SPRING – An image processing package for single-particle based helical reconstruction from electron cryomicrographs

Helical reconstruction from electron cryomicrographs has become a routine technique for macromolecular structure determination of helical assemblies since the first days of Fourier-based three-dimensional image reconstruction. In the past decade, the single-particle technique has had an important impact on the advancement of helical reconstruction. Here, we present the software package SPRING that combines Fourier based symmetry analysis and real-space helical processing into a single workflow. One of the most time-consuming steps in helical reconstruction is the determination of the initial symmetry parameters. First, we propose a class-based helical reconstruction approach that enables the simultaneous exploration and evaluation of many symmetry combinations at low resolution. Second, multiple symmetry solutions can be further assessed and refined by single-particle based helical reconstruction using the correlation of simulated and experimental power spectra. Finally, the 3D structure can be determined to high resolution. In order to validate the procedure, we use the reference specimen Tobacco Mosaic Virus (TMV). After refinement of the helical symmetry, a total of 50,000 asymmetric units from two micrographs are sufficient to reconstruct a subnanometer 3D structure of TMV at 6.4 Å resolution. Furthermore, we introduce the individual programs of the software and discuss enhancements of the helical reconstruction workflow. Thanks to its user-friendly interface and documentation, SPRING can be utilized by the novice as well as the expert user. In addition to the study of well-ordered helical structures, the development of a streamlined workflow for single-particle based helical reconstruction opens new possibilities to analyze specimens that are heterogeneous in symmetries.     

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.     

Arrangement of myosin heads in relaxed thick filaments from frog skeletal muscle

The distribution of myosin heads on the surface of frog skeletal muscle thick filaments has been determined by computer processing of electron micrographs of isolated filaments stained with tannic acid and uranyl acetate. The heads are arranged in three strands but not in a strictly helical manner and so the structure has cylindrical symmetry. This accounts for the "forbidden" meridional reflections seen in diffraction patterns. Each layer-line therefore represents the sum of terms of Bessel orders 0, +/- 3, +/- 6, +/- 9 and so on. These terms interact so that, unlike a helical object without terms from overlapping Bessel orders, as the azimuth is changed, the amplitude on a layer-line at a particular radius varies substantially and its phase does not alter linearly. Consequently, a three-dimensional reconstruction cannot be produced from a single view. We have therefore used tilt series of three individual filaments to decompose the data on layer-lines 0 to 6 into terms of Bessel orders up to +/- 9 using a least-squares procedure. These data had a least-squares residual of 0.32 and enabled a three-dimensional reconstruction to be obtained at a nominal resolution of 6 nm. This showed, at a radius of about 10 nm, three strands of projecting morphological units with three units spaced along each strand every 42.9 nm axially. We have identified these units with pairs of myosin heads. Successive units along a strand are perturbed axially, azimuthally and radially from the positions expected if the structure was perfectly helical. This may simply be a consequence of steric restrictions in packing the heads on the thick filament surface, but could also reflect an underlying non-helical arrangement of myosin tails, which would be consistent with the thick filament shaft being constructed from three subfilaments in which the tails were arranged regularly. There was also material at a radius of about 6 nm spaced 42.9 nm axially, which we tentatively identified with accessory proteins. The filament shaft had a pronounced pattern of axial staining.     

A helical processing pipeline for EM structure determination of membrane proteins

Electron crystallography plays a key role in the structural biology of integral membrane proteins (IMPs) by offering one of the most direct means of providing insight into the functional state of these molecular machines in their lipid-associated forms, and also has the potential to facilitate examination of physiologically relevant transitional states and complexes. Helical or tubular crystals, which are the natural product of proteins crystallizing on the surface of a cylindrical vesicle, offer some unique advantages, such as three-dimensional (3D) information from a single view, compared to other crystalline forms. While a number of software packages are available for processing images of helical crystals to produce 3D electron density maps, widespread exploitation of helical image reconstruction is limited by a lack of standardized approaches and the initial effort and specialized expertise required. Our goal is to develop an integrated pipeline to enable structure determination by transmission electron microscopy (TEM) of IMPs in the form of tubular crystals. We describe here the integration of standard Fourier-Bessel helical analysis techniques into Appion, an integrated, database-driven pipeline.     

