scholarly journals Generative adversarial networks as a tool to recover structural information from cryo-electron microscopy data

2018 ◽  
Author(s):  
Min Su ◽  
Hantian Zhang ◽  
Kevin Schawinski ◽  
Ce Zhang ◽  
Michael A. Cianfrocco
Keyword(s):  
Electron Microscopy ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Generative Adversarial Networks ◽  
Biological Macromolecules ◽  
Adversarial Networks ◽  
Cryo Electron Microscopy ◽  
Microscopy Data ◽  
Individual Particles ◽  
Particle Interpretation

ABSTRACTCryo-electron microscopy (cryo-EM) is a powerful structural biology technique capable of determining atomic-resolution structures of biological macromolecules. Despite this ability, the low signal-to-noise ratio of cryo-EM data continues to remain a hurdle for assessing raw cryo-EM micrographs and subsequent image analysis. To help address this problem, we have performed proof-of-principle studies with generative adversarial networks, a form of artificial intelligence, to denoise individual particles. This approach effectively recovers global structural information for both synthetic and real cryo-EM data, facilitating per-particle assessment from noisy raw images. Our results suggest that generative adversarial networks may be able to provide an approach to denoise raw cryo-EM images to facilitate particle selection and raw particle interpretation for single particle and tomography cryo-EM data.

Progress in high-resolution CRYO-SEM imaging of viral particles

1996 ◽  
Vol 54 ◽  
pp. 818-819
Author(s):  
Ya Chen ◽  
Geoffrey Letchworth ◽  
John White
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
High Resolution ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Flexible Structures ◽  
Simian Virus ◽  
Topographic Features ◽  
Viral Particles ◽  
Scanning Electron

Low-temperature high-resolution scanning electron microscopy (cryo-HRSEM) has been successfully utilized to image biological macromolecular complexes at nanometer resolution. Recently, imaging of individual viral particles such as reovirus using cryo-HRSEM or simian virus (SIV) using HRSEM, HV-STEM and AFM have been reported. Although conventional electron microscopy (e.g., negative staining, replica, embedding and section), or cryo-TEM technique are widely used in studying of the architectures of viral particles, scanning electron microscopy presents two major advantages. First, secondary electron signal of SEM represents mostly surface topographic features. The topographic details of a biological assembly can be viewed directly and will not be obscured by signals from the opposite surface or from internal structures. Second, SEM may produce high contrast and signal-to-noise ratio images. As a result of this important feature, it is capable of visualizing not only individual virus particles, but also asymmetric or flexible structures. The 2-3 nm resolution obtained using high resolution cryo-SEM made it possible to provide useful surface structural information of macromolecule complexes within cells and tissues. In this study, cryo-HRSEM is utilized to visualize the distribution of glycoproteins of a herpesvirus.

scholarly journals Electron microscopy snapshots of single particles from single cells

2018 ◽  
Vol 294 (5) ◽  
pp. 1602-1608 ◽  
Author(s):  
Xiunan Yi ◽  
Eric J. Verbeke ◽  
Yiran Chang ◽  
Daniel J. Dickinson ◽  
David W. Taylor
Keyword(s):  
Electron Microscopy ◽  
Single Particle ◽  
Protein Complexes ◽  
Signal To Noise Ratio ◽  
Single Cells ◽  
Particle Analysis ◽  
Biological Macromolecules ◽  
Single Particle Analysis ◽  
Whole Cells ◽  
Potential Applications

Cryo-electron microscopy (cryo-EM) has become an indispensable tool for structural studies of biological macromolecules. Two additional predominant methods are available for studying the architectures of multiprotein complexes: 1) single-particle analysis of purified samples and 2) tomography of whole cells or cell sections. The former can produce high-resolution structures but is limited to highly purified samples, whereas the latter can capture proteins in their native state but has a low signal-to-noise ratio and yields lower-resolution structures. Here, we present a simple, adaptable method combining microfluidic single-cell extraction with single-particle analysis by EM to characterize protein complexes from individual Caenorhabditis elegans embryos. Using this approach, we uncover 3D structures of ribosomes directly from single embryo extracts. Moreover, we investigated structural dynamics during development by counting the number of ribosomes per polysome in early and late embryos. This approach has significant potential applications for counting protein complexes and studying protein architectures from single cells in developmental, evolutionary, and disease contexts.

scholarly journals A resolution record for cryoEM

2021 ◽  
Vol 10 ◽  
Author(s):  
Jonathan Ashmore ◽  
Bridget Carragher ◽  
Peter B Rosenthal ◽  
William Weis
Keyword(s):  
Electron Microscopy ◽  
Image Analysis ◽  
Structure Determination ◽  
Test Specimen ◽  
Structural Information ◽  
Atomic Resolution ◽  
Fast Growing ◽  
Cryo Electron Microscopy ◽  
New Instrument ◽  
Resolution Structure

Cryo electron microscopy (cryoEM) is a fast-growing technique for structure determination. Two recent papers report the first atomic resolution structure of a protein obtained by averaging images of frozen-hydrated biomolecules. They both describe maps of symmetric apoferritin assemblies, a common test specimen, in unprecedented detail. New instrument improvements, different in the two studies, have contributed better images, and image analysis can extract structural information sufficient to resolve individual atomic positions. While true atomic resolution maps will not be routine for most proteins, the studies suggest structures determined by cryoEM will continue to improve, increasing their impact on biology and medicine.

