Automated identification of filaments in cryoelectron microscopy images

Helical reconstruction of Salmonella and Shigella needle filaments attached to type 3 basal bodies

Gram-negative pathogens evolved a syringe-like nanomachine, termed type 3 secretion system, to deliver protein effectors into the cytoplasm of host cells. An essential component of this system is a long helical needle filament that protrudes from the bacterial surface and connects the cytoplasms of the bacterium and the eukaryotic cell. Previous structural research was predominantly focused on reconstituted type 3 needle filaments, which lacked the biological context. In this work we introduce a facile procedure to obtain high-resolution cryo-EM structure of needle filaments attached to the basal body of type 3 secretion systems. We validate our approach by solving the structure of Salmonella PrgI filament and demonstrate its utility by obtaining the first high-resolution cryo-EM reconstruction of Shigella MxiH filament. Our work paves the way to systematic structural characterization of attached type 3 needle filaments in the context of mutagenesis studies, protein structural evolution and drug development.

Automated tracing of helical assemblies from electron cryo-micrographs

Structure determination of helical specimens commonly requires datasets from thousands of micrographs often obtained by automated cryo-EM data acquisition. Interactive tracing of helical assemblies from such a number of micrographs is labor-intense and time-consuming. Here, we introduce an automated tracing tool MicHelixTrace that precisely locates helix traces from micrographs of rigid as well as very flexible helical assemblies with small numbers of false positives. The computer program is fast and has low computational requirements. In addition to helix coordinates required for a subsequent helical reconstruction work-flow, we determine the persistence length of the polymer ensemble. This information provides a useful measure to characterize mechanical properties of helical assemblies and to evaluate the potential for high-resolution structure determination.

Three-dimensional reconstruction of helical polymers

The field of three-dimensional electron microscopy began more than 45years ago with a reconstruction of a helical phage tail, and helical polymers continue to be important objects for three-dimensional reconstruction due to the centrality of helical protein and nucleoprotein polymers in all aspects of biology. We are now witnessing a fundamental revolution in this area, made possible by direct electron detectors, which has led to near-atomic resolution for a number of important helical structures. Most importantly, the possibility of achieving such resolution routinely for a vast number of helical samples is within our reach. One of the main problems in helical reconstruction, ambiguities in assigning the helical symmetry, is overcome when one reaches a resolution where secondary structure is clearly visible. However, obstacles still exist due to the intrinsic variability within many helical filaments.

Virus-based nanocarriers for drug delivery

New nanocarrier platforms based on natural biological building blocks offer great promises in revolutionalizing medicine. The usage of specific protein cage structures: virus-like particles (VLPs) for drug packaging and targetted delivery is summarized here. Versatile chemical and genetic modifications on the outer surfaces and inner cavities of VLPs facilitate the preparation of new materials that could meet the biocompatibility, solubility and high uptake efficiency requirements for drug delivery. A full evaluation on the toxicity, bio-distribution and immunology of these materials are envisaged to boost their application potentials.

Multiclass maximum-likelihood symmetry determination and motif reconstruction of 3-D helical objects from projection images for electron microscopy

Many micro- to nano-scale 3-D biological objects have a helical symmetry. Cryo electron microscopy provides 2-D projection images where, however, the images have low SNR and unknown projection directions. The object is described as a helical array of identical motifs, where both the parameters of the helical symmetry and the motif are unknown. Using a detailed image formation model, a maximum-likelihood estimator for the parameters of the symmetry and the 3-D motif based on images of many objects and algorithms for computing the estimate are described. The possibility that the objects are not identical but rather come from a small set of homogeneous classes is included. The first example is based on 316 128 × 100 pixel experimental images of Tobacco Mosaic Virus, has one class, and achieves 12.40-Å spatial resolution in the reconstruction. The second example is based on 400 128 × 128 pixel synthetic images of helical objects constructed from NaK ion channel pore macromolecular complexes, has two classes differing in helical symmetry, and achieves 7.84- and 7.90-Å spatial resolution in the reconstructions for the two classes.

Reconstruction of helical filaments and tubes

While Fourier-Bessel methods gave rise to the first three-dimensional reconstruction of an object from electron microscopic images, and these methods have dominated three-dimensional reconstruction of helical filaments and tubes for 30 years, single-particle approaches to helical reconstruction have emerged within the past 10 years that are now the main method being used. The Iterative Helical Real Space Reconstruction (IHRSR) approach has been the main methodology, and it surmounts many of the problems posed by real polymers that are flexible, display less than crystalline order, or are weakly scattering. The main difficulty in applying this method, or even Fourier-Bessel methods, is in determining the approximate helical symmetry. This chapter focuses on some of the intrinsic ambiguities that are present when trying to determine the helical symmetry from power spectra of images and argues that complementary techniques or some form of prior knowledge about the subunit may be needed to have confidence in the solution that is found.

Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics

A novel method to flexibly fit atomic structures into electron microscopy (EM) maps using molecular dynamics simulations is presented. The simulations incorporate the EM data as an external potential added to the molecular dynamics force field, allowing all internal features present in the EM map to be used in the fitting process, while the model remains fully flexible and stereochemically correct. The molecular dynamics flexible fitting (MDFF) method is validated for available crystal structures of protein and RNA in different conformations; measures to assess and monitor the fitting process are introduced. The MDFF method is then used to obtain high-resolution structures of the E. coli ribosome in different functional states imaged by cryo-EM.

Plant viruses as biotemplates for materials and their use in nanotechnology

In recent years, plant virus capsids, the protein shells that form the surface of a typical plant virus particle, have emerged as useful biotemplates for material synthesis. All virus capsids are assembled from virus-coded protein subunits. Many plant viruses assemble capsids with precise 3D structures providing nanoscale architectures that are highly homogeneous and can be produced in large quantities. Capsids are amenable to both genetic and chemical modifications allowing new functions to be incorporated into their structure by design. The three capsid surfaces, the interior surface, the exterior surface, or the interface between coat protein subunits, can be independently functionalized to produce multifunctional biotemplates. In this review, we examine the recent advances in using plant virus capsids as biotemplates for nanomaterials and their potential for applications in nanotechnology, especially medicine.

3D electron microscopy of biological nanomachines: principles and applications

Transmission electron microscopy is a powerful technique for studying the three-dimensional (3D) structure of a wide range of biological specimens. Knowledge of this structure is crucial for fully understanding complex relationships among macromolecular complexes and organelles in living cells. In this paper, we present the principles and main application domains of 3D transmission electron microscopy in structural biology. Moreover, we survey current developments needed in this field, and discuss the close relationship of 3D transmission electron microscopy with other experimental techniques aimed at obtaining structural and dynamical information from the scale of whole living cells to atomic structure of macromolecular complexes.

A novel method for improvement of visualization of power spectra for sorting cryo-electron micrographs and their local areas

In a context of automation of cryo-electron microscopy, we developed a novel method for improving visibility of diffraction rings in the power spectra of cryo-electron micrographs of vitreous ice (without carbon film or high concentration of diffracting material). We used these enhanced spectra to semi-automatically detect and remove micrographs and/or local areas introducing errors in the global 3D map (drifted and charged areas) or those unable to increase global signal-to-noise ratio (non-diffracting areas). Our strategy also allows a detection of micrographs/areas with a strong astigmatism. These images should be removed when using algorithms that do not correct astigmatism. Our sorting method is simple and fast since it uses the normalized cross-correlation between enhanced spectra and their copies rotated by 90 degrees. It owes its success mainly to the novel pre-processing of power spectra. The improved visibility also allows an easier visual check of accuracy of sorting. We show that our algorithm can even improve the visibility of diffraction rings of cryo-electron micrographs of pure water. Moreover, we show that this visibility depends strongly on ice thickness. This algorithm is implemented in the Xmipp (open-source image processing package) and is freely available for implementation in any other software package.

Viruses: making friends with old foes

The study of viruses has traditionally focused on their roles as infectious agents and as tools for understanding cell biology. Viruses are now finding a new expanded role as nanoplatforms with applications in materials science and medicine. Viruses form highly symmetrical monodisperse architectures and are ideal templates for engineering multifunctionality, including multivalent display of surface ligands and encapsulation of inorganic and organic materials. These developments assure that viruses will find applications as versatile nanoscale materials.

Particle picking by segmentation: a comparative study with SPIDER-based manual particle picking

Boxing hundreds of thousands of particles in low-dose electron micrographs is one of the major bottle-necks in advancing toward achieving atomic resolution reconstructions of biological macromolecules. We have shown that a combination of pre-processing operations and segmentation can be used as an effective, automatic tool for identifying and boxing single-particle images. This paper provides a brief description of how this method has been applied to a large data set of micrographs of ice-embedded ribosomes, including a comparative analysis of the efficiency of the method. Some results on processing micrographs of tripeptidyl peptidase II particles are also shown. In both cases, we have achieved our goal of selecting at least 80% of the particles that an expert would select with less than 10% false positives.

