any study involving screening over one hundred sample conditions, it is fair to call OpNS a high-throughput method for studying small proteins. Hopefully the OpNS protocol presented here can be a useful tool to push the boundaries of EM and accelerate EM studies into small protein structure, dynamics and mechanisms.