Advances in the field of single-particle cryo-electron microscopy over the last decade

All-atom RNA structure determination from cryo-EM maps

Many methods exist for determining protein structures from cryogenic electron microscopy maps, but this remains challenging for RNA structures. Here we developed EMRNA, a method for accurate, automated determination of full-length all-atom RNA structures from cryogenic electron microscopy maps. EMRNA integrates deep learning-based detection of nucleotides, three-dimensional backbone tracing and scoring with consideration of sequence and secondary structure information, and full-atom construction of the RNA structure. We validated EMRNA on 140 diverse RNA maps ranging from 37 to 423 nt at 2.0-6.0 Å resolutions, and compared EMRNA with auto-DRRAFTER, phenix.map_to_model and CryoREAD on a set of 71 cases. EMRNA achieves a median accuracy of 2.36 Å root mean square deviation and 0.86 TM-score for full-length RNA structures, compared with 6.66 Å and 0.58 for auto-DRRAFTER. EMRNA also obtains a high residue coverage and sequence match of 93.30% and 95.30% in the built models, compared with 58.20% and 42.20% for phenix.map_to_model and 56.45% and 52.3% for CryoREAD. EMRNA is fast and can build an RNA structure of 100 nt within 3 min.

Determining Macromolecular Structures Using Cryo-Electron Microscopy

Structural insights into macromolecular and protein complexes provide key clues about the molecular basis of the function. Cryogenic electron microscopy (cryo-EM) has emerged as a powerful structural biology method for studying protein and macromolecular structures at high resolution in both native and near-native states. Despite the ability to get detailed structural insights into the processes underlying protein function using cryo-EM, there has been hesitancy amongst plant biologists to apply the method for biomolecular interaction studies. This is largely evident from the relatively fewer structural depositions of proteins and protein complexes from plant origin in electron microscopy databank. Even though the progress has been slow, cryo-EM has significantly contributed to our understanding of the molecular biology processes underlying photosynthesis, energy transfer in plants, besides viruses infecting plants. This chapter introduces sample preparation for both negative-staining electron microscopy (NSEM) and cryo-EM for plant proteins and macromolecular complexes and data analysis using single particle analysis for beginners.

Targeting structural flexibility in low density lipoprotein by integrating cryo-electron microscopy and high-speed atomic force microscopy

Low-density lipoprotein (LDL) plays a crucial role in cholesterol metabolism. Responsible for cholesterol transport from the liver to the organs, LDL accumulation in the arteries is a primary cause of cardiovascular diseases, such as atherosclerosis. This work focuses on the fundamental question of the LDL molecular structure, as well as the topology and molecular motions of apolipoprotein B-100 (apo B-100), which is addressed by single-particle cryo-electron microscopy (cryo-EM) and high-speed atomic force microscopy (HS-AFM). Our results suggest a revised model of the LDL core organization with respect to the cholesterol ester (CE) arrangement. In addition, a high-density region close to the flattened poles could be identified, likely enriched in free cholesterol. The most remarkable new details are two protrusions on the LDL surface, attributed to the protein apo B-100. HS-AFM adds the dimension of time and reveals for the first time a highly dynamic direct description of LDL, where we could follow large domain fluctuations of the protrusions in real time. To tackle the inherent flexibility and heterogeneity of LDL, the cryo-EM maps are further assessed by 3D variability analysis. Our study gives a detailed explanation how to approach the intrinsic flexibility of a complex system comprising lipids and protein.

Improvement of cryo-EM maps by simultaneous local and non-local deep learning

Cryo-EM has emerged as the most important technique for structure determination of macromolecular complexes. However, raw cryo-EM maps often exhibit loss of contrast at high resolution and heterogeneity over the entire map. As such, various post-processing methods have been proposed to improve cryo-EM maps. Nevertheless, it is still challenging to improve both the quality and interpretability of EM maps. Addressing the challenge, we present a three-dimensional Swin-Conv-UNet-based deep learning framework to improve cryo-EM maps, named EMReady, by not only implementing both local and non-local modeling modules in a multiscale UNet architecture but also simultaneously minimizing the local smooth L1 distance and maximizing the non-local structural similarity between processed experimental and simulated target maps in the loss function. EMReady was extensively evaluated on diverse test sets of 110 primary cryo-EM maps and 25 pairs of half-maps at 3.0-6.0 Å resolutions, and compared with five state-of-the-art map post-processing methods. It is shown that EMReady can not only robustly enhance the quality of cryo-EM maps in terms of map-model correlations, but also improve the interpretability of the maps in automatic de novo model building.

Design of an ultrafast pulsed ponderomotive phase plate for cryo-electron tomography

Ponderomotive phase plates have shown that temporally consistent phase contrast is possible within electron microscopes via high-fluence static laser modes resonating in Fabry-Perot cavities. Here, we explore using pulsed laser beams as an alternative method of generating high fluences. We find through forward-stepping finite element models that picosecond or shorter interactions are required for meaningful fluences and phase shifts, with higher pulse energies and smaller beam waists leading to predicted higher fluences. An additional model based on quasi-classical assumptions is used to discover the shape of the phase plate by incorporating the oscillatory nature of the electric field. From these results, we find the transient nature of the laser pulses removes the influence of Kapitza-Dirac diffraction patterns that appear in the static resonator cases. We conclude by predicting that a total laser pulse energy of 8.7 μJ is enough to induce the required π/2 phase shift for Zernike-like phase microscopy.

Structural Insights into the Advances and Mechanistic Understanding of Human Dicer

The RNase III endoribonuclease Dicer was discovered to be associated with cleavage of double-stranded RNA in 2001. Since then, many advances in our understanding of Dicer function have revealed that the enzyme plays a major role not only in microRNA biology but also in multiple RNA interference-related pathways. Yet, there is still much to be learned regarding Dicer structure-function in relation to how Dicer and Dicer-like enzymes initiate their cleavage reaction and release the desired RNA product. This Perspective describes the latest advances in Dicer structural studies, expands on what we have learned from this data, and outlines key gaps in knowledge that remain to be addressed. More specifically, we focus on human Dicer and highlight the intermediate processing steps where there is a lack of structural data to understand how the enzyme traverses from pre-cleavage to cleavage-competent states. Understanding these details is necessary to model Dicer's function as well as develop more specific microRNA-targeted therapeutics for the treatment of human diseases.

