Machine learning-based real-time object locator/evaluator for cryo-EM data collection

Structural insights into thermophilic chaperonin complexes

Group I chaperonins are dual heptamer protein complexes that play significant roles in protein homeostasis. The structure and function of the Escherichia coli chaperonin are well characterized. However, the dynamic properties of chaperonins, such as large ATPase-dependent conformational changes by binding of lid-like co-chaperonin GroES, have made structural analyses challenging, and our understanding of these changes during the turnover of chaperonin complex formation is limited. In this study, we used single-particle cryogenic electron microscopy to investigate the structures of GroES-bound chaperonin complexes from the thermophilic hydrogen-oxidizing bacteria Hydrogenophilus thermoluteolus and Hydrogenobacter thermophilus in the presence of ATP and AMP-PNP. We captured the structure of an intermediate state chaperonin complex, designated as an asymmetric football-shaped complex, and performed analyses to decipher the dynamic structural variations. Our structural analyses of inter- and intra-subunit communications revealed a unique mechanism of complex formation through the binding of a second GroES to a bullet-shaped complex.

Applications and limitations of electron 3D crystallography

Three-dimensional electron diffraction (3D ED) is a measurement and analysis technique in transmission electron microscopy that is used for determining atomic structures from small crystals. Diverse targets such as proteins, polypeptides, and organic compounds, whose crystals exist in aqueous solutions and organic solvents, or as dried powders, can be studied with 3D ED. We have been involved in the development of this technique, which can now rapidly process a large number of data collected through AI control, enabling efficient structure determination. Here, we introduce this method and describe our recent results. These include the structures and pathogenic mechanisms of wild-type and mutant polypeptides associated with the debilitating disease amyotrophic lateral sclerosis (ALS), the double helical structure of nanographene promoting nanofiber formation, and the structural properties of an organic semiconductor containing disordered regions. We also discuss the limitations and prospects of 3D ED compared to microcrystallography with X-ray free electron lasers.

Development of a 1:1-binding biparatopic anti-TNFR2 antagonist by reducing signaling activity through epitope selection

Conventional bivalent antibodies against cell surface receptors often initiate unwanted signal transduction by crosslinking two antigen molecules. Biparatopic antibodies (BpAbs) bind to two different epitopes on the same antigen, thus altering crosslinking ability. In this study, we develop BpAbs against tumor necrosis factor receptor 2 (TNFR2), which is an attractive immune checkpoint target. Using different pairs of antibody variable regions specific to topographically distinct TNFR2 epitopes, we successfully regulate the size of BpAb-TNFR2 immunocomplexes to result in controlled agonistic activities. Our series of results indicate that the relative positions of the two epitopes recognized by the BpAb are critical for controlling its signaling activity. One particular antagonist, Bp109-92, binds TNFR2 in a 1:1 manner without unwanted signal transduction, and its structural basis is determined using cryo-electron microscopy. This antagonist suppresses the proliferation of regulatory T cells expressing TNFR2. Therefore, the BpAb format would be useful in designing specific and distinct antibody functions.

Structures of a FtsZ single protofilament and a double-helical tube in complex with a monobody

FtsZ polymerizes into protofilaments to form the Z-ring that acts as a scaffold for accessory proteins during cell division. Structures of FtsZ have been previously solved, but detailed mechanistic insights are lacking. Here, we determine the cryoEM structure of a single protofilament of FtsZ from Klebsiella pneumoniae (KpFtsZ) in a polymerization-preferred conformation. We also develop a monobody (Mb) that binds to KpFtsZ and FtsZ from Escherichia coli without affecting their GTPase activity. Crystal structures of the FtsZ-Mb complexes reveal the Mb binding mode, while addition of Mb in vivo inhibits cell division. A cryoEM structure of a double-helical tube of KpFtsZ-Mb at 2.7 Å resolution shows two parallel protofilaments. Our present study highlights the physiological roles of the conformational changes of FtsZ in treadmilling that regulate cell division.

Identification and Analysis of Monoclonal Antibodies with Neutralizing Activity against Diverse SARS-CoV-2 Variants

We identified neutralizing monoclonal antibodies against severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) variants (including Omicron variants BA.5 and BA.2.75) from individuals who received two doses of mRNA vaccination after they had been infected with the D614G virus. We named them MO1, MO2, and MO3. Among them, MO1 showed particularly high neutralizing activity against authentic variants: D614G, Delta, BA.1, BA.1.1, BA.2, BA.2.75, and BA.5. Furthermore, MO1 suppressed BA.5 infection in hamsters. A structural analysis revealed that MO1 binds to the conserved epitope of seven variants, including Omicron variants BA.5 and BA.2.75, in the receptor-binding domain of the spike protein. MO1 targets an epitope conserved among Omicron variants BA.1, BA.2, and BA.5 in a unique binding mode. Our findings confirm that D614G-derived vaccination can induce neutralizing antibodies that recognize the epitopes conserved among the SARS-CoV-2 variants. IMPORTANCE Omicron variants of SARS-CoV-2 acquired escape ability from host immunity and authorized antibody therapeutics and thereby have been spreading worldwide. We reported that patients infected with an early SARS-CoV-2 variant, D614G, and who received subsequent two-dose mRNA vaccination have high neutralizing antibody titer against Omicron lineages. It was speculated that the patients have neutralizing antibodies broadly effective against SARS-CoV-2 variants by targeting common epitopes. Here, we explored human monoclonal antibodies from B cells of the patients. One of the monoclonal antibodies, named MO1, showed high potency against broad SARS-CoV-2 variants including BA.2.75 and BA.5 variants. The results prove that monoclonal antibodies that have common neutralizing epitopes among several Omicrons were produced in patients infected with D614G and who received mRNA vaccination.

Structure and antigenicity of divergent Henipavirus fusion glycoproteins

In August 2022, a novel henipavirus (HNV) named Langya virus (LayV) was isolated from patients with severe pneumonic disease in China. This virus is closely related to Mòjiāng virus (MojV), and both are divergent from the bat-borne HNV members, Nipah (NiV) and Hendra (HeV) viruses. The spillover of LayV is the first instance of a HNV zoonosis to humans outside of NiV and HeV, highlighting the continuing threat this genus poses to human health. In this work, we determine the prefusion structures of MojV and LayV F proteins via cryogenic electron microscopy to 2.66 and 3.37 Å, respectively. We show that despite sequence divergence from NiV, the F proteins adopt an overall similar structure but are antigenically distinct as they do not react to known antibodies or sera. Glycoproteomic analysis revealed that while LayV F is less glycosylated than NiV F, it contains a glycan that shields a site of vulnerability previously identified for NiV. These findings explain the distinct antigenic profile of LayV and MojV F, despite the extent to which they are otherwise structurally similar to NiV. Our results carry implications for broad-spectrum HNV vaccines and therapeutics, and indicate an antigenic, yet not structural, divergence from prototypical HNVs.

Structure of a monomeric photosystem I core associated with iron-stress-induced-A proteins from Anabaena sp. PCC 7120

Iron-stress-induced-A proteins (IsiAs) are expressed in cyanobacteria under iron-deficient conditions. The cyanobacterium Anabaena sp. PCC 7120 has four isiA genes; however, their binding property and functional roles in PSI are still missing. We analyzed a cryo-electron microscopy structure of a PSI-IsiA supercomplex isolated from Anabaena grown under an iron-deficient condition. The PSI-IsiA structure contains six IsiA subunits associated with the PsaA side of a PSI core monomer. Three of the six IsiA subunits were identified as IsiA1 and IsiA2. The PSI-IsiA structure lacks a PsaL subunit; instead, a C-terminal domain of IsiA2 occupies the position of PsaL, which inhibits the oligomerization of PSI, leading to the formation of a PSI monomer. Furthermore, excitation-energy transfer from IsiAs to PSI appeared with a time constant of 55 ps. These findings provide insights into both the molecular assembly of the Anabaena IsiA family and the functional roles of IsiAs.

Epoxidized graphene grid for highly efficient high-resolution cryoEM structural analysis

Functionalization of graphene is one of the most important fundamental technologies in a wide variety of fields including industry and biochemistry. We have successfully achieved a novel oxidative modification of graphene using photoactivated ClO₂^· as a mild oxidant and confirmed the oxidized graphene grid is storable with its functionality for at least three months under N₂ atmosphere. Subsequent chemical functionalization enabled us to develop an epoxidized graphene grid (EG-grid™), which effectively adsorbs protein particles for electron cryomicroscopy (cryoEM) image analysis. The EG-grid dramatically improved the particle density and orientation distribution. The density maps of GroEL and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were reconstructed at 1.99 and 2.16 Å resolution from only 504 and 241 micrographs, respectively. A sample solution of 0.1 mg ml^-1 was sufficient to reconstruct a 3.10 Å resolution map of SARS-CoV-2 spike protein from 1163 micrographs. The map resolutions of β-galactosidase and apoferritin easily reached 1.81 Å and 1.29 Å resolution, respectively, indicating its atomic-resolution imaging capability. Thus, the EG-grid will be an extremely powerful tool for highly efficient high-resolution cryoEM structural analysis of biological macromolecules.

TLR3 forms a laterally aligned multimeric complex along double-stranded RNA for efficient signal transduction

Toll-like receptor 3 (TLR3) is a member of the TLR family, which plays an important role in the innate immune system and is responsible for recognizing viral double-stranded RNA (dsRNA). Previous biochemical and structural studies have revealed that a minimum length of approximately 40-50 base pairs of dsRNA is necessary for TLR3 binding and dimerization. However, efficient TLR3 activation requires longer dsRNA and the molecular mechanism underlying its dsRNA length-dependent activation remains unknown. Here, we report cryo-electron microscopy analyses of TLR3 complexed with longer dsRNA. TLR3 dimers laterally form a higher multimeric complex along dsRNA, providing the basis for cooperative binding and efficient signal transduction.

Fully automated multi-grid cryoEM screening using Smart Leginon

Single-particle cryo-electron microscopy (cryoEM) is a swiftly growing method for understanding protein structure. With increasing demand for high-throughput, high-resolution cryoEM services comes greater demand for rapid and automated cryoEM grid and sample screening. During screening, optimal grids and sample conditions are identified for subsequent high-resolution data collection. Screening is a major bottleneck for new cryoEM projects because grids must be optimized for several factors, including grid type, grid hole size, sample concentration, buffer conditions, ice thickness and particle behavior. Even for mature projects, multiple grids are commonly screened to select a subset for high-resolution data collection. Here, machine learning and novel purpose-built image-processing and microscope-handling algorithms are incorporated into the automated data-collection software Leginon, to provide an open-source solution for fully automated high-throughput grid screening. This new version, broadly called Smart Leginon, emulates the actions of an operator in identifying areas on the grid to explore as potentially useful for data collection. Smart Leginon Autoscreen sequentially loads and examines grids from an automated specimen-exchange system to provide completely unattended grid screening across a set of grids. Comparisons between a multi-grid autoscreen session and conventional manual screening by 5 expert microscope operators are presented. On average, Autoscreen reduces operator time from ∼6 h to <10 min and provides a percentage of suitable images for evaluation comparable to the best operator. The ability of Smart Leginon to target holes that are particularly difficult to identify is analyzed. Finally, the utility of Smart Leginon is illustrated with three real-world multi-grid user screening/collection sessions, demonstrating the efficiency and flexibility of the software package. The fully automated functionality of Smart Leginon significantly reduces the burden on operator screening time, improves the throughput of screening and recovers idle microscope time, thereby improving availability of cryoEM services.

Human antibody recognition and neutralization mode on the NTD and RBD domains of SARS-CoV-2 spike protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Variants of concern (VOCs) such as Delta and Omicron have developed, which continue to spread the pandemic. It has been reported that these VOCs reduce vaccine efficacy and evade many neutralizing monoclonal antibodies (mAbs) that target the receptor binding domain (RBD) of the glycosylated spike (S) protein, which consists of the S1 and S2 subunits. Therefore, identification of optimal target regions is required to obtain neutralizing antibodies that can counter VOCs. Such regions have not been identified to date. We obtained 2 mAbs, NIBIC-71 and 7G7, using peripheral blood mononuclear cells derived from volunteers who recovered from COVID-19. Both mAbs had neutralizing activity against wild-type SARS-CoV-2 and Delta, but not Omicron. NIBIC-71 binds to the RBD, whereas 7G7 recognizes the N-terminal domain of the S1. In particular, 7G7 inhibited S1/S2 cleavage but not the interaction between the S protein and angiotensin-converting enzyme 2; it suppressed viral entry. Thus, the efficacy of a neutralizing mAb targeting inhibition of S1/2 cleavage was demonstrated. These results suggest that neutralizing mAbs targeting blockade of S1/S2 cleavage are likely to be cross-reactive against various VOCs.

Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook

In the last few years, electron microscopy has experienced a new methodological paradigm aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine learning and artificial intelligence are answering this call providing powerful resources towards automation, exploration, and development. In this review, we evaluate the state-of-the-art of machine learning applied to electron microscopy (and obliquely, to materials and nano-sciences). We start from the traditional imaging techniques to reach the newest higher-dimensionality ones, also covering the recent advances in spectroscopy and tomography. Additionally, the present review provides a practical guide for microscopists, and in general for material scientists, but not necessarily advanced machine learning practitioners, to straightforwardly apply the offered set of tools to their own research. To conclude, we explore the state-of-the-art of other disciplines with a broader experience in applying artificial intelligence methods to their research (e.g., high-energy physics, astronomy, Earth sciences, and even robotics, videogames, or marketing and finances), in order to narrow down the incoming future of electron microscopy, its challenges and outlook.

Automated systematic evaluation of cryo-EM specimens with SmartScope

Finding the conditions to stabilize a macromolecular target for imaging remains the most critical barrier to determining its structure by cryo-electron microscopy (cryo-EM). While automation has significantly increased the speed of data collection, specimens are still screened manually, a laborious and subjective task that often determines the success of a project. Here, we present SmartScope, the first framework to streamline, standardize, and automate specimen evaluation in cryo-EM. SmartScope employs deep-learning-based object detection to identify and classify features suitable for imaging, allowing it to perform thorough specimen screening in a fully automated manner. A web interface provides remote control over the automated operation of the microscope in real time and access to images and annotation tools. Manual annotations can be used to re-train the feature recognition models, leading to improvements in performance. Our automated tool for systematic evaluation of specimens streamlines structure determination and lowers the barrier of adoption for cryo-EM.

Better, Faster, Cheaper: Recent Advances in Cryo-Electron Microscopy

Cryo-electron microscopy (cryo-EM) continues its remarkable growth as a method for visualizing biological objects, which has been driven by advances across the entire pipeline. Developments in both single-particle analysis and in situ tomography have enabled more structures to be imaged and determined to better resolutions, at faster speeds, and with more scientists having improved access. This review highlights recent advances at each stageof the cryo-EM pipeline and provides examples of how these techniques have been used to investigate real-world problems, including antibody development against the SARS-CoV-2 spike during the recent COVID-19 pandemic.