Zernike phase contrast cryo-electron tomography of whole mounted frozen cells

Cryo-electron tomography of frozen hydrated cells has provided cell biologists with an indispensable tool for delineating three-dimensional arrangements of cellular ultrastructure. To avoid the damage induced by electron irradiation, images of frozen hydrated biological specimens are generally acquired under low-dose conditions, resulting in weakly contrasted images that are difficult to interpret, and in which ultrastructural details remain ambiguous. Zernike phase contrast transmission electron microscopy can improve contrast, and can also fix a fatal problem related to the inherent low contrast of conventional electron microscopy, namely, image modulation due to the unavoidable setting of deep defocus. In this study, we applied cryo-electron tomography enhanced with a Zernike phase plate, which avoids image modulation by allowing in-focus setting. The Zernike phase contrast cryo-electron tomography has a potential to suppress grainy background generation. Due to the smoother background in comparison with defocus phase contrast cryo-electron tomography, Zernike phase contrast cryo-electron tomography could yield higher visibility for particulate or filamentous ultrastructure inside the cells, and allowed us to clearly recognize membrane protein structures.     

Tuning of the Zernike phase-plate for visualization of detailed ultrastructure in complex biological specimens

In order to acquire phase-contrast images with adequate contrast, conventional TEM requires large amount of defocus. Increasing the defocus improves the low-frequency components but attenuates the high-frequency ones. On the other hand, Zernike phase-contrast TEM (ZPC-TEM) can recover low-frequency components without losing the high-frequency ones under in-focus conditions. ZPC-TEM however, has another problem, especially in imaging of complex biological specimens such as cells and tissues; strong halos appear around specimen structures, and these halos hinder the interpretation of images. Due to this problem, the application of ZPC-TEM has been restricted to imaging of smaller particles. In order to improve the halo appearance, we fabricated a new quarter-wave thin film phase-plate with a smaller central hole and tested it on vitreous biological specimens. ZPC-TEM with the new plate could successfully visualize, in in-focus images, the intracellular fine features of cultured cells and brain tissues. This result indicates that reduction of the central hole diameter makes ZPC-TEM applicable on size scales ranging from protein particles to tissue sections. The application of ZPC-TEM to vitreous biological specimens will be a powerful method to advance the new field of imaging science for ultrastructures in close-to-physiological state.     

Automated image acquisition for single-particle reconstruction using p97 as the biological sample

We have used Leginon, a fully automatic system capable of acquiring cryo-electron micrographs, to collect data of single particles, specifically of the AAA ATPase p97. The images were acquired under low-dose conditions and required no operator intervention other than the initial setup and periodic refilling of the cold-stage dewar. Each image was acquired at two different defocus values. Two-dimensional projection maps of p97 were calculated from these data and compared to results previously obtained using the conventional manual data collection methods to film. The results demonstrate that Leginon performs as well as an experienced microscopist for the acquisition of single-particle data. The general advantages of automation are discussed.     

Improved specimen reconstruction by Hilbert phase contrast tomography

The low signal-to-noise ratio (SNR) in images of unstained specimens recorded with conventional defocus phase contrast makes it difficult to interpret 3D volumes obtained by electron tomography (ET). The high defocus applied for conventional tilt series generates some phase contrast but leads to an incomplete transfer of object information. For tomography of biological weak-phase objects, optimal image contrast and subsequently an optimized SNR are essential for the reconstruction of details such as macromolecular assemblies at molecular resolution. The problem of low contrast can be partially solved by applying a Hilbert phase plate positioned in the back focal plane (BFP) of the objective lens while recording images in Gaussian focus. Images recorded with the Hilbert phase plate provide optimized positive phase contrast at low spatial frequencies, and the contrast transfer in principle extends to the information limit of the microscope. The antisymmetric Hilbert phase contrast (HPC) can be numerically converted into isotropic contrast, which is equivalent to the contrast obtained by a Zernike phase plate. Thus, in-focus HPC provides optimal structure factor information without limiting effects of the transfer function. In this article, we present the first electron tomograms of biological specimens reconstructed from Hilbert phase plate image series. We outline the technical implementation of the phase plate and demonstrate that the technique is routinely applicable for tomography. A comparison between conventional defocus tomograms and in-focus HPC volumes shows an enhanced SNR and an improved specimen visibility for in-focus Hilbert tomography.     

