Measuring the optimal exposure for single particle cryo-EM using a 2.6 A reconstruction of rotavirus VP6.
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ABSTRACT:
SUBMITTER: Grant T
PROVIDER: S-EPMC4471936 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cryogenic electron microscopy (cryo-EM) and single-particle analysis now enables the determination of high-resolution structures of macromolecular assemblies that have resisted X-ray crystallography and other approaches. We developed the SIMPLE open-source image-processing suite for analysing cryo-EM images of single-particles. A core component of SIMPLE is the probabilistic PRIME algorithm for identifying clusters of images in 2D and determine relative orientations of single-particle projections in 3D. Here, we extend our previous work on PRIME and introduce new stochastic optimization algorithms that improve the robustness of the approach. Our refined method for identification of homogeneous subsets of images in accurate register substantially improves the resolution of the cluster centers and of the ab initio 3D reconstructions derived from them. We now obtain maps with a resolution better than 10 Å by exclusively processing cluster centers. Excellent parallel code performance on over-the-counter laptops and CPU workstations is demonstrated.
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Project description:BackgroundCryo-EM data generated by electron tomography (ET) contains images for individual protein particles in different orientations and tilted angles. Individual cryo-EM particles can be aligned to reconstruct a 3D density map of a protein structure. However, low contrast and high noise in particle images make it challenging to build 3D density maps at intermediate to high resolution (1-3 Å). To overcome this problem, we propose a fully automated cryo-EM 3D density map reconstruction approach based on deep learning particle picking.ResultsA perfect 2D particle mask is fully automatically generated for every single particle. Then, it uses a computer vision image alignment algorithm (image registration) to fully automatically align the particle masks. It calculates the difference of the particle image orientation angles to align the original particle image. Finally, it reconstructs a localized 3D density map between every two single-particle images that have the largest number of corresponding features. The localized 3D density maps are then averaged to reconstruct a final 3D density map. The constructed 3D density map results illustrate the potential to determine the structures of the molecules using a few samples of good particles. Also, using the localized particle samples (with no background) to generate the localized 3D density maps can improve the process of the resolution evaluation in experimental maps of cryo-EM. Tested on two widely used datasets, Auto3DCryoMap is able to reconstruct good 3D density maps using only a few thousand protein particle images, which is much smaller than hundreds of thousands of particles required by the existing methods.ConclusionsWe design a fully automated approach for cryo-EM 3D density maps reconstruction (Auto3DCryoMap). Instead of increasing the signal-to-noise ratio by using 2D class averaging, our approach uses 2D particle masks to produce locally aligned particle images. Auto3DCryoMap is able to accurately align structural particle shapes. Also, it is able to construct a decent 3D density map from only a few thousand aligned particle images while the existing tools require hundreds of thousands of particle images. Finally, by using the pre-processed particle images, Auto3DCryoMap reconstructs a better 3D density map than using the original particle images.
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Project description:The fast development of single-particle cryogenic electron microscopy (cryo-EM) has made it more feasible to obtain the 3D structure of well-behaved macromolecules with a molecular weight higher than 300 kDa at ~3 Å resolution. However, it remains a challenge to obtain the high-resolution structures of molecules smaller than 200 kDa using single-particle cryo-EM. In this work, we apply the Cs-corrector-VPP-coupled cryo-EM to study the 52 kDa streptavidin (SA) protein supported on a thin layer of graphene and embedded in vitreous ice. We are able to solve both the apo-SA and biotin-bound SA structures at near-atomic resolution using single-particle cryo-EM. We demonstrate that the method has the potential to determine the structures of molecules as small as 39 kDa.
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Project description:Recent advances in single-particle cryogenic electron microscopy (cryo-EM) have enabled the structural determination of numerous protein assemblies at high resolution, yielding unprecedented insights into their function. However, despite its extraordinary capabilities, cryo-EM remains time-consuming and resource-intensive. It is therefore beneficial to have a means for rapidly assessing and optimizing the quality of samples prior to lengthy cryo-EM analyses. To do this, we have developed a native mass spectrometry (nMS) platform that provides rapid feedback on sample quality and highly streamlined biochemical screening. Because nMS enables accurate mass analysis of protein complexes, it is well suited to routine evaluation of the composition, integrity, and homogeneity of samples prior to their plunge-freezing on EM grids. We demonstrate the utility of our nMS-based platform for facilitating cryo-EM studies using structural characterizations of exemplar bacterial transcription complexes as well as the replication-transcription assembly from the SARS-CoV-2 virus that is responsible for the COVID-19 pandemic.