Fragment-Based Drug Discovery against Mycobacteria: The Success and Challenges

The emergence of drug-resistant mycobacteria, including Mycobacterium tuberculosis (Mtb) and non-tuberculous mycobacteria (NTM), poses an increasing global threat that urgently demands the development of new potent anti-mycobacterial drugs. One of the approaches toward the identification of new drugs is fragment-based drug discovery (FBDD), which is the most ingenious among other drug discovery models, such as structure-based drug design (SBDD) and high-throughput screening. Specialized techniques, such as X-ray crystallography, nuclear magnetic resonance spectroscopy, and many others, are part of the drug discovery approach to combat the Mtb and NTM global menaces. Moreover, the primary drawbacks of traditional methods, such as the limited measurement of biomolecular toxicity and uncertain bioavailability evaluation, are successfully overcome by the FBDD approach. The current review focuses on the recognition of fragment-based drug discovery as a popular approach using virtual, computational, and biophysical methods to identify potent fragment molecules. FBDD focuses on designing optimal inhibitors against potential therapeutic targets of NTM and Mtb (PurC, ArgB, MmpL3, and TrmD). Additionally, we have elaborated on the challenges associated with the FBDD approach in the identification and development of novel compounds. Insights into the applications and overcoming the challenges of FBDD approaches will aid in the identification of potential therapeutic compounds to treat drug-sensitive and drug-resistant NTMs and Mtb infections.

Ab-initio contrast estimation and denoising of cryo-EM images

BACKGROUND AND OBJECTIVE

The contrast of cryo-EM images varies from one to another, primarily due to the uneven thickness of the ice layer. This contrast variation can affect the quality of 2-D class averaging, 3-D ab-initio modeling, and 3-D heterogeneity analysis. Contrast estimation is currently performed during 3-D iterative refinement. As a result, the estimates are not available at the earlier computational stages of class averaging and ab-initio modeling. This paper aims to solve the contrast estimation problem directly from the picked particle images in the ab-initio stage, without estimating the 3-D volume, image rotations, or class averages.

METHODS

The key observation underlying our analysis is that the 2-D covariance matrix of the raw images is related to the covariance of the underlying clean images, the noise variance, and the contrast variability between images. We show that the contrast variability can be derived from the 2-D covariance matrix and we apply the existing Covariance Wiener Filtering (CWF) framework to estimate it. We also demonstrate a modification of CWF to estimate the contrast of individual images.

RESULTS

Our method improves the contrast estimation by a large margin, compared to the previous CWF method. Its estimation accuracy is often comparable to that of an oracle that knows the ground truth covariance of the clean images. The more accurate contrast estimation also improves the quality of image restoration as demonstrated in both synthetic and experimental datasets.

CONCLUSIONS

This paper proposes an effective method for contrast estimation directly from noisy images without using any 3-D volume information. It enables contrast correction in the earlier stage of single particle analysis, and may improve the accuracy of downstream processing.

Membranes under the Magnetic Lens: A Dive into the Diverse World of Membrane Protein Structures Using Cryo-EM

Membrane proteins are highly diverse in both structure and function and can, therefore, present different challenges for structure determination. They are biologically important for cells and organisms as gatekeepers for information and molecule transfer across membranes, but each class of membrane proteins can present unique obstacles to structure determination. Historically, many membrane protein structures have been investigated using highly engineered constructs or using larger fusion proteins to improve solubility and/or increase particle size. Other strategies included the deconstruction of the full-length protein to target smaller soluble domains. These manipulations were often required for crystal formation to support X-ray crystallography or to circumvent lower resolution due to high noise and dynamic motions of protein subdomains. However, recent revolutions in membrane protein biochemistry and cryo-electron microscopy now provide an opportunity to solve high resolution structures of both large, >1 megadalton (MDa), and small, <100 kDa (kDa), drug targets in near-native conditions, routinely reaching resolutions around or below 3 Å. This review provides insights into how the recent advances in membrane biology and biochemistry, as well as technical advances in cryo-electron microscopy, help us to solve structures of a large variety of membrane protein groups, from small receptors to large transporters and more complex machineries.

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.

Current Methods and Prospects for Analysis and Characterization of Nanomaterials in the Environment

Analysis and characterization of naturally occurring and engineered nanomaterials in the environment are critical for understanding their environmental behaviors and defining real exposure scenarios for environmental risk assessment. However, this is challenging primarily due to the low concentration, structural heterogeneity, and dynamic transformation of nanomaterials in complex environmental matrices. In this critical review, we first summarize sample pretreatment methods developed for separation and preconcentration of nanomaterials from environmental samples, including natural waters, wastewater, soils, sediments, and biological media. Then, we review the state-of-the-art microscopic, spectroscopic, mass spectrometric, electrochemical, and size-fractionation methods for determination of mass and number abundance, as well as the morphological, compositional, and structural properties of nanomaterials, with discussion on their advantages and limitations. Despite recent advances in detecting and characterizing nanomaterials in the environment, challenges remain to improve the analytical sensitivity and resolution and to expand the method applications. It is important to develop methods for simultaneous determination of multifaceted nanomaterial properties for in situ analysis and characterization of nanomaterials under dynamic environmental conditions and for detection of nanoscale contaminants of emerging concern (e.g., nanoplastics and biological nanoparticles), which will greatly facilitate the standardization of nanomaterial analysis and characterization methods for environmental samples.