Automated molecular microscopy: the new Leginon system

We report here on the current state of our efforts in automated molecular microscopy. Our primary automated data acquisition software system, Leginon, has been completely redesigned over the past two years. The new distributed system has been developed using the Python programming language and is compatible with both Linux and Windows operating systems. The new flexible architecture was designed to allow for the development of customized data collection protocols, several of which are described here. The system has been used to acquire data for approximately 150 experiments and we have demonstrated the capacity for high throughput data acquisition by acquiring images of more than 100,000 particles in a single session at the microscope.

High-throughput film-densitometry: an efficient approach to generate large data sets

A film-handling machine (robot) has been built which can, in conjunction with a commercially available film densitometer, exchange and digitize over 300 electron micrographs per day. Implementation of robotic film handling effectively eliminates the delay and tedium associated with digitizing images when data are initially recorded on photographic film. The modulation transfer function (MTF) of the commercially available densitometer is significantly worse than that of a high-end, scientific microdensitometer. Nevertheless, its signal-to-noise ratio (S/N) is quite excellent, allowing substantial restoration of the output to "near-to-perfect" performance. Due to the large area of the standard electron microscope film that can be digitized by the commercial densitometer (up to 10,000 x 13,680 pixels with an appropriately coded holder), automated film digitization offers a fast and inexpensive alternative to high-end CCD cameras as a means of acquiring large amounts of image data in electron microscopy.

ACE: automated CTF estimation

We present a completely automated algorithm for estimating the parameters of the contrast transfer function (CTF) of a transmission electron microscope. The primary contribution of this paper is the determination of the astigmatism prior to the estimation of the CTF parameters. The CTF parameter estimation is then reduced to a 1D problem using elliptical averaging. We have also implemented an automated method to calculate lower and upper cutoff frequencies to eliminate regions of the power spectrum which perturb the estimation of the CTF parameters. The algorithm comprises three optimization subproblems, two of which are proven to be convex. Results of the CTF estimation method are presented for images of carbon support films as well as for images of single particles embedded in ice and suspended over holes in the support film. A MATLAB implementation of the algorithm, called ACE, is freely available.

Image segmentation for automatic particle identification in electron micrographs based on hidden Markov random field models and expectation maximization

Three-dimensional reconstruction of large macromolecules like viruses at resolutions below 10 A requires a large set of projection images. Several automatic and semi-automatic particle detection algorithms have been developed along the years. Here we present a general technique designed to automatically identify the projection images of particles. The method is based on Markov random field modelling of the projected images and involves a pre-processing of electron micrographs followed by image segmentation and post-processing. The image is modelled as a coupling of two fields--a Markovian and a non-Markovian. The Markovian field represents the segmented image. The micrograph is the non-Markovian field. The image segmentation step involves an estimation of coupling parameters and the maximum á posteriori estimate of the realization of the Markovian field i.e, segmented image. Unlike most current methods, no bootstrapping with an initial selection of particles is required.

Automated three-dimensional reconstruction of keyhole limpet hemocyanin type 1

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.

Automatic particle detection through efficient Hough transforms

Manual selection of single particles in images acquired using cryo-electron microscopy (cryoEM) will become a significant bottleneck when a very large number of images are required to achieve three-dimensional reconstructions at near atomic resolution. Investigation of fast, accurate approaches for automatic particle detection has become one of the current challenges in the cryoEM community. At the same time, the investigation is hampered by the fact that few benchmark particles or image datasets exist in the community. The unavailability of such data makes it difficult to evaluate newly developed algorithms and to leverage expertise from other disciplines. The paper presents our recent contribution to this effort. It also describes our newly developed computational framework for particle detection, through the application of edge detection and a sequence of ordered Hough transforms. Experimental results using keyhole limpet hemocyanin (KLH) as a model particle are very promising. In addition, it introduces a newly established web site, designed to support the investigation of automatic particle detection by providing an annotated image dataset of KLH available to the general scientific community.

From words to literature in structural proteomics

Technical advances on several frontiers have expanded the applicability of existing methods in structural biology and helped close the resolution gaps between them. As a result, we are now poised to integrate structural information gathered at multiple levels of the biological hierarchy - from atoms to cells - into a common framework. The goal is a comprehensive description of the multitude of interactions between molecular entities, which in turn is a prerequisite for the discovery of general structural principles that underlie all cellular processes.