Visualizing flexibility at molecular resolution: analysis of heterogeneity in single-particle electron microscopy reconstructions

CryoRes: Local Resolution Estimation of Cryo-EM Density Maps by Deep Learning

Recent progress in cryo-EM research has ignited a revolution in biological macromolecule structure determination. Resolution is an essential parameter for quality assessment of a cryo-EM density map, and it is known that resolution varies in different regions of a map. Currently available methods for local resolution estimation require manual adjustment of parameters and in some cases necessitate acquisition or de novo generation of so-called "half maps". Here, we developed CryoRes, a deep-learning algorithm to estimate local resolution directly from a single final cryo-EM density map, specifically by learning resolution-aware patterns of density map voxels through supervised training on a large dataset comprising 1,174 experimental cryo-EM density maps. CryoRes significantly outperforms all of the state-of-the-art competing resolution estimation methods, achieving an average RMSE of 2.26 Å for local resolution estimation relative to the currently most reliable FSC-based method blocres, yet requiring only the single final map as input. Further, CryoRes is able to generate a molecular mask for each map, with accuracy 12.12% higher than the masks generated by ResMap. CryoRes is ultra-fast, fully automatic, parameter-free, applicable to cryo-EM subtomogram data, and freely available at https://cryores.zhanglab.net.

Genomics-based strategies toward the identification of a Z-ISO carotenoid biosynthetic enzyme suitable for structural studies

Over the past 20years, structural genomics efforts have proven enormously successful for the determination of integral membrane protein structures, particularly for those of prokaryotic origin. However, traditional genomic expansion screens have included up to hundreds of targets, necessitating the use of robotics and other automation not available to most laboratories. Moreover, such large-scale screens of eukaryotic targets are not easily performed at such a scale. To have broader appeal, traditional structural genomic approaches need to be modified and improved such that they are feasible for most laboratories and especially so for proteins from eukaryotic organisms. One such refinement, termed "microgenomic expansion," has been recently described. This approach improves the process of target selection by making target screening a two-step process, with a minimal number of targets tested at each step. Microgenomic expansion methods are applied here theoretically to a project that has the objective of acquiring a structure for the plant 15-cis-ζ-carotene isomerase, Z-ISO.

Analysis of transient membrane protein interactions by single-molecule diffusional mobility shift assay

Various repertoires of membrane protein interactions determine cellular responses to diverse environments around cells dynamically in space and time. Current assays, however, have limitations in unraveling these interactions in the physiological states in a living cell due to the lack of capability to probe the transient nature of these interactions on the crowded membrane. Here, we present a simple and robust assay that enables the investigation of transient protein interactions in living cells by using the single-molecule diffusional mobility shift assay (smDIMSA). Utilizing smDIMSA, we uncovered the interaction profile of EGFR with various membrane proteins and demonstrated the promiscuity of these interactions depending on the cancer cell line. The transient interaction profile obtained by smDIMSA will provide critical information to comprehend the crosstalk among various receptors on the plasma membrane.

Should Virus Capsids Assemble Perfectly? Theory and Observation of Defects

Although published structural models of viral capsids generally exhibit a high degree of regularity or symmetry, structural defects might be expected because of the fluctuating environment in which capsids assemble and the requirement of some capsids for disassembly before genome delivery. Defective structures are observed in computer simulations, and are evident in single-particle cryoelectron microscopy studies. Here, we quantify the conditions under which defects might be expected, using a statistical mechanics model allowing for ideal, defective, and vacant sites. The model displays a threshold in affinity parameters below which there is an appreciable population of defective capsids. Even when defective sites are not allowed, there is generally some population of vacancies. Analysis of single particles in cryoelectron microscopy micrographs yields a confirmatory ≳15% of defective particles. Our findings suggest structural heterogeneity in virus capsids may be under-appreciated, and also points to a nontraditional strategy for assembly inhibition.

