MRC2014: Extensions to the MRC format header for electron cryo-microscopy and tomography

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.

Accurate magnification determination for cryoEM using gold

Determining the correct magnified pixel size of single-particle cryoEM micrographs is necessary to maximize resolution and enable accurate model building. Here we describe a simple and rapid procedure for determining the absolute magnification in an electron cryomicroscope to a precision of <0.5%. We show how to use the atomic lattice spacings of crystals of thin and readily available test specimens, such as gold, as an absolute reference to determine magnification for both room temperature and cryogenic imaging. We compare this method to other commonly used methods, and show that it provides comparable accuracy in spite of its simplicity. This magnification calibration method provides a definitive reference quantity for data analysis and processing, simplifies the combination of multiple datasets from different microscopes and detectors, and improves the accuracy with which the contrast transfer function of the microscope can be determined. We also provide an open source program, magCalEM, which can be used to accurately estimate the magnified pixel size of a cryoEM dataset ex post facto.

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. It is larger and of higher quality than any existing, publicly available dataset. We trained and tested deep learning models on Cryo2StructData to make sure it is ready for the large-scale development of AI methods for building atomic models from cryo-EM density maps.

A standard data format for 3DED/MicroED

Electron diffraction from three dimensional crystals, as a technique for solving molecular structures, is rapidly increasing in popularity. The development of methodology and software has borrowed, to great effect, from macromolecular X-ray crystallography. However, standardization lags behind the development of the technique, and practitioners are forced to work with inadequate data formats that are unable to capture a full description of their experiments. This creates obstacles that are increasingly difficult to overcome as experiments become ever faster and the need for data autoprocessing becomes more pressing. We present a data format standard based on best practice from macromolecular crystallography and demonstrate how the adoption of this standard enabled autoprocessing of datasets collected with a high-throughput detector system.

Thirty Years of the DICOM Standard

Digital Imaging and Communications in Medicine (DICOM) is an international standard that defines a format for storing medical images and a protocol to enable and facilitate data communication among medical imaging systems. The DICOM standard has been instrumental in transforming the medical imaging world over the last three decades. Its adoption has been a significant experience for manufacturers, healthcare users, and research scientists. In this review, thirty years after introducing the standard, we discuss the innovation, advantages, and limitations of adopting the DICOM and its possible future directions.

MRC2020: improvements to Ximdisp and the MRC image-processing programs

The great success of single-particle electron cryo-microscopy (cryoEM) during the last decade has involved the development of powerful new computer programs and packages that guide the user along a recommended processing workflow, in which the wisdom and choices made by the developers help everyone, especially new users, to obtain excellent results. The ability to carry out novel, non-standard or unusual combinations of image-processing steps is sometimes compromised by the convenience of a standard procedure. Some of the older programs were written with great flexibility and are still very valuable. Among these, the original MRC image-processing programs for structure determination by 2D crystal and helical processing alongside general-purpose utility programs such as Ximdisp, label, imedit and twofile are still available. This work describes an updated version of the MRC software package (MRC2020) that is freely available from CCP-EM. It includes new features and improvements such as extensions to the MRC format that retain the versatility of the package and make it particularly useful for testing novel computational procedures in cryoEM.

Investigation of the milling characteristics of different focused-ion-beam sources assessed by three-dimensional electron diffraction from crystal lamellae

