Hydrogen properties and charges in a sub-1.2 Å resolution cryo-EM structure revealed by a cold field emission beam

The cold field emission (CFE) beam produces the less-attenuated contrast transfer function of electron microscopy, thereby enhancing high-resolution signals and this particularly benefits higher-resolution single particle cryogenic electron microscopy. Here, we present a sub-1.2 Å resolution structure of a standard protein sample, apoferritin. Image data were collected with the CFE beam in a high-throughput scheme while minimizing beam tilt deviations from the coma-free axis. A difference map reveals positive densities for most hydrogen atoms in the core region of the protein complex including those in water molecules, while negative densities around acidic amino-acid side chains likely represent negative charges. The position of the hydrogen densities depends on parent bonded-atom type, which is validated by an estimated level of coordinate errors.

Differential programming enabled functional imaging with Lorentz transmission electron microscopy

Lorentz transmission electron microscopy is an advanced characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials. Information such as magnetization and electric potentials is carried by the phase of the electron wave, and is lost during image acquisition. Various methods have been proposed to retrieve the phase of the electron wavefunction using intensities of the acquired images, most of which work only in the small defocus limit. Imaging at strong defoci not only carries more quantitative phase information, but is essential to the study of weak magnetic and electrostatic fields at the nanoscale. In this work we develop a method based on differentiable programming to solve the inverse problem of phase retrieval. We show that our method maintains a high spatial resolution and robustness against noise even at the upper defocus limit of the microscope. More importantly, our proposed method can go beyond recovering just the phase information. We demonstrate this by retrieving the electron-optical parameters of the contrast transfer function alongside the electron exit wavefunction.

Simplified Approach for Preparing Graphene Oxide TEM Grids for Stained and Vitrified Biomolecules

In this manuscript, we report the application of graphene oxide (GO) in the preparation of cryo-electron microscopy (cryo-EM) and transmission electron microscopy (TEM) grids. We treated GO with water and organic solvents, such as, methanol, ethanol and isopropanol separately to isolate significantly large GO monolayer flake to fabricate the grids for cryo-EM and TEM study. We implemented a simplified approach to isolate flakes of GO monolayer for constructing the TEM grids, independent of expensive heavy equipment (Langmuir–Blodgett trough, glow-discharge system, carbon-evaporator or plasma-cleaner or peristaltic pumps). We employed confocal microscopy, SEM and TEM to characterize the flake size, stability and transparency of the GO monolayer and atomic force microscopy (AFM) to probe the depth of GO coated grids. Additionally, GO grids are visualized at cryogenic condition for suitability of GO monolayer for cryo-EM study. In addition, GO-Met-H2O grids reduce the effect of preferred orientation of biological macromolecules within the amorphous ice. The power-spectrum and contrast-transfer-function unequivocally suggest that GO-Met-H2O fabricated holey grids have excellent potential for application in high-resolution structural characterization of biomolecules. Furthermore, only 200 movies and ~8000 70S ribosome particles are selected on GO-coated grids for cryo-EM reconstruction to achieve high-resolution structure.

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

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.

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

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 Å 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 < 200 kDa proteins using 200 kV cryo-EM.

CryoGAN: A New Reconstruction Paradigm for Single-Particle Cryo-EM via Deep Adversarial Learning

We present CryoGAN, a new paradigm for single-particle cryo-EM reconstruction based on unsupervised deep adversarial learning. The major challenge in single-particle cryo-EM is that the imaged particles have unknown poses. Current reconstruction techniques are based on a marginalized maximum-likelihood formulation that requires calculations over the set of all possible poses for each projection image, a computationally demanding procedure. CryoGAN sidesteps this problem by using a generative adversarial network (GAN) to learn the 3D structure that has simulated projections that most closely match the real data in a distributional sense. The architecture of CryoGAN resembles that of standard GAN, with the twist that the generator network is replaced by a model of the cryo-EM image acquisition process. CryoGAN is an unsupervised algorithm that only demands projection images and an estimate of the contrast transfer function parameters. No initial volume estimate or prior training is needed. Moreover, CryoGAN requires minimal user interaction and can provide reconstructions in a matter of hours on a high-end GPU. In addition, we provide sound mathematical guarantees on the recovery of the correct structure. CryoGAN currently achieves a 8.6 Å resolution on a realistic synthetic dataset. Preliminary results on real β-galactosidase data demonstrate CryoGAN’s ability to exploit data statistics under standard experimental imaging conditions. We believe that this paradigm opens the door to a family of novel likelihood-free algorithms for cryo-EM reconstruction.