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Many molluscs transport oxygen using a very large cylindrical multimeric copper-containing protein named hemocyanin. The molluscan hemocyanin forms a decamer (cephalopods) or multidecamer (gastropods) of approximately 330-450kDa subunits, resulting in a molecular mass >3.3MDa. Therefore, molluscan hemocyanin is one of the largest proteins. The reason why these organisms use such a large supermolecule for oxygen transport remains unclear. Atomic-resolution X-ray crystallographic analysis is necessary to unveil the detailed molecular structure of this mysterious large molecule. However, its propensity to dissociate in solution has hampered the crystallization of its intact form. In the present study, we successfully obtained the first crystals of an intact decameric molluscan hemocyanin. The diffraction dataset at 3.0-Å resolution was collected by merging the datasets of two isomorphic crystals. Electron microscopy analysis of the dissolved crystals revealed cylindrical particles. Furthermore, self-rotation function analysis clearly showed the presence of a fivefold symmetry with several twofold symmetries perpendicular to the fivefold axis. The absorption spectrum of the crystals showed an absorption peak around 345nm. These results indicated that the crystals contain intact hemocyanin decamers in the oxygen-bound form., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Arthropod hemocyanins (Hcs) are a family of large, high molecular mass, extracellular oxygen transport proteins. They form oligomeric quaternary structures based on different arrangements of a basic 6×75 kDa hexameric unit. Their complex quaternary structures present binding sites for allosteric effectors and regulate the oxygen binding process in a cooperative manner. In order to describe the functional regulation of arthropod Hcs, a detailed description of their quaternary structure is necessary. We have utilized small angle X-ray scattering to characterize the structure of three arthropod Hcs in unperturbed conditions. Two different levels of complexity are evaluated: for the 2×6-meric case, we analyzed the Hcs of the portunid crab Carcinus aestuarii and stomatopod Squilla mantis, while in the case of 4×6-meric structures, we studied the Hc of the thalassinid shrimp Upogebia pusilla. While C. aestuarii Hc presented a structure comparable to other 2×6-meric crustacean Hcs, S. mantis Hc shows a peculiar and quite unique arrangement of its building blocks, resembling a substructure of giant Hcs found among cheliceratans. For U. pusilla, the arrangement of its subunits is described as tetrahedral, in contrast to the more common square planar 4×6-meric structure found in other arthropod Hcs., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Electron tomography is currently the highest resolution imaging modality available to study the 3D structures of pleomorphic macromolecular assemblies, viruses, organelles and cells. Unfortunately, the resolution is currently limited to 3-5nm by several factors including the dose tolerance of biological specimens and the inaccessibility of certain tilt angles. Here we report the first experimental demonstration of equally-sloped tomography (EST) to alleviate these problems. As a proof of principle, we applied EST to reconstructing frozen-hydrated keyhole limpet hemocyanin molecules from a tilt-series taken with constant slope increments. In comparison with weighted back-projection (WBP), the algebraic reconstruction technique (ART) and the simultaneous algebraic reconstruction technique (SART), EST reconstructions exhibited higher contrast, less peripheral noise, more easily detectable molecular boundaries and reduced missing wedge effects. More importantly, EST reconstructions including only two-thirds the original images appeared to have the same resolution as full WBP reconstructions, suggesting that EST can either reduce the dose required to reach a given resolution or allow higher resolutions to be achieved with a given dose. EST was also applied to reconstructing a frozen-hydrated bacterial cell from a tilt-series taken with constant angular increments. The results confirmed similar benefits when standard tilts are utilized.

Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that approximately 10(4)-10(5) particle projections are required to attain a 3A resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present Swarm(PS), a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (approximately 10(2)), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. Swarm(PS) is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites.

SIGNATURE is a particle selection system for molecular electron microscopy. It applies a hierarchical screening procedure to identify molecular particles in EM micrographs. The user interface of the program provides versatile functions to facilitate image data visualization, particle annotation and particle quality inspection. The system design emphasizes both functionality and usability. This software has been released to the EM community and has been successfully applied to macromolecular structural analyses.