Three-dimensional electron diffraction (3DED) from nanocrystals of biological macromolecules requires the use of very small crystals. These are typically less than 300 nm-thick in the direction of the electron beam due to the strong interaction between electrons and matter. In recent years, focused-ion-beam (FIB) milling has been used in the preparation of thin samples for 3DED. These instruments typically use a gallium liquid metal ion source. Inductively coupled plasma (ICP) sources in principle offer faster milling rates. Little work has been done to quantify the damage these sources cause to delicate biological samples at cryogenic temperatures. Here, an analysis of the effect that milling with plasma FIB (pFIB) instrumentation has on lysozyme crystals is presented. This work evaluates both argon and xenon plasmas and compares them with crystals milled with a gallium source. A milling protocol was employed that utilizes an overtilt to produce wedge-shaped lamellae with a shallow thickness gradient which yielded very thin crystalline samples. 3DED data were then acquired and standard data-processing statistics were employed to assess the quality of the diffraction data. An upper bound to the depth of the pFIB-milling damage layer of between 42.5 and 50 nm is reported, corresponding to half the thickness of the thinnest lamellae that resulted in usable diffraction data. A lower bound of between 32.5 and 40 nm is also reported, based on a literature survey of the minimum amount of diffracting material required for 3DED.

Prediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental data

The hydration structures of proteins, which are necessary for their folding, stability, and functions, were visualized using X-ray and neutron crystallography and transmission electron microscopy. However, complete visualization of hydration structures over the entire protein surface remains difficult. To compensate for this incompleteness, we developed a three-dimensional convolutional neural network to predict the probability distribution of hydration water molecules on the hydrophilic and hydrophobic surfaces, and in the cavities of proteins. The neural network was optimized using the distribution patterns of protein atoms around the hydration water molecules identified in the high-resolution X-ray crystal structures. We examined the feasibility of the neural network using water sites in the protein crystal structures that were not included in the datasets. The predicted distribution covered most of the experimentally identified hydration sites, with local maxima appearing in their vicinity. This computational approach will help to highlight the relevance of hydration structures to the biological functions and dynamics of proteins.

Graph identification of proteins in tomograms (GRIP-Tomo)

In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three-dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo-multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single-domain protein native topologies as well as distinct single-domain proteins from multimeric complexes within noisy volumes.

Precision requirements and data compression in CryoEM/CryoET

With larger, higher speed detectors and improved automation, individual CryoEM instruments are capable of producing a prodigious amount of data each day, which must then be stored, processed and archived. While it has become routine to use lossless compression on raw counting-mode movies, the averages which result after correcting these movies no longer compress well. These averages could be considered sufficient for long term archival, yet they are conventionally stored with 32 bits of precision, despite high noise levels. Derived images are similarly stored with excess precision, providing an opportunity to decrease project sizes and improve processing speed. We present a simple argument based on propagation of uncertainty for safe bit truncation of flat-fielded images combined with lossless compression. The same method can be used for most derived images throughout the processing pipeline. We test the proposed strategy on two standard, data-limited CryoEM data sets, demonstrating that these limits are safe for real-world use. We find that 5 bits of precision is sufficient for virtually any raw CryoEM data and that 8-12 bits is sufficient for intermediate averages or final 3-D structures. Additionally, we detail and recommend specific rules for discretization of data as well as a practical compressed data representation that is tuned to the specific needs of CryoEM.

Bsoft: Image Processing for Structural Biology

Bsoft is a software package primarily developed for processing electron micrographs, with the goal of determining the structures of biologically relevant molecules, molecular assemblies, and parts of cells. However, it incorporates many ways to deal with images, from the mundane to very sophisticated algorithms. This article is an introduction into its use, illustrating that it is an extensive toolbox, for manipulating and understanding images. Bsoft has over 150 programs, allowing the user an infinite number of ways to process images. These programs can be executed on the command line, or through the interactive program called brun. The main visualization program is bshow, providing numerous ways to manipulate and interpret images. The primary aim is to provide the user with powerful capabilities, including processing large numbers of images. An important additional aim is to make it as accessible as possible, making it easier to deal with image formats and features, and enhance productivity.

Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

Python-based Helix Indexer: A graphical user interface program for finding symmetry of helical assembly through Fourier-Bessel indexing of electron microscopic data

Many macromolecules form helical assemblies to carry out their functions. Helical reconstruction from electron microscopic images is a powerful approach for solving high-resolution structures of such assemblies. Determination of the symmetry parameters of the helical assemblies is a prerequisite step in helical reconstruction. The most widely used method for deducing the symmetry is through Fourier-Bessel indexing the diffraction pattern of the helical assemblies. This method, however, often leads to incorrect solutions, due to intrinsic ambiguities in indexing helical diffraction patterns. Here, we present Python-based Helix Indexer (PyHI), which provides a graphical user interface (GUI) to guide the users through the process of symmetry determination. Diffraction patterns can be read into the program directly or calculated on the fly from two-dimensional class averages of helical assemblies. PyHI allows deducing the Bessel orders of diffraction peaks by using both the amplitudes and phases of the diffraction data. Based on the Bessel orders of two unit vectors, the Fourier space lattice is constructed with minimal user inputs. The program then uses a refinement algorithm to optimize the Fourier space lattice, and subsequently generate the helical assembly in real space. The program provides both a publication-quality graphic representation of the helical assembly and the symmetry parameters required for subsequent helical reconstruction steps.

EMDA: A Python package for Electron Microscopy Data Analysis

An open-source Python library EMDA for cryo-EM map and model manipulation is presented with a specific focus on validation. The use of several functionalities in the library is presented through several examples. The utility of local correlation as a metric for identifying map-model differences and unmodeled regions in maps, and how it is used as a metric of map-model validation is demonstrated. The mapping of local correlation to individual atoms, and its use to draw insights on local signal variations are discussed. EMDA’s likelihood-based map overlay is demonstrated by carrying out a superposition of two domains in two related structures. The overlay is carried out first to bring both maps into the same coordinate frame and then to estimate the relative movement of domains. Finally, the map magnification refinement in EMDA is presented with an example to highlight the importance of adjusting the map magnification in structural comparison studies.

Flexible STEM with Simultaneous Phase and Depth Contrast

Recent advances in scanning transmission electron microscopy (STEM) have rekindled interest in multi-channel detectors and prompted the exploration of unconventional scan patterns. These emerging needs are not yet addressed by standard commercial hardware. The system described here incorporates a flexible scan generator that enables exploration of low-acceleration scan patterns, while data are recorded by a scalable eight-channel array of nonmultiplexed analog-to-digital converters. System integration with SerialEM provides a flexible route for automated acquisition protocols including tomography. Using a solid-state quadrant detector with additional annular rings, we explore the generation and detection of various STEM contrast modes. Through-focus bright-field scans relate to phase contrast, similarly to wide-field TEM. More strikingly, comparing images acquired from different off-axis detector elements reveals lateral shifts dependent on defocus. Compensation of this parallax effect leads to decomposition of integrated differential phase contrast (iDPC) to separable contributions relating to projected electric potential and to defocus. Thus, a single scan provides both a computationally refocused phase contrast image and a second image in which the signed intensity, bright or dark, represents the degree of defocus.

Parakeet: a digital twin software pipeline to assess the impact of experimental parameters on tomographic reconstructions for cryo-electron tomography

In cryo-electron tomography (cryo-ET) of biological samples, the quality of tomographic reconstructions can vary depending on the transmission electron microscope (TEM) instrument and data acquisition parameters. In this paper, we present Parakeet, a 'digital twin' software pipeline for the assessment of the impact of various TEM experiment parameters on the quality of three-dimensional tomographic reconstructions. The Parakeet digital twin is a digital model that can be used to optimize the performance and utilization of a physical instrument to enable in silico optimization of sample geometries, data acquisition schemes and instrument parameters. The digital twin performs virtual sample generation, TEM image simulation, and tilt series reconstruction and analysis within a convenient software framework. As well as being able to produce physically realistic simulated cryo-ET datasets to aid the development of tomographic reconstruction and subtomogram averaging programs, Parakeet aims to enable convenient assessment of the effects of different microscope parameters and data acquisition parameters on reconstruction quality. To illustrate the use of the software, we present the example of a quantitative analysis of missing wedge artefacts on simulated planar and cylindrical biological samples and discuss how data collection parameters can be modified for cylindrical samples where a full 180° tilt range might be measured.

