Single-particle reconstruction statistics: a diagnostic tool in solving biomolecular structures by cryo-EM.

In single-particle analysis (SPA), the aim is to obtain a 3D reconstruction of a biological molecule from 2D electron micrographs to the highest level of detail or resolution as possible. Current practice is to collect large volumes of data, hoping to reach high-resolution maps through sheer numbers. However, adding more particles from a specific data set eventually leads to diminishing improvements in resolution. Understanding what these resolution limits are and how to deal with them are important in optimization and automation of SPA. This study revisits the theory of 3D reconstruction and demonstrates how the associated statistics can provide a diagnostic tool to improve SPA. Small numbers of images already give sufficient information on micrograph quality and the amount of data required to reach high resolution. Such feedback allows the microscopist to improve sample-preparation and imaging parameters before committing to extensive data collection. Once a larger data set is available, a B factor can be determined describing the suppression of the signal owing to one or more causes, such as specimen movement, radiation damage, alignment inaccuracy and structural variation. Insight into the causes of signal suppression can then guide the user to consider appropriate actions to obtain better reconstructions.

Consideration of sample motion in cryo-tomography based on alignment residual interpolation.

Recently, it has been shown that the resolution in cryo-tomography could be improved by considering the sample motion in tilt-series alignment and reconstruction, where a set of quadratic polynomials were used to model this motion. One requirement of this polynomial method is the optimization of a large number of parameters, which may limit its practical applicability. In this work, we propose an alternative method for modeling the sample motion. Starting from the standard fiducial-based tilt-series alignment, the method uses the alignment residual as local estimates of the sample motion at the 3D fiducial positions. Then, a scattered data interpolation technique characterized by its smoothness and a closed-form solution is applied to model the sample motion. The motion model is then integrated in the tomographic reconstruction. The new method improves the tomogram quality similar to the polynomial one, with the important advantage that the determination of the motion model is greatly simplified, thereby overcoming one of the major limitations of the polynomial model. Therefore, the new method is expected to make the beam-induced motion correction methodology more accessible to the cryoET community.

Big data in cryoEM: automated collection, processing and accessibility of EM data.

The scope and complexity of cryogenic electron microscopy (cryoEM) data has greatly increased, and will continue to do so, due to recent and ongoing technical breakthroughs that have led to much improved resolutions for macromolecular structures solved using this method. This big data explosion includes single particle data as well as tomographic tilt series, both generally acquired as direct detector movies of ∼10-100 frames per image or per tilt-series. We provide a brief survey of the developments leading to the current status, and describe existing cryoEM pipelines, with an emphasis on the scope of data acquisition, methods for automation, and use of cloud storage and computing.

Blob-ology and biology of cryo-EM: an interview with Helen Saibil.

Helen Saibil is Bernal Professor of Structural Biology at Birkbeck, University of London. After undergraduate work at McGill University, Canada, Helen moved to London for her PhD at Kings College. After stints at CEA Grenoble and the University of Oxford, she moved to Birkbeck where her lab studies the operation of macromolecular machinery-including molecular chaperones, protein folding/misfolding, and host cell interactions with pathogens. Helen is a Fellow of the Royal Society, Fellow of the Academy of Medical Sciences, and an Honorary Member of both the British Biophysical Society and the Royal Microscopical Society. She talked to us about the background, recent developments, and future prospects in cryo-electron microscopy.

Databases and Archiving for CryoEM.

CryoEM in structural biology is currently served by three public archives-EMDB for 3DEM reconstructions, PDB for models built from 3DEM reconstructions, and EMPIAR for the raw 2D image data used to obtain the 3DEM reconstructions. These archives play a vital role for both the structural community and the wider biological community in making the data accessible so that results may be reused, reassessed, and integrated with other structural and bioinformatics resources. The important role of the archives is underpinned by the fact that many journals mandate the deposition of data to PDB and EMDB on publication. The field is currently undergoing transformative changes where on the one hand high-resolution structures are becoming a routine occurrence while on the other hand electron tomography is enabling the study of macromolecules in the cellular context. Concomitantly the archives are evolving to best serve their stakeholder communities. In this chapter, we describe the current state of the archives, resources available for depositing, accessing, searching, visualizing and validating data, on-going community-wide initiatives and opportunities, and challenges for the future.

