Showing papers on "Contrast transfer function published in 2020"

2.7 Å cryo-EM structure of vitrified M. Musculus H-chain apoferritin from a compact 200 keV cryo-microscope

Abstract: Here we present the structure of mouse H-chain apoferritin at 2.7 A (FSC = 0.143) solved by single particle cryogenic electron microscopy (cryo-EM) using a 200 kV device, the Thermo Fisher Glacios®. This is a compact, two-lens illumination system with a constant power objective lens, without any energy filters or aberration correctors, often thought of as a “screening cryo-microscope”. Coulomb potential maps reveal clear densities for main chain carbonyl oxygens, residue side chains (including alternative conformations) and bound solvent molecules. We used a quasi-crystallographic reciprocal space approach to fit model coordinates to the experimental cryo-EM map. We argue that the advantages offered by (a) the high electronic and mechanical stability of the microscope, (b) the high emission stability and low beam energy spread of the high brightness Field Emission Gun (X-FEG), (c) direct electron detection technology and (d) particle-based Contrast Transfer Function (CTF) refinement have contributed to achieving high resolution. Overall, we show that basic electron optical settings for automated cryo-electron microscopy imaging can be used to determine structures approaching atomic resolution.

Size matters: optimal mask diameter and box size for single-particle cryogenic electron microscopy

Abstract: Recently it has been demonstrated that single-particle cryogenic electron microscopy (cryo-EM) at 200 keV is capable of determining protein structures, including those smaller than 100 kDa, at sub-3.0 A resolutions, without using significant defocus or a phase plate. However, the majority of near-atomic resolution cryo-EM structures has been determined using 300 keV. Consequently, many typical parameter settings for the cryo-EM computational image processing steps, especially those associated with the contrast transfer function, are based on the accumulated experience of 300 kV cryo-EM. We have therefore revised these parameters, established theoretical bases for criteria to find an optimal mask diameter and box size for a given dataset irrespective of acceleration voltage or protein size, and proposed a protocol. Considering the defocus distributions of the datasets, merely optimizing the mask diameters and box sizes yielded meaningful resolution improvements for the reconstruction of

Nanoscale x-ray holotomography of human brain tissue with phase retrieval based on multienergy recordings

Abstract: X-ray cone-beam holotomography of unstained tissue from the human central nervous system reveals details down to subcellular length scales. This visualization of variations in the electron density of the sample is based on phase-contrast techniques using intensities formed by self-interference of the beam between object and detector. Phase retrieval inverts diffraction and overcomes the phase problem by constraints such as several measurements at different Fresnel numbers for a single projection. Therefore, the object-to-detector distance (defocus) can be varied. However, for cone-beam geometry, changing defocus changes magnification, which can be problematic in view of image processing and resolution. Alternatively, the photon energy can be altered (multi-E). Far from absorption edges, multi-E data yield the wavelength-independent electron density. We present the multi-E holotomography at the Gottingen Instrument for Nano-Imaging with X-Rays (GINIX) setup of the P10 beamline at Deutsches Elektronen-Synchrotron. The instrument is based on a combined optics of elliptical mirrors and an x-ray waveguide positioned in the focal plane for further coherence, spatial filtering, and high numerical aperture. Previous results showed the suitability of this instrument for nanoscale tomography of unstained brain tissue. We demonstrate that upon energy variation, the focal spot is stable enough for imaging. To this end, a double-crystal monochromator and automated alignment routines are required. Three tomograms of human brain tissue were recorded and jointly analyzed using phase retrieval based on the contrast transfer function formalism generalized to multiple photon energies. Variations of the electron density of the sample are successfully reconstructed.

Contrast Transfer Function-Based Exit-Wave Reconstruction and Denoising of Atomic-Resolution Transmission Electron Microscopy Images of Graphene and Cu Single Atom Substitutions by Deep Learning Framework.