The Development of iDPC-STEM and Its Application in Electron Beam Sensitive Materials

The main aspects of material research: material synthesis, material structure, and material properties, are interrelated. Acquiring atomic structure information of electron beam sensitive materials by electron microscope, such as porous zeolites, organic-inorganic hybrid perovskites, metal-organic frameworks, is an important and challenging task. The difficulties in characterization of the structures will inevitably limit the optimization of their synthesis methods and further improve their performance. The emergence of integrated differential phase contrast scanning transmission electron microscopy (iDPC-STEM), a STEM characterization technique capable of obtaining images with high signal-to-noise ratio under lower doses, has made great breakthroughs in the atomic structure characterization of these materials. This article reviews the developments and applications of iDPC-STEM in electron beam sensitive materials, and provides an outlook on its capabilities and development.

An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics

Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough discoveries in areas such as energy storage, quantum computing, and biomedicine. Scanning transmission electron microscopy (STEM), a cornerstone of the study of chemical and materials systems, stands to benefit greatly from AI-driven automation. However, present barriers to low-level instrument control, as well as generalizable and interpretable feature detection, make truly automated microscopy impractical. Here, we discuss the design of a closed-loop instrument control platform guided by emerging sparse data analytics. We hypothesize that a centralized controller, informed by machine learning combining limited a priori knowledge and task-based discrimination, could drive on-the-fly experimental decision-making. This platform may unlock practical, automated analysis of a variety of material features, enabling new high-throughput and statistical studies.

NMMD: Efficient cryo-EM flexible fitting based on simultaneous Normal Mode and Molecular Dynamics atomic displacements

Atomic models of cryo electron microscopy (cryo-EM) maps of biomolecular conformations are often obtained by flexible fitting of the maps with available atomic structures of other conformations (e.g., obtained by X-ray crystallography). This article presents a new flexible fitting method, NMMD, which combines normal mode analysis (NMA) and molecular dynamics simulation (MD). Given an atomic structure and a cryo-EM map to fit, NMMD simultaneously estimates global atomic displacements based on NMA and local displacements based on MD. NMMD was implemented by modifying EMfit, a flexible fitting method using MD only, in GENESIS 1.4. As EMfit, NMMD can be run with replica exchange umbrella sampling procedure. The new method was tested using a variety of EM maps (synthetic and experimental, with different noise levels and resolutions). The results of the tests show that adding normal modes to MD-based fitting makes the fitting faster (40% in average) and, in the majority of cases, more accurate.

Prediction and Modeling of Protein–Protein Interactions Using “Spotted” Peptides with a Template-Based Approach

Protein–peptide interactions (PpIs) are a subset of the overall protein–protein interaction (PPI) network in the living cell and are pivotal for the majority of cell processes and functions. High-throughput methods to detect PpIs and PPIs usually require time and costs that are not always affordable. Therefore, reliable in silico predictions represent a valid and effective alternative. In this work, a new algorithm is described, implemented in a freely available tool, i.e., “PepThreader”, to carry out PPIs and PpIs prediction and analysis. PepThreader threads multiple fragments derived from a full-length protein sequence (or from a peptide library) onto a second template peptide, in complex with a protein target, “spotting” the potential binding peptides and ranking them according to a sequence-based and structure-based threading score. The threading algorithm first makes use of a scoring function that is based on peptides sequence similarity. Then, a rerank of the initial hits is performed, according to structure-based scoring functions. PepThreader has been benchmarked on a dataset of 292 protein–peptide complexes that were collected from existing databases of experimentally determined protein–peptide interactions. An accuracy of 80%, when considering the top predicted 25 hits, was achieved, which performs in a comparable way with the other state-of-art tools in PPIs and PpIs modeling. Nonetheless, PepThreader is unique in that it is able at the same time to spot a binding peptide within a full-length sequence involved in PPI and model its structure within the receptor. Therefore, PepThreader adds to the already-available tools supporting the experimental PPIs and PpIs identification and characterization.

Preparation of RNA Polymerase Complexes for Their Analysis by Single-Particle Cryo-Electron Microscopy

Recent technological progress revealed new prospects of high-resolution structure determination of macromolecular complexes using cryo-electron microscopy (cryo-EM) . In the field of RNA polymerase (Pol) I research, a number of cryo-EM studies contributed to understanding the highly specialized mechanisms underlying the transcription of ribosomal RNA genes . Despite a broad applicability of the cryo-EM method itself, preparation of samples for high-resolution data collection can be challenging. Here, we describe strategies for the purification and stabilization of Pol I complexes, exemplarily considering advantages and disadvantages of the methodology. We further provide an easy-to-implement protocol for the coating of EM-grids with self-made carbon support films. In sum, we present an efficient workflow for cryo-grid preparation and optimization, including early stage cryo-EM screening that can be adapted to a wide range of soluble samples for high-resolution structure determination .

Plasmodesmata Ultrastructure Determination Using Electron Tomography

Plant plasmodesmata (PD) are complex intercellular channels consisting of a thin endoplasmic reticulum (ER) tubule enveloped by the plasma membrane (PM). PD were first observed by electron microscopy about 50 years ago and, since, numerous studies in transmission and scanning electron microscopy have provided important information regarding their overall organization, revealing at the same time their diversity in terms of structure and morphology. However, and despite the fact that PD cell-cell communication is of critical importance for plant growth, development, cellular patterning, and response to biotic and abiotic stresses, linking their structural organization to their functional state has been proven difficult. This is in part due to their small size (20-50 nm in diameter) and the difficulty to resolve these structures in three dimensions at nanometer resolution to provide details of their internal organization.In this protocol, we provide in detail a complete process to produce high-resolution transmission electron tomograms of PD. We describe the preparation of the plant sample using high-pressure cryofixation and cryo-substitution. We also describe how to prepare filmed grids and how to cut and collect the sections using an ultramicrotome. We explain how to acquire a tilt series and how to reconstruct a tomogram from it using the IMOD software. We also give a few guidelines on segmentation of the reconstructed tomogram.

EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps

Cryo-electron microscopy (cryo-EM) has become one of important experimental methods in structure determination. However, despite the rapid growth in the number of deposited cryo-EM maps motivated by advances in microscopy instruments and image processing algorithms, building accurate structure models for cryo-EM maps remains a challenge. Protein secondary structure information, which can be extracted from EM maps, is beneficial for cryo-EM structure modeling. Here, we present a novel secondary structure annotation framework for cryo-EM maps at both intermediate and high resolutions, named EMNUSS. EMNUSS adopts a three-dimensional (3D) nested U-net architecture to assign secondary structures for EM maps. Tested on three diverse datasets including simulated maps, middle resolution experimental maps, and high-resolution experimental maps, EMNUSS demonstrated its accuracy and robustness in identifying the secondary structures for cyro-EM maps of various resolutions. The EMNUSS program is freely available at http://huanglab.phys.hust.edu.cn/EMNUSS.

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.

Cryo-EM as a powerful tool for drug discovery: recent structural based studies of SARS-CoV-2

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has arisen as a global pandemic affecting the respiratory system showing acute respiratory distress syndrome (ARDS). However, there is no targeted therapeutic agent yet and due to the growing cases of infections and the rising death tolls, discovery of the possible drug is the need of the hour. In general, the study for discovering therapeutic agent for SARS-CoV-2 is largely focused on large-scale screening with fragment-based drug discovery (FBDD). With the recent advancement in cryo-electron microscopy (Cryo-EM), it has become one of the widely used tools in structural biology. It is effective in investigating the structure of numerous proteins in high-resolution and also had an intense influence on drug discovery, determining the binding reaction and regulation of known drugs as well as leading the design and development of new drug candidates. Here, we review the application of cryo-EM in a structure-based drug design (SBDD) and in silico screening of the recently acquired FBDD in SARS-CoV-2. Such insights will help deliver better understanding in the procurement of the effective remedial solution for this pandemic.

Cryo-EM: A new dawn in thyroid biology

The thyroid gland accumulates the rare dietary element iodine and incorporates it into iodinated thyroid hormones, utilising several tightly regulated reactions and molecular mechanisms. Thyroid hormones are essential in vertebrates and play a central role in many biological processes, such as development, thermogenesis and growth. The control of these functions is exerted through the binding of hormones to nuclear thyroid hormone receptors that rule the transcription of numerous metabolic genes. Over the last 50 years, thyroid biology has been studied extensively at the cellular and organismal levels, revealing its multiple clinical implications, yet, a complete molecular understanding is still lacking. This includes the atomic structures of crucial pathway components that would be needed to elucidate molecular mechanisms. Here we review the currently known protein structures involved in thyroid hormone synthesis, regulation, transport, and actions. We also highlight targets for future investigations that will significantly benefit from recent advances in macromolecular structure determination by electron cryo-microscopy (cryo-EM). As an example, we demonstrate how cryo-EM was crucial to obtain the structure of the large thyroid hormone precursor protein, thyroglobulin. We discuss modern cryo-EM compared to other structure determination methods and how an integrated structural and cell biological approach will help filling the molecular knowledge gap in our understanding of thyroid hormone metabolism. Together with clinical, cellular and high-throughput 'omics' studies, atomic structures of thyroid components will provide an important framework to map disease mutations and to interpret and predict thyroid phenotypes.

Sub-3 Å Cryo-EM Structures of Necrosis Virus Particles via the Use of Multipurpose TEM with Electron Counting Camera

During this global pandemic, cryo-EM has made a great impact on the structure determination of COVID-19 proteins. However, nearly all high-resolution results are based on data acquired on state-of-the-art microscopes where their availability is restricted to a number of centers across the globe with the studies on infectious viruses being further regulated or forbidden. One potential remedy is to employ multipurpose microscopes. Here, we investigated the capability of 200 kV multipurpose microscopes equipped with a direct electron camera in determining the structures of infectious particles. We used 30 nm particles of the grouper nerve necrosis virus as a test sample and obtained the cryo-EM structure with a resolution as high as ∼2.7 Å from a setting that used electron counting. For comparison, we tested a high-end cryo-EM (Talos Arctica) using a similar virus (Macrobrachium rosenbergii nodavirus) to obtain virtually the same resolution. Those results revealed that the resolution is ultimately limited by the depth of field. Our work updates the density maps of these viruses at the sub-3Å level to allow for building accurate atomic models from de novo to provide structural insights into the assembly of the capsids. Importantly, this study demonstrated that multipurpose TEMs are capable of the high-resolution cryo-EM structure determination of infectious particles and is thus germane to the research on pandemics.

Improved Efficiency in Automated Acquisition of Ultra-high Resolution Electron Holograms Using Automated Target Detection

An automated hologram acquisition system for big-data analysis and for improving the statistical precision of phase analysis has been upgraded with automated particle detection technology. The coordinates of objects in low-magnification images are automatically detected using zero-mean normalized cross-correlation with preselected reference images. In contrast with the conventional scanning acquisitions from the whole area of a microgrid and/or a thin specimen, the new method allows efficient data collections only from the desired fields of view including the particles. The acquisition time of the cubic/triangular nanoparticles that were observed was shortened by about 1/58 that of the conventional scanning acquisition method because of the efficient data collections. The developed technology can improve statistical precision in electron holography with shorter acquisition time and is applicable to the analysis of electromagnetic fields for various kinds of nanoparticles.