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.     

Automatic lattice determination for two-dimensional crystal images

Electron crystallography determines the structure of membrane proteins and other periodic samples by recording either images or diffraction patterns. Computer processing of recorded images requires the determination of the reciprocal lattice parameters in the Fourier transform of the image. We have developed a set of three programs 2dx_peaksearch, 2dx_findlat and 2dx_getlat, which can determine the reciprocal lattice from a Fourier transformation of a 2D crystal image automatically. 2dx_peaksearch determines a list of Fourier peak coordinates from a processed calculated diffraction pattern. These coordinates are evaluated by 2dx_findlat to determine one or more lattices, using a-priori knowledge of the real-space crystal unit cell dimensions, and the sample tilt geometry. If these are unknown, then the program 2dx_getlat can be used to obtain a guess for the unit cell dimensions. These programs are available as part of the 2dx software package for the image processing of 2D crystal images at http://2dx.org.     

Ruby-Helix: an implementation of helical image processing based on object-oriented scripting language

Helical image analysis in combination with electron microscopy has been used to study three-dimensional structures of various biological filaments or tubes, such as microtubules, actin filaments, and bacterial flagella. A number of packages have been developed to carry out helical image analysis. Some biological specimens, however, have a symmetry break (seam) in their three-dimensional structure, even though their subunits are mostly arranged in a helical manner. We refer to these objects as "asymmetric helices". All the existing packages are designed for helically symmetric specimens, and do not allow analysis of asymmetric helical objects, such as microtubules with seams. Here, we describe Ruby-Helix, a new set of programs for the analysis of "helical" objects with or without a seam. Ruby-Helix is built on top of the Ruby programming language and is the first implementation of asymmetric helical reconstruction for practical image analysis. It also allows easier and semi-automated analysis, performing iterative unbending and accurate determination of the repeat length. As a result, Ruby-Helix enables us to analyze motor-microtubule complexes with higher throughput to higher resolution.     

数字式一体化口腔临床工程系统的研制

运用数字总线技术实现多模块化控制,对CT或X光片、口腔数字化扫描仪、印模扫描图像等进行三维重建、立体构图,开发系列规划软件,为口腔医生提供优化治疗、修复方案。同时,计算机可联接微型CAD／CAM自动进行义齿、贴面快速加工,以及种植导板等产品的设计、加工;联接手术导航仪进行牙种植手术导航;联接PACS、HIS等系统,实现数字化图像传输以及远程医疗功能。在诊所内一体化完成诊断、治疗、制作、修复、整形、美容等系列复杂、精细工作。     

Application of the iterative helical real-space reconstruction method to large membranous tubular crystals of P-type ATPases

Since the development of three-dimensional helical reconstruction methods in the 1960's, advances in Fourier-Bessel methods have facilitated structure determination to near-atomic resolution. A recently developed iterative helical real-space reconstruction (IHRSR) method provides an alternative that uses single-particle analysis in conjunction with the imposition of helical symmetry. In this work, we have adapted the IHRSR algorithm to work with frozen-hydrated tubular crystals of P-type ATPases. In particular, we have implemented layer-line filtering to improve the signal-to-noise ratio, Wiener-filtering to compensate for the contrast transfer function, solvent flattening to improve reference reconstructions, out-of-plane tilt compensation to deal with flexibility in three dimensions, systematic calculation of Fourier shell correlations to track the progress of the refinement, and tools to control parameters as the refinement progresses. We have tested this procedure on datasets from Na(+)/K(+)-ATPase, rabbit skeletal Ca(2+)-ATPase and scallop Ca(2+)-ATPase in order to evaluate the potential for sub-nanometer resolution as well as the robustness in the presence of disorder. We found that Fourier-Bessel methods perform better for well-ordered samples of skeletal Ca(2+)-ATPase and Na(+)/K(+)-ATPase, although improvements to IHRSR are discussed that should reduce this disparity. On the other hand, IHRSR was very effective for scallop Ca(2+)-ATPase, which was too disordered to analyze by Fourier-Bessel methods.     

