High-resolution electron cryomicroscopy of macromolecular assemblies

The Chikungunya virus is carried by mosquitos and can cause a number of diseases in humans including encephalitis, which can be fatal in some cases, and severe arthritis. A recent mutation in the E1 protein of the virus has allowed it to efficiently reproduce in a different species of mosquitos, leading to a Chikungunya epidemic in Réunion Island in 2005 and the subsequent infection of millions of individuals in Africa and Asia. The virus also has the potential to spread to many areas of Europe and the Americas. Chikungunya virus has a single-stranded RNA genome that codes for four non-structural proteins and five structural proteins. Based on this knowledge it has been possible to develop virus-like particles that can be used to immunise non-human primates against Chikungunya infection by inducing antibody production. However, the development of vaccines for Chikungunya in humans will require a deeper understanding of how these antibodies produced by the vaccine interact with the virus and more detailed information about the structures of the virus and antibodies. Sun et al. have used two techniques – X-ray crystallography and electron cryo-microscopy – to determine the structure of Chikungunya virus-like particles, and to obtain new insights into the interactions of these particles with four related antibodies. Electron cryo-microscopy was used to figure out the structure of the particles at near atomic resolution, and X-ray crystallography was used to determine the atomic resolution structures of two of the four Fab antibodies that neutralize the Chikungunya virus. Electron cryo-microscopy was also used to probe the complex formed by the interactions between the virus-like particles and the antibodies. Sun et al. were able to identify the likely viral receptor site that is blocked by three of the antibodies when they neutralize the virus; the fourth antibody is thought to act by immobilizing one of the domains of protein E2, thereby hiding the “fusion loop” that allows the virus to enter and infect human tissue. It is hoped that these findings will contribute to efforts to combat the spread of the Chikungunya virus worldwide.

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d20682e98">Cryo-electron microscopy (Cryo-EM) has emerged as a powerful tool for determining the structures of biomolecules, especially in cases where traditional methods like X-ray crystallography and nuclear magnetic resonance (NMR) fall short [ <a class="xref-link" href="#r1">1</a>]. Its ability to visualize biomolecules in near-native states at cryogenic temperatures has revolutionized structural biology, leading to the resolution of complex molecular machines such as the ribosome and membrane proteins, which are critical targets for drug development. The recent “resolution revolution” [ <a class="xref-link" href="#r2">2</a>] in Cryo-EM has made it possible to achieve atomic or near-atomic resolution for many large macromolecular assemblies. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d20682e106">In Cryo-EM, a substantial volume of particle data is often excluded due to inadequate phase contrast, which impedes full utilization of these particles. This limited insight into discarded structures constrains our capacity to attain the utmost resolution. Furthermore, the 2D classification task in single-particle reconstruction proves especially challenging for heterogeneous samples, low-concentration or low-symmetry structures, and small (&lt;250 kDa) or flexible molecules. To enhance phase contrast, a conventional approach involves integrating a phase-shifting device—such as Zernike or Volta phase plates—within the back focal plane of the objective lens. However, these devices are prone to high-frequency signal attenuation, variability in fabrication quality, reliability issues, and shortened operational lifespans due to electrostatic charging. In recent years, computational phase retrieval algorithms have advanced markedly and are now widely applied in coherent diffraction imaging, holographic imaging, and Fourier ptychographic microscopy. Some studies in Cryo-EM have also begun investigating the potential of computational phase retrieval to extend imaging contrast to the limits allowable by our understanding of the physics of contrast formation [ <a class="xref-link" href="#r3">3</a>].

Macromolecular crystallography has been, for the last few decades, the main source of structural information of biological macromolecular systems and it is one of the most powerful techniques for the analysis of enzyme mechanisms and macromolecular interactions at the atomic level. In addition, it is also an extremely powerful tool for drug design. Recent technological and methodological developments in macromolecular X-ray crystallography have allowed solving structures that until recently were considered difficult or even impossible, such as structures at atomic or subatomic resolution or large macromolecular complexes and assemblies at low resolution. These developments have also helped to solve the 3D-structure of macromolecules from twin crystals. Recently, this technique complemented with cryo-electron microscopy and neutron crystallography has provided the structure of large macromolecular machines with great precision allowing understanding of the mechanisms of their function.