Reconstruction of Three-Dimensional Conformations of Bacterial ClpB from High-Speed Atomic-Force-Microscopy Images

ClpB belongs to the cellular disaggretase machinery involved in rescuing misfolded or aggregated proteins during heat or other cellular shocks. The function of this protein relies on the interconversion between different conformations in its native condition. A recent high-speed-atomic-force-microscopy (HS-AFM) experiment on ClpB from Thermus thermophilus shows four predominant conformational classes, namely, open, closed, spiral, and half-spiral. Analyses of AFM images provide only partial structural information regarding the molecular surface, and thus computational modeling of three-dimensional (3D) structures of these conformations should help interpret dynamical events related to ClpB functions. In this study, we reconstruct 3D models of ClpB from HS-AFM images in different conformational classes. We have applied our recently developed computational method based on a low-resolution representation of 3D structure using a Gaussian mixture model, combined with a Monte-Carlo sampling algorithm to optimize the agreement with target AFM images. After conformational sampling, we obtained models that reflect conformational variety embedded within the AFM images. From these reconstructed 3D models, we described, in terms of relative domain arrangement, the different types of ClpB oligomeric conformations observed by HS-AFM experiments. In particular, we highlighted the slippage of the monomeric components around the seam. This study demonstrates that such details of information, necessary for annotating the different conformational states involved in the ClpB function, can be obtained by combining HS-AFM images, even with limited resolution, and computational modeling.

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

ProDy 2.0: Increased Scale and Scope after 10 Years of Protein Dynamics Modelling with Python

Summary

ProDy, an integrated application programming interface developed for modelling and analysing protein dynamics, has significantly evolved in recent years in response to the growing data and needs of the computational biology community. We present major developments that led to ProDy 2.0: (i) improved interfacing with databases and parsing new file formats, (ii) SignDy for signature dynamics of protein families, (iii) CryoDy for collective dynamics of supramolecular systems using cryo-EM density maps and (iv) essential site scanning analysis for identifying sites essential to modulating global dynamics.

Availability and implementation

ProDy is open-source and freely available under MIT License from https://github.com/prody/ProDy.

Supplementary information

Supplementary data are available at Bioinformatics online.

TEMPy2: a Python library with improved 3D electron microscopy density-fitting and validation workflows

Structural determination of molecular complexes by cryo-EM requires large, often complex processing of the image data that are initially obtained. Here, TEMPy2, an update of the TEMPy package to process, optimize and assess cryo-EM maps and the structures fitted to them, is described. New optimization routines, comprehensive automated checks and workflows to perform these tasks are described.

Electron-event representation data enable efficient cryoEM file storage with full preservation of spatial and temporal resolution

Direct detector device (DDD) cameras have revolutionized electron cryomicroscopy (cryoEM) with their high detective quantum efficiency (DQE) and output of movie data. A high ratio of camera frame rate (frames per second) to camera exposure rate (electrons per pixel per second) allows electron counting, which further improves the DQE and enables the recording of super-resolution information. Movie output also allows the correction of specimen movement and compensation for radiation damage. However, these movies come at the cost of producing large volumes of data. It is common practice to sum groups of successive camera frames to reduce the final frame rate, and therefore the file size, to one suitable for storage and image processing. This reduction in the temporal resolution of the camera requires decisions to be made during data acquisition that may result in the loss of information that could have been advantageous during image analysis. Here, experimental analysis of a new electron-event representation (EER) data format for electron-counting DDD movies is presented, which is enabled by new hardware developed by Thermo Fisher Scientific for their Falcon DDD cameras. This format enables the recording of DDD movies at the raw camera frame rate without sacrificing either spatial or temporal resolution. Experimental data demonstrate that the method retains super-resolution information and allows the correction of specimen movement at the physical frame rate of the camera while maintaining manageable file sizes. The EER format will enable the development of new methods that can utilize the full spatial and temporal resolution of DDD cameras.