IPET and FETR: experimental approach for studying molecular structure dynamics by cryo-electron tomography of a single-molecule structure

The dynamic personalities and structural heterogeneity of proteins are essential for proper functioning. Structural determination of dynamic/heterogeneous proteins is limited by conventional approaches of X-ray and electron microscopy (EM) of single-particle reconstruction that require an average from thousands to millions different molecules. Cryo-electron tomography (cryoET) is an approach to determine three-dimensional (3D) reconstruction of a single and unique biological object such as bacteria and cells, by imaging the object from a series of tilting angles. However, cconventional reconstruction methods use large-size whole-micrographs that are limited by reconstruction resolution (lower than 20 Å), especially for small and low-symmetric molecule (<400 kDa). In this study, we demonstrated the adverse effects from image distortion and the measuring tilt-errors (including tilt-axis and tilt-angle errors) both play a major role in limiting the reconstruction resolution. Therefore, we developed a “focused electron tomography reconstruction” (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance protein. FETR can tolerate certain levels of image-distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. To describe this method, a set of simulated cryoET images was employed; to validate this approach, the real experimental images from negative-staining and cryoET were used. Since this approach can obtain the structure of a single-instance molecule/particle, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single “snapshot” molecule structure determination. Thus, FETR/IPET provides a completely new opportunity for a single-molecule structure determination, and could be used to study the dynamic character and equilibrium fluctuation of macromolecules.     

A microtubule RELION-based pipeline for cryo-EM image processing

Microtubules are polar filaments built from αβ-tubulin heterodimers that exhibit a range of architectures in vitro and in vivo. Tubulin heterodimers are arranged helically in the microtubule wall but many physiologically relevant architectures exhibit a break in helical symmetry known as the seam. Noisy 2D cryo-electron microscopy projection images of pseudo-helical microtubules therefore depict distinct but highly similar views owing to the high structural similarity of α- and β-tubulin. The determination of the αβ-tubulin register and seam location during image processing is essential for alignment accuracy that enables determination of biologically relevant structures. Here we present a pipeline designed for image processing and high-resolution reconstruction of cryo-electron microscopy microtubule datasets, based in the popular and user-friendly RELION image-processing package, Microtubule RELION-based Pipeline (MiRP). The pipeline uses a combination of supervised classification and prior knowledge about geometric lattice constraints in microtubules to accurately determine microtubule architecture and seam location. The presented method is fast and semi-automated, producing near-atomic resolution reconstructions with test datasets that contain a range of microtubule architectures and binding proteins.     

Studies of the structure of the T4 bacteriophage tail sheath: I. The recovery of three-dimensional structural information from the extended sheath

The extended tail sheath of bacteriophage T4 has been used to study the transfer of information from an electron micrograph to the three-dimensional reconstruction obtained from it. Two methods have been developed to assess micrograph images of helical particles and their reconstructions. First, a filter has been designed which eliminates all structure in the image inconsistent with the symmetry and assumed radius of the helical particle. Individual micrographs can therefore be assessed with respect to their consistency with the assumed symmetry and radius, before reconstruction. Second, a map of the root-meansquare deviation of individual reconstructions from their average provides a quantitative measure of the consistency of the individual sets of tail data and allows the regions in the average reconstruction which are most sensitive to differences between the particles to be identified.The averaged reconstruction is used to examine the problems related to resolution and reproducibility of the structural information and to define the extent of the different components of the extended sheath.     

Arrangement of the heads of myosin in relaxed thick filaments from tarantula muscle

Thick filaments from leg muscle of tarantula, maintained under relaxing conditions (Mg-ATP and EGTA), were negatively stained and photographed with minimal electron dose. Particles were selected for three-dimensional image reconstruction by general visual appearance and by the strength and symmetry of their optical diffraction patterns, the best of which extend to spacings of 1/5 nm-1. The helical symmetry is such that, on a given layer-line, Bessel function contributions of different orders start to overlap at fairly low resolution and must therefore be separated computationally by combining data from different views. Independent reconstructions agree well and show more detail than previous reconstructions of thick filaments from Limulus and scallop. The strongest feature is a set of four long-pitch right-handed helical ridges (pitch 4 X 43.5 nm) formed by the elongated myosin heads. The long-pitch helices are modulated to give ridges with an axial spacing of 14.5 nm, lying in planes roughly normal to the filament axis and running circumferentially. We suggest that the latter may be formed by the stacking of a subfragment 1 (S1) head from one myosin molecule on an S1 from an axially neighbouring molecule. Internal features in the map indicate an approximate local twofold axis relating the putative heads within a molecule. The heads appear to point in opposite directions along the filament axis and are located very close to the filament backbone. Thus, for the first time, the two heads of the myosin molecule appear to have been visualized in a native thick filament under relaxing conditions.     