WITHDRAWN: Structural studies of vitrified biological proteins and macromolecules - A review on the microimaging aspects of cryo-electron microscopy

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Simulation-Based Methods for Model Building and Refinement in Cryoelectron Microscopy

Advances in cryoelectron microscopy (cryo-EM) have revolutionized the structural investigation of large macromolecular assemblies. In this review, we first provide a broad overview of modeling methods used for flexible fitting of molecular models into cryo-EM density maps. We give special attention to approaches rooted in molecular simulations-atomistic molecular dynamics and Monte Carlo. Concise descriptions of the methods are given along with discussion of their advantages, limitations, and most popular alternatives. We also describe recent extensions of the widely used molecular dynamics flexible fitting (MDFF) method and discuss how different model-building techniques could be incorporated into new hybrid modeling schemes and simulation workflows. Finally, we provide two illustrative examples of model-building and refinement strategies employing MDFF, cascade MDFF, and RosettaCM. These examples come from recent cryo-EM studies that elucidated transcription preinitiation complexes and shed light on the functional roles of these assemblies in gene expression and gene regulation.

Structure Determination by Single-Particle Cryo-Electron Microscopy: Only the Sky (and Intrinsic Disorder) is the Limit

Traditionally, X-ray crystallography and NMR spectroscopy represent major workhorses of structural biologists, with the lion share of protein structures reported in protein data bank (PDB) being generated by these powerful techniques. Despite their wide utilization in protein structure determination, these two techniques have logical limitations, with X-ray crystallography being unsuitable for the analysis of highly dynamic structures and with NMR spectroscopy being restricted to the analysis of relatively small proteins. In recent years, we have witnessed an explosive development of the techniques based on Cryo-electron microscopy (Cryo-EM) for structural characterization of biological molecules. In fact, single-particle Cryo-EM is a special niche as it is a technique of choice for the structural analysis of large, structurally heterogeneous, and dynamic complexes. Here, sub-nanometer atomic resolution can be achieved (i.e., resolution below 10 Å) via single-particle imaging of non-crystalline specimens, with accurate 3D reconstruction being generated based on the computational averaging of multiple 2D projection images of the same particle that was frozen rapidly in solution. We provide here a brief overview of single-particle Cryo-EM and show how Cryo-EM has revolutionized structural investigations of membrane proteins. We also show that the presence of intrinsically disordered or flexible regions in a target protein represents one of the major limitations of this promising technique.

Role of integrative structural biology in understanding transcriptional initiation

Integrative structural biology combines data from multiple experimental techniques to generate complete structural models for the biological system of interest. Most commonly cross-linking data sets are employed alongside electron microscopy maps, crystallographic structures, and other data by computational methods that integrate all known information and produce structural models at a level of resolution that is appropriate to the input data. The precision of these modelled solutions is limited by the sparseness of cross-links observed, the length of the cross-linking reagent, the ambiguity arisen from the presence of multiple copies of the same protein, and structural and compositional heterogeneity. In recent years integrative structural biology approaches have been successfully applied to a range of RNA polymerase II complexes. Here we will provide a general background to integrative structural biology, a description of how it should be practically implemented and how it has furthered our understanding of the biology of large transcriptional assemblies. Finally, in the context of recent breakthroughs in microscope and direct electron detector technology, where increasingly EM is capable of resolving structural features directly without the aid of other structural techniques, we will discuss the future role of integrative structural techniques.

A Local Agreement Filtering Algorithm for Transmission EM Reconstructions

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We propose an algorithm, LAFTER, that recovers features with more signal than noise from half maps.

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LAFTER is shown to recover features over a wide range of FSCs and local signal-to-noise ratios.

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We suggest effective local noise suppression be evaluated by comparing the filter-sum xFSC to C_ref.

We present LAFTER, an algorithm for de-noising single particle reconstructions from cryo-EM.

Single particle analysis entails the reconstruction of high-resolution volumes from tens of thousands of particle images with low individual signal-to-noise. Imperfections in this process result in substantial variations in the local signal-to-noise ratio within the resulting reconstruction, complicating the interpretation of molecular structure. An effective local de-noising filter could therefore improve interpretability and maximise the amount of useful information obtained from cryo-EM maps.

LAFTER is a local de-noising algorithm based on a pair of serial real-space filters. It compares independent half-set reconstructions to identify and retain shared features that have power greater than the noise. It is capable of recovering features across a wide range of signal-to-noise ratios, and we demonstrate recovery of the strongest features at Fourier shell correlation (FSC) values as low as 0.144 over a 256³-voxel cube. A fast and computationally efficient implementation of LAFTER is freely available.