Recent Insights into the Structure and Function of Mycobacterial Membrane Proteins Facilitated by Cryo-EM

Mycobacterium tuberculosis (Mtb) is one of the deadliest pathogens encountered by humanity. Over the decades, its characteristic membrane organization and composition have been understood. However, there is still limited structural information and mechanistic understanding of the constituent membrane proteins critical for drug discovery pipelines. Recent advances in single-particle cryo-electron microscopy and cryo-electron tomography have provided the much-needed impetus towards structure determination of several vital Mtb membrane proteins whose structures were inaccessible via X-ray crystallography and NMR. Important insights into membrane composition and organization have been gained via a combination of electron tomography and biochemical and biophysical assays. In addition, till the time of writing this review, 75 new structures of various Mtb proteins have been reported via single-particle cryo-EM. The information obtained from these structures has improved our understanding of the mechanisms of action of these proteins and the physiological pathways they are associated with. These structures have opened avenues for structure-based drug design and vaccine discovery programs that might help achieve global-TB control. This review describes the structural features of selected membrane proteins (type VII secretion systems, Rv1819c, Arabinosyltransferase, Fatty Acid Synthase, F-type ATP synthase, respiratory supercomplex, ClpP1P2 protease, ClpB disaggregase and SAM riboswitch), their involvement in physiological pathways, and possible use as a drug target. Tuberculosis is a deadly disease caused by Mycobacterium tuberculosis. The Cryo-EM and tomography have simplified the understanding of the mycobacterial membrane organization. Some proteins are located in the plasma membrane; some span the entire envelope, while some, like MspA, are located in the mycomembrane. Cryo-EM has made the study of such membrane proteins feasible.

Full-length de novo protein structure determination from cryo-EM maps using deep learning

MOTIVATION

Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-EM maps. However, building accurate models for the EM maps at 3-5 Å resolution remains a challenging and time-consuming process. With the rapid growth of deposited EM maps, there is an increasing gap between the maps and reconstructed/modeled 3-dimensional (3D) structures. Therefore, automatic reconstruction of atomic-accuracy full-atomstructures fromEMmaps is pressingly needed.

RESULTS

We present a semi-automatic de novo structure determination method using a deep learningbased framework, named as DeepMM, which builds atomic-accuracy all-atom models from cryo-EM maps at near-atomic resolution. In our method, the main-chain and Cα positions as well as their amino acid and secondary structure types are predicted in the EM map using Densely Connected Convolutional Networks. DeepMM was extensively validated on 40 simulated maps at 5 Å resolution and 30 experimental maps at 2.6-4.8 Å resolution as well as an EMDB-wide data set of 2931 experimental maps at 2.6-4.9 Å resolution, and compared with state-of-the-art algorithms including RosettaES, MAINMAST, and Phenix. Overall, our DeepMM algorithm obtained a significant improvement over existing methods in terms of both accuracy and coverage in building full-length protein structures on all test sets, demonstrating the efficacy and general applicability of DeepMM.

AVAILABILITY

http://huanglab.phys.hust.edu.cn/DeepMM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Scanning Compton X-ray microscopy

X-ray microscopy offers the opportunity to image biological and radiosensitive materials without special sample preparations, bridging optical and electron microscopy capabilities. However, the performance of such microscopes, when imaging radiosensitive samples, is not limited by their intrinsic resolution, but by the radiation damage induced on such samples. Here, we demonstrate a novel, to the best of our knowledge, radio-efficient microscope, scanning Compton X-ray microscopy (SCXM), which uses coherently and incoherently (Compton) scattered photons to minimize the deposited energy per unit of mass for a given imaging signal. We implemented SCXM, using lenses capable of efficiently focusing 60 keV X-ray photons into the sub-micrometer scale, and probe its radio-efficient capabilities. SCXM, when implemented in high-energy diffraction-limited storage rings, e.g., European Synchrotron Radiation Facility Extremely Brilliant Source and PETRA IV, will open the opportunity to explore the nanoscale of unstained, unsectioned, and undamaged radiosensitive materials.

Revisiting staining of biological samples for electron microscopy: perspectives for recent research

This review revisits essential staining protocols for electron microscopy focussing on the visualization of active sites, i.e. enzymes, metabolites or proteins, in cells and tissues, which have been developed 50 to 60 years ago, however, never were established as standard protocols being used in electron microscopy in a routine fashion. These approaches offer numerous possibilities to expand the knowledge of cellular function and specifically address the localization of active compounds of these systems. It is our conviction, that many of these techniques are still useful, in particular when applied in conjunction with correlative light and electron microscopy. Revisiting specialized classical electron microscopy staining protocols for use in correlative microscopy is particularly promising, as some of these protocols were originally developed as staining methods for light microscopy. To account for this history, rather than summarizing the most recent achievements in literature, we instead first provide an overview of techniques that have been used in the past. While some of these techniques have been successfully implemented into modern microscopy techniques during recent years already, more possibilities are yet to be re-discovered and provide exciting new perspectives for their future use.

VDAC-A Primal Perspective

The evolution of the eukaryotic cell from the primal endosymbiotic event involved a complex series of adaptations driven primarily by energy optimization. Transfer of genes from endosymbiont to host and concomitant expansion (by infolding) of the endosymbiont's chemiosmotic membrane greatly increased output of adenosine triphosphate (ATP) and placed selective pressure on the membrane at the host-endosymbiont interface to sustain the energy advantage. It is hypothesized that critical functions at this interface (metabolite exchange, polypeptide import, barrier integrity to proteins and DNA) were managed by a precursor β-barrel protein ("pβB") from which the voltage-dependent anion-selective channel (VDAC) descended. VDAC's role as hub for disparate and increasingly complex processes suggests an adaptability that likely springs from a feature inherited from pβB, retained because of important advantages conferred. It is proposed that this property is the remarkable structural flexibility evidenced in VDAC's gating mechanism, a possible origin of which is discussed.

Molecular basis for protein-protein interactions

This minireview provides an overview on the current knowledge of protein-protein interactions, common characterisation methods to characterise them, and their role in protein complex formation with some examples. A deep understanding of protein-protein interactions and their molecular interactions is important for a number of applications, including drug design. Protein-protein interactions and their discovery are thus an interesting avenue for understanding how protein complexes, which make up the majority of proteins, work.

Cryo-EM as a powerful tool for drug discovery

The recent revolution in cryo-EM has produced an explosion of structures at near-atomic or better resolution. This has allowed cryo-EM structures to provide visualization of bound small-molecule ligands in the macromolecules, and these new structures have provided unprecedented insights into the molecular mechanisms of complex biochemical processes. They have also had a profound impact on drug discovery, defining the binding modes and mechanisms of action of well-known drugs as well as driving the design and development of new compounds. This review will summarize and highlight some of these structures. Most excitingly, the latest cryo-EM technology has produced structures at 1.2 Å resolution, further solidifying cryo-EM as a powerful tool for drug discovery. Therefore, cryo-EM will play an ever-increasing role in drug discovery in the coming years.