Mitigating local over-fitting during single particle reconstruction with SIDESPLITTER

Single particle analysis has become a key structural biology technique. Experimental images are extremely noisy, and during iterative refinement it is possible to stably incorporate noise into the reconstruction. Such "over-fitting" can lead to misinterpretation of the structure and flawed biological results. Several strategies are routinely used to prevent over-fitting, the most common being independent refinement of two sides of a split dataset. In this study, we show that over-fitting remains an issue within regions of low local signal-to-noise, despite independent refinement of half datasets. We propose a modification of the refinement process through the application of a local signal-to-noise filter: SIDESPLITTER. We show that our approach can reduce over-fitting for both idealised and experimental data while maintaining independence between the two sides of a split refinement. SIDESPLITTER refinement leads to improved density, and can also lead to improvement of the final resolution in extreme cases where datasets are prone to severe over-fitting, such as small membrane proteins.

Integration of Cryo-EM Model Building Software in Scipion

Advances in cryo-electron microscopy (cryo-EM) have made it possible to obtain structures of large biological macromolecules at near-atomic resolution. This "resolution revolution" has encouraged the use and development of modeling tools able to produce high-quality atomic models from cryo-EM density maps. Unfortunately, many practical problems appear when combining different packages in the same processing workflow, which make difficult the use of these tools by non-experts and, therefore, reduce their utility. We present here a major extension of the image processing framework Scipion that provides inter-package integration in the model building area and full tracking of the complete workflow, from image processing to structure validation.

Investigating eukaryotic cells with cryo-ET

The interior of eukaryotic cells is mysterious. How do the large communities of macromolecular machines interact with each other? How do the structures and positions of these nanoscopic entities respond to new stimuli? Questions like these can now be answered with the help of a method called electron cryotomography (cryo-ET). Cryo-ET will ultimately reveal the inner workings of a cell at the protein, secondary structure, and perhaps even side-chain levels. Combined with genetic or pharmacological perturbation, cryo-ET will allow us to answer previously unimaginable questions, such as how structure, biochemistry, and forces are related in situ. Because it bridges structural biology and cell biology, cryo-ET is indispensable for structural cell biology-the study of the 3-D macromolecular structure of cells. Here we discuss some of the key ideas, strategies, auxiliary techniques, and innovations that an aspiring structural cell biologist will consider when planning to ask bold questions.

MicroED with the Falcon III direct electron detector

Microcrystal electron diffraction (MicroED) combines crystallography and electron cryo-microscopy (cryo-EM) into a method that is applicable to high-resolution structure determination. In MicroED, nanosized crystals, which are often intractable using other techniques, are probed by high-energy electrons in a transmission electron microscope. Diffraction data are recorded by a camera in movie mode: the nanocrystal is continuously rotated in the beam, thus creating a sequence of frames that constitute a movie with respect to the rotation angle. Until now, diffraction-optimized cameras have mostly been used for MicroED. Here, the use of a direct electron detector that was designed for imaging is reported. It is demonstrated that data can be collected more rapidly using the Falcon III for MicroED and with markedly lower exposure than has previously been reported. The Falcon III was operated at 40 frames per second and complete data sets reaching atomic resolution were recorded in minutes. The resulting density maps to 2.1 Å resolution of the serine protease proteinase K showed no visible signs of radiation damage. It is thus demonstrated that dedicated diffraction-optimized detectors are not required for MicroED, as shown by the fact that the very same cameras that are used for imaging applications in electron microscopy, such as single-particle cryo-EM, can also be used effectively for diffraction measurements.

