The Core Complex of Yeast COMPASS and Human Mixed-Lineage Leukemia (MLL), Structure, Function, and Recognition of the Nucleosome.

Yeast COMPASS (complex of proteins associated with Set1) and human MLL (mixed-lineage leukemia) complexes are histone H3 lysine 4 methyltransferases with critical roles in gene regulation and embryonic development. Both complexes share a conserved C-terminal SET domain, responsible for catalyzing histone H3 K4 methylation on nucleosomes. Notably, their catalytic activity toward nucleosomes is enhanced and optimized with assembly of auxiliary subunits. In this review, we aim to illustrate the recent X-ray and cryo-EM structures of yeast COMPASS and human MLL1 core complexes bound to either unmodified nucleosome core particle (NCP) or H2B mono-ubiquitinated NCP (H2Bub.NCP). We further delineate how each auxiliary component of the complex contributes to the NCP and ubiquitin recognition to maximize the methyltransferase activity.

Human Transient Receptor Potential Ankyrin 1 Channel: Structure, Function, and Physiology.

The transient receptor potential ion channel TRPA1 is a Ca2+-permeable nonselective cation channel widely expressed in sensory neurons, but also in many nonneuronal tissues typically possessing barrier functions, such as the skin, joint synoviocytes, cornea, and the respiratory and intestinal tracts. Here, the primary role of TRPA1 is to detect potential danger stimuli that may threaten the tissue homeostasis and the health of the organism. The ability to directly recognize signals of different modalities, including chemical irritants, extreme temperatures, or osmotic changes resides in the characteristic properties of the ion channel protein complex. Recent advances in cryo-electron microscopy have provided an important framework for understanding the molecular basis of TRPA1 function and have suggested novel directions in the search for its pharmacological regulation. This chapter summarizes the current knowledge of human TRPA1 from a structural and functional perspective and discusses the complex allosteric mechanisms of activation and modulation that play important roles under physiological or pathophysiological conditions. In this context, major challenges for future research on TRPA1 are outlined.

Structure and Dynamics of Type 4a Pili and Type 2 Secretion System Endopili.

Within the highly diverse type four filament (TFF or T4F) superfamily, the machineries of type IVa pili (T4aP) and the type 2 secretion system (T2SS) in diderm bacteria exhibit a substantial sequence similarity despite divergent functions and distinct appearances: T4aP can extend micrometers beyond the outer membrane, whereas the endopili in the T2SS are restricted to the periplasm. The determination of the structure of individual components and entire filaments is crucial to understand how their structure enables them to serve different functions. However, the dynamics of these filaments poses a challenge for their high-resolution structure determination. This review presents different approaches that have been used to study the structure and dynamics of T4aP and T2SS endopili by means of integrative structural biology, cryo-electron microscopy (cryo-EM), and molecular dynamics simulations. Their conserved features and differences are presented. The non-helical stretch in the long-conserved N-terminal helix which is characteristic of all members of the TFF and the impact of calcium on structure, function, and dynamics of these filaments are discussed in detail.

De novo atomic protein structure modeling for cryoEM density maps using 3D transformer and HMM.

Accurately building 3D atomic structures from cryo-EM density maps is a crucial step in cryo-EM-based protein structure determination. Converting density maps into 3D atomic structures for proteins lacking accurate homologous or predicted structures as templates remains a significant challenge. Here, we introduce Cryo2Struct, a fully automated de novo cryo-EM structure modeling method. Cryo2Struct utilizes a 3D transformer to identify atoms and amino acid types in cryo-EM density maps, followed by an innovative Hidden Markov Model (HMM) to connect predicted atoms and build protein backbone structures. Cryo2Struct produces substantially more accurate and complete protein structural models than the widely used ab initio method Phenix. Additionally, its performance in building atomic structural models is robust against changes in the resolution of density maps and the size of protein structures.

Comprehensive encoding of conformational and compositional protein structural ensembles through the mmCIF data structure.