We also propose a new way to evaluate the effectiveness of real-space filters for noise suppression, based on the correspondence between two FSC curves: 1) the FSC between the filtered and unfiltered volumes, and 2) C_ref, the FSC between the unfiltered volume and a hypothetical noiseless volume, which can readily be estimated from the FSC between two half-set reconstructions.

A Multi-model Approach to Assessing Local and Global Cryo-EM Map Quality

There does not currently exist a standardized indicator of how well cryo-EM-derived models represent the density from which they were generated. We present a straightforward methodology that utilizes freely available tools to generate a suite of independent models and to evaluate their convergence in an EM density. These analyses provide both a quantitative and qualitative assessment of the precision of the models and their representation of the density, respectively, while concurrently providing a platform for assessing both global and local EM map quality. We further use standardized datasets to provide an expected deviation within a suite of models refined against EM maps reported to be at 5 Å resolution or better. Associating multiple atomic models with a deposited EM map provides a rapid and accessible reporter of convergence, a strong indicator of highly resolved molecular detail, and is an important step toward an FSC-independent assessment of map and model quality.

De novo computational RNA modeling into cryo-EM maps of large ribonucleoprotein complexes

Increasingly, cryo-electron microscopy (cryo-EM) is used to determine the structures of RNA-protein assemblies, but nearly all maps determined with this method have biologically important regions where the local resolution does not permit RNA coordinate tracing. To address these omissions, we present de novo ribonucleoprotein modeling in real space through assembly of fragments together with experimental density in Rosetta (DRRAFTER). We show that DRRAFTER recovers near-native models for a diverse benchmark set of RNA-protein complexes including the spliceosome, mitochondrial ribosome, and CRISPR-Cas9-sgRNA complexes; rigorous blind tests include yeast U1 snRNP and spliceosomal P complex maps. Additionally, to aid in model interpretation, we present a method for reliable in situ estimation of DRRAFTER model accuracy. Finally, we apply DRRAFTER to recently determined maps of telomerase, the HIV-1 reverse transcriptase initiation complex, and the packaged MS2 genome, demonstrating the acceleration of accurate model building in challenging cases.

Searching for 3D structural models from a library of biological shapes using a few 2D experimental images

Background

Advancements in biophysical experimental techniques have pushed the limits in terms of the types of phenomena that can be characterized, the amount of data that can be produced and the resolution at which we can visualize them. Single particle techniques such as Electron Microscopy (EM) and X-ray free electron laser (XFEL) scattering require a large number of 2D images collected to resolve three-dimensional (3D) structures. In this study, we propose a quick strategy to retrieve potential 3D shapes, as low-resolution models, from a few 2D experimental images by searching a library of 2D projection images generated from existing 3D structures.

Results

We developed the protocol to assemble a non-redundant set of 3D shapes for generating the 2D image library, and to retrieve potential match 3D shapes for query images, using EM data as a test. In our strategy, we disregard differences in volume size, giving previously unknown structures and conformations a greater number of 3D biological shapes as possible matches. We tested the strategy using images from three EM models as query images for searches against a library of 22750 2D projection images generated from 250 random EM models. We found that our ability to identify 3D shapes that match the query images depends on how complex the outline of the 2D shapes are and whether they are represented in the search image library.

Conclusions

Through our computational method, we are able to quickly retrieve a 3D shape from a few 2D projection images. Our approach has the potential for exploring other types of 2D single particle structural data such as from XFEL scattering experiments, for providing a tool to interpret low-resolution data that may be insufficient for 3D reconstruction, and for estimating the mixing of states or conformations that could exist in such experimental data.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2358-0) contains supplementary material, which is available to authorized users.

Single particle tracking-based reaction progress kinetic analysis reveals a series of molecular mechanisms of cetuximab-induced EGFR processes in a single living cell

Cellular processes occur through the orchestration of multi-step molecular reactions. Reaction progress kinetic analysis (RPKA) can provide the mechanistic details to elucidate the multi-step molecular reactions. However, current tools have limited ability to simultaneously monitor dynamic variations in multiple complex states at the single molecule level to apply RPKA in living cells. In this research, a single particle tracking-based reaction progress kinetic analysis (sptRPKA) was developed to simultaneously determine the kinetics of multiple states of protein complexes in the membrane of a single living cell. The subpopulation ratios of different states were quantitatively (and statistically) reliably extracted from the diffusion coefficient distribution rapidly acquired by single particle tracking at constant and high density over a long period of time using super-resolution microscopy. Using sptRPKA, a series of molecular mechanisms of epidermal growth factor receptor (EGFR) cellular processing induced by cetuximab were investigated. By comprehensively measuring the rate constants and cooperativity of the molecular reactions involving four EGFR complex states, a previously unknown intermediate state was identified that represents the rate limiting step responsible for the selectivity of cetuximab-induced EGFR endocytosis to cancer cells.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

