Protein Secondary Structure Determination by Constrained Single-Particle Cryo-Electron Tomography

Zoonotic poxvirus infections pose significant threat to human health as we have witnessed recent spread of monkeypox. Therefore, insights into molecular mechanism behind poxvirus replication cycle are needed for the development of efficient antiviral strategies. Virion assembly is one of the key steps that determine the fate of replicating poxviruses. However, in-depth understanding of poxvirus assembly is challenging due to the complex nature of multi-step morphogenesis and heterogeneous virion structures. Despite these challenges, decades of research have revealed virion morphologies at various maturation stages, critical protein components and interactions with host cell compartments. Transmission electron microscopy has been employed as an indispensable tool for the examination of virion morphology, and more recently for the structure determination of protein complexes. In this review, we describe some of the major findings in poxvirus morphogenesis and the contributions of continuously advancing electron microscopy techniques.

Electron cryomicroscopy (cryo-EM) is a powerful tool in structural biology for determining 3D structures of macromolecular complexes. In the previous decade, many technological advancements have been introduced to improve the methodology of single particle cryo-EM, and hence the resolution of its protein reconstructions. These advancements include developments in both software algorithms and microscope hardware. Despite all these developments, the resolution of single particle cryo-EM cannot surpass 1.5 Å, a barrier blocking direct visualization of atomic details of the protein structure. Here, we show that by improving the optical performance of the electron microscope with new hardware, such resolution barrier can be removed, and atomic resolution of 1.25 Å can be reached with an engineered protein apoferritin. The atomic resolution protein structure helped set benchmarks for validating data quality in high resolution cryo-EM. We found that the new microscope also benefited to other proteins with lower contrast and higher flexibility, such as proteasome, chaperonin and fatty acid synthetase. For these proteins, sample properties and behavior were the major limitations. We anticipate that this would be alleviated by introducing other new microscope hardware, so that in the future, time and effort of structural biologists can concentrate on biochemical preparation of the sample, and single particle cryo-EM can routinely yield high quality protein structures at atomic resolution.

Membrane proteins are an important class of macromolecules found in all living organisms and many of them serve as important drug targets. In order to understand their biological and biochemical functions and to exploit them for structure-based drug design, high-resolution and accurate structures of membrane proteins are needed, but are still rarely available, e.g., predominantly from X-ray crystallography, and more recently from single particle cryo-EM — an increasingly powerful tool for membrane protein structure determination. However, while protein-lipid interactions play crucial roles for the structural and functional integrity of membrane proteins, for historical reasons and due to technological limitations, until recently, the primary method for membrane protein crystallization has relied on detergents. Bicelle and lipid cubic phase (LCP) methods have also been used for membrane protein crystallization, but the first step requires detergent extraction of the protein from its native cell membrane. The resulting, crystal structures have been occasionally questioned, but such concerns were generally dismissed as accidents or ignored. However, even a hint of controversy indicates that methodological drawbacks in such structural research may exist. In the absence of caution, structures determined using these methods are often assumed to be correct, which has led to surprising hypotheses for their mechanisms of action. In this communication, several examples of structural studies on membrane proteins or complexes will be discussed: Resistance-Nodulation-Division (RND) family transporters, microbial rhodopsins, Tryptophan-rich Sensory Proteins (TSPO), and Energy-Coupling Factor (ECF) type ABC transporters. These analyses should focus the attention of membrane protein structural biologists on the potential problems in structure determination relying on detergent-based methods. Furthermore, careful examination of membrane proteins in their native cell environments by biochemical and biophysical techniques is warranted, and completely detergent-free systems for membrane protein research are crucially needed.

Single-step antibody-based affinity cryo-electron microscopy for imaging and structural analysis of macromolecular assemblies.

Proteins are the molecules carry out the vital functions and make more than the half of dry weight in every cell. Protein in nature folds into a unique and energetically favorable 3-Dimensional (3-D) structure which is critical and unique to its biological function. In contrast to other methods for protein structure determination, Electron Cryo-rricroscopy (CryoEM) is able to produce volumetric maps of proteins that are poorly soluble, large and hard to crystallize. Furthermore, it studies the proteins in their native environment. Unfortunately, the volumetric maps generated by current advances in CryoEM technique produces protein maps at medium resolution about (~5 to 10A) in which it is hard to determine the atomic-structure of the protein. However, the resolution of the volumetric maps is improving steadily, and recent works could obtain atomic models at higher resolutions (~3A). De novo protein modeling is the process of building the structure of the protein using its CryoEM volumetric map. Thereupon, the volumetric maps at medium resolution generated by CryoEM technique proposed a new challenge. At the medium resolution, the location and orientation of secondary structure elements (SSE) can be visually and computationally identified. However, the order and direction (called protein topology) of the SSEs detected from the CryoEM volumetric map are not visible. In order to determine the protein structure, the topology of the SSEs has to be figured out and then the backbone can be built. Consequently, the topology problem has become a bottle neck for protein modeling using CryoEM In this dissertation, we focus to establish an effective computational framework to derive the atomic structure of a protein from the medium resolution CryoEM volumetric maps. This framework includes a topology graph component to rank effectively the topologies of the SSEs and a model building component. In order to generate the small subset of candidate topologies, the problem is translated into a layered graph representation. We developed a dynamic programming algorithm (TopoDP) for the new representation to overcome the problem of large search space. Our approach shows the improved accuracy, speed and memory use when compared with existing methods. However, the generating of such set was infeasible using a brute force method. Therefore, the topology graph component effectively reduces the topological space using the geometrical features of the secondary structures through a constrained K-shortest paths method in our layered graph. The model building component involves the bending of a helix and the loop construction using skeleton of the volumetric map. The forward-backward CCD is applied to bend the helices and model the loops.