Different fragments of the hemocyanin (Hc) isolated from the gastropod Rapana venosa containing a single functional unit (50 kDa), two functional units (100 kDa) and three functional units (150 kDa) were obtained in a dissociating buffer in the presence of Zn2+ and purified to homogeneity. Their conformations in solution were studied by means of small angle X-ray scattering (SAXS) and compared with those of the corresponding fragments previously obtained by limited proteolysis [Arch. Biochem. Biophys., 2000, 373, 154]. The overall shape of each fragment was determined using an ab initio approach. The crystal structures of the functional unit e from the same Hc and from another molluscan Hc (Octopus dofleini) were used to model 100 and 150 kDa fragments using rigid body movements to fit the corresponding SAXS patterns. Interesting differences were observed between the functional unit organization in the low-molecular mass fragments according to the two preparation methods, suggesting different localizations within the 11S functional subunit.

A new learning-based approach is presented for particle detection in cryo-electron micrographs using the Adaboost learning algorithm. The approach builds directly on the successful detectors developed for the domain of face detection. It is a discriminative algorithm which learns important features of the particle's appearance using a set of training examples of the particles and a set of images that do not contain particles. The algorithm is fast (10 s on a 1.3 GHz Pentium M processor), is generic, and is not limited to any particular shape or size of the particle to be detected. The method has been evaluated on a publicly available dataset of 82 cryoEM images of keyhole lympet hemocyanin (KLH). From 998 automatically extracted particle images, the 3-D structure of KLH has been reconstructed at a resolution of 23.2 A which is the same resolution as obtained using particles manually selected by a trained user.

Accurate and automatic particle detection from cryo-electron microscopy (cryo-EM images) is very important for high-resolution reconstruction of large macromolecular structures. In this paper, we present a method for particle picking based on shape feature detection. Two fundamental concepts of computational geometry, namely, the distance transform and the Voronoi diagram, are used for detection of critical features as well as for accurate location of particles from the images or micrographs. Unlike the conventional template-matching methods, our approach detects the particles based on their boundary features instead of intensities. The geometric features derived from the boundaries provide an efficient way for locating particles quickly and accurately, which avoids a brute-force searching for the best position/orientation. Our approach is fully automatic and has been successfully applied to detect particles with approximately circular or rectangular shapes (e.g., KLH particles). Particle detection can be enhanced by multiple sets of parameters used in edge detection and/or by anisotropic filtering. We also discuss the extension of this approach to other types of particles with certain geometric features.

The FindEM particle picking program was tested on the publicly available keyhole limpet hemocyanin (KLH) dataset, and the results were submitted for the "bakeoff" contest at the recent particle picking workshop (Zhu et al., 2003b). Two alternative ways of using the program are demonstrated and the results are compared. The first of these approximates exhaustive projection matching with a full set of expected views, which need to be known. This could correspond to the task of extending a known structure to higher resolution, for which many 1000's of additional images are required. The second procedure illustrates use of multivariate statistical analysis (MSA) to filter a preliminary set of candidate particles containing a high proportion of false particles. This set was generated using the FindEM program to search with one template that crudely represents the expected views. Classification of the resultant set of candidate particles then allows the desired classes to be selected while the rest can be ignored. This approach requires no prior information of the structure and is suitable for the initial investigation of an unknown structure--the class averages indicate the symmetry and oligomeric state of the particles. Potential improvements in speed and accuracy are discussed.

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.

Template matching together with the comprehensive theory of image formation in electron microscope provides an optimal (in Bayesian sense) tool for solving one of the outstanding problems in single particle analysis, i.e., automatic selection of particle views from noisy micrograph fields. The method is based on the assumption that the reference three-dimensional structure is known and that the relevant parameters of the model of the image formation process can be estimated. In the first stage of the procedure, a set of possible particle views is generated using the available reference structure. The template images are constructed as linear combinations of available particle views using a clustering technique. Next, the micrograph noise characteristic is established using an automated contrast transfer function (CTF) estimation procedure. Finally, the CTF parameters calculated are used to construct a matched filter and correlation functions corresponding to the available template images are calculated. In order to alleviate the problem of the biased caused by varying image formation conditions, a decision making strategy based on the predicted distribution of correlation coefficients is proposed. It is demonstrated that due to the inclusion of CTF considerations, the template matching method performed very well in a broad range of microscopy conditions.