In the folded state, biomolecules exchange between multiple conformational states crucial for their function. However, most structural models derived from experiments and computational predictions only encode a single state. To represent biomolecules accurately, we must move towards modeling and predicting structural ensembles. Information about structural ensembles exists within experimental data from X-ray crystallography and cryo-electron microscopy. Although new tools are available to detect conformational and compositional heterogeneity within these ensembles, the legacy PDB data structure does not robustly encapsulate this complexity. We propose modifications to the macromolecular crystallographic information file (mmCIF) to improve the representation and interrelation of conformational and compositional heterogeneity. These modifications will enable the capture of macromolecular ensembles in a human and machine-interpretable way, potentially catalyzing breakthroughs for ensemble-function predictions, analogous to the achievements of AlphaFold with single-structure prediction.

Accurate Prediction of Protein Structural Flexibility by Deep Learning Integrating Intricate Atomic Structures and Cryo-EM Density Information.

The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and produces the best results in a large-scale protein dynamics dataset; this model can accurately infer the dynamic information of a protein in only a few seconds. By learning effectively from experimental protein structure data and cryo-electron microscopy (cryo-EM) data integration, our approach is able to accurately identify the interactive bidirectional constraints and supervision between cryo-EM maps and PDB models in maximizing the dynamic prediction efficacy. Rigorous 5-fold cross-validation on the dataset demonstrates that RMSF-net achieves test correlation coefficients of 0.746 ± 0.127 at the voxel level and 0.765 ± 0.109 at the residue level, showcasing its ability to deliver dynamic predictions closely approximating molecular dynamics simulations. Additionally, it offers real-time dynamic inference with minimal storage overhead on the order of megabytes. RMSF-net is a freely accessible tool and is anticipated to play an essential role in the study of protein dynamics.

Thickness determination of hydroperoxidized lipid bilayers from medium-resolution cryo-TEM images.

As the primary products of lipid oxidation, lipid hydroperoxides constitute an important class of lipids generated by aerobic metabolism. However, despite several years of effort, the structure of the hydroperoxidized bilayer has not yet been observed under electron microscopy. Here we use a 200 kV Cryo-TEM to image small unilamellar vesicles (SUVs) made (i) of pure POPC or SOPC, (ii) of their pure hydroperoxidized form, and (iii) of their equimolar mixtures. We show that the challenges posed by the determination of the thickness of the hydroperoxidized bilayers under these observation conditions can be addressed by an image analysis method that we developed and describe here.

Phase separation in model lipid membranes investigated with cryogenic electron microscopy.

We describe a method for investigating lateral membrane heterogeneity using cryogenic electron microscopy (cryo-EM) images of liposomes. The method takes advantage of differences in the thickness and molecular density of ordered and disordered phases that are resolvable in phase contrast cryo-EM. Compared to biophysical techniques like FRET or neutron scattering that yield ensemble-averaged information, cryo-EM provides direct visualization of individual vesicles and can therefore reveal variability that would otherwise be obscured by averaging. Moreover, because the contrast mechanism involves inherent properties of the lipid phases themselves, no extrinsic probes are required. We explain and discuss various complementary analyses of spatially resolved thickness and intensity measurements that enable an assessment of the membrane's phase state. The method opens a window to nanodomain structure in synthetic and biological membranes that should lead to an improved understanding of lipid raft phenomena.

Structural characterization of lateral phase separation in polymer-lipid hybrid membranes.

Hierarchic self-assembly is the main mechanism used to create diverse structures using soft materials. This is a case for both synthetic materials and biomolecular systems, as exemplified by the non-covalent organization of lipids into membranes. In nature, lipids often assemble into single bilayers, but other nanostructures are encountered, such as bilayer stacks and tubular and vesicular aggregates. Synthetic block copolymers can be engineered to recapitulate many of the structures, forms, and functions of lipid systems. When block copolymers are amphiphilic, they can be inserted or co-assembled into hybrid membranes that exhibit synergistic structural, permeability, and mechanical properties. One example is the emergence of lateral phase separation akin to the raft formation in biomembranes. When higher-order structures, such as hybrid membranes, are formed, this lateral phase separation can be correlated across membranes in the stack. This chapter outlines a set of important methods, such as X-ray Scattering, Atomic Force Microscopy, and Cryo-Electron Microscopy, that are relevant to characterizing and evaluating lateral and correlated phase separation in hybrid membranes at the nano and mesoscales. Understanding the phase behavior of polymer-lipid hybrid materials could lead to innovative advancements in biomimetic membrane separation systems.

