Single-particle cryo-EM Data Research Articles

Cryo-EM for Structure Determination of Mitochondrial Ribosome Samples.

Single-particle cryoelectron microscopy (cryo-EM) allows structure determination of large macromolecular complexes from conformationally and compositionally heterogeneous mixtures of particles. This technique has been used to reveal the architecture of the mitochondrial ribosome and to visualize transient states that occur during the translation cycle or during mitoribosome biogenesis. Here, we outline an exemplary workflow for the analysis of single-particle cryo-EM data of human mitoribosome samples. In addition, we provide an example dataset which can be used for training purposes alongside the protocol.

Towards automating single-particle cryo-EM data acquisition.

Target selection for single-particle cryo-EM data acquisition sessions is mostly done manually by human operators, which is time consuming and leads to the inefficient use of instruments. The software toolbox Ptolemy [Kim et al. (2023). IUCrJ, 10, 90–102] provides solutions for automated target selection for cryo-EM imaging.

Uncovering structural ensembles from single-particle cryo-EM data using cryoDRGN.

Single-particle cryogenic electron microscopy (cryo-EM) has emerged as a powerful technique to visualize the structural landscape sampled by a protein complex. However, algorithmic and computational bottlenecks in analyzing heterogeneous cryo-EM datasets have prevented the full realization of this potential. CryoDRGN is a machine learning system for heterogeneous cryo-EM reconstruction of proteins and protein complexes from single-particle cryo-EM data. Central to this approach is a deep generative model for heterogeneous cryo-EM density maps, which we empirically find is effective in modeling both discrete and continuous forms of structural variability. Once trained, cryoDRGN is capable of generating an arbitrary number of 3D density maps, and thus interpreting the resulting ensemble is a challenge. Here, we showcase interactive and automated processing approaches for analyzing cryoDRGN results. Specifically, we detail a step-by-step protocol for the analysis of an existing assembling 50S ribosome dataset, including preparation of inputs, network training and visualization of the resulting ensemble of density maps. Additionally, we describe and implement methods to comprehensively analyze and interpret the distribution of volumes with the assistance of an associated atomic model. This protocol is appropriate for structural biologists familiar with processing single-particle cryo-EM datasets and with moderate experience navigating Python and Jupyter notebooks. It requires 3-4 days to complete. CryoDRGN is open source software that is freely available.

It started with a Cys: Spontaneous cysteine modification during cryo-EM grid preparation.

Advances in single particle cryo-EM data collection and processing have seen a significant rise in its use. However, the influences of the environment generated through grid preparation, by for example interactions of proteins with the air-water interface are poorly understood and can be a major hurdle in structure determination by cryo-EM. Initial interactions of proteins with the air-water interface occur quickly and proteins can adopt preferred orientation or partially unfold within hundreds of milliseconds. It has also been shown previously that thin-film layers create hydroxyl radicals. To investigate the potential this might have in cryo-EM sample preparation, we studied two proteins, HSPD1, and beta-galactosidase, and show that cysteine residues are modified in a time-dependent manner. In the case of both HSPD1 and beta-galactosidase, this putative oxidation is linked to partial protein unfolding, as well as more subtle structural changes. We show these modifications can be alleviated through increasing the speed of grid preparation, the addition of DTT, or by sequestering away from the AWI using continuous support films. We speculate that the modification is oxidation by reactive oxygen species which are formed and act at the air-water interface. Finally, we show grid preparation on a millisecond timescale outruns cysteine modification, showing that the reaction timescale is in the range of 100s to 1,000s milliseconds and offering an alternative approach to prevent spontaneous cysteine modification and its consequences during cryo-EM grid preparation.

Particles Per Hour as a Metric for Single-particle Cryo-EM Data Collection Speed When Comparing Super-resolution and Hardware-binned Data

Particles Per Hour as a Metric for Single-particle Cryo-EM Data Collection Speed When Comparing Super-resolution and Hardware-binned Data

CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images.

Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic challenge of cryo-EM is to jointly estimate the unknown 3D poses and the 3D electron scattering potential of a biomolecule from millions of extremely noisy 2D images. Existing reconstruction algorithms, however, cannot easily keep pace with the rapidly growing size of cryo-EM datasets due to their high computational and memory cost. We introduce cryoAI, an ab initio reconstruction algorithm for homogeneous conformations that uses direct gradient-based optimization of particle poses and the electron scattering potential from single-particle cryo-EM data. CryoAI combines a learned encoder that predicts the poses of each particle image with a physics-based decoder to aggregate each particle image into an implicit representation of the scattering potential volume. This volume is stored in the Fourier domain for computational efficiency and leverages a modern coordinate network architecture for memory efficiency. Combined with a symmetrized loss function, this framework achieves results of a quality on par with state-of-the-art cryo-EM solvers for both simulated and experimental data, one order of magnitude faster for large datasets and with significantly lower memory requirements than existing methods.

Advances in modelling continuous heterogeneity from single-particle cryo-EM data

Advances in modelling continuous heterogeneity from single-particle cryo-EM data

3D variability analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM

Single particle cryo-EM excels in determining static structures of protein molecules, but existing 3D reconstruction methods have been ineffective in modelling flexible proteins. We introduce 3D variability analysis (3DVA), an algorithm that fits a linear subspace model of conformational change to cryo-EM data at high resolution. 3DVA enables the resolution and visualization of detailed molecular motions of both large and small proteins, revealing new biological insight from single particle cryo-EM data. Experimental results demonstrate the ability of 3DVA to resolve multiple flexible motions of α-helices in the sub-50 kDa transmembrane domain of a GPCR complex, bending modes of a sodium ion channel, five types of symmetric and symmetry-breaking flexibility in a proteasome, large motions in a spliceosome complex, and discrete conformational states of a ribosome assembly. 3DVA is implemented in the cryoSPARC software package.

Setup and Troubleshooting of Volta Phase Plate Cryo-EM Data Collection.

Cryoelectron microscopy (cryo-EM) has become a method of choice in structural biology to analyze isolated complexes and cellular structures. This implies adequate imaging of the specimen and advanced image-processing methods to obtain high-resolution 3D reconstructions. The use of a Volta phase plate in cryo-EM drastically increases the image contrast while being able to record images at high acceleration voltage and close to focus, i.e., at conditions where high-resolution information is best preserved. During image processing, higher contrast images can be aligned and classified better than lower quality ones resulting in increased data quality and the need for less data. Here, we give step-by-step guidelines on how to set up high-quality VPP cryo-EM single particle data collections, as exemplified by human ribosome data acquired during a one-day data collection session. Further, we describe specific technical details in image processing that differ from conventional single particle cryo-EM data analysis.

A self-supervised workflow for particle picking in cryo-EM.

High-resolution single-particle cryo-EM data analysis relies on accurate particle picking. To facilitate the particle picking process, a self-supervised workflow has been developed. This includes an iterative strategy, which uses a 2D class average to improve training particles, and a progressively improved convolutional neural network for particle picking. To automate the selection of particles, a threshold is defined (%/Res) using the ratio of percentage class distribution and resolution as a cutoff. This workflow has been tested using six publicly available data sets with different particle sizes and shapes, and can automatically pick particles with minimal user input. The picked particles support high-resolution reconstructions at 3.0 Å or better. This workflow is a step towards automated single-particle cryo-EM data analysis at the stage of particle picking. It may be used in conjunction with commonly used single-particle analysis packages such as Relion, cryoSPARC, cisTEM, SPHIRE and EMAN2.

Propagation of Conformational Coordinates Across Angular Space in Mapping the Continuum of States from Cryo-EM Data by Manifold Embedding.

Recent approaches to the study of biological molecules employ manifold learning to single-particle cryo-EM data sets to map the continuum of states of a molecule into a low-dimensional space spanned by eigenvectors or "conformational coordinates". This is done separately for each projection direction (PD) on an angular grid. One important step in deriving a consolidated map of occupancies, from which the free energy landscape of the molecule can be derived, is to propagate the conformational coordinates from a given choice of "anchor PD" across the entire angular space. Even when one eigenvector dominates, its sign might invert from one PD to the next. The propagation of the second eigenvector is particularly challenging when eigenvalues of the second and third eigenvector are closely matched, leading to occasional inversions in their ranking as we move across the angular grid. In the absence of a computational approach, this propagation across the angular space has been done thus far "by hand" using visual clues, thus greatly limiting the general use of the technique. In this work we have developed a method that is able to solve the propagation problem computationally, by using optical flow and a probabilistic graphical model. We demonstrate its utility by selected examples.