Software for automated acquisition of electron tomography tilt series

For automated acquisition of tilt series for electron tomography, software needs to handle complications such as movements of the sample in x/y and z, increased projected thickness at high tilt, specimen drift, etc. In addition, many applications require special functionality such as low dose acquisition, automated sequential (batch) tomography, or montage tomography. After reviewing how these difficulties can be addressed and a closer look at what advanced acquisition strategies are employed in biosciences, this chapter introduces acquisition software both developed in academia as well as by hardware vendors. It covers the hardware requirements and compatibility, the functional principle and workflow implemented, as well as what advanced functions are supported by the individual programs.

A collection of yeast cellular electron cryotomography data

BACKGROUND

Cells are powered by a large set of macromolecular complexes, which work together in a crowded environment. The in situ mechanisms of these complexes are unclear because their 3D distribution, organization, and interactions are largely unknown. Electron cryotomography (cryo-ET) can address these knowledge gaps because it produces cryotomograms-3D images that reveal biological structure at ∼4-nm resolution. Cryo-ET uses no fixation, dehydration, staining, or plastic embedment, so cellular features are visualized in a life-like, frozen-hydrated state. To study chromatin and mitotic machinery in situ, we subjected yeast cells to genetic and chemical perturbations, cryosectioned them, and then imaged the cells by cryo-ET.

FINDINGS

Here we share >1,000 cryo-ET raw datasets of cryosectioned budding yeast Saccharomyces cerevisiaecollected as part of previously published studies. These data will be valuable to cell biologists who are interested in the nanoscale organization of yeasts and of eukaryotic cells in general. All the unpublished tilt series and a subset of corresponding cryotomograms have been deposited in the EMPIAR resource for the community to use freely. To improve tilt series discoverability, we have uploaded metadata and preliminary notes to publicly accessible Google Sheets, EMPIAR, and GigaDB.

CONCLUSIONS

Cellular cryo-ET data can be mined to obtain new cell-biological, structural, and 3D statistical insights in situ. These data contain structures not visible in traditional electron-microscopy data. Template matching and subtomogram averaging of known macromolecular complexes can reveal their 3D distributions and low-resolution structures. Furthermore, these data can serve as testbeds for high-throughput image-analysis pipelines, as training sets for feature-recognition software, for feasibility analysis when planning new structural-cell-biology projects, and as practice data for students.

Reducing cryoEM file storage using lossy image formats

Recent advances in instrumentation and software for cryoEM have increased the applicability and utility of this method. High levels of automation and faster data acquisition rates require hard decisions to be made regarding data retention. Here we investigate the efficacy of data compression applied to aligned summed movie files. Surprisingly, these images can be compressed using a standard lossy method that reduces file storage by 90-95% and yet can still be processed to provide sub-2 Å reconstructed maps. We do not advocate this as an archival method, but it may provide a useful means for retaining images as an historical record, especially at large facilities.

Experimental steering of electron microscopy studies using prior X-ray computed tomography

•

Using microCT pre-scans to accurately steer serial block face SEM.

•

High throughput screening and mapping samples to reduce time hunting for features of interest.

•

Using microCT to optimise specimen preparation and staining.

•

Using microCT to guide site-specific TEM sample preparation.

Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) can provide unrivalled high-resolution images of specific features and volumes of interest. However, the regions interrogated are typically very small, and sample preparation is both time-consuming and destructive. Here we consider how prior X-ray micro-computed tomography (microCT) presents an opportunity to increase the efficiency of electron microscopy in biology. We demonstrate how it can be used to; select the most promising samples and target site-specific locations; provide a wider context of the location being interrogated (multiscale correlative imaging); guide sample preparation and 3D imaging schemes; as well as quantify the effects of destructive sample preparation and staining procedures. We present a workflow utilising open source software in which microCT can be used either broadly, or precisely, to experimentally steer and inform subsequent electron microscopy studies. As automated sample registration procedures are developed to enable correlative microscopy, experimental steering by prior CT could be beneficially routinely incorporated into many experimental workflows.

A Local Agreement Filtering Algorithm for Transmission EM Reconstructions

•

We propose an algorithm, LAFTER, that recovers features with more signal than noise from half maps.