Automated multiconformer model building for X-ray crystallography and cryo-EM.

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift toward modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior Rfree and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g., Coot) and fit can be further improved by refinement using standard pipelines (e.g., Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

CryoEM grid preparation: a closer look at advancements and impact of preparation mode and new approaches.

Sample preparation can present a significant hurdle within single particle cryo-electron microscopy (cryoEM), resulting in issues with reproducibility, data quality or an inability to visualise the sample. There are several factors which can influence this, including sample or buffer composition, grid type, route of sample preparation and interactions with the air-water interface (AWI). Here, we review some of the current routes for sample preparation and the associated challenges. We discuss a range of approaches for overcoming these challenges, such as minimising the grid preparation time, surfactants, grid type and biochemical approaches such as nanomagnetic beads. Finally, we discuss how a set of commercially available protein samples may serve as a benchmark suite for future technologies. This provides a route to compare techniques' abilities not just to generate high-resolution structures but also to overcome the challenges traditionally associated with cryoEM. As the field continues to produce new approaches to sample preparation and we start to better understand the underlying principles behind the behaviour of proteins within a thin film and in response to different environments, especially grid composition, it is hoped that more universal solutions can be provided that make the intractable systems tractable, improve resolution and, importantly, speed up data collection and reduce the currently required dataset sizes.

Cryo-EM structures reveal tau filaments from Down syndrome adopt Alzheimer's disease fold.

Down syndrome (DS) is a common genetic condition caused by trisomy of chromosome 21. Among their complex clinical features, including musculoskeletal, neurological, and cardiovascular disabilities, individuals with DS have an increased risk of developing progressive dementia and early-onset Alzheimer's disease (AD). This dementia is attributed to the increased gene dosage of the amyloid-ß (Aß) precursor protein gene, the formation of self-propagating Aß and tau prion conformers, and the deposition of neurotoxic Aß plaques and tau neurofibrillary tangles. Tau amyloid fibrils have previously been established to adopt many distinct conformations across different neurodegenerative conditions. Here, we report the characterization of brain samples from four DS cases spanning 36-63 years of age by spectral confocal imaging with conformation-specific dyes and cryo-electron microscopy (cryo-EM) to determine structures of isolated tau fibrils. High-resolution structures revealed paired helical filament (PHF) and straight filament (SF) conformations of tau that were identical to those determined from AD cases. The PHFs and SFs are made of two C-shaped protofilaments, each containing a cross-ß/ß-helix motif. Similar to filaments from AD cases, most filaments from the DS cases adopted the PHF form, while a minority (approximately 20%) formed SFs. Samples from the youngest individual with no documented dementia had sparse tau deposits. To isolate tau for cryo-EM from this challenging sample we used a novel affinity-grid method involving a graphene oxide surface derivatized with anti-tau antibodies. This method improved isolation and revealed that primarily tau PHFs and a minor population of chronic traumatic encephalopathy type II-like filaments were present in this youngest case. These findings expand the similarities between AD and DS to the molecular level, providing insight into their related pathologies and the potential for targeting common tau filament folds by small-molecule therapeutics and diagnostics.

Factors affecting macromolecule orientations in thin films formed in cryo-EM.