Structure of the bacterial ribosome at 2 Å resolution

Using cryo-electron microscopy (cryo-EM), we determined the structure of the Escherichia coli 70S ribosome with a global resolution of 2.0 Å. The maps reveal unambiguous positioning of protein and RNA residues, their detailed chemical interactions, and chemical modifications. Notable features include the first examples of isopeptide and thioamide backbone substitutions in ribosomal proteins, the former likely conserved in all domains of life. The maps also reveal extensive solvation of the small (30S) ribosomal subunit, and interactions with A-site and P-site tRNAs, mRNA, and the antibiotic paromomycin. The maps and models of the bacterial ribosome presented here now allow a deeper phylogenetic analysis of ribosomal components including structural conservation to the level of solvation. The high quality of the maps should enable future structural analyses of the chemical basis for translation and aid the development of robust tools for cryo-EM structure modeling and refinement.

Structure of the bacterial ribosome at 2 Å resolution

Using cryo-electron microscopy (cryo-EM), we determined the structure of the Escherichia coli 70S ribosome with a global resolution of 2.0 Å. The maps reveal unambiguous positioning of protein and RNA residues, their detailed chemical interactions, and chemical modifications. Notable features include the first examples of isopeptide and thioamide backbone substitutions in ribosomal proteins, the former likely conserved in all domains of life. The maps also reveal extensive solvation of the small (30S) ribosomal subunit, and interactions with A-site and P-site tRNAs, mRNA, and the antibiotic paromomycin. The maps and models of the bacterial ribosome presented here now allow a deeper phylogenetic analysis of ribosomal components including structural conservation to the level of solvation. The high quality of the maps should enable future structural analyses of the chemical basis for translation and aid the development of robust tools for cryo-EM structure modeling and refinement.

A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulation

BACKGROUND

Cryo-electron tomography is an important and powerful technique to explore the structure, abundance, and location of ultrastructure in a near-native state. It contains detailed information of all macromolecular complexes in a sample cell. However, due to the compact and crowded status, the missing edge effect, and low signal to noise ratio (SNR), it is extremely challenging to recover such information with existing image processing methods. Cryo-electron tomogram simulation is an effective solution to test and optimize the performance of the above image processing methods. The simulated images could be regarded as the labeled data which covers a wide range of macromolecular complexes and ultrastructure. To approximate the crowded cellular environment, it is very important to pack these heterogeneous structures as tightly as possible. Besides, simulating non-deformable and deformable components under a unified framework also need to be achieved.

RESULT

In this paper, we proposed a unified framework for simulating crowded cryo-electron tomogram images including non-deformable macromolecular complexes and deformable ultrastructures. A macromolecule was approximated using multiple balls with fixed relative positions to reduce the vacuum volume. A ultrastructure, such as membrane and filament, was approximated using multiple balls with flexible relative positions so that this structure could deform under force field. In the experiment, 400 macromolecules of 20 representative types were packed into simulated cytoplasm by our framework, and numerical verification proved that our method has a smaller volume and higher compression ratio than the baseline single-ball model. We also packed filaments, membranes and macromolecules together, to obtain a simulated cryo-electron tomogram image with deformable structures. The simulated results are closer to the real Cryo-ET, making the analysis more difficult. The DOG particle picking method and the image segmentation method are tested on our simulation data, and the experimental results show that these methods still have much room for improvement.

CONCLUSION

The proposed multi-ball model can achieve more crowded packaging results and contains richer elements with different properties to obtain more realistic cryo-electron tomogram simulation. This enables users to simulate cryo-electron tomogram images with non-deformable macromolecular complexes and deformable ultrastructures under a unified framework. To illustrate the advantages of our framework in improving the compression ratio, we calculated the volume of simulated macromolecular under our multi-ball method and traditional single-ball method. We also performed the packing experiment of filaments and membranes to demonstrate the simulation ability of deformable structures. Our method can be used to do a benchmark by generating large labeled cryo-ET dataset and evaluating existing image processing methods. Since the content of the simulated cryo-ET is more complex and crowded compared with previous ones, it will pose a greater challenge to existing image processing methods.

Mitigating local over-fitting during single particle reconstruction with SIDESPLITTER

Single particle analysis has become a key structural biology technique. Experimental images are extremely noisy, and during iterative refinement it is possible to stably incorporate noise into the reconstruction. Such "over-fitting" can lead to misinterpretation of the structure and flawed biological results. Several strategies are routinely used to prevent over-fitting, the most common being independent refinement of two sides of a split dataset. In this study, we show that over-fitting remains an issue within regions of low local signal-to-noise, despite independent refinement of half datasets. We propose a modification of the refinement process through the application of a local signal-to-noise filter: SIDESPLITTER. We show that our approach can reduce over-fitting for both idealised and experimental data while maintaining independence between the two sides of a split refinement. SIDESPLITTER refinement leads to improved density, and can also lead to improvement of the final resolution in extreme cases where datasets are prone to severe over-fitting, such as small membrane proteins.

WITHDRAWN: Structural studies of vitrified biological proteins and macromolecules - A review on the microimaging aspects of cryo-electron microscopy

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Research journey of respirasome

Respirasome, as a vital part of the oxidative phosphorylation system, undertakes the task of transferring electrons from the electron donors to oxygen and produces a proton concentration gradient across the inner mitochondrial membrane through the coupled translocation of protons. Copious research has been carried out on this lynchpin of respiration. From the discovery of individual respiratory complexes to the report of the high-resolution structure of mammalian respiratory supercomplex I1III2IV1, scientists have gradually uncovered the mysterious veil of the electron transport chain (ETC). With the discovery of the mammalian respiratory mega complex I2III2IV2, a new perspective emerges in the research field of the ETC. Behind these advances glitters the light of the revolution in both theory and technology. Here, we give a short review about how scientists 'see' the structure and the mechanism of respirasome from the macroscopic scale to the atomic scale during the past decades.

Live Analysis and Reconstruction of Single-Particle Cryo-Electron Microscopy Data with CryoFLARE

Efficient, reproducible and accountable single-particle cryo-electron microscopy structure determination is tedious and often impeded by the lack of a standardized procedure for data analysis and processing. To address this issue, we have developed the FMI Live Analysis and Reconstruction Engine (CryoFLARE). CryoFLARE is a modular open-source platform offering easy integration of new processing algorithms developed by the cryo-EM community. It provides a user-friendly interface that allows fast setup of standardized workflows, serving the need of pharmaceutical industry and academia alike who need to optimize throughput of their microscope. To consistently document how data is processed, CryoFLARE contains an integrated reporting facility to create reports. Live analysis and processing parallel to data acquisition are used to monitor and optimize data quality. Problems at the level of the sample preparation (heterogeneity, ice thickness, sparse particles, areas selected for acquisition, etc.) or misalignments of the microscope optics can quickly be detected and rectified before data collection is continued. Interfacing with automated data collection software for retrieval of acquisition metadata reduces user input needed for analysis, and with it minimizes potential sources of errors and workflow inconsistencies. Local and remote export support in Relion-compatible job and data format allows seamless integration into the refinement process. The support for nonlinear workflows and fine-grained scheduling for mixed workflows with separate CPU and GPU based calculation steps ensures optimal use of processing hardware. CryoFLARE's flexibility allows it to be used for all types of image acquisitions, ranging from sample screening to high-resolution data collection, and it offers a new alternative for setting up image processing workflows. It can be used without modifications of the hardware/software delivered by the microscope supplier. As it runs on a server in parallel to the hardware used for acquisition, it can easily be set up for remote display connections and fast control of the acquisition status.

Imaging Beam-Sensitive Materials by Electron Microscopy

Electron microscopy allows the extraction of multidimensional spatiotemporally correlated structural information of diverse materials down to atomic resolution, which is essential for figuring out their structure-property relationships. Unfortunately, the high-energy electrons that carry this important information can cause damage by modulating the structures of the materials. This has become a significant problem concerning the recent boost in materials science applications of a wide range of beam-sensitive materials, including metal-organic frameworks, covalent-organic frameworks, organic-inorganic hybrid materials, 2D materials, and zeolites. To this end, developing electron microscopy techniques that minimize the electron beam damage for the extraction of intrinsic structural information turns out to be a compelling but challenging need. This article provides a comprehensive review on the revolutionary strategies toward the electron microscopic imaging of beam-sensitive materials and associated materials science discoveries, based on the principles of electron-matter interaction and mechanisms of electron beam damage. Finally, perspectives and future trends in this field are put forward.

Automated acquisition of vast numbers of electron holograms with atomic-scale phase information

An automated acquisition system for collecting a large number of electron holograms, to improve the statistical precision of phase analysis, was developed. A technique for shifting the electron beam in combination with stage movement allows data to be acquired over a wide area of a TEM-specimen grid. Undesired drift in the hologram position, which may occur during the hologram acquisition, can be corrected in real time by automated detection of the interference-fringe region in an image. To demonstrate the usefulness of the developed automated hologram acquisition system, gold nanoparticles dispersed on a carbon foil were observed with a 1.2-MV atomic resolution holography electron microscope. The system could obtain 1024 holograms, which provided phase maps for more than 500 nanoparticles with a lateral resolution of 0.14 nm, in just 1 h. The observation results revealed an anomalous increase in mean inner potential for a particle size smaller than 4 nm. The developed automated hologram acquisition system can be applied to improve the precision of phase measurement by averaging many phase images, as demonstrated by single particle analysis for biological entities. Moreover, the system makes it possible to study electrostatic potential of catalysts and other functional nanoparticles at atomic resolution.

Single-particle cryo-electron microscopy: Mathematical theory, computational challenges, and opportunities

In recent years, an abundance of new molecular structures have been elucidated using cryo-electron microscopy (cryo-EM), largely due to advances in hardware technology and data processing techniques. Owing to these new exciting developments, cryo-EM was selected by Nature Methods as Method of the Year 2015, and the Nobel Prize in Chemistry 2017 was awarded to three pioneers in the field. The main goal of this article is to introduce the challenging and exciting computational tasks involved in reconstructing 3-D molecular structures by cryo-EM. Determining molecular structures requires a wide range of computational tools in a variety of fields, including signal processing, estimation and detection theory, high-dimensional statistics, convex and non-convex optimization, spectral algorithms, dimensionality reduction, and machine learning. The tools from these fields must be adapted to work under exceptionally challenging conditions, including extreme noise levels, the presence of missing data, and massively large datasets as large as several Terabytes. In addition, we present two statistical models: multi-reference alignment and multi-target detection, that abstract away much of the intricacies of cryo-EM, while retaining some of its essential features. Based on these abstractions, we discuss some recent intriguing results in the mathematical theory of cryo-EM, and delineate relations with group theory, invariant theory, and information theory.

Structural proteomics, electron cryo-microscopy and structural modeling approaches in bacteria-human protein interactions

A central challenge in infection medicine is to determine the structure and function of host-pathogen protein-protein interactions to understand how these interactions facilitate bacterial adhesion, dissemination and survival. In this review, we focus on proteomics, electron cryo-microscopy and structural modeling to showcase instances where affinity-purification (AP) and cross-linking (XL) mass spectrometry (MS) has advanced our understanding of host-pathogen interactions. We highlight cases where XL-MS in combination with structural modeling has provided insight into the quaternary structure of interspecies protein complexes. We further exemplify how electron cryo-tomography has been used to visualize bacterial-human interactions during attachment and infection. Lastly, we discuss how AP-MS, XL-MS and electron cryo-microscopy and -tomography together with structural modeling approaches can be used in future studies to broaden our knowledge regarding the function, dynamics and evolution of such interactions. This knowledge will be of relevance for future drug and vaccine development programs.