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Project description: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.
| S-EPMC6317460 | biostudies-literature
Project description:In this paper, we present a refinement method for cryo-electron microscopy (cryo-EM) single-particle reconstruction, termed as OPUS-SSRI (Sparseness and Smoothness Regularized Imaging). In OPUS-SSRI, spatially varying sparseness and smoothness priors are incorporated to improve the regularity of electron density map, and a type of real space penalty function is designed. Moreover, we define the back-projection step as a local kernel regression and propose a first-order method to solve the resulting optimization problem. On the seven cryo-EM datasets that we tested, the average improvement in resolution by OPUS-SSRI over that from RELION 3.0, the commonly used image-processing software for single-particle cryo-EM, was 0.64 Å, with the largest improvement being 1.25 Å. We expect OPUS-SSRI to be an invaluable tool to the broad field of cryo-EM single-particle analysis. The implementation of OPUS-SSRI can be found at https://github.com/alncat/cryoem.
| S-EPMC7812788 | biostudies-literature
Project description:Cryo electron microscopy facilities running multiple instruments and serving users with varying skill levels need a robust and reliable method for benchmarking both the hardware and software components of their single particle analysis workflow. The workflow is complex, with many bottlenecks existing at the specimen preparation, data collection and image analysis steps; the samples and grid preparation can be of unpredictable quality, there are many different protocols for microscope and camera settings, and there is a myriad of software programs for analysis that can depend on dozens of settings chosen by the user. For this reason, we believe it is important to benchmark the entire workflow, using a standard sample and standard operating procedures, on a regular basis. This provides confidence that all aspects of the pipeline are capable of producing maps to high resolution. Here we describe benchmarking procedures using a test sample, rabbit muscle aldolase.
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Project description:The three-dimensional positions of atoms in protein molecules define their structure and their roles in biological processes. The more precisely atomic coordinates are determined, the more chemical information can be derived and the more mechanistic insights into protein function may be inferred. Electron cryo-microscopy (cryo-EM) single-particle analysis has yielded protein structures with increasing levels of detail in recent years1,2. However, it has proved difficult to obtain cryo-EM reconstructions with sufficient resolution to visualize individual atoms in proteins. Here we use a new electron source, energy filter and camera to obtain a 1.7 Å resolution cryo-EM reconstruction for a human membrane protein, the β3 GABAA receptor homopentamer3. Such maps allow a detailed understanding of small-molecule coordination, visualization of solvent molecules and alternative conformations for multiple amino acids, and unambiguous building of ordered acidic side chains and glycans. Applied to mouse apoferritin, our strategy led to a 1.22 Å resolution reconstruction that offers a genuine atomic-resolution view of a protein molecule using single-particle cryo-EM. Moreover, the scattering potential from many hydrogen atoms can be visualized in difference maps, allowing a direct analysis of hydrogen-bonding networks. Our technological advances, combined with further approaches to accelerate data acquisition and improve sample quality, provide a route towards routine application of cryo-EM in high-throughput screening of small molecule modulators and structure-based drug discovery.
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Project description:Random spherically-constrained (RSC) reconstruction is a new form of single particle reconstruction (SPR) using cryo-EM images of membrane proteins embedded in spherical lipid vesicles to generate a 3D protein structure. The method has many advantages over conventional SPR, including a more native environment for protein particles and an initial estimate of the particle's angular orientation. These advances allow us to determine structures of membrane proteins such as ion channels and derive more reliable structure estimates. We present an algorithm that relates conventional SPR to the RSC model, and generally, to projection images of particles embedded with an axis parallel to the local normal of a general 2D manifold. We illustrate the performance of this algorithm in the spherical system using synthetic data.
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Project description:Rotavirus is a well-studied RNA virus that causes severe gastroenteritis in children. During viral entry, the outer layer of the virion is shed, creating a double-layered particle (DLP) that is competent to perform viral transcription (i.e., mRNA synthesis) and launch infection. While inactive forms of rotavirus DLPs have been structurally characterized in detail, information about the transcriptionally-active DLP remains limited. Here, we used cryo-Electron Microscopy (cryo-EM) and 3D image reconstructions to compare the structures of internal protein components in transcriptionally-active versus inactive DLPs. Our findings showed that transcriptionally-active DLPs gained internal order as mRNA synthesis unfolded, while inactive DLPs remained dynamically disordered. Regions of viral protein/RNA constituents were analyzed across two different axes of symmetry to provide a more comprehensive view of moving components. Taken together, our results bring forth a new view of active DLPs, which may enable future pharmacological strategies aimed at obliterating rotavirus transcription as a therapeutic approach.
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