DOI:http://dx.doi.org/10.7554/eLife.16105.001

To understand the roles that proteins and other large molecules play inside cells, it is important to determine their structures. One of the techniques that researchers can use to do this is called cryo-electron microscopy (cryo-EM), which rapidly freezes molecules to fix them in position before imaging them in fine detail.

The cryo-EM images are like maps that show the approximate position of atoms. These images must then be processed in order to build a three-dimensional model of the protein that shows how its atoms are arranged relative to each other. One computational approach called Molecular Dynamics Flexible Fitting (MDFF) works by flexibly fitting possible atomic structures into cryo-EM maps. Although this approach works well with relatively undetailed (or ‘low resolution’) cryo-EM images, it struggles to handle the high-resolution cryo-EM maps now being generated.

Singharoy, Teo, McGreevy et al. have now developed two MDFF methods – called cascade MDFF and resolution exchange MDFF – that help to resolve atomic models of biological molecules from cryo-EM images. Each method can refine poorly guessed models into ones that are consistent with the high-resolution experimental images. The refinement is achieved by interpreting a range of images that starts with a ‘fuzzy’ image. The contrast of the image is then progressively improved until an image is produced that has a resolution that is good enough to almost distinguish individual atoms.

The method works because each cryo-EM image shows not just one, but a collection of atomic structures that the molecule can take on, with the fuzzier parts of the image representing the more flexible parts of the molecule. By taking into account this flexibility, the large-scale features of the protein structure can be determined first from the fuzzier images, and increasing the contrast of the images allows smaller-scale refinements to be made to the structure.

The MDFF tools have been designed to be easy to use and are available to researchers at low cost through cloud computing platforms. They can now be used to unravel the structure of many different proteins and protein complexes including those involved in photosynthesis, respiration and protein synthesis.

DOI:http://dx.doi.org/10.7554/eLife.16105.002

Local analysis of strains and rotations for macromolecular electron microscopy maps

Macromolecular complexes perform their physiological functions by local rearrangements of their constituents and biochemically interacting with their reaction partners. These rearrangements may involve local rotations and the induction of local strains causing different mechanical efforts and stretches at the different areas of the protein. The analysis of these local deformations may reveal important insight into the way proteins perform their tasks. In this paper we introduce a method to perform this kind of local analysis using Electron Microscopy volumes in a fully objective and automatic manner. For doing so, we exploit the continuous nature of the result of an elastic image registration using B-splines as its basis functions. We show that the results obtained by the new automatic method are consistent with previous observations on these macromolecules.

Continuous changes in structure mapped by manifold embedding of single-particle data in cryo-EM

Cryo-electron microscopy, when combined with single-particle reconstruction, is a powerful method for studying macromolecular structure. Recent developments in detector technology have pushed the resolution into a range comparable to that of X-ray crystallography. However, cryo-EM is able to separate and thus recover the structure of each of several discrete structures present in the sample. For the more general case involving continuous structural changes, a novel technique employing manifold embedding has been recently demonstrated. Potentially, the entire work-cycle of a molecular machine may be observed as it passes through a continuum of states, and its free-energy landscape may be mapped out. This technique will be outlined and discussed in the context of its application to a large single-particle dataset of yeast ribosomes.

2.9 Å Resolution Cryo-EM 3D Reconstruction of Close-Packed Virus Particles

Single-particle cryoelectron microscopy typically discards close-packed particle images as unusable data. Here, we report an image processing strategy and case study of obtaining near-atomic resolution 3D reconstructions from close-packed particles. Multiple independent de novo initial models were constructed to determine and cross-validate the particle parameters. The particles with consistent views were further refined including not only Euler angles and center positions but also defocus, astigmatism, beam tilt, and overall and anisotropic magnification. We demonstrated this strategy with a 2.9 Å resolution reconstruction of a 1.67 MDa virus-like particle of a circovirus, PCV2, recorded on 86 photographic films. The map resolution was further validated with a phase-randomization test and local resolution assessment, and the atomic model was validated with MolProbity and EMRinger. Close-packed virus particles were thus shown not only to be useful for high-resolution 3D reconstructions but also to allow data collection at significantly improved throughput for near-atomic resolution reconstructions.