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.

Reduced representation templates are used in a real-space pattern matching framework to facilitate automatic particle picking from electron micrographs. The procedure consists of five parts. First, reduced templates are constructed either from models or directly from the data. Second, a real-space pattern matching algorithm is applied using the reduced representations as templates. Third, peaks are selected from the resulting score map using peak-shape characteristics. Fourth, the surviving peaks are tested for distance constraints. Fifth, a correlation-based outlier screening is applied. Test applications to a data set of keyhole limpet hemocyanin particles indicate that the method is robust and reliable.

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.

Particle selection is an essential but tedious step in the determination of macromolecular structures by single particle reconstruction. This paper presents an automatic, multi-reference particle detection scheme that is based on the classical matched filter principle. It makes use of a pre-whitening filter to standardize the noise, a reduced representation of the references by means of principal component analysis, and a statistic for distinguishing particles from image artifacts. Standardizing the noise allows the noise-induced false-positive frequency to be estimated, and also allows the distribution of the discrimination statistic to be calculated a priori. The method is demonstrated with an annotated dataset of cryo-EM images.

We have reconstructed a three-dimensional map of keyhole limpet hemocyanin isoform 1 (KLH1), using our automated data collection software, Leginon, integrated with particle selection algorithms, and the SPIDER reconstruction package. KLH1, a 7.9 MDa macromolecule, is an extracellular respiratory pigment composed of two asymmetric decamers, and presents an overall D(5) point-group symmetry. The reconstruction is in agreement with previous data published on molluscan hemocyanins. The reconstructed map (11.3A resolution, 3sigma criterion) was used to fit an available X-ray crystallography structure of Octopus dofleini Odg, solved at 2.3A [J. Mol. Biol. 278 (4) (1998) 855], with satisfactory results. The results validate the approach of automating the cryoEM process and demonstrate that the quality of the images acquired and the particles selected is comparable to those obtained using manual methods. Several problems remain to be solved however before these results can be generalized.

The current theory of image formation in electron microscopy has been semi-quantitatively successful in describing data. The theory involves parameters due to the transfer function of the microscope (defocus, spherical aberration constant, and amplitude constant ratio) as well as parameters used to describe the background and attenuation of the signal. We present empirical evidence that at least one of the features of this model has not been well characterized. Namely the spectrum of the noise background is not accurately described by a Gaussian and associated "B-factor;" this becomes apparent when one studies high-quality far-from focus data. In order to have both our analysis and conclusions free from any innate bias, we have approached the questions by developing an automated fitting algorithm. The most important features of this routine, not currently found in the literature, are (i). a process for determining the cutoff for those frequencies below which observations and the currently adopted model are not in accord, (ii). a method for determining the resolution at which no more signal is expected to exist, and (iii). a parameter-with units of spatial frequency-that characterizes which frequencies mainly contribute to the signal. Whereas no general relation is seen to exist between either of these two quantities and the defocus, a simple empirical relationship approximately relates all three.

Immunoelectron microscopy has been performed using negatively stained immune complexes of keyhole limpet hemocyanin isoform 1 (KLH1) decamers and a functional unit-specific monoclonal antibody anti-KLH1-c1. The antibody links hemocyanin molecules at both the collar and the collarless edge of the decamer, indicating a peripheral localization of functional units c. In isoform 2 (KLH2) the positions of functional units c have been identified with the peanut agglutinin (PNA), which has previously been shown to exclusively bind to KLH2-c. Ferritin linked to PNA was used to visualize labeled molecules electron microscopically. The pattern of labeling also indicates a peripheral localization of the c functional units. The data presented in this paper support only one of two possible models for the subunit orientation within the hemocyanin decamer.