scholarly journals Structure of the Infective Getah Virus at 2.8 Å-resolution Determined by Cryo-electron Microscopy

2021 ◽  
Author(s):  
Aojie Wang ◽  
Feng Zhou ◽  
Congcong Liu ◽  
Dongsheng Gao ◽  
Ruxi Qi ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Immune Evasion ◽  
Cell Invasion ◽  
Structural Information ◽  
Host Cell Invasion ◽  
Hydrophobic Pocket ◽  
Viral Immune Evasion ◽  
Cryo Electron Microscopy ◽  
Reproductive Losses ◽  
Getah Virus

Getah virus (GETV) is a mosquito-borne pathogen that can cause a mild illness and reproductive losses in animals. Although antibodies to GETV have been found in humans, there are no reports of clinical symptom associated with GETV. However, antivirals or vaccine against GETV is still unavailable due to lack of knowledge of the structure of GETV virion. Here, we present the structure of mature GETV at a resolution of 2.8 Å with capsid protein, envelope glycoproteins E1 and E2. Glycosylation and S-acylation sites in E1 and E2 are identified. The surface-exposed glycans demonstrated their impact on the viral immune evasion and host cell invasion. The S-acylation sites strongly stabilize the virion. In addition, a cholesterol and phospholipid molecule are observed in transmembrane hydrophobic pocket, together with two more cholesterols surround the pocket. These structural information are helpful for structure-based antivirals and vaccine design.

scholarly journals Unravelling biological macromolecules with cryo-electron microscopy

Nature ◽  
2016 ◽  
Vol 537 (7620) ◽  
pp. 339-346 ◽  
Author(s):  
Rafael Fernandez-Leiro ◽  
Sjors H. W. Scheres
Keyword(s):  
Electron Microscopy ◽  
Biological Macromolecules ◽  
Cryo Electron Microscopy

scholarly journals Green Fluorescent Protein and Phase-Contrast Image Fusion via Generative Adversarial Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Tang ◽  
Yu Liu ◽  
Chao Zhang ◽  
Juan Cheng ◽  
Hu Peng ◽  
...  
Keyword(s):  
Phase Contrast ◽  
Fluorescent Protein ◽  
Structural Information ◽  
Generative Adversarial Networks ◽  
Phase Contrast Image ◽  
Functional Information ◽  
Adversarial Networks ◽  
Fused Image ◽  
Green Fluorescent ◽  
Contrast Image

In the field of cell and molecular biology, green fluorescent protein (GFP) images provide functional information embodying the molecular distribution of biological cells while phase-contrast images maintain structural information with high resolution. Fusion of GFP and phase-contrast images is of high significance to the study of subcellular localization, protein functional analysis, and genetic expression. This paper proposes a novel algorithm to fuse these two types of biological images via generative adversarial networks (GANs) by carefully taking their own characteristics into account. The fusion problem is modelled as an adversarial game between a generator and a discriminator. The generator aims to create a fused image that well extracts the functional information from the GFP image and the structural information from the phase-contrast image at the same time. The target of the discriminator is to further improve the overall similarity between the fused image and the phase-contrast image. Experimental results demonstrate that the proposed method can outperform several representative and state-of-the-art image fusion methods in terms of both visual quality and objective evaluation.

scholarly journals The Resolution in X-ray Crystallography and Single-Particle Cryogenic Electron Microscopy

Crystals ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 580
Author(s):  
Victor R.A. Dubach ◽  
Albert Guskov
Keyword(s):  
Electron Microscopy ◽  
Single Particle ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Particle Analysis ◽  
Biological Macromolecules ◽  
Single Particle Analysis ◽  
X Ray ◽  
X Ray Crystallography ◽  
The Fourier Transform

X-ray crystallography and single-particle analysis cryogenic electron microscopy are essential techniques for uncovering the three-dimensional structures of biological macromolecules. Both techniques rely on the Fourier transform to calculate experimental maps. However, one of the crucial parameters, resolution, is rather broadly defined. Here, the methods to determine the resolution in X-ray crystallography and single-particle analysis are summarized. In X-ray crystallography, it is becoming increasingly more common to include reflections discarded previously by traditionally used standards, allowing for the inclusion of incomplete and anisotropic reflections into the refinement process. In general, the resolution is the smallest lattice spacing given by Bragg’s law for a particular set of X-ray diffraction intensities; however, typically the resolution is truncated by the user during the data processing based on certain parameters and later it is used during refinement. However, at which resolution to perform such a truncation is not always clear and this makes it very confusing for the novices entering the structural biology field. Furthermore, it is argued that the effective resolution should be also reported as it is a more descriptive measure accounting for anisotropy and incompleteness of the data. In single particle cryo-EM, the situation is not much better, as multiple ways exist to determine the resolution, such as Fourier shell correlation, spectral signal-to-noise ratio and the Fourier neighbor correlation. The most widely accepted is the Fourier shell correlation using a threshold of 0.143 to define the resolution (so-called “gold-standard”), although it is still debated whether this is the correct threshold. Besides, the resolution obtained from the Fourier shell correlation is an estimate of varying resolution across the density map. In reality, the interpretability of the map is more important than the numerical value of the resolution.

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