In modern structural biology, there are three major methods for structural biologists to obtain structural information of macromolecules: cryo-electron microscopy (cryo-EM), nuclear magnetic resonance (NMR), and X-ray crystallography. Cryo-EM, in comparison with the other two methods, allows structural biologists to obtain the structures of various macromolecules in a more native and less perturbed system. Over the past decade, cryo-EM has enabled scientists to determine the structures of protein complexes at atomic resolution and made a profound impact in molecular bioscience and pharmaceutical sectors. Along with cryo-EM, another emerging technique called cryo-electron tomography (cryo-ET) has gained increasing importance in structural biology. It has the potential to visualize macromolecular complexes and assemblies in their native environments at high resolution, but there are still some challenges for small, sparse subjects and in approaching atomic resolution in situ. This chapter summarizes the major steps involved in structure determination using cryo-EM and cryo-ET and highlights the major challenges for in situ cryo-ET. We also present a few examples of near-atomic resolution structure determination of macromolecular assemblies both in purified systems in vitro and in native contexts in situ. Future perspectives are discussed as well.

Spherical viruses

Cryo-EM in Enzymology

Structural studies of biocomplexes using single-particle cryo-electron microscopy (cryo-EM) is now a well-established technique in structural biology and has become competitive with X-ray crystallography. The latest advances in EM enable us to determine structures of protein complexes at 3-5 Å resolution for an extremely broad range of sizes from ~200 kDa up to hundreds of megadaltons (Bartesaghi et al., Science 348(6239):1147-1151, 2051; Bai et al., Nature 525(7568):212-217, 2015; Vinothkumar et al., Nature 515(7525):80-84, 2014; Grigorieff and Harrison, Curr Opin Struct Biol 21(2):265-273, 2011). The majority of biocomplexes comprise a number of different components and are not amenable to crystallisation. Secretion systems are typical examples of such multi-protein complexes, and structural studies of them are extremely challenging. The only feasible approach to revealing their spatial organisation and functional modification is cryo-EM. The development of systems for digital registration of images and algorithms for the fast and efficient processing of recorded images and subsequent analysis facilitated the determination of structures at near-atomic resolution. In this review we will describe sample preparation for cryo-EM, how data are collected by new detectors, and the logistics of image analysis through the basic steps required for reconstructions of both small and large biological complexes and their refinement to nearly atomic resolution. The processing workflow is illustrated using examples of EM analysis of a Type IV Secretion System.

Ric-8A is a cytosolic Guanine Nucleotide exchange Factor (GEF) that activates heterotrimeric G protein alpha subunits (Gα) and serves as an essential Gα chaperone. Mechanisms by which Ric-8A catalyzes these activities, which are stimulated by Casein Kinase II phosphorylation, are unknown. We report the structure of the nanobody-stabilized complex of nucleotide-free Gα bound to phosphorylated Ric-8A at near atomic resolution by cryo-electron microscopy and X-ray crystallography. The mechanism of Ric-8A GEF activity differs considerably from that employed by G protein-coupled receptors at the plasma membrane. Ric-8A engages a specific conformation of Gα at multiple interfaces to form a complex that is stabilized by phosphorylation within a Ric-8A segment that connects two Gα binding sites. The C-terminus of Gα is ejected from its beta sheet core, thereby dismantling the GDP binding site. Ric-8A binds to the exposed Gα beta sheet and switch II to stabilize the nucleotide-free state of Gα.

The quad-HIDAC PET scanner offers unparalleled high resolution PET imaging capability (<1 mm), combined with notable count rate performance (400 kcps) and sensitivity (up to 2% with scatter correction). To some extent the image resolution realized by the system is determined by the choice of image reconstruction algorithm. This work compares 4 reconstruction techniques applied to data from the quad-HIDAC scanner: 2 iterative methods (ROPLE and 3D OSEM) and 2 analytic methods (BPF and 3D RP). These four methods were chosen so as to include both a list-mode based and a projection-based method in each category. The algorithms were compared in terms of contrast, noise and resolution for a specially designed cylindrical phantom. The results indicate that the iterative methods offer improved resolution and contrast for a given noise level compared to the analytic methods. Of these iterative methods, the new list-mode technique (ROPLE) performed better than the projection-based technique.

Membrane proteins are responsible for many significant biological functions, including those of enzymes, channels and receptors. Unfortunately, membrane proteins present serious obstacles for applications of the most widely used methods of structural biology; in particular, membrane proteins are notoriously difficult to crystallize and the multidimensional NMR methods that are successful in determining the structures of globular proteins in solution are hampered by the slow reorientation rates of proteins complexed with lipids. As a consequence of these experimental problems, descriptions of the structures and dynamics of membrane proteins have lagged far behind those of globular proteins. The few structures of membrane proteins determined by diffraction (Deisenhofer et al., 1985; Rees et al., 1989; Weiss et al., 1991) and image reconstruction (Henderson et al., 1990) have proven to be exceptions, since many other interesting membrane proteins have not been amenable to crystallization. Although NMR spectroscopy is at an even earlier stage in its application to membrane proteins than X-ray crystallography, it is now emerging as an effective method for describing the dynamics of membrane proteins, and substantial progress is being made in its development as a method for determining the structures of membrane proteins.

Since the 1970s and for about 40years, X-ray crystallography has been by far the most powerful approach for determining virus structures at close to atomic resolutions. Information provided by these studies has deeply and extensively enriched and shaped our vision of the virus world. In turn, the ever-increasing complexity and size of the virus structures being investigated have constituted a major driving force for methodological and conceptual developments in X-ray macromolecular crystallography (MX). Landmarks of the structure determination of viral particles, such as the ones from the first animal viruses or from the first membrane-containing viruses, have often been associated with methodological breakthroughs in X-ray crystallography.In recent years, the advent of new detectors with fast frame rate, high sensitivity, and low-noise background has changed the way MX data is collected, enabling new types of studies at X-ray free-electron laser and synchrotron facilities. In parallel, a very high degree of automation has been established at most MX synchrotron beamlines, allowing the screening of large number of crystals with very high throughputs. This has proved crucial for fragment-based drug design projects, of special relevance for the identification of new antiviral drugs.This change in the usage of X-ray crystallography is also mirrored in the recent advances in cryo-electron microscopy (cryo-EM), which can nowadays produce macromolecule structures at resolutions comparable to those obtained by MX. Since this technique is especially amenable for large protein assemblies, cryo-EM has progressively turned into the favored technique to study the structure of large viral particles at high resolution.In this chapter, we present the common ground of proteins and virus crystallography with an emphasis in the peculiarities of virus-related studies.

Circular dichroism (CD) spectroscopy is a well-established technique for studying the secondary structures, dynamics, folding pathways, and interactions of soluble proteins, and is complementary to the high resolution but generally static structures produced by X-ray crystallography, NMR spectroscopy, and cryo electron microscopy. CD spectroscopy has special relevance for the study of membrane proteins, which are difficult to crystallise and largely ignored in structural genomics projects. However, the requirement for membrane proteins to be embedded in amphipathic environments such as membranes, lipid vesicles, detergent micelles, bicelles, oriented bilayers, or nanodiscs, in order for them to be soluble or dispersed in solution whilst maintaining their structure and function, necessitates the use of different experimental and analytical approaches than those employed for soluble proteins. This review discusses specialised methods for collecting and analysing membrane protein CD data, highlighting where protocols for soluble and membrane proteins diverge.

An approach to multidimensional smoothing is introduced that is based on a penalized likelihood with a modified discretized Laplacian penalty term. The choice of penalty simplifies computational difficulties associated with standard multidimensional Laplacian smoothing methods yet without compromising mean squared error characteristics, at least on the interior of the region of interest. For linear smoothing in hyper-rectangular domains, which has wide application in image reconstruction and restoration problems, computations are carried out using fast Fourier transforms. Nonlinear smoothing is accomplished by iterative application of the linear smoothing technique. The iterative procedure is shown to be convergent under general conditions. Adaptive choice of the amount of smoothing is based on approximate cross-validation type scores. An importance sampling technique is used to estimate the degrees of freedom of the smooth. The methods are implemented in one- and two-dimensional settings. Some i...

In algebraic reconstruction of images in computerized tomography we are dealing with rectangular, large, sparse and ill‐conditioned linear systems of equations. In this paper we describe a two‐grid algorithm for solving such kind of linear systems, which uses Kaczmarz's projection method as relaxation. The correction step is performed with a special “local” aggregation / disaggregation type procedure. In this respect, we have to solve a small sized minimization problem associated to each coarse grid pixel. The information so obtained is then “distributed” to the neighbour fine grid pixels. Some image reconstruction experiments are also presented. (© 2010 Wiley‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)

.Significance: Photoacoustic (PA) imaging can provide structural, functional, and molecular information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal detection deteriorates image quality, and quantitative PAI (QPAI) remains challenging due to the unknown light fluence spectra in deep tissue. In recent years, deep learning (DL) has shown outstanding performance when implemented in PAI, with applications in image reconstruction, quantification, and understanding.Aim: We provide (i) a comprehensive overview of the DL techniques that have been applied in PAI, (ii) references for designing DL models for various PAI tasks, and (iii) a summary of the future challenges and opportunities.Approach: Papers published before November 2020 in the area of applying DL in PAI were reviewed. We categorized them into three types: image understanding, reconstruction of the initial pressure distribution, and QPAI.Results: When applied in PAI, DL can effectively process images, improve reconstruction quality, fuse information, and assist quantitative analysis.Conclusion: DL has become a powerful tool in PAI. With the development of DL theory and technology, it will continue to boost the performance and facilitate the clinical translation of PAI.