The iterative helical real space reconstruction method: surmounting the problems posed by real polymers

Many important biological macromolecules exist as helical polymers. Examples are actin, tubulin, myosin, RecA, Rad51, flagellin, pili, and filamentous bacteriophage. The first application of three-dimensional reconstruction from electron microscopic images was to a helical polymer, and a number of laboratories today are using helical tubes of integral membrane proteins for solving the structure of these proteins in the electron microscope at near atomic resolution. We have developed a method to analyze and reconstruct electron microscopic images of macromolecular helical polymers, the iterative helical real space reconstruction (IHRSR) algorithm. We can show that when there is disorder or heterogeneity, when the specimens diffract weakly, or when Bessel functions overlap, we can do far better with our method than can be done using traditional Fourier-Bessel approaches. In many cases, structures that were not even amenable to analysis can be solved at fairly high resolution using our method. The problems inherent in the traditional approach are discussed, and examples are presented illustrating how the IHRSR approach surmounts these problems.     

Averaging data derived from images of helical structures with different symmetries.

There are many examples of macromolecules that form helical tubes or crystals, which are useful for structure determination by electron microscopy and image processing. Helical crystals can be thought of as two-dimensional crystals that have been rolled into a cylinder such that two lattice points are superimposed. In many real cases, helical crystals of a particular macromolecule derive from an identical two-dimensional lattice but have different lattice points superimposed, thus producing different helical symmetries which cannot be simply averaged in Fourier-space. When confronted with this situation, one can select images corresponding to one of the observed symmetries at the expense of reducing the number of images that can be used for data collection and averaging, or one can calculate separate density maps from each symmetry, then align and average them together in real-space. Here, we present a third alternative, which is based on averaging of the Fourier-Bessel coefficients, gn,l(r), and which allows the inclusion of data from all symmetry groups derived from a common two-dimensional lattice. The method is straightforward and simple in practice and is shown, through a specific example with real data, to give results comparable to real-space averaging.     

An automated program to find animals and crop photographs for individual recognition

Detailed data on individual animals are critical to ecological and evolutionary studies, but attaching identifying marks can alter individual fates and behavior leading to biases in parameter estimates and ethical issues. Individual-recognition software has been developed to assist in identifying many species from non-invasive photographic data. These programs utilize algorithms to find unique individual characteristics and compare images to a catalogue of known individuals. Currently, all applications for individual identification require manual processing to crop images so only the area of interest remains, or the area of interest must be manually delineated in each image. Thus, one of the main bottlenecks in processing data from photographic capture-recapture surveys is in cropping to an area of interest so that matching algorithms can identify the individual. Here, we describe the development and testing of an automated cropping program. The methods and techniques we describe are broadly applicable to any system where raw photos must be cropped down to a specific area of interest before pattern recognition software can be used for individual identification. We developed and tested the program for use with identification photos of wild giraffes.     

CT-based semi-automatic quantification of vertebral fracture restoration

Minimally invasive surgeries aiming to restore fractured vertebral body are increasing; therefore, our goals were to create a 3D vertebra reconstruction process and design clinical indices to assess the vertebral restoration in terms of heights, angles and volumes. Based on computed tomography (CT)-scan of the vertebral spine, a 3D reconstruction method as well as relevant clinical indices were developed. First, a vertebra initial solution requiring 5 min of manual adjustments is built. Then an image processing algorithm places this solution in the CT-scan images volume to adjust the model's nodes. On the vertebral body's anterior and posterior parts, nine robust heights, volume and endplate angle measurement methods were developed. These parameters were evaluated by reproducibility and accuracy studies. The vertebral body reconstruction accuracy was 1.0 mm; heights and volume accuracy were, respectively, 1.2 and 179 mm³. In conclusion, a 3D vertebra reconstruction process requiring little user time was proposed as well as 3D clinical indices assessing fractured and restored vertebra.