Accurate determination of local defocus and specimen tilt in electron microscopy

Accurate knowledge of defocus and tilt parameters is essential for the determination of three-dimensional protein structures at high resolution using electron microscopy. We present two computer programs, CTFFIND3 and CTFTILT, which determine defocus parameters from images of untilted specimens, as well as defocus and tilt parameters from images of tilted specimens, respectively. Both programs use a simple algorithm that fits the amplitude modulations visible in a power spectrum with a calculated contrast transfer function (CTF). The background present in the power spectrum is calculated using a low-pass filter. The background is then subtracted from the original power spectrum, allowing the fitting of only the oscillatory component of the CTF. CTFTILT determines specimen tilt parameters by measuring the defocus at a series of locations on the image while constraining them to a single plane. We tested the algorithm on images of two-dimensional crystals by comparing the results with those obtained using crystallographic methods. The images also contained contrast from carbon support film that added to the visibility of the CTF oscillations. The tests suggest that the fitting procedure is able to determine the image defocus with an error of about 10nm, whereas tilt axis and tilt angle are determined with an error of about 2 degrees and 1 degrees, respectively. Further tests were performed on images of single protein particles embedded in ice that were recorded from untilted or slightly tilted specimens. The visibility of the CTF oscillations from these images was reduced due to the lack of a carbon support film. Nevertheless, the test results suggest that the fitting procedure is able to determine image defocus and tilt angle with errors of about 100 nm and 6 degrees, respectively.     

FASTDEF: Fast defocus and astigmatism estimation for high-throughput transmission electron microscopy

In this work we present a fast and automated algorithm for estimating the contrast transfer function (CTF) of a transmission electron microscope. The approach is very suitable for High Throughput work because: (a) it does not require any initial defocus estimation, (b) it is almost an order of magnitude faster than existing approaches, (c) it opens the way to well-defined extensions to the estimation of higher order aberrations, at the same time that provides defocus and astigmatism estimations comparable in accuracy to well established methods, such as Xmipp and CTFFIND3 approaches. The new algorithm is based on obtaining the wrapped modulating phase of the power spectra density pattern by the use of a quadrature filter. This phase is further unwrapped in order to obtain the continuous and smooth absolute phase map; then a Zernike polynomial fitting is performed and the defocus and astigmatism parameters are determined. While the method does not require an initial estimation of the defocus parameters or any non-linear optimization procedure, these approaches can be used if further refinement is desired. Results of the CTF estimation method are presented for standard negative stained images, cryo-electron microscopy images in the absence of carbon support, as well as micrographs with only ice. Additionally, we have also tested the proposed method with micrographs acquired from tilted and untilted samples, obtaining good results. The algorithm is freely available as a part of the Xmipp package [http://xmipp.cnb.csic.es].     

3.9 ? structure of the nucleosome core particle determined by phase-plate cryo-EM

The Volta phase plate is a recently developed electron cryo-microscopy (cryo-EM) device that enables contrast enhancement of biological samples. Here we have evaluated the potential of combining phase-plate imaging and single particle analysis to determine the structure of a small protein–DNA complex. To test the method, we made use of a 200 kDa Nucleosome Core Particle (NCP) reconstituted with 601 DNA for which a high-resolution X-ray crystal structure is known. We find that the phase plate provides a significant contrast enhancement that permits individual NCPs and DNA to be clearly identified in amorphous ice. The refined structure from 26,060 particles has an overall resolution of 3.9 Å and the density map exhibits structural features consistent with the estimated resolution, including clear density for amino acid side chains and DNA features such as the phosphate backbone. Our results demonstrate that phase-plate cryo-EM promises to become an important method to determine novel near-atomic resolution structures of small and challenging samples, such as nucleosomes in complex with nucleosome-binding factors.     

Symmetry-adapted spherical harmonics method for high-resolution 3D single-particle reconstructions

Three-dimensional (3D) reconstruction is the last and an essential step toward high-resolution structural determination in single-particle cryo-electron microscopy (cryoEM). We have implemented a new algorithm for reconstructing 3D structures of macromolecular complexes with icosahedral symmetry from cryoEM images. Icosahedral symmetry-adapted functions (ISAFs) are used to interpolate structural factors in the reciprocal space to generate a 3D reconstruction in spherical coordinates. In our implementation, we introduced a recursive method for deriving higher order ISAFs from three lower order seed functions. We demonstrate improvements of our new method in both the noise suppression and the effective resolution in 3D reconstruction over the commonly used Fourier-Bessel synthesis method introduced by Crowther et al. three decades ago. Our 3D reconstruction method can be extended to macromolecular complexes with other symmetry types and is thus likely to impact future high-resolution cryoEM single-particle reconstruction efforts in general.     