Accurate membrane tracing in three-dimensional reconstructions from electron cryotomography data.

The connection between the extracellular matrix and the cell is of major importance for mechanotransduction and mechanobiology. Electron cryo-tomography, in principle, enables better than nanometer-resolution analysis of these connections, but restrictions of data collection geometry hamper the accurate extraction of the ventral membrane location from these tomograms, an essential prerequisite for the analysis. Here, we introduce a novel membrane tracing strategy that enables ventral membrane extraction at high fidelity and extraordinary accuracy. The approach is based on detecting the boundary between the inside and the outside of the cell rather than trying to explicitly trace the membrane. Simulation studies show that over 99% of the membrane can be correctly modeled using this principle and the excellent match of visually identifiable membrane stretches with the extracted boundary of experimental data indicates that the accuracy is comparable for actual data.

Cryo-EM enters a new era.

Advances in detector hardware and image-processing software have led to a revolution in the use of electron cryo-microscopy to determine complex molecular structures at high resolution.

Beam-induced motion correction for sub-megadalton cryo-EM particles.

In electron cryo-microscopy (cryo-EM), the electron beam that is used for imaging also causes the sample to move. This motion blurs the images and limits the resolution attainable by single-particle analysis. In a previous Research article (Bai et al., 2013) we showed that correcting for this motion by processing movies from fast direct-electron detectors allowed structure determination to near-atomic resolution from 35,000 ribosome particles. In this Research advance article, we show that an improved movie processing algorithm is applicable to a much wider range of specimens. The new algorithm estimates straight movement tracks by considering multiple particles that are close to each other in the field of view, and models the fall-off of high-resolution information content by radiation damage in a dose-dependent manner. Application of the new algorithm to four data sets illustrates its potential for significantly improving cryo-EM structures, even for particles that are smaller than 200 kDa.

M-free: scoring the reference bias in sub-tomogram averaging and template matching.

Cryo-electron tomography provides a snapshot of the cellular proteome. With template matching, the spatial positions of various macromolecular complexes within their native cellular context can be detected. However, the growing awareness of the reference bias introduced by the cross-correlation based approaches, and more importantly the lack of a reliable confidence measurement in the selection of these macromolecular complexes, has restricted the use of these applications. Here we propose a heuristic, in which the reference bias is measured in real space in an analogous way to the R-free value in X-ray crystallography. We measure the reference bias within the mask used to outline the area of the template, and do not modify the template itself. The heuristic works by splitting the mask into a working and a testing area in a volume ratio of 9:1. While the working area is used during the calculation of the cross-correlation function, the information from both areas is explored to calculate the M-free score. We show using artificial data, that the M-free score gives a reliable measure for the reference bias. The heuristic can be applied in template matching and in sub-tomogram averaging. We further test the applicability of the heuristic in tomograms of purified macromolecules, and tomograms of whole Mycoplasma cells.

Deep classification of a large cryo-EM dataset defines the conformational landscape of the 26S proteasome.

The 26S proteasome is a 2.5 MDa molecular machine that executes the degradation of substrates of the ubiquitin-proteasome pathway. The molecular architecture of the 26S proteasome was recently established by cryo-EM approaches. For a detailed understanding of the sequence of events from the initial binding of polyubiquitylated substrates to the translocation into the proteolytic core complex, it is necessary to move beyond static structures and characterize the conformational landscape of the 26S proteasome. To this end we have subjected a large cryo-EM dataset acquired in the presence of ATP and ATP-γS to a deep classification procedure, which deconvolutes coexisting conformational states. Highly variable regions, such as the density assigned to the largest subunit, Rpn1, are now well resolved and rendered interpretable. Our analysis reveals the existence of three major conformations: in addition to the previously described ATP-hydrolyzing (ATPh) and ATP-γS conformations, an intermediate state has been found. Its AAA-ATPase module adopts essentially the same topology that is observed in the ATPh conformation, whereas the lid is more similar to the ATP-γS bound state. Based on the conformational ensemble of the 26S proteasome in solution, we propose a mechanistic model for substrate recognition, commitment, deubiquitylation, and translocation into the core particle.

CTER-rapid estimation of CTF parameters with error assessment.

In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03Å without, and 3.85Å with, inclusion of astigmatism parameters.

Enhanced sampling and overfitting analyses in structural refinement of nucleic acids into electron microscopy maps.