Estimation of high-order aberrations and anisotropic magnification from cryo-EM data sets in RELION-3.1.

Methods are presented that detect three types of aberrations in single-particle cryo-EM data sets: symmetrical and antisymmetrical optical aberrations and magnification anisotropy. Because these methods only depend on the availability of a preliminary 3D reconstruction from the data, they can be used to correct for these aberrations for any given cryo-EM data set, a posteriori. Using five publicly available data sets, it is shown that considering these aberrations improves the resolution of the 3D reconstruction when these effects are present. The methods are implemented in version 3.1 of the open-source software package RELION.

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Single particle analysis for structure determination in cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are not designed to handle heterogeneous mixtures of structures from many distinct macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. The feasibility of this approach is first demonstrated on a large set of synthetic reprojections from 35 unique macromolecular structures spanning a mass range of hundreds to thousands of kilodaltons. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort single particle cryo-EM data from extremely heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.

LAT1 (SLC7A5) and CD98hc (SLC3A2) complex dynamics revealed by single-particle cryo-EM.

Solute carriers are a large class of transporters that play key roles in normal and disease physiology. Among the solute carriers, heteromeric amino-acid transporters (HATs) are unique in their quaternary structure. LAT1-CD98hc, a HAT, transports essential amino acids and drugs across the blood-brain barrier and into cancer cells. It is therefore an important target both biologically and therapeutically. During the course of this work, cryo-EM structures of LAT1-CD98hc in the inward-facing conformation and in either the substrate-bound or apo states were reported to 3.3-3.5 Å resolution [Yan et al. (2019), Nature (London), 568, 127-130]. Here, these structures are analyzed together with our lower resolution cryo-EM structure, and multibody 3D auto-refinement against single-particle cryo-EM data was used to characterize the dynamics of the interaction of CD98hc and LAT1. It is shown that the CD98hc ectodomain and the LAT1 extracellular surface share no substantial interface. This allows the CD98hc ectodomain to have a high degree of movement within the extracellular space. The functional implications of these aspects are discussed together with the structure determination.

Algorithmic Advances in Single Particle Cryo-EM Data Processing

Algorithmic Advances in Single Particle Cryo-EM Data Processing

Processing apoferritin with the Appion pipeline.

The 3DEM map challenge provided an opportunity to test different algorithms and workflows for processing single particle cryo-EM data. We were interested in testing whether we could use the standard Appion workflow with minimal manual intervention to achieve similar or better resolution than other challengers. Another question we were interested in testing was what the influence of particle sorting and elimination would be on the resolution and quality of 3D reconstructions. Since apoferritin is historically a challenging particle for single particle reconstruction and the authors of the original map challenge data used only a fraction of the particles present in the dataset, we focused on the apoferritin dataset for our entry. We submitted a 3.7 Å map from 25,844 particles and a 3.6 Å map from 53,334 particles and after assessment were among the best of the apoferritin maps that were submitted. Here we present the details of our reconstruction strategy and compare our strategy to that of another high-scoring apoferritin map. Altogether, our results suggest that for a relatively conformationally homogeneous particle like apoferritin, including as many particles as possible after elimination of junk leads to the highest resolution, and the choice of parameters for custom mask creation can lead to subtle but significant changes in the resolution of 3D reconstructions.

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin.

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the 'Einstein from random noise' problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous ('four-dimensional') cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, 'random-startup' three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external 'starting models'. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive 'ABC-4D' pipeline is based on the two-dimensional reference-free 'alignment by classification' (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure.

Collecting and processing single-particle cryo-EM data with tilts

Collecting and processing single-particle cryo-EM data with tilts

Single-particle cryo-EM data acquisition by using direct electron detection camera.

Recent advances in single-particle electron cryo-microscopy (cryo-EM) were largely facilitated by the application of direct electron detection cameras. These cameras feature not only a significant improvement in detective quantum efficiency but also a high frame rate that enables images to be acquired as 'movies' made of stacks of many frames. In this review, we discuss how the applications of direct electron detection cameras in cryo-EM have changed the way the data are acquired.