Accurate determination of protein secondary structure from the chemical shift information is a key step for NMR tertiary structure determination. Relatively few work has been done on this subject. There needs to be a systematic investigation of algorithms that are (a) robust for large datasets; (b) easily extendable to (the dynamic) new databases; and (c) approaching to the limit of accuracy. We introduce new approaches using k-nearest neighbor algorithm to do the basic prediction and use the BCJR algorithm to smooth the predictions and combine different predictions from chemical shifts and based on sequence information only. Our new system, SUCCES, improves the accuracy of all existing methods on a large dataset of 805 proteins (at 86% Q(3) accuracy and at 92.6% accuracy when the boundary residues are ignored), and it is easily extendable to any new dataset without requiring any new training. The software is publicly available at http://monod.uwaterloo.ca/nmr/succes.

We demonstrate the utility of a new 206.5-nm continuous-wave UV laser excitation source for spectroscopic studies of proteins and CVD diamond. Excitation at 206.5 nm is obtained by intracavity frequency doubling the 413-nm line of a krypton-ion laser. We use this excitation to excite resonance Raman spectra within the π → π amide transition of the protein peptide backbone. The 206.5-nm excitation resonance enhances the protein amide vibrational modes. We use these high signal-to-noise spectral data to determine protein secondary structure. We also demonstrate the utility of this source to excite CVD and gem-quality diamond within its electronic bandgap. The diamond Raman spectra have very high signal-to-noise ratios and show no interfering broad-band luminescence. Excitation within the diamond bandgap also gives rise to narrow photoluminescence peaks from diamond defects. These features have previously been observed only by cathodoluminescence measurements. This new continuous-wave UV source is superior to the previous pulsed sources, because it avoids nonlinear optical phenomena and thermal sample damage; Photoluminescence.

The β subunit of the voltage-gated Ca(2+) channel (α1, α2δ, and β subunits) is a member of the MAGUK family of proteins and plays an essential role in regulating Ca(2+) channel trafficking and gating. It also serves as a central interaction partner for various Ca(2+) channel regulatory proteins. We report here the nearly complete (1)H, (13)C, and (15)N backbone resonance assignments of the 37kDa core SH3-GK domains of the β4 subunit. This is the first report of solution assignments for β subunits, and as such will lay the foundation for future investigations of interaction site mapping, functional dynamics, and protein complex structure determination.

Single particle cryoEM has emerged as a powerful method for structure determination of proteins and complexes, complementing X-ray crystallography and NMR spectroscopy. Yet, for many systems, the resolution of cryoEM density map has been limited to 4-6 Å, which only allows for resolving bulky amino acids side chains, thus hindering accurate model building from the density map. On the other hand, experimental chemical shifts (CS) from solution and solid state MAS NMR spectra provide atomic level data for each amino acid within a molecule or a complex; however, structure determination of large complexes and assemblies based on NMR data alone remains challenging. Here, we present a novel integrated strategy to combine the highly complementary experimental data from cryoEM and NMR computationally by molecular dynamics simulations to derive an atomistic model, which is not attainable by either approach alone. We use the HIV-1 capsid protein (CA) C-terminal domain as well as the large capsid assembly to demonstrate the feasibility of this approach, termed NMR CS-biased cryoEM structure refinement.

Single particle cryo-electron microscopy (cryo-EM) has matured into a robust method for the determination of biological macromolecule structures in the past decade, complementing X-ray crystallography and nuclear magnetic resonance. Constant methodological improvements in both cryo-EM hardware and image processing software continue to contribute to an exponential growth in the number of structures solved annually. In this review, we provide a historical view of the many steps that were required to make cryo-EM a successful method for the determination of high-resolution protein complex structures. We further discuss aspects of cryo-EM methodology that are the greatest pitfalls challenging successful structure determination to date. Lastly, we highlight and propose potential future developments that would improve the method even further in the near future.

Volta phase plate data collection facilitates image processing and cryo-EM structure determination.

Editorial overview: New protein production tools for structural biology

High-resolution structures of membrane and soluble proteins can be obtained by cryo-electron crystallography, given highly-ordered cryo-preparations of perfectly flat 2D crystals are available. Studies of membrane proteins, which are embedded into a lipid membrane, mimicking the native cell membrane, are of particular biological interest. However there are multiple reasons why electron crystallography is far from being a mainstream protein structure determination technique. In this thesis we address three major difficulties of electron crystallography: (i) resolution loss due to not perfectly flat crystals, (ii) reliable high-throughput automatic image processing and (iii) correction of electron beam-induced motion of the sample.
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\nThe conventional electron crystallography image processing procedure assumes perfectly flat 2D crystals, which are almost impossible to obtain. Our new processing approach, described in Chapter 2, weakens this assumption tremendously. Traditional processing assigns the same tilt geometry to all proteins of one 2D crystal. Thus local tilt geometry variations, due to not perfectly flat crystals, are neglected. We developed an algorithm that optimizes the tilt geometry of each protein separately, while exploiting the correlation between neighboring proteins. The new method proves the feasibility of this approach, improves the achieved resolution and opens the doors to new studies, i.e. structural studies of membrane proteins embedded into lipid vesicles.
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\nRecently a new generation of digital detectors tremendously changed the cryo-electron microscopy field. Beside a significantly increased signal-to-noise ratio these detectors record dose-fractionated movies of the sample under the electron beam. Previous cameras only recorded one image instead. This new exposure mode enables the computational correction for beam-induced sample movements. In Chapter 3 we describe a new “real-time” automation pipeline for electron crystallography using direct electron detectors. The novel pipeline automatically corrects for homogeneous sample drift on frame level and processes the acquired images automatically. Both, the time-to-solution and the quality of the obtained 3D reconstructions are significantly improved.
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\nHeterogeneous beam-induced sample movements are the most severe resolution- limiting factor in modern cryo-electron crystallography. In Chapter 4 we present an algorithm, termed movie-mode unbending, which corrects for inhomogeneous beam- induced sample drift. In contrast to the previous homogeneous drift-correction, the novel algorithm can correct for locally varying beam-induced sample motion. This novel approach significantly increases the resolution of electron cryo-crystallographic studies recorded on the latest detectors.
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\nChapter 5 covers multiple successful applications of the methods introduced above. For instance the real-time drift-correction module of the developed automation pipeline was used for multiple near-atomic resolution single particle and helical image processing projects. The high-throughput crystal image processing was applied to different kinds of 2D crystals and enabled the qualitative assessment of different sample preparation methods. Additionally we describe the implementation of a high-throughput single particle automation pipeline, which will enable the generation of near-atomic resolution single particle cryo-electron microscopy density maps on a daily basis.

Revealing the structure of complex biological macromolecules, such as proteins, is an essential step for understanding the chemical mechanisms that determine the diversity of their functions. Synchrotron based X-ray crystallography and cryo-electron microscopy have made major contributions in determining thousands of protein structures even from micro-sized crystals. They suffer from some limitations that have not been overcome, such as radiation damage, the natural inability to crystallize a number of proteins, and experimental conditions for structure determination that are incompatible with the physiological environment. Today, the ultra-short and ultra-bright pulses of X-ray free-electron lasers have made attainable the dream to determine protein structures before radiation damage starts to destroy the samples. However, the signal-to-noise ratio remains a great challenge to obtain usable diffraction patterns from a single protein molecule. With the perspective to overcome these challenges, we describe here a new methodology that has the potential to overcome the signal-to-noise-ratio and protein crystallization limits. Using a multidisciplinary approach, we propose to create ordered, two dimensional protein arrays with defined orientation attached on a self-assembled-monolayer. We develop a literature-based flexible toolbox capable of assembling different kinds of proteins on a functionalized surface and consider using a graphene cover layer that will allow performing experiments with proteins in physiological conditions.

Cryo-electron microscopy (cryo-EM) has become a leading approach for protein structure determination, but it remains challenging to accurately model atomic structures with cryo-EM density maps. We propose a hybrid method, CR-I-TASSER, which integrates deep neural-network learning with I-TASSER assembly simulations for automated cryo-EM structure determination. The method is benchmarked on 778 proteins with simulated and experimental density maps, where CR-I-TASSER constructs models with a correct fold (TM-score>0.5) for 643 targets that is 64% higher than the best of other de novo and refinement-based approaches on high-resolution data samples. Detailed data analyses showed that the major advantage of CR-I-TASSER lies in the deep-learning based position prediction, which significantly improves the threading template quality and therefore boosts the accuracy of final models through optimized fragment assembly simulations. These results demonstrate a new avenue to determine cryo-EM protein structures with high accuracy and robustness covering various target types and density-map resolutions.