Flexible fitting computational algorithms are often useful to interpret low-resolution maps of many macromolecular complexes generated by electron microscopy (EM) imaging. One such atomistic simulation technique is molecular dynamics flexible fitting (MDFF), which has been widely applied to generate structural models of large ribonucleoprotein assemblies such as the ribosome. We have previously shown that MDFF simulations of globular proteins are sensitive to the resolution of the target EM map and the strength of restraints used to preserve the secondary structure elements during fitting (Vashisth, H.; et al. Structure 2012, 20, 1453-1462). In this work, we aim to systematically examine the quality of structural models of various nucleic acids obtained via MDFF by varying the map resolution and the strength of structural restraints. We also demonstrate how an enhanced conformational sampling technique for proteins, temperature-accelerated molecular dynamics (TAMD), can be combined with MDFF for the structural refinement of nucleic acids in EM maps. Finally, we also demonstrate application of TAMD-assisted MDFF (TAMDFF) on a RNA/protein complex and suggest that TAMDFF is a viable strategy for enhanced conformational fitting in target maps of ribonucleoprotein complexes.

Workshop on the validation and modeling of electron cryo-microscopy structures of biological nanomachines.

Electron cryo-microscopy (cryoEM) is a rapidly maturing methodology in structural biology, which now enables the determination of 3D structures of molecules, macromolecular complexes and cellular components at resolutions as high as 3.5Å, bridging the gap between light microscopy and X-ray crystallography/NMR. In recent years structures of many complex molecular machines have been visualized using this method. Single particle reconstruction, the most widely used technique in cryoEM, has recently demonstrated the capability of producing structures at resolutions approaching those of X-ray crystallography, with over a dozen structures at better than 5 Å resolution published to date. This method represents a significant new source of experimental data for molecular modeling and simulation studies. CryoEM derived maps and models are archived through EMDataBank.org joint deposition services to the EM Data Bank (EMDB) and Protein Data Bank (PDB), respectively. CryoEM maps are now being routinely produced over the 3 - 30 Å resolution range, and a number of computational groups are developing software for building coordinate models based on this data and developing validation techniques to better assess map and model accuracy. In this workshop we will present the results of the first cryoEM modeling challenge, in which computational groups were asked to apply their tools to a selected set of published cryoEM structures. We will also compare the results of the various applied methods, and discuss the current state of the art and how we can most productively move forward.

Quantitative analysis of cryo-EM density map segmentation by watershed and scale-space filtering, and fitting of structures by alignment to regions.

Cryo-electron microscopy produces 3D density maps of molecular machines, which consist of various molecular components such as proteins and RNA. Segmentation of individual components in such maps is a challenging task, and is mostly accomplished interactively. We present an approach based on the immersive watershed method and grouping of the resulting regions using progressively smoothed maps. The method requires only three parameters: the segmentation threshold, a smoothing step size, and the number of smoothing steps. We first apply the method to maps generated from molecular structures and use a quantitative metric to measure the segmentation accuracy. The method does not attain perfect accuracy, however it produces single or small groups of regions that roughly match individual proteins or subunits. We also present two methods for fitting of structures into density maps, based on aligning the structures with single regions or small groups of regions. The first method aligns centers and principal axes, whereas the second aligns centers and then rotates the structure to find the best fit. We describe both interactive and automated ways of using these two methods. Finally, we show segmentation and fitting results for several experimentally-obtained density maps.

Cryo-EM image alignment based on nonuniform fast Fourier transform.

In single particle analysis, two-dimensional (2-D) alignment is a fundamental step intended to put into register various particle projections of biological macromolecules collected at the electron microscope. The efficiency and quality of three-dimensional (3-D) structure reconstruction largely depends on the computational speed and alignment accuracy of this crucial step. In order to improve the performance of alignment, we introduce a new method that takes advantage of the highly accurate interpolation scheme based on the gridding method, a version of the nonuniform fast Fourier transform, and utilizes a multi-dimensional optimization algorithm for the refinement of the orientation parameters. Using simulated data, we demonstrate that by using less than half of the sample points and taking twice the runtime, our new 2-D alignment method achieves dramatically better alignment accuracy than that based on quadratic interpolation. We also apply our method to image to volume registration, the key step in the single particle EM structure refinement protocol. We find that in this case the accuracy of the method not only surpasses the accuracy of the commonly used real-space implementation, but results are achieved in much shorter time, making gridding-based alignment a perfect candidate for efficient structure determination in single particle analysis.

Modeling experimental image formation for likelihood-based classification of electron microscopy data.

The coexistence of multiple distinct structural states often obstructs the application of three-dimensional cryo-electron microscopy to large macromolecular complexes. Maximum likelihood approaches are emerging as robust tools for solving the image classification problems that are posed by such samples. Here, we propose a statistical data model that allows for a description of the experimental image formation within the formulation of 2D and 3D maximum-likelihood refinement. The proposed approach comprises a formulation of the probability calculations in Fourier space, including a spatial frequency-dependent noise model and a description of defocus-dependent imaging effects. The Expectation-Maximization-like algorithms presented are generally applicable to the alignment and classification of structurally heterogeneous projection data. Their effectiveness is demonstrated with various examples, including 2D classification of top views of the archaeal helicase MCM and 3D classification of 70S E. coli ribosome and Simian Virus 40 large T-antigen projections.

Electronic detectors for electron microscopy.

Due to the increasing popularity of electron cryo-microscopy (cryoEM) in the structural analysis of large biological molecules and macro-molecular complexes and the need for simple, rapid and efficient readout, there is a persuasive need for improved detectors. Commercial detectors, based on phosphor/fibre optics-coupled CCDs, provide adequate performance for many applications, including electron diffraction. However, due to intrinsic light scattering within the phosphor, spatial resolution is limited. Careful measurements suggest that CCDs have superior performance at lower resolution while all agree that film is still superior at higher resolution. Consequently, new detectors are needed based on more direct detection, thus avoiding the intermediate light conversion step required for CCDs. Two types of direct detectors are discussed in this review. First, there are detectors based on hybrid technology employing a separate pixellated sensor and readout electronics connected with bump bonds-hybrid pixel detectors (HPDs). Second, there are detectors, which are monolithic in that sensor and readout are all in one plane (monolithic active pixel sensor, MAPS). Our discussion is centred on the main parameters of interest to cryoEM users, viz. detective quantum efficiency (DQE), resolution or modulation transfer function (MTF), robustness against radiation damage, speed of readout, signal-to-noise ratio (SNR) and the number of independent pixels available for a given detector.

Automated cryoelectron microscopy of "single particles" applied to the 26S proteasome.

The 26S proteasome is a large molecular machine with a central role in intracellular protein degradation in eukaryotes. The 2.5 MDa complex, which is built from two copies each of more than 30 different subunits, is labile and prone to dissociation into subcomplexes. Hence it is difficult if not impossible, to obtain structurally homogeneous preparations and, as a consequence, it is very cumbersome to obtain large numbers of images of the holocomplex. In this communication, we describe an automated procedure for the acquisition of large data sets of cryoelectron micrographs. The application of this procedure to the 26S proteasome from Drosophila has allowed us to determine the three-dimensional structure of the complex to a resolution of 2.9 nm and the prospects for further improvements are good.

A method of focused classification, based on the bootstrap 3D variance analysis, and its application to EF-G-dependent translocation.

The bootstrap-based method for calculation of the 3D variance in cryo-EM maps reconstructed from sets of their projections was applied to a dataset of functional ribosomal complexes containing the Escherichia coli 70S ribosome, tRNAs, and elongation factor G (EF-G). The variance map revealed regions of high variability in the intersubunit space of the ribosome: in the locations of tRNAs, in the putative location of EF-G, and in the vicinity of the L1 protein. This result indicated heterogeneity of the dataset. A method of focused classification was put forward in order to sort out the projection data into approximately homogenous subsets. The method is based on the identification and localization of a region of high variance that a subsequent classification step can be focused on by the use of a 3D spherical mask. After initial classification, template volumes are created and are subsequently refined using a multireference 3D projection alignment procedure. In the application to the ribosome dataset, the two resulting structures were interpreted as resulting from ribosomal complexes with bound EF-G and an empty A site, or, alternatively, from complexes that had no EF-G bound but had both A and P sites occupied by tRNA. The proposed method of focused classification proved to be a successful tool in the analysis of the heterogeneous cryo-EM dataset. The associated calculation of the correlations within the density map confirmed the conformational variability of the complex, which could be interpreted in terms of the ribosomal elongation cycle.