Retrofit implementation of Zernike phase plate imaging for cryo-TEM

In-focus phase-plate imaging is particularly beneficial for cryo-TEM because it offers a substantial overall increase in image contrast, without an electron dose penalty, and it simplifies image interpretation. We show how phase-plate cryo-TEM can be implemented with an appropriate existing TEM, and provide a basic practical introduction to use of thin-film (carbon) phase plates. We point out potential pitfalls of phase-plate operation, and discuss solutions. We provide information on evaluating a particular TEM for its suitability.     

Automatic CTF correction for single particles based upon multivariate statistical analysis of individual power spectra

Three-dimensional electron cryomicroscopy of randomly oriented single particles is a method that is suitable for the determination of three-dimensional structures of macromolecular complexes at molecular resolution. However, the electron-microscopical projection images are modulated by a contrast transfer function (CTF) that prevents the calculation of three-dimensional reconstructions of biological complexes at high resolution from uncorrected images. We describe here an automated method for the accurate determination and correction of the CTF parameters defocus, twofold astigmatism and amplitude-contrast proportion from single-particle images. At the same time, the method allows the frequency-dependent signal decrease (B factor) and the non-convoluted background signal to be estimated. The method involves the classification of the power spectra of single-particle images into groups with similar CTF parameters; this is done by multivariate statistical analysis (MSA) and hierarchically ascending classification (HAC). Averaging over several power spectra generates class averages with enhanced signal-to-noise ratios. The correct CTF parameters can be deduced from these class averages by applying an iterative correlation procedure with theoretical CTF functions; they are then used to correct the raw images. Furthermore, the method enables the tilt axis of the sample holder to be determined and allows the elimination of individual poor-quality images that show high drift or charging effects.     

Historical background: Why is it important to improve automated particle selection methods?

A current trend in single-particle electron microscopy is to compute three-dimensional reconstructions with ever-increasing numbers of particles in the data sets. Since manual--or even semi-automated--selection of particles represents a major bottleneck when the data set exceeds several thousand particles, there is growing interest in developing automatic methods for selecting images of individual particles. Except in special cases, however, it has proven difficult to achieve the degree of efficiency and reliability that would make fully automated particle selection a useful tool. The simplest methods such as cross correlation (i.e., matched filtering) do not perform well enough to be used for fully automated particle selection. Geometric properties (area, perimeter-to-area ratio, etc.) and the integrated "mass" of candidate particles are additional factors that could improve automated particle selection if suitable methods of contouring particles could be developed. Another suggestion is that data be always collected as pairs of images, the first taken at low defocus (to capture information at the highest possible resolution) and the second at very high defocus (to improve the visibility of the particle). Finally, it is emphasized that well-annotated, open-access data sets need to be established in order to encourage the further development and validation of methods for automated particle selection.     

CTF determination and correction for low dose tomographic tilt series

The resolution of cryo-electron tomography can be limited by the first zero of the microscope’s contrast transfer function (CTF). To achieve higher resolution, it is critical to determine the CTF and correct its phase inversions. However, the extremely low signal-to-noise ratio (SNR) and the defocus gradient in the projections of tilted specimens make this process challenging. Two programs, CTFPLOTTER and CTFPHASEFLIP, have been developed to address these issues. CTFPLOTTER obtains a 1D power spectrum by periodogram averaging and rotational averaging and it estimates the noise background with a novel approach, which uses images taken with no specimen. The background-subtracted 1D power spectra from image regions at different defocus values are then shifted to align their first zeros and averaged together. This averaging improves the SNR sufficiently that it becomes possible to determine the defocus for subsets of the tilt series rather than just the entire series. CTFPHASEFLIP corrects images line-by-line by inverting phases appropriately in thin strips of the image at nearly constant defocus. CTF correction by these methods is shown to improve the resolution of aligned, averaged particles extracted from tomograms. However, some restoration of Fourier amplitudes at high frequencies is important for seeing the benefits from CTF correction.     

Recognition and separation of single particles with size variation by statistical analysis of their images

Macromolecules may occupy conformations with structural differences that cannot be resolved biochemically. The separation of mixed molecular populations is a pressing problem in single-particle analysis. Until recently, the task of distinguishing small structural variations was intractable, but developments in cryo-electron microscopy hardware and software now make it possible to address this problem. We have developed a general strategy for recognizing and separating structures of variable size from cryo-electron micrographs of single particles. The method uses a combination of statistical analysis and projection matching to multiple models. Identification of size variations by multivariate statistical analysis was used to do an initial separation of the data and generate starting models by angular reconstitution. Refinement was performed using alternate projection matching to models and angular reconstitution of the separated subsets. The approach has been successful at intermediate resolution, taking it within range of resolving secondary structure elements of proteins. Analysis of simulated and real data sets is used to illustrate the problems encountered and possible solutions. The strategy developed was used to resolve the structures of two forms of a small heat shock protein (Hsp26) that vary slightly in diameter and subunit packing.     