Abstract: The exit wave is the state of a uniform plane incident electron wave exiting immediately after passing through a specimen and before the atomic-resolution transmission electron microscopy (ARTEM) image is modified by the aberration of the optical system and the incoherence effect of the electron. Although exit-wave reconstruction has been developed to prevent the misinterpretation of ARTEM images, there have been limitations in the use of conventional exit-wave reconstruction in ARTEM studies of the structure and dynamics of two-dimensional materials. In this study, we propose a framework that consists of the convolutional dual-decoder autoencoder to reconstruct the exit wave and denoise ARTEM images. We calculated the contrast transfer function (CTF) for real ARTEM and assigned the output of each decoder to the CTF as the amplitude and phase of the exit wave. We present exit-wave reconstruction experiments with ARTEM images of monolayer graphene and compare the findings with those of a simulated exit wave. Cu single atom substitution in monolayer graphene was, for the first time, directly identified through exit-wave reconstruction experiments. Our exit-wave reconstruction experiments show that the performance of the denoising task is improved when compared to the Wiener filter in terms of the signal-to-noise ratio, peak signal-to-noise ratio, and structural similarity index map metrics.

exCTF simulator: Simulation tool for phase contrast transfer function for aberration-corrected transmission electron microscopy

Abstract: The contrast transfer function (CTF) is an important principle in the field of transmission electron microscopy (TEM) imaging. It provides information on how the electron wave that interacted with a sample (in frequency domain) in an objective lens is transferred to the imaging system (in real space domain) depending on the effects of lens aberrations. Based on the CTF calculation, various useful results, such as the TEM instrumental information limit and optimal imaging condition, can be estimated. Recently, aberration-corrected TEM (AC-TEM) has been widely applied in various research fields for imaging at the nanoscale or atomic scale. To use AC-TEM effectively, a deep understanding of the complicated CTF with an electron wave controlled via an aberration corrector is required. Unfortunately, this complicated CTF is difficult to understand for most microscopists without the use of computational tools. In this study, we develop the extended CTF (exCTF) simulator to perform the full as well as simple CTF calculation. We successfully developed the exCTF simulator, which can obtain more information than previously reported software. The exCTF simulator not only calculates the CTF for basic optical information that can be obtained in conventional TEM, but also can calculate the extended CTF with various aberrations (up to fifth order) for more detailed information obtained in advanced high-performance AC-TEM in one-dimensional and two-dimensional formats. The user interface of the simulator includes CTF calculation, saving, and edit functions for five graphs for different conditions, allowing for detailed comparative analysis. We confirmed that the exCTF simulator produced reliable calculation data for various applications. The exCTF simulator made it easy to obtain instrumental performance information and demonstrated the influence of optical aberrations on the actual resolution of AC-TEM. Consequently, the proposed exCTF simulator is expected to be useful to microscopists as a simulation tool for electron microscopy and as a training tool for electron optics.

Model-based Reconstruction for Single Particle Cryo-Electron Microscopy

Abstract: Single particle cryo-electron microscopy is a vital tool for 3D characterization of protein structures. A typical workflow involves acquiring projection images of a collection of randomly oriented particles, picking and classifying individual particle projections by orientation, and finally using the individual particle projections to reconstruct a 3D map of the electron density profile. The reconstruction is challenging because of the low signal-to-noise ratio of the data, the unknown orientation of the particles, and the sparsity of data especially when dealing with flexible proteins where there may not be sufficient data corresponding to each class to obtain an accurate reconstruction using standard algorithms. In this paper we present a model-based image reconstruction technique that uses a regularized cost function to reconstruct the 3D density map by assuming known orientations for the particles. Our method casts the reconstruction as minimizing a cost function involving a novel forward model term that accounts for the contrast transfer function of the microscope, the orientation of the particles and the center of rotation offsets. We combine the forward model term with a regularizer that enforces desirable properties in the volume to be reconstructed. Using simulated data, we demonstrate how our method can significantly improve upon the typically used approach.