Dynamic Viral Glycoprotein Machines: Approaches for Probing Transient States That Drive Membrane Fusion

The fusion glycoproteins that decorate the surface of enveloped viruses undergo dramatic conformational changes in the course of engaging with target cells through receptor interactions and during cell entry. These refolding events ultimately drive the fusion of viral and cellular membranes leading to delivery of the genetic cargo. While well-established methods for structure determination such as X-ray crystallography have provided detailed structures of fusion proteins in the pre- and post-fusion fusion states, to understand mechanistically how these fusion glycoproteins perform their structural calisthenics and drive membrane fusion requires new analytical approaches that enable dynamic intermediate states to be probed. Methods including structural mass spectrometry, small-angle X-ray scattering, and electron microscopy have begun to provide new insight into pathways of conformational change and fusion protein function. In combination, the approaches provide a significantly richer portrait of viral fusion glycoprotein structural variation and fusion activation as well as inhibition by neutralizing agents. Here recent studies that highlight the utility of these complementary approaches will be reviewed with a focus on the well-characterized influenza virus hemagglutinin fusion glycoprotein system.

A local-optimization refinement algorithm in single particle analysis for macromolecular complex with multiple rigid modules

Single particle analysis, which can be regarded as an average of signals from thousands or even millions of particle projections, is an efficient method to study the three-dimensional structures of biological macromolecules. An intrinsic assumption in single particle analysis is that all the analyzed particles must have identical composition and conformation. Thus specimen heterogeneity in either composition or conformation has raised great challenges for high-resolution analysis. For particles with multiple conformations, inaccurate alignments and orientation parameters will yield an averaged map with diminished resolution and smeared density. Besides extensive classification approaches, here based on the assumption that the macromolecular complex is made up of multiple rigid modules whose relative orientations and positions are in slight fluctuation around equilibriums, we propose a new method called as local optimization refinement to address this conformational heterogeneity for an improved resolution. The key idea is to optimize the orientation and shift parameters of each rigid module and then reconstruct their three-dimensional structures individually. Using simulated data of 80S/70S ribosomes with relative fluctuations between the large (60S/50S) and the small (40S/30S) subunits, we tested this algorithm and found that the resolutions of both subunits are significantly improved. Our method provides a proof-of-principle solution for high-resolution single particle analysis of macromolecular complexes with dynamic conformations.

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. This review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated.

Heat-passing framework for robust interpretation of data in networks

Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transforming this data into knowledge. We develop a new framework, called heat-passing, which exploits intrinsic similarity relationships within noisy and incomplete raw data, and constructs a meaningful map of the data. The proposed framework is able to rank, cluster, and visualize the data all at once. The novelty of this framework is derived from an analogy between the process of data interpretation and that of heat transfer, in which all data points contribute simultaneously and globally to reveal intrinsic similarities between regions of data, meaningful coordinates for embedding the data, and exemplar data points that lie at optimal positions for heat transfer. We demonstrate the effectiveness of the heat-passing framework for robustly partitioning the complex networks, analyzing the globin family of proteins and determining conformational states of macromolecules in the presence of high levels of noise. The results indicate that the methodology is able to reveal functionally consistent relationships in a robust fashion with no reference to prior knowledge. The heat-passing framework is very general and has the potential for applications to a broad range of research fields, for example, biological networks, social networks and semantic analysis of documents.

A tilt-pair based method for assigning the projection directions of randomly oriented single-particle molecules

In this article, we describe an improved method to assign the projection angle for averaged images using tilt-pair images for three-dimensional reconstructions from randomly oriented single-particle molecular images. Our study addressed the so-called 'initial volume problem' in the single-particle reconstruction, which involves estimation of projection angles of the particle images. The projected images of the particles in different tilt observations were mixed and averaged for the characteristic views. After the ranking of these group average images in terms of reliable tilt angle information, mutual tilt angles between images are assigned from the constituent tilt-pair information. Then, multiples of the conical tilt series are made and merged to construct a network graph of the particle images in terms of projection angles, which are optimized for the three-dimensional reconstruction. We developed the method with images of a synthetic object and applied it to a single-particle image data set of the purified deacetylase from archaea. With the introduction of low-angle tilt observations to minimize unfavorable imaging conditions due to tilting, the results demonstrated reasonable reconstruction models without imposing symmetry to the structure. This method also guides its users to discriminate particle images of different conformational state of the molecule.

Conformations of macromolecules and their complexes from heterogeneous datasets

We describe a new generation of algorithms capable of mapping the structure and conformations of macromolecules and their complexes from large ensembles of heterogeneous snapshots, and demonstrate the feasibility of determining both discrete and continuous macromolecular conformational spectra. These algorithms naturally incorporate conformational heterogeneity without resort to sorting and classification, or prior knowledge of the type of heterogeneity present. They are applicable to single-particle diffraction and image datasets produced by X-ray lasers and cryo-electron microscopy, respectively, and particularly suitable for systems not easily amenable to purification or crystallization.

Quantifying the local resolution of cryo-EM density maps

We propose a definition of local resolution for three-dimensional electron cryo-microscopy (cryo-EM) density maps that uses local sinusoidal features. Our algorithm has no free parameters and is applicable to other imaging modalities, including tomography. By evaluating the local resolution of single-particle reconstructions and subtomogram averages for four example data sets, we report variable resolution across a 4- to 40-Å range.

Structure, assembly and dynamics of macromolecular complexes by single particle cryo-electron microscopy

BACKGROUND

Proteins in their majority act rarely as single entities. Multisubunit macromolecular complexes are the actors in most of the cellular processes. These nanomachines are hold together by weak protein-protein interactions and undergo functionally important conformational changes. TFIID is such a multiprotein complex acting in eukaryotic transcription initiation. This complex is first to be recruited to the promoter of the genes and triggers the formation of the transcription preinitiation complex involving RNA polymerase II which leads to gene transcription. The exact role of TFIID in this process is not yet understood.

METHODS

Last generation electron microscopes, improved data collection and new image analysis tools made it possible to obtain structural information of biological molecules at atomic resolution. Cryo-electron microscopy of vitrified samples visualizes proteins in a fully hydrated, close to native state. Molecular images are recorded at liquid nitrogen temperature in low electron dose conditions to reduce radiation damage. Digital image analysis of these noisy images aims at improving the signal-to-noise ratio, at separating distinct molecular views and at reconstructing a three-dimensional model of the biological particle.

RESULTS

Using these methods we showed the early events of an activated transcription initiation process. We explored the interaction of the TFIID coactivator with the yeast Rap1 activator, the transcription factor TFIIA and the promoter DNA. We demonstrated that TFIID serves as an assembly platform for transient protein-protein interactions, which are essential for transcription initiation.

CONCLUSIONS

Recent developments in electron microscopy have provided new insights into the structural organization and the dynamic reorganization of large macromolecular complexes. Examples of near-atomic resolutions exist but the molecular flexibility of macromolecular complexes remains the limiting factor in most case. Electron microscopy has the potential to provide both structural and dynamic information of biological assemblies in order to understand the molecular mechanisms of their functions.

Bayesian analysis of individual electron microscopy images: towards structures of dynamic and heterogeneous biomolecular assemblies

We develop a method to extract structural information from electron microscopy (EM) images of dynamic and heterogeneous molecular assemblies. To overcome the challenge of disorder in the imaged structures, we analyze each image individually, avoiding information loss through clustering or averaging. The Bayesian inference of EM (BioEM) method uses a likelihood-based probabilistic measure to quantify the consistency between each EM image and given structural models. The likelihood function accounts for uncertainties in the molecular position and orientation, variations in the relative intensities and noise in the experimental images. The BioEM formalism is physically intuitive and mathematically simple. We show that for experimental GroEL images, BioEM correctly identifies structures according to the functional state. The top-ranked structure is the corresponding X-ray crystal structure, followed by an EM structure generated previously from a superset of the EM images used here. To analyze EM images of highly flexible molecules, we propose an ensemble refinement procedure, and validate it with synthetic EM maps of the ESCRT-I-II supercomplex. Both the size of the ensemble and its structural members are identified correctly. BioEM offers an alternative to 3D-reconstruction methods, extracting accurate population distributions for highly flexible structures and their assemblies. We discuss limitations of the method, and possible applications beyond ensemble refinement, including the cross-validation and unbiased post-assessment of model structures, and the structural characterization of systems where traditional approaches fail. Overall, our results suggest that the BioEM framework can be used to analyze EM images of both ordered and disordered molecular systems.

Single-particle cryo-EM of calcium release channels: structural validation

Few tools are available to determine the structure of large integral membrane proteins such as intracellular Ca(2+) release channels, RyRs and IP3Rs. Single particle cryo-EM can readily determine the structure of such channels to intermediate resolution, and can be used to quantitatively assess conformational variability. However, due to the, often low, image contrast of these cryospecimens, methods for validation are critical to insure the accuracy of such structures, and to put limits on their interpretability. The low-resolution structure of RyR has been well established for some time, but high-resolution has been slow to emerge. The structure of IP3R channel by cryo-EM had a number of false-starts, but improved validation methods have recently lead to a demonstrably accurate reconstruction.

One number does not fit all: mapping local variations in resolution in cryo-EM reconstructions

The resolution of density maps from single particle analysis is usually measured in terms of the highest spatial frequency to which consistent information has been obtained. This calculation represents an average over the entire reconstructed volume. In practice, however, substantial local variations in resolution may occur, either from intrinsic properties of the specimen or for technical reasons such as a non-isotropic distribution of viewing orientations. To address this issue, we propose the use of a space-frequency representation, the short-space Fourier transform, to assess the quality of a density map, voxel-by-voxel, i.e. by local resolution mapping. In this approach, the experimental volume is divided into small subvolumes and the resolution determined for each of them. It is illustrated in applications both to model data and to experimental density maps. Regions with lower-than-average resolution may be mobile components or ones with incomplete occupancy or result from multiple conformational states. To improve the interpretability of reconstructions, we propose an adaptive filtering approach that reconciles the resolution to which individual features are calculated with the results of the local resolution map.

Regulatory interplay between TFIID's conformational transitions and its modular interaction with core promoter DNA

Recent structural and biochemical studies of human TFIID have significantly increased our understanding of the mechanisms underlying the recruitment of TFIID to promoter DNA and its role in transcription initiation. Structural studies using cryo-EM revealed that modular interactions underlie TFIID’s ability to bind simultaneously multiple promoter motifs and to define a DNA state that will facilitate transcription initiation. Here we propose a general model of promoter binding by TFIID, where co-activators, activators, and histone modifications promote and/or stabilize a conformational state of TFIID that results in core promoter engagement. Within this high affinity conformation, we propose that TFIID’s extensive interaction with promoter DNA leads to topological changes in the DNA that facilitate the eventual loading of RNAP II. While more work is required to dissect the individual contributions of activators and repressors to TFIID’s DNA binding, the recent cryo-EM studies provide a physical framework to guide future structural, biophysical, and biochemical experiments.

Human TFIID binds to core promoter DNA in a reorganized structural state

A mechanistic description of metazoan transcription is essential for understanding the molecular processes that govern cellular decisions. To provide structural insights into the DNA recognition step of transcription initiation, we used single-particle electron microscopy (EM) to visualize human TFIID with promoter DNA. This analysis revealed that TFIID coexists in two predominant and distinct structural states that differ by a 100 Å translocation of TFIID's lobe A. The transition between these structural states is modulated by TFIIA, as the presence of TFIIA and promoter DNA facilitates the formation of a rearranged state of TFIID that enables promoter recognition and binding. DNA labeling and footprinting, together with cryo-EM studies, were used to map the locations of TATA, Initiator (Inr), motif ten element (MTE), and downstream core promoter element (DPE) promoter motifs within the TFIID-TFIIA-DNA structure. The existence of two structurally and functionally distinct forms of TFIID suggests that the different conformers may serve as specific targets for the action of regulatory factors.