•

LAFTER is shown to recover features over a wide range of FSCs and local signal-to-noise ratios.

•

We suggest effective local noise suppression be evaluated by comparing the filter-sum xFSC to C_ref.

We present LAFTER, an algorithm for de-noising single particle reconstructions from cryo-EM.

Single particle analysis entails the reconstruction of high-resolution volumes from tens of thousands of particle images with low individual signal-to-noise. Imperfections in this process result in substantial variations in the local signal-to-noise ratio within the resulting reconstruction, complicating the interpretation of molecular structure. An effective local de-noising filter could therefore improve interpretability and maximise the amount of useful information obtained from cryo-EM maps.

LAFTER is a local de-noising algorithm based on a pair of serial real-space filters. It compares independent half-set reconstructions to identify and retain shared features that have power greater than the noise. It is capable of recovering features across a wide range of signal-to-noise ratios, and we demonstrate recovery of the strongest features at Fourier shell correlation (FSC) values as low as 0.144 over a 256³-voxel cube. A fast and computationally efficient implementation of LAFTER is freely available.

We also propose a new way to evaluate the effectiveness of real-space filters for noise suppression, based on the correspondence between two FSC curves: 1) the FSC between the filtered and unfiltered volumes, and 2) C_ref, the FSC between the unfiltered volume and a hypothetical noiseless volume, which can readily be estimated from the FSC between two half-set reconstructions.

Map segmentation, automated model-building and their application to the Cryo-EM Model Challenge

A recently-developed method for identifying a compact, contiguous region representing the unique part of a density map was applied to 218 Cryo-EM maps with resolutions of 4.5 Å or better. The key elements of the segmentation procedure are (1) identification of all regions of density above a threshold and (2) choice of a unique set of these regions, taking symmetry into consideration, that maximize connectivity and compactness. This segmentation approach was then combined with tools for automated map sharpening and model-building to generate models for the 12 maps in the 2016 Cryo-EM Model Challenge in a fully automated manner. The resulting models have completeness from 24% to 82% and RMS distances from reference interpretations of 0.6 Å-2.1 Å.

Development of a Prototype System for Archiving Integrative/Hybrid Structure Models of Biological Macromolecules

Essential processes in biology are carried out by large macromolecular assemblies, whose structures are often difficult to determine by traditional methods. Increasingly, researchers combine measured data and computed information from several complementary methods to obtain "hybrid" or "integrative" structural models of macromolecules and their assemblies. These integrative/hybrid (I/H) models are not archived in the PDB because of the absence of standard data representations and processing mechanisms. Here we present the development of data standards and a prototype system for archiving I/H models. The data standards provide the definitions required for representing I/H models that span multiple spatiotemporal scales and conformational states, as well as spatial restraints derived from different experimental techniques. Based on these data definitions, we have built a prototype system called PDB-Dev, which provides the infrastructure necessary to archive I/H structural models. PDB-Dev is now accepting structures and is open to the community for new submissions.

Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy

The orientation distribution of a single-particle electron cryomicroscopy specimen limits the resolution of the reconstructed density map. Here we define a statistical quantity, the efficiency, E_od, which characterises the orientation distribution via its corresponding point spread function. The efficiency measures the ability of the distribution to provide uniform information and resolution in all directions of the reconstruction, independent of other factors. This metric allows rapid and rigorous evaluation of specimen preparation methods, assisting structure determination to high resolution with minimal data.

A number of parameters influence the resolution of a cryo-EM structure. Here the authors investigate the effects of specimen orientation in single particle cryo-EM and present open-source software for rapidly assessing orientation distributions to improve data collection.