Keyhole limpet hemocyanin (KLH) is a mixture of two hemocyanin isoforms, termed KLH1 and KLH2. Within KLH1 eight oxygen-binding functional units (FUs), 1-a to 1-h, have been identified, in contrast to KLH2, which was previously thought to be organized in seven FUs (2-a to 2-g). By limited proteolysis of KLH2 subunits, isolation of the polypeptide fragments, and N-terminal sequencing, we have now identified an eighth FU of type h, with a molecular mass of 43 kDa. This is unusually small for a FU h from a gastropodan hemocyanin. It is also shown that KLH2 didecamers can be split into a stable and homogeneous population of decamers by dialysis against 50 mM Tris/HCl, pH 7.5, in the absence of divalent cations. Electron microscopic immunolocalization using a specific monoclonal antibody reveals that FU KLH2-h is located at the collar of the decamer., (Copyright 1999 Academic Press.)

Hemocyanins, the respiratory molecules of cephalopod mollusks, are hollow cylinders with five internal arches. Three hemocyanins representative of three orders of cephalopods (Benthoctopus species, Octopoda; Vampyroteuthis infernalis, Vampyromorpha; Sepia officinalis, Sepioidea) were subjected to cryoelectron microscopy and three-dimensional (3D) reconstruction. The structure of Benthoctopus hemocyanin, solved at 26.4-A resolution, possesses arches comprising two identical functional units. The similarity between these functional units and the structure recently observed in X-ray crystallography for Octopus by Cuff et al. (J. Mol. Biol., 1998, 232, 522-529) allows the identification of their N- and C-terminal domains in the 3D reconstruction volume. Conversely, arches present in the 3D reconstruction volume of Sepia hemocyanin (21.8 A resolution) contain four functional units that are disposed differently. The strong resemblance between the reconstruction volumes of Vampyroteuthis (21.4-A resolution) and Benthoctopus hemocyanins suggests that Sepioidea diverged from a group containing Octopoda and Vampyromorpha., (Copyright 1999 Academic Press.)

Sigma (Software of Imagery and Graphics for Molecular Architecture) is a software package designed for visualization and exploration of three-dimensional (3D) molecular electron microscopy data. It comprises a text and two graphic modes. In the text mode, a language allows the writing of scripts for repetitive tasks. The two graphic modes are based on the multiwindow environment with a mouse as pointer. The first graphic mode is dedicated to vectorial objects and the second to pixel/voxel objects. The data imported by SIGMA have various origins such as 3D reconstruction volumes, Protein Data Bank data, or geometrical objects like spheres, cubes, or cylinders. These 3D objects are interactively rotated, translated, and rendered with SIGMA. This software, written in C language, runs on Silicon Graphics workstations using the X-Window plus Motif environment. The specific 3D routines are based on the Silicon Graphics GL library.

An immunocomplex formed by the 4 x 6 meric hemocyanin of the scorpion Androctonus australis with the monoclonal antibody L104 was studied by cryoelectron microscopy and subjected to three-dimensional (3D) reconstruction. The reconstructed particle reflects the structure of the immunocomplex in its hydrated state and is devoid of the flattening that was previously observed with a negatively stained preparation. A 3D fitting of the X-ray data of the Panulirus interruptus hemocyanin and of the Fab R19.9 to the reconstruction volume allowed the first quantitative measurement of the structural parameters of the antigen, and the localization of the epitope at the surface of subunit Aa6. The independent alignment of the Fabs and the hexamers provides a direct verification for the accuracy of the fit and allows the building of the most detailed model of a cheliceratan 4 x 6meric complex and its attached monoclonal antibodies.

An immunocomplex of the 4 x 6-meric hemocyanin of the scorpion Androctonus australis with the monoclonal Fab fragment L104 was reconstructed from electron micrographs of a negatively stained specimen, using the double-carbon-layer technique. The resulting structure enables a clear visualization of the Fab fragments bound to the four copies of the Aa6 subunit and directly confirms a previous localization of the L104 epitope deduced from two-dimensional image processing. Despite a strong flattening effect produced by the negative-staining technique the orientations of the Fab fragments are well characterized. Moreover, the observation of a central hole within the elbow bends of the Fab fragments provides information about the disposition of the Fabs around their main axis.