Molecular basis of transcription initiation in Archaea

Compared with eukaryotes, the archaeal transcription initiation machinery-commonly known as the Pre-Initiation Complex-is relatively simple. The archaeal PIC consists of the TFIIB ortholog TFB, TBP, and an 11-subunit RNA polymerase (RNAP). The relatively small size of the entire archaeal PIC makes it amenable to structural analysis. Using purified RNAP, TFB, and TBP from the thermophile Pyrococcus furiosus, we assembled the biochemically active PIC at 65ºC. The intact archaeal PIC was isolated by implementing a cross-linking technique followed by size-exclusion chromatography, and the structure of this 440 kDa assembly was determined using electron microscopy and single-particle reconstruction techniques. Combining difference maps with crystal structure docking of various sub-domains, TBP and TFB were localized within the macromolecular PIC. TBP/TFB assemble near the large RpoB subunit and the RpoD/L "foot" domain behind the RNAP central cleft. This location mimics that of yeast TBP and TFIIB in complex with yeast RNAP II. Collectively, these results define the structural organization of the archaeal transcription machinery and suggest a conserved core PIC architecture.

Capturing RNA-dependent pathways for cryo-EM analysis

Cryo-Electron Microscopy (EM) is a powerful technique to visualize biological processes at nanometer resolution. Structural studies of macromolecular assemblies are typically performed on individual complexes that are biochemically isolated from their cellular context. Here we present a molecular imaging platform to capture and view multiple components of cellular pathways within a functionally relevant framework. We utilized the bacterial protein synthesis machinery as a model system to develop our approach. By using modified Affinity Grid surfaces, we were able to recruit multiple protein assemblies bound to nascent strands of mRNA. The combined use of Affinity Capture technology and single particle electron microscopy provide the basis for visualizing RNA-dependent pathways in a remarkable new way.

A helical processing pipeline for EM structure determination of membrane proteins

Electron crystallography plays a key role in the structural biology of integral membrane proteins (IMPs) by offering one of the most direct means of providing insight into the functional state of these molecular machines in their lipid-associated forms, and also has the potential to facilitate examination of physiologically relevant transitional states and complexes. Helical or tubular crystals, which are the natural product of proteins crystallizing on the surface of a cylindrical vesicle, offer some unique advantages, such as three-dimensional (3D) information from a single view, compared to other crystalline forms. While a number of software packages are available for processing images of helical crystals to produce 3D electron density maps, widespread exploitation of helical image reconstruction is limited by a lack of standardized approaches and the initial effort and specialized expertise required. Our goal is to develop an integrated pipeline to enable structure determination by transmission electron microscopy (TEM) of IMPs in the form of tubular crystals. We describe here the integration of standard Fourier-Bessel helical analysis techniques into Appion, an integrated, database-driven pipeline.

Bayesian algorithms for recovering structure from single-particle diffraction snapshots of unknown orientation: a comparison

The advent of X-ray free-electron lasers promises the possibility to determine the structure of individual particles such as microcrystallites, viruses and biomolecules from single-shot diffraction snapshots obtained before the particle is destroyed by the intense femtosecond pulse. This program requires the ability to determine the orientation of the particle giving rise to each snapshot at signal levels as low as ~10(-2) photons per pixel. Two apparently different approaches have recently demonstrated this capability. Here we show they represent different implementations of the same fundamental approach, and identify the primary factors limiting their performance.

Structural insights into the architecture and allostery of full-length AMP-activated protein kinase

AMP-activated protein kinase (AMPK) is a heterotrimeric complex composed of α catalytic subunit, β scaffolding subunit, and γ regulatory subunit with critical roles in maintaining cellular energy homeostasis. However, the molecular architecture of the intact complex and the allostery associated with the adenosine binding-induced regulation of kinase activity remain unclear. Here, we determine the three-dimensional reconstruction and subunit organization of the full-length rat AMPK (α1β1γ1) through single-particle electron-microscopy. By comparing the structures of AMPK in ATP- and AMP-bound states, we are able to visualize the sequential conformational changes underlying kinase activation that transmits from the adenosine binding sites in the γ subunit to the kinase domain of the α subunit. These results not only make substantial revision to the current model of AMPK assembly, but also highlight a central role of the linker sequence of the α subunit in mediating the allostery of AMPK.

Three-dimensional reconstruction of Trypanosoma brucei editosomes using single-particle electron microscopy

RNA editing within the mitochondria of kinetoplastid protozoa is performed by a multicomponent -macromolecular machine known as the editosome. Editosomes are high molecular mass protein assemblies that consist of about 15-25 individual polypeptides. They bind pre-edited transcripts and convert them into translation-competent mRNAs through a biochemical reaction cycle of enzyme-catalyzed steps. At steady-state conditions, several distinct complexