Single-particle cryo-electron microscopy (cryo-EM) has become an essential structural determination technique with recent hardware developments making it possible to reach atomic resolution, at which individual atoms, including hydrogen atoms, can be resolved. In this study, we used the enzyme involved in the penultimate step of riboflavin biosynthesis as a test specimen to benchmark a recently installed microscope and determine if other protein complexes could reach a resolution of 1.5 Å or better, which so far has only been achieved for the iron carrier ferritin. Using state-of-the-art microscope and detector hardware as well as the latest software techniques to overcome microscope and sample limitations, a 1.42 Å map of Aquifex aeolicus lumazine synthase (AaLS) was obtained from a 48 h microscope session. In addition to water molecules and ligands involved in the function of AaLS, we can observe positive density for ∼50% of the hydrogen atoms. A small improvement in the resolution was achieved by Ewald sphere correction which was expected to limit the resolution to ∼1.5 Å for a molecule of this diameter. Our study confirms that other protein complexes can be solved to near-atomic resolution. Future improvements in specimen preparation and protein complex stabilization may allow more flexible macromolecules to reach this level of resolution and should become a priority of study in the field.

Lipid-based nanomedicines (LBNMs), including liposomes, lipid nanoparticles (LNPs) and extracellular vesicles (EVs), are recognized as one of the most clinically acceptable nano-formulations. However, the bench-to-bedside translation efficiency is far from satisfactory, mainly due to the lack of in-depth understanding of their physical and biochemical attributes at the single-particle level. In this review, we first give a brief introduction of LBNMs, highlighting some milestones and related scientific and clinical achievements in the past several decades, as well as the grand challenges in the characterization of LBNMs. Next, we present an overview of each category of LBNMs as well as the core properties that largely dictate their biological characteristics and clinical performance, such as size distribution, particle concentration, morphology, drug encapsulation and surface properties. Then, the recent applications of several analytical techniques including electron microscopy, atomic force microscopy, fluorescence microscopy, Raman microscopy, nanoparticle tracking analysis, tunable resistive pulse sensing and flow cytometry on the single-particle characterization of LBNMs are thoroughly discussed. Particularly, the comparative advantages of the newly developed nano-flow cytometry that enables quantitative analysis of both the physical and biochemical characteristics of LBNMs smaller than 40 nm with high throughput and statistical robustness are emphasized. The overall aim of this review article is to illustrate the importance, challenges and achievements associated with single-particle characterization of LBNMs.

The 21st amino acid, selenocysteine (Sec), is synthesized on its dedicated transfer RNA (tRNASec). In bacteria, Sec is synthesized from Ser-tRNA[Ser]Sec by Selenocysteine Synthase (SelA), which is a pivotal enzyme in the biosynthesis of Sec. The structural characterization of bacterial SelA is of paramount importance to decipher its catalytic mechanism and its role in the regulation of the Sec-synthesis pathway. Here, we present a comprehensive single-particle cryo-electron microscopy (SPA cryoEM) structure of the bacterial SelA with an overall resolution of 2.69 Å. Using recombinant Escherichia coli SelA, we purified and prepared samples for single-particle cryoEM. The structural insights from SelA, combined with previous in vivo and in vitro knowledge, underscore the indispensable role of decamerization in SelA\'s function. Moreover, our structural analysis corroborates previous results that show that SelA adopts a pentamer of dimers configuration, and the active site architecture, substrate binding pocket, and key K295 catalytic residue are identified and described in detail. The differences in protein architecture and substrate coordination between the bacterial enzyme and its counterparts offer compelling structural evidence supporting the independent molecular evolution of the bacterial and archaea/eukarya Ser-Sec biosynthesis present in the natural world.

In addressing the challenges faced by laboratories and universities with limited (or no) cryo-electron microscopy (cryo-EM) infrastructure, the ESRF, in collaboration with the Grenoble Institute for Structural Biology (IBS), has implemented the cryo-EM Solution-to-Structure (SOS) pipeline. This inclusive process, spanning grid preparation to high-resolution data collection, covers single-particle analysis and cryo-electron tomography (cryo-ET). Accessible through a rolling access route, proposals undergo scientific merit and technical feasibility evaluations. Stringent feasibility criteria demand robust evidence of sample homogeneity. Two distinct entry points are offered: users can either submit purified protein samples for comprehensive processing or initiate the pipeline with already vitrified cryo-EM grids. The SOS pipeline integrates negative stain imaging (exclusive to protein samples) as a first quality step, followed by cryo-EM grid preparation, grid screening and preliminary data collection for single-particle analysis, or only the first two steps for cryo-ET. In both cases, if the screening steps are successfully completed, high-resolution data collection will be carried out using a Titan Krios microscope equipped with a latest-generation direct electron counting detector coupled to an energy filter. The SOS pipeline thus emerges as a comprehensive and efficient solution, further democratizing access to cryo-EM research.

Cryo-electron microscopy (cryo-EM) is an imaging technique that allows the visualization of proteins and macromolecular complexes at near-atomic resolution. The low electron doses used to prevent radiation damage to the biological samples result in images where the power of noise is 100 times stronger than that of the signal. Accurate identification of proteins from these low signal-to-noise ratio (SNR) images is a critical task, as the detected positions serve as inputs for the downstream 3D structure determination process. Current methods either fail to identify all true positives or result in many false positives, especially when analyzing images from smaller-sized proteins that exhibit extremely low contrast, or require manual labeling that can take days to complete. Acknowledging the fact that accurate protein identification is dependent upon the visual interpretability of micrographs, we propose a framework that can perform denoising and detection in a joint manner and enable particle localization under extremely low SNR conditions using self-supervised denoising and particle identification from sparsely annotated data. We validate our approach on three challenging single-particle cryo-EM datasets and projection images from one cryo-electron tomography dataset with extremely low SNR, showing that it outperforms existing state-of-the-art methods used for cryo-EM image analysis by a significant margin. We also evaluate the performance of our algorithm under decreasing SNR conditions and show that our method is more robust to noise than competing methods.

High-resolution structures of biomolecules can be obtained using single-particle cryo-electron microscopy (SPA cryo-EM), and the rapidly growing number of structures solved by this method is encouraging more researchers to utilize this technique. As with other structural biology methods, sample preparation for an SPA cryo-EM data collection requires some expertise and an understanding of the strengths and limitations of the technique in order to make sensible decisions in the sample-preparation process. In this article, common strategies and pitfalls are described and practical advice is given to increase the chances of success when starting an SPA cryo-EM project.

Single-particle cryo-electron microscopy (cryo-EM) is a powerful imaging modality capable of visualizing proteins and macromolecular complexes at near-atomic resolution. The low electron-doses used to prevent radiation damage to the biological samples, however, result in images where the power of the noise is 100 times greater than the power of the signal. To overcome these low signal-to-noise ratios (SNRs), hundreds of thousands of particle projections are averaged to determine the three-dimensional structure of the molecule of interest. The sampling requirements of high-resolution imaging impose limitations on the pixel sizes that can be used for acquisition, limiting the size of the field of view and requiring data collection sessions of several days to accumulate sufficient numbers of particles. Meanwhile, recent image super-resolution (SR) techniques based on neural networks have shown state-of-the-art performance on natural images. Building on these advances, here, we present a multiple-image SR algorithm based on deep internal learning designed specifically to work under low-SNR conditions. Our approach leverages the internal image statistics of cryo-EM movies and does not require training on ground-truth data. When applied to single-particle datasets of apoferritin and T20S proteasome, we show that the resolution of the 3D structure obtained from SR micrographs can surpass the limits imposed by the imaging system. Our results indicate that the combination of low magnification imaging with in silico image SR has the potential to accelerate cryo-EM data collection by virtue of including more particles in each exposure and doing so without sacrificing resolution.

The surface layer of Sulfolobus acidocaldarius consists of a flexible but stable outer protein layer that interacts with an inner, membrane-bound protein.

Surface layers (S-layers) are resilient two-dimensional protein lattices that encapsulate many bacteria and most archaea. In archaea, S-layers usually form the only structural component of the cell wall and thus act as the final frontier between the cell and its environment. Therefore, S-layers are crucial for supporting microbial life. Notwithstanding their importance, little is known about archaeal S-layers at the atomic level. Here, we combined single-particle cryo electron microscopy, cryo electron tomography, and Alphafold2 predictions to generate an atomic model of the two-component S-layer of Sulfolobus acidocaldarius. The outer component of this S-layer (SlaA) is a flexible, highly glycosylated, and stable protein. Together with the inner and membrane-bound component (SlaB), they assemble into a porous and interwoven lattice. We hypothesise that jackknife-like conformational changes in SlaA play important roles in S-layer assembly.

Cryogenic electron microscopy (cryo-EM) single-particle analysis has revolutionized the structural analysis of icosahedral viruses, including tailed bacteriophages. In recent years, localized (or focused) reconstruction has emerged as a powerful data analysis method to capture symmetry mismatches and resolve asymmetric features in icosahedral viruses. Here, we describe the methods used to reconstruct the 2.65-MDa tail apparatus of the Shigella phage Sf6, a representative member of the Podoviridae superfamily.