A Bayesian view on cryo-EM structure determination

Three-dimensional (3D) structure determination by single-particle analysis of cryo-electron microscopy (cryo-EM) images requires many parameters to be determined from extremely noisy data. This makes the method prone to overfitting, that is, when structures describe noise rather than signal, in particular near their resolution limit where noise levels are highest. Cryo-EM structures are typically filtered using ad hoc procedures to prevent overfitting, but the tuning of arbitrary parameters may lead to subjectivity in the results. I describe a Bayesian interpretation of cryo-EM structure determination, where smoothness in the reconstructed density is imposed through a Gaussian prior in the Fourier domain. The statistical framework dictates how data and prior knowledge should be combined, so that the optimal 3D linear filter is obtained without the need for arbitrariness and objective resolution estimates may be obtained. Application to experimental data indicates that the statistical approach yields more reliable structures than existing methods and is capable of detecting smaller classes in data sets that contain multiple different structures.     

Visualization of alpha-helical features in a density map constructed using 9 molecular images of the 1.8 MDa icosahedral core of pyruvate dehydrogenase

Strategies to achieve the highest resolutions in structures of protein complexes determined by cryo-electron microscopy generally involve averaging information from large numbers of individual molecular images. However, significant limitations are posed by heterogeneity in image quality and in protein conformation that are inherent to large data sets of images. Here, we demonstrate that the combination of iterative refinement and stringent molecular sorting is an effective method to obtain substantial improvements in map quality of the 1.8 MDa icosahedral catalytic core of the pyruvate dehydrogenase complex from Bacillus stearothermophilus. From a starting set of 42,945 images of the core complex, we show that using only the best 139 particles in the data set produces a map that is superior to those constructed with greater numbers of images, and that the location of many of the alpha-helices in the structure can be unambiguously visualized in a map constructed from as few as 9 particles.     

Automatic particle selection: results of a comparative study

Manual selection of single particles in images acquired using cryo-electron microscopy (cryoEM) will become a significant bottleneck when datasets of a hundred thousand or even a million particles are required for structure determination at near atomic resolution. Algorithm development of fully automated particle selection is thus an important research objective in the cryoEM field. A number of research groups are making promising new advances in this area. Evaluation of algorithms using a standard set of cryoEM images is an essential aspect of this algorithm development. With this goal in mind, a particle selection "bakeoff" was included in the program of the Multidisciplinary Workshop on Automatic Particle Selection for cryoEM. Twelve groups participated by submitting the results of testing their own algorithms on a common dataset. The dataset consisted of 82 defocus pairs of high-magnification micrographs, containing keyhole limpet hemocyanin particles, acquired using cryoEM. The results of the bakeoff are presented in this paper along with a summary of the discussion from the workshop. It was agreed that establishing benchmark particles and using bakeoffs to evaluate algorithms are useful in promoting algorithm development for fully automated particle selection, and that the infrastructure set up to support the bakeoff should be maintained and extended to include larger and more varied datasets, and more criteria for future evaluations.     

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.     

Zernike phase contrast electron microscopy of ice-embedded influenza A virus

The ultrastructure of the frozen-hydrated influenza A virus was examined by Zernike phase contrast electron microscopy. Using this new microscopy, not only lipid bilayers but also individual glycoprotein spikes on viral envelopes were clearly resolved with high contrast in micrographs taken in focus. In addition to spherical and elongated virions, three other classes of virions were distinguished on the basis of the features of their viral envelope: virions with a complete matrix layer, which were the most predominant, virions with a partial matrix layer, and virions with no matrix layer under the lipid bilayer. About 450 glycoprotein spikes were present in an average-sized spherical virion. Eight ribonucleoprotein complexes, that is, a central one surrounded by seven others, were distinguished in one viral particle. Thus, Zernike phase contrast electron microscopy is a powerful tool for resolving the ultrastructure of viruses, because it enables high-contrast images of ice-embedded particles free of contrast transfer function artifacts that can be a problem in conventional cryo-electron microscopy.     

Human tripeptidyl peptidase II: a gentle giant

Molecular structures can serve to either validate or rule out existing hypotheses, and they can also spawn new, deeper proposals about biochemical mechanism. In this issue of Structure, Sch?negge et al. use single-particle cryo-electron microscopy and flexible docking to examine the function of human tripeptidyl peptidase II, including the role of conformational changes in enzyme activation.