Recent developments in the CCP-EM software suite

As part of its remit to provide computational support to the cryo-EM community, the Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) has produced a software framework which enables easy access to a range of programs and utilities. The resulting software suite incorporates contributions from different collaborators by encapsulating them in Python task wrappers, which are then made accessible via a user-friendly graphical user interface as well as a command-line interface suitable for scripting. The framework includes tools for project and data management. An overview of the design of the framework is given, together with a survey of the functionality at different levels. The current CCP-EM suite has particular strength in the building and refinement of atomic models into cryo-EM reconstructions, which is described in detail.

A pipeline approach to single-particle processing in RELION

The formal concept of a workflow to single-particle analysis of cryo-electron microscopy (cryo-EM) images in the RELION program is described. In this approach, the structure-determination process is considered as a graph, where intermediate results in the form of images or metadata are the vertices, and different functionalities of the program are the edges. The new implementation automatically logs all user actions, facilitates file management and disk cleaning, and allows convenient browsing of the history of a project. Moreover, new functionality to iteratively execute consecutive jobs allows on-the-fly image processing, which will lead to more efficient data acquisition by providing faster feedback on data quality. The possibility of exchanging data-processing procedures among users will contribute to the development of standardized image-processing procedures, and hence increase accessibility for new users in this rapidly expanding field.

Focus: The interface between data collection and data processing in cryo-EM

We present a new software package called Focus that interfaces cryo-transmission electron microscopy (cryo-EM) data collection with computer image processing. Focus creates a user-friendly environment to import and manage data recorded by direct electron detectors and perform elemental image processing tasks in a high-throughput manner while new data is being acquired at the microscope. It provides the functionality required to remotely monitor the progress of data collection and data processing, which is essential now that automation in cryo-EM allows a steady flow of images of single particles, two-dimensional crystals, or electron tomography data to be recorded in overnight sessions. The rapid detection of any errors that may occur greatly increases the productivity of recording sessions at the electron microscope.

Tilt series STEM simulation of a 25×25×25nm semiconductor with characteristic X-ray emission

The detection and quantification of fabrication defects is vital to the ongoing miniaturization of integrated circuits. The atomic resolution of HAADF-STEM combined with the chemical sensitivity of EDS could provide the means by which this is achieved for the next generation of semiconductor devices. To realize this, however, a streamlined acquisition and analysis procedure must first be developed. Here, we report the simulation of a HAADF-STEM and EDS tilt-series dataset of a PMOS finFET device which will be used as a testbed for such a development. The methods used to calculate the data and the details of the specimen model are fully described here. The dataset consists of 179 projections in 2° increments with HAADF images and characteristic X-ray maps for each projection. This unusually large calculation has been made possible through the use of a national supercomputer and will be made available for the development and assessment of reconstruction and analysis procedures for this highly significant industrial application.

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.

The Electron Microscopy eXchange (EMX) initiative

Three-dimensional electron microscopy (3DEM) of ice-embedded samples allows the structural analysis of large biological macromolecules close to their native state. Different techniques have been developed during the last forty years to process cryo-electron microscopy (cryo-EM) data. Not surprisingly, success in analysis and interpretation is highly correlated with the continuous development of image processing packages. The field has matured to the point where further progress in data and methods sharing depends on an agreement between the packages on how to describe common image processing tasks. Such standardization will facilitate the use of software as well as seamless collaboration, allowing the sharing of rich information between different platforms. Our aim here is to describe the Electron Microscopy eXchange (EMX) initiative, launched at the 2012 Instruct Image Processing Center Developer Workshop, with the intention of developing a first set of standard conventions for the interchange of information for single-particle analysis (EMX version 1.0). These conventions cover the specification of the metadata for micrograph and particle images, including contrast transfer function (CTF) parameters and particle orientations. EMX v1.0 has already been implemented in the Bsoft, EMAN, Xmipp and Scipion image processing packages. It has been and will be used in the CTF and EMDataBank Validation Challenges respectively. It is also being used in EMPIAR, the Electron Microscopy Pilot Image Archive, which stores raw image data related to the 3DEM reconstructions in EMDB.

Automated batch fiducial-less tilt-series alignment in Appion using Protomo

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy.