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.     

Model-based particle picking for cryo-electron microscopy

We describe an algorithm for finding particle images in cryo-EM micrographs. The algorithm starts from a crude 3D map of the target particle, computed from a relatively small number of manually picked images, and then projects the map in many different directions to give synthetic 2D templates. The templates are clustered and averaged and then cross-correlated with the micrographs. A probabilistic model of the imaging process then scores cross-correlation peaks to produce the final picks. We give quantitative results on two quite different target particles: keyhole limpet hemocyanin and p97 AAA ATPase. On these particles our automatic particle picker shows human performance level, as measured by the Fourier shell correlations of 3D reconstructions.     

Focus gradient correction applied to tilt series image data used in electron tomography

The resolution in 3D reconstructions from tilt series is limited to the information below the first zero of the contrast transfer function unless the signal is corrected computationally. The restoration is usually based on the assumption of a linear space-invariant system and a linear relationship between object mass density and observed image contrast. The space-invariant model is no longer valid when applied to tilted micrographs because the defocus varies in a direction perpendicular to the tilt axis and with it the shape of the associated point spread function. In this paper, a method is presented for determining the defocus gradient in thin specimens such as sections and 2D crystals, and for restoration of the images subsequently used for 3D reconstruction. The alignment procedure for 3D reconstruction includes area matching and tilt geometry refinement. A map with limited resolution computed from uncorrected micrographs is compared to a volume computed from corrected micrographs with extended resolution.     

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.     

EMAN: semiautomated software for high-resolution single-particle reconstructions

We present EMAN (Electron Micrograph ANalysis), a software package for performing semiautomated single-particle reconstructions from transmission electron micrographs. The goal of this project is to provide software capable of performing single-particle reconstructions beyond 10 A as such high-resolution data become available. A complete single-particle reconstruction algorithm is implemented. Options are available to generate an initial model for particles with no symmetry, a single axis of rotational symmetry, or icosahedral symmetry. Model refinement is an iterative process, which utilizes classification by model-based projection matching. CTF (contrast transfer function) parameters are determined using a new paradigm in which data from multiple micrographs are fit simultaneously. Amplitude and phase CTF correction is then performed automatically as part of the refinement loop. A graphical user interface is provided, so even those with little image processing experience will be able to begin performing reconstructions. Advanced users can directly use the lower level shell commands and even expand the package utilizing EMAN's extensive image-processing library. The package was written from scratch in C++ and is provided free of charge on our Web site. We present an overview of the package as well as several conformance tests with simulated data.     

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.     

Developing a denoising filter for electron microscopy and tomography data in the cloud

The low radiation conditions and the predominantly phase-object image formation of cryo-electron microscopy (cryo-EM) result in extremely high noise levels and low contrast in the recorded micrographs. The process of single particle or tomographic 3D reconstruction does not completely eliminate this noise and is even capable of introducing new sources of noise during alignment or when correcting for instrument parameters. The recently developed Digital Paths Supervised Variance (DPSV) denoising filter uses local variance information to control regional noise in a robust and adaptive manner. The performance of the DPSV filter was evaluated in this review qualitatively and quantitatively using simulated and experimental data from cryo-EM and tomography in two and three dimensions. We also assessed the benefit of filtering experimental reconstructions for visualization purposes and for enhancing the accuracy of feature detection. The DPSV filter eliminates high-frequency noise artifacts (density gaps), which would normally preclude the accurate segmentation of tomography reconstructions or the detection of alpha-helices in single-particle reconstructions. This collaborative software development project was carried out entirely by virtual interactions among the authors using publicly available development and file sharing tools.     

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.     

The orthogonal tilt reconstruction method: an approach to generating single-class volumes with no missing cone for ab initio reconstruction of asymmetric particles

Generating reliable initial models is a critical step in the reconstruction of asymmetric single-particles by 3D electron microscopy. This is particularly difficult to do if heterogeneity is present in the sample. The Random Conical Tilt (RCT) method, arguably the most robust presently to accomplish this task, requires significant user intervention to solve the "missing cone" problem. We present here a novel approach, termed the orthogonal tilt reconstruction method, that eliminates the missing cone altogether, making it possible for single-class volumes to be used directly as initial references in refinement without further processing. The method involves collecting data at +45 degrees and -45 degrees tilts and only requires that particles adopt a relatively large number of orientations on the grid. One tilted data set is used for alignment and classification and the other set--which provides views orthogonal to those in the first--is used for reconstruction, resulting in the absence of a missing cone. We have tested this method with synthetic data and compared its performance to that of the RCT method. We also propose a way of increasing the level of homogeneity in individual 2D classes (and volumes) in a heterogeneous data set and identifying the most homogeneous volumes.     

A two step approach for semi-automated particle selection from low contrast cryo-electron micrographs

Over recent years advances in cryo-electron microscopy for the study of macromolecular structure have resulted in resolutions in the range 10-15 A becoming routine. With this drive for increased resolution comes the need to collect larger datasets, commonly >10,000 particle images. Manual selection of particles from micrographs is often difficult and with such large numbers of particles now involved it is also laborious and a common bottleneck. Automated methods do exist but are normally restricted to specific samples or data, i.e., spherical particles, no aggregation, high contrast, and low noise. A two step approach has been developed that remains general and can be applied to low contrast, high noise micrographs of small molecules. Specifically, application of the approach is presented using micrographs of Escherichia coli RNA polymerase, which due to low contrast and the relatively small size of the molecule prove difficult to pick manually. To test the automated approach, independent reconstructions of RNA polymerase were carried out using manual and automatically picked data. The two reconstructions are shown to be comparable and the reconstruction from the automatically picked dataset is at a higher resolution, due to an increase in the number of particles picked.     

Tilt aftereffects generated by bilaterally symmetrical patterns

Tilt aftereffects were generated by bilaterally symmetrical dot patterns. Both expansion and contraction effects, similar in size and magnitude to effects usually reported with luminance contours, were observed after adaptation to symmetrical patterns tilted 15 deg or 75 deg respectively from a vertically oriented test. Large effects were found when both adapting and test stimuli were symmetrical patterns while smaller effects were found when the adapting stimulus was symmetrical and test stimulus was a grating. A third experiment, which manipulated the number of dots near the axis line, confirmed the above findings; expansion and contraction effects were observed again. The results of these experiments suggest that the neural mechanism underlying the perception of luminance contours may be linked to the mechanism for the detection of symmetry.     

Patch averaging of electron images of GP3*I crystals with variable thickness.

The combination of Fourier and correlation averaging techniques with multivariate statistical analysis and classification, a method known as patch averaging, is used to analyze untilted and tilted images of negatively stained GP32*I crystals, which exhibit variable thicknesses in a single crystal. Within a single image, coherent areas of the same apparent thickness can be distinguished from areas of differing thicknesses. Analysis using the phase relationships among symmetry-related reflections from reconstituted images obtained from untilted micrographs confirms the ability of the method to classify these variable thicknesses properly. Furthermore, the phases from some of the reconstituted images obtained from both untilted and tilted micrographs were found to match well with the phases in a previously determined three-dimensional data set of this crystal with pg symmetry along the crystallographic b axis. These results indicate the utility of the patch averaging procedures in the structural determination of protein crystals with different thicknesses.     

Gold finder: a computer method for fast automatic double gold labeling detection,counting, and color overlay in electron microscopic images

This work presents a computerized method to identify, detect, evaluate, and, by colored overlay, present gold particle pairs in electron microscopy (EM), even in wide-field views. Double gold immunolabeled specimens were analyzed in a LEO 912 electron microscope equipped with a 2k x 2k-pixel slow-scan cooled CCD camera connected to a computer with analySIS 3.1 PRO image processing software. The acquisition of a high-resolution and high-dynamic-range image by the camera allowed correct segmentation of the gold particles, separating them from other cell structures and from the substrate. Particle identification was performed by a classification module designed by us. Based on shape and size, the computer recognized the group of small particles and classified them as either singular or clustered and differentiated these from the single bigger type. The final image shows the particle types separated and colored, and indicates the total number of objects encountered in the specific region of interest. Moreover, a montage tool allowed us to obtain final representative images of large microscopic fields, which on analysis by the Gold Finder module provided information on the distribution and localization of antigens comparable to that provided by the wide-field light microscope images.     

Periodic distributions of hydrophobic amino acids allows the definition of fundamental building blocks to align distantly related proteins

Several studies on large and small families of proteins proved in a general manner that hydrophobic amino acids are globally conserved even if they are subjected to high rate substitution. Statistical analysis of amino acids evolution within blocks of hydrophobic amino acids detected in sequences suggests their usage as a basic structural pattern to align pairs of proteins of less than 25% sequence identity, with no need of knowing their 3D structure. The authors present a new global alignment method and an automatic tool for Proteins with HYdrophobic Blocks ALignment (PHYBAL) based on the combinatorics of overlapping hydrophobic blocks. Two substitution matrices modeling a different selective pressure inside and outside hydrophobic blocks are constructed, the Inside Hydrophobic Blocks Matrix and the Outside Hydrophobic Blocks Matrix, and a 4D space of gap values is explored. PHYBAL performance is evaluated against Needleman and Wunsch algorithm run with Blosum 30, Blosum 45, Blosum 62, Gonnet, HSDM, PAM250, Johnson and Remote Homo matrices. PHYBAL behavior is analyzed on eight randomly selected pairs of proteins of >30% sequence identity that cover a large spectrum of structural properties. It is also validated on two large datasets, the 127 pairs of the Domingues dataset with >30% sequence identity, and 181 pairs issued from BAliBASE 2.0 and ranked by percentage of identity from 7 to 25%. Results confirm the importance of considering substitution matrices modeling hydrophobic contexts and a 4D space of gap values in aligning distantly related proteins. Two new notions of local and global stability are defined to assess the robustness of an alignment algorithm and the accuracy of PHYBAL. A new notion, the SAD-coefficient, to assess the difficulty of structural alignment is also introduced. PHYBAL has been compared with Hydrophobic Cluster Analysis and HMMSUM methods.     

Toward understanding the structure and interactions of microtubules and motor proteins

To obtain an overall three-dimensional picture of the interaction between microtubules and the motor proteins of the kinesin family it will be necessary to take account of both atomic resolution structures obtained by X-ray crystallography and medium resolution reconstructions obtained by electron cryomicroscopy. We examine the problems associated with obtaining the required structural information from electron micrographs of vitreous ice-embedded microtubules decorated with motor domains. We find that the minus-end directed motor, ncd, decorates microtubules with an 80 Å periodicity as for kinesin. Our theoretical analysis and experiments with ncd illustrate the difficulty in determining unambiguously the surface lattice organization by diffraction analysis of micrographs. 3D reconstructions of decorated microtubules are required to accurately locate the motor domains. Helical diffraction theory is not usually applicable because microtubules are cylindrical structures that rarely have complete helical symmetry. We propose using a back-projection method based on the long pitch helices formed by individual protofilaments. Model reconstructions show that this approach is feasible. © 1995 Wiley-Liss, Inc.     

A new cryo-EM single-particle ab initio reconstruction method visualizes secondary structure elements in an ATP-fueled AAA+ motor

The generation of ab initio three-dimensional (3D) models is a bottleneck in the studies of large macromolecular assemblies by single-particle cryo-electron microscopy. We describe here a novel method, in which established methods for two-dimensional image processing are combined with newly developed programs for joint rotational 3D alignment of a large number of class averages (RAD) and calculation of 3D volumes from aligned projections (VolRec). We demonstrate the power of the method by reconstructing an ∼ 660-kDa ATP-fueled AAA+ motor to 7.5 Å resolution, with secondary structure elements identified throughout the structure. We propose the method as a generally applicable automated strategy to obtain 3D reconstructions from unstained single particles imaged in vitreous ice.     

Single particle reconstructions of the transferrin-transferrin receptor complex obtained with different specimen preparation techniques

The outcome of three-dimensional (3D) reconstructions in single particle electron microscopy (EM) depends on a number of parameters. We have used the well-characterized structure of the transferrin (Tf)-transferrin receptor (TfR) complex to study how specimen preparation techniques influence the outcome of single particle EM reconstructions. The Tf-TfR complex is small (290kDa) and of low symmetry (2-fold). Angular reconstitution from images of vitrified specimens does not reliably converge on the correct structure. Random conical tilt reconstructions from negatively stained specimens are reliable, but show variable degrees of artifacts depending on the negative staining protocol. Alignment of class averages from vitrified specimens to a 3D negative stain reference model using FREALIGN largely eliminated artifacts in the resulting 3D maps, but not completely. Our results stress the need for critical evaluation of structures determined by single particle EM.     

Three-dimensional organization of retroviral capsid proteins on a lipid monolayer

We have used a method for the two-dimensional crystallization of retroviral structural proteins to obtain a three-dimensional structure of negatively stained, membrane-bound, histidine-tagged Moloney murine leukemia virus (M-MuLV) capsid protein (his-MoCA) arrays. Tilted and untilted micrographs from crystals formed by purified his-MoCA proteins incubated beneath lipid monolayers containing nickel-chelating lipids were used in 3D reconstructions. The 2D crystals had unit cell dimensions of a=72.6 A, b=72.5 A and gamma=119.5 degrees, but appeared to have no intrinsic symmetry (p1) in 3D, in contrast to the trigonal or hexagonal appearance of their 2D projections. Membrane-bound his-MoCA proteins showed a strand-like organization, apparently with dimer building blocks. Membrane-proximal regions, or putative N-terminal domains (NTDs), dimerized with different partners than the membrane-distal putative C-terminal domains (CTDs). Evidence also suggests that CTDs can adopt alternate orientations relative to their NTDs, forming interstrand connections. Our results are consistent with helical-spiral models for retrovirus particle assembly, but are not easily reconcilable with icosahedral models.     

An electron microscopy journey in the study of microtubule structure and dynamics

Structural characterization of microtubules has been the realm of three‐dimensional electron microscopy and thus has evolved hand in hand with the progress of this technique, from the initial 3D reconstructions of stained tubulin assemblies, and the first atomic model of tubulin by electron crystallography of 2D sheets of protofilaments, to the ever more detailed cryoelectron microscopy structures of frozen‐hydrated microtubules. Most recently, hybrid helical and single particle image processing techniques, and the latest detector technology, have lead to atomic models built directly into the density maps of microtubules in different functional states, shading new light into the critical process of microtubule dynamic instability.     

Applications of a bilateral denoising filter in biological electron microscopy

Due to the sensitivity of biological sample to the radiation damage, the low dose imaging conditions used for electron microscopy result in extremely noisy images. The processes of digitization, image alignment, and 3D reconstruction also introduce additional sources of noise in the final 3D structure. In this paper, we investigate the effectiveness of a bilateral denoising filter in various biological electron microscopy applications. In contrast to the conventional low pass filters, which inevitably smooth out both noise and structural features simultaneously, we found that bilateral filter holds a distinct advantage in being capable of effectively suppressing noise without blurring the high resolution details. In as much, we have applied this technique to individual micrographs, entire 3D reconstructions, segmented proteins, and tomographic reconstructions.