Integrative biology of native cell extracts: a new era for structural characterization of life processes

Advances in electron microscopy have provided unprecedented access to the structural characterization of large, flexible and heterogeneous complexes. Until recently, cryo-electron microscopy (cryo-EM) has been applied to understand molecular organization in either highly purified, isolated biomolecules or in situ. An emerging field is developing, bridging the gap between the two approaches, and focuses on studying molecular organization in native cell extracts. This field has demonstrated its potential by resolving the structure of fungal fatty acid synthase (FAS) at 4.7 Å [Fourier shell correlation (FSC) = 0.143]; FAS was not only less than 50% enriched, but also retained higher-order binders, previously unknown. Although controversial in the sense that the lysis step might introduce artifacts, cell extracts preserve aspects of cellular function. In addition, cell extracts are accessible, besides cryo-EM, to modern proteomic methods, chemical cross-linking, network biology and biophysical modeling. We expect that automation in imaging cell extracts, along with the integration of molecular/cell biology approaches, will provide remarkable achievements in the study of closer-to-life biomolecular states of pronounced biotechnological and medical importance. Such steps will, eventually, bring us a step closer to the biophysical description of cellular processes in an integrative, holistic approach.

Re-examining the spectra of macromolecules. Current practice of spectral quasi B-factor flattening

The analysis of structure factors in 3D cryo-EM Coulomb potential maps and their "enhancement" at the end of the reconstruction process is a well-established practice, normally referred to as sharpening. The aim is to increase contrast and, in this way, to help tracing the atomic model. The most common way to accomplish this enhancement is by means of the so-called B-factor correction, which applies a global filter to boost high frequencies with some dampening considerations related to noise amplification. The results are maps with a better visual aspect and a quasiflat spectrum at medium and high frequencies. This practice is so widespread that most map depositions in the Electron Microscopy Data Base (EMDB) only contain sharpened maps. Here, the use in cryoEM of global B-factor corrections is theoretically and experimentally analyzed. Results clearly illustrate that protein spectra present a falloff. Thus, spectral quasi-flattening may produce protein spectra with distortions when compared with experimental ones, this fact, combined with the practice of reporting only sharpened maps, generates a sub-optimal situation in terms of data preservation, reuse and reproducibility. Now that the field is more advanced, we put forward two suggestions: (1) to use methods which keep more faithfully the original experimental signal properties of macromolecules when "enhancing" the map, and (2) to further stress the need to deposit the original experimental maps without any postprocessing or sharpening, not only the enhanced maps. In the absence of access to these original maps data is lost, preventing their future analysis with new methods.

Developments, applications, and prospects of cryo-electron microscopy

Cryo‐electron microscopy (cryo‐EM) is a structural biological method that is used to determine the 3D structures of biomacromolecules. After years of development, cryo‐EM has made great achievements, which has led to a revolution in structural biology. In this article, the principle, characteristics, history, current situation, workflow, and common problems of cryo‐EM are systematically reviewed. In addition, the new development direction of cryo‐EM—cryo‐electron tomography (cryo‐ET), is discussed in detail. Also, cryo‐EM is prospected from the following aspects: the structural analysis of small proteins, the improvement of resolution and efficiency, and the relationship between cryo‐EM and drug development. This review is dedicated to giving readers a comprehensive understanding of the development and application of cryo‐EM, and to bringing them new insights.

In situ Microfluidic Cryofixation for Cryo Focused Ion Beam Milling and Cryo Electron Tomography

We present a microfluidic platform for studying structure-function relationships at the cellular level by connecting video rate live cell imaging with in situ microfluidic cryofixation and cryo-electron tomography of near natively preserved, unstained specimens. Correlative light and electron microscopy (CLEM) has been limited by the time required to transfer live cells from the light microscope to dedicated cryofixation instruments, such as a plunge freezer or high-pressure freezer. We recently demonstrated a microfluidic based approach that enables sample cryofixation directly in the light microscope with millisecond time resolution, a speed improvement of up to three orders of magnitude. Here we show that this cryofixation method can be combined with cryo-electron tomography (cryo-ET) by using Focused Ion Beam milling at cryogenic temperatures (cryo-FIB) to prepare frozen hydrated electron transparent sections. To make cryo-FIB sectioning of rapidly frozen microfluidic channels achievable, we developed a sacrificial layer technique to fabricate microfluidic devices with a PDMS bottom wall <5 µm thick. We demonstrate the complete workflow by rapidly cryo-freezing Caenorhabditis elegans roundworms L1 larvae during live imaging in the light microscope, followed by cryo-FIB milling and lift out to produce thin, electron transparent sections for cryo-ET imaging. Cryo-ET analysis of initial results show that the structural preservation of the cryofixed C. elegans was suitable for high resolution cryo-ET work. The combination of cryofixation during live imaging enabled by microfluidic cryofixation with the molecular resolution capabilities of cryo-ET offers an exciting avenue to further advance space-time correlative light and electron microscopy (st-CLEM) for investigation of biological processes at high resolution in four dimensions.

Structural Biology of Telomerase

Telomerase is a DNA polymerase that extends the 3' ends of chromosomes by processively synthesizing multiple telomeric repeats. It is a unique ribonucleoprotein (RNP) containing a specialized telomerase reverse transcriptase (TERT) and telomerase RNA (TER) with its own template and other elements required with TERT for activity (catalytic core), as well as species-specific TER-binding proteins important for biogenesis and assembly (core RNP); other proteins bind telomerase transiently or constitutively to allow association of telomerase and other proteins with telomere ends for regulation of DNA synthesis. Here we describe how nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography of TER and protein domains helped define the structure and function of the core RNP, laying the groundwork for interpreting negative-stain and cryo electron microscopy (cryo-EM) density maps of Tetrahymena thermophila and human telomerase holoenzymes. As the resolution has improved from ∼30 Å to ∼5 Å, these studies have provided increasingly detailed information on telomerase architecture and mechanism.