The formation of a vitrified thin film embedded with randomly oriented macromolecules is an essential prerequisite for cryogenic sample electron microscopy. Most commonly, this is achieved using the plunge-freeze method first described nearly 40 years ago. Although this is a robust method, the behaviour of different macromolecules shows great variation upon freezing and often needs to be optimized to obtain an isotropic, high-resolution reconstruction. For a macromolecule in such a film, the probability of encountering the air-water interface in the time between blotting and freezing and adopting preferred orientations is very high. 3D reconstruction using preferentially oriented particles often leads to anisotropic and uninterpretable maps. Currently, there are no general solutions to this prevalent issue, but several approaches largely focusing on sample preparation with the use of additives and novel grid modifications have been attempted. In this study, the effect of physical and chemical factors on the orientations of macromolecules was investigated through an analysis of selected well studied macromolecules, and important parameters that determine the behaviour of proteins on cryo-EM grids were revealed. These insights highlight the nature of the interactions that cause preferred orientations and can be utilized to systematically address orientation bias for any given macromolecule and to provide a framework to design small-molecule additives to enhance sample stability and behaviour.

Validation of electron-microscopy maps using solution small-angle X-ray scattering.

The determination of the atomic resolution structure of biomacromolecules is essential for understanding details of their function. Traditionally, such a structure determination has been performed with crystallographic or nuclear resonance methods, but during the last decade, cryogenic transmission electron microscopy (cryo-TEM) has become an equally important tool. As the blotting and flash-freezing of the samples can induce conformational changes, external validation tools are required to ensure that the vitrified samples are representative of the solution. Although many validation tools have already been developed, most of them rely on fully resolved atomic models, which prevents early screening of the cryo-TEM maps. Here, a novel and automated method for performing such a validation utilizing small-angle X-ray scattering measurements, publicly available through the new software package AUSAXS, is introduced and implemented. The method has been tested on both simulated and experimental data, where it was shown to work remarkably well as a validation tool. The method provides a dummy atomic model derived from the EM map which best represents the solution structure.

MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search.

Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.

Protocol to study CCT-mediated folding of Gß5 by single-particle cryo-EM.

The chaperonin CCT mediates folding of many cytosolic proteins, including G protein ß subunits (Gßs). Here, we present a protocol for isolating Gß5 bound to CCT and its co-chaperone PhLP1 and determining the CCT-mediated folding trajectory of Gß5 using single-particle cryoelectron microscopy (cryo-EM) techniques. We describe steps for purifying CCT-Gß5-PhLP1 from human cells, stabilizing the closed CCT conformation, preparing and imaging cryo-EM specimens, and processing data to recover multiple Gß5 folding intermediates. This protocol permits visualization of protein folding by CCT. For complete details on the use and execution of this protocol, please refer to Sass et al.1.

Mitigating the Blurring Effect of CryoEM Averaging on a Flexible and Highly Symmetric Protein Complex through Sub-Particle Reconstruction.

Many macromolecules are inherently flexible as a feature of their structure and function. During single-particle CryoEM processing, flexible protein regions can be detrimental to high-resolution reconstruction as signals from thousands of particles are averaged together. This "blurring" effect can be difficult to overcome and is possibly more pronounced when averaging highly symmetric complexes. Approaches to mitigating flexibility during CryoEM processing are becoming increasingly critical as the technique advances and is applied to more dynamic proteins and complexes. Here, we detail the use of sub-particle averaging and signal subtraction techniques to precisely target and resolve flexible DARPin protein attachments on a designed tetrahedrally symmetric protein scaffold called DARP14. Particles are first aligned as full complexes, and then the symmetry is reduced by alignment and focused refinement of the constituent subunits. The final reconstructions we obtained were vastly improved over the fully symmetric reconstructions, with observable secondary structure and side-chain placement. Additionally, we were also able to reconstruct the core region of the scaffold to 2.7 Å. The data processing protocol outlined here is applicable to other dynamic and symmetric protein complexes, and our improved maps could allow for new structure-guided variant designs of DARP14.

Human Kir2.1 Potassium Channel: Protocols for Cryo-EM Data Processing and Molecular Dynamics Simulations.

Kir channels are potassium (K+) channels responsible for the mechanism of inward rectification, which plays a fundamental role in maintaining the resting membrane potential. There are seven Kir subfamilies, and their opening and closing mechanism is regulated by different regulatory factors. Genetically inherited defects in Kir channels are responsible for several rare human diseases, and for most of them, there are currently no effective therapeutic treatments. High-resolution structural information is not available for several members within the Kir subfamilies. Recently, our group achieved a significant breakthrough by utilizing cryo-EM single-particle analysis to elucidate the first structure of the human Kir2.1 channel. We present here the data processing protocol of the cryo-EM data of the human Kir2.1 channel, which is applicable to the structural determination of other ion channels by cryo-EM single-particle analysis. We also introduce a protocol designed to assess the structural heterogeneity within the cryo-EM data, allowing for the identification of other possible protein structure conformations present in the collected data. Moreover, we present a protocol for conducting all-atom molecular dynamics (MD) simulations for K+ channels, which can be incorporated into various membrane models to simulate different environments. We also propose some methods for analyzing the MD simulations, with a particular emphasis on assessing the local mobility of protein residues.

Pillar data-acquisition strategies for cryo-electron tomography of beam-sensitive biological samples.

For cryo-electron tomography (cryo-ET) of beam-sensitive biological specimens, a planar sample geometry is typically used. As the sample is tilted, the effective thickness of the sample along the direction of the electron beam increases and the signal-to-noise ratio concomitantly decreases, limiting the transfer of information at high tilt angles. In addition, the tilt range where data can be collected is limited by a combination of various sample-environment constraints, including the limited space in the objective lens pole piece and the possible use of fixed conductive braids to cool the specimen. Consequently, most tilt series are limited to a maximum of ±70°, leading to the presence of a missing wedge in Fourier space. The acquisition of cryo-ET data without a missing wedge, for example using a cylindrical sample geometry, is hence attractive for volumetric analysis of low-symmetry structures such as organelles or vesicles, lysis events, pore formation or filaments for which the missing information cannot be compensated by averaging techniques. Irrespective of the geometry, electron-beam damage to the specimen is an issue and the first images acquired will transfer more high-resolution information than those acquired last. There is also an inherent trade-off between higher sampling in Fourier space and avoiding beam damage to the sample. Finally, the necessity of using a sufficient electron fluence to align the tilt images means that this fluence needs to be fractionated across a small number of images; therefore, the order of data acquisition is also a factor to consider. Here, an n-helix tilt scheme is described and simulated which uses overlapping and interleaved tilt series to maximize the use of a pillar geometry, allowing the entire pillar volume to be reconstructed as a single unit. Three related tilt schemes are also evaluated that extend the continuous and classic dose-symmetric tilt schemes for cryo-ET to pillar samples to enable the collection of isotropic information across all spatial frequencies. A fourfold dose-symmetric scheme is proposed which provides a practical compromise between uniform information transfer and complexity of data acquisition.

CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net.

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step in the cryo-EM-based structure determination. However, existing methods trained on a limited amount of cryo-EM data still cannot accurately pick protein particles from noisy cryo-EM images. The general foundational artificial intelligence-based image segmentation model such as Meta's Segment Anything Model (SAM) cannot segment protein particles well because their training data do not include cryo-EM images. Here, we present a novel approach (CryoSegNet) of integrating an attention-gated U-shape network (U-Net) specially designed and trained for cryo-EM particle picking and the SAM. The U-Net is first trained on a large cryo-EM image dataset and then used to generate input from original cryo-EM images for SAM to make particle pickings. CryoSegNet shows both high precision and recall in segmenting protein particles from cryo-EM micrographs, irrespective of protein type, shape and size. On several independent datasets of various protein types, CryoSegNet outperforms two top machine learning particle pickers crYOLO and Topaz as well as SAM itself. The average resolution of density maps reconstructed from the particles picked by CryoSegNet is 3.33 Å, 7% better than 3.58 Å of Topaz and 14% better than 3.87 Å of crYOLO. It is publicly available at https://github.com/jianlin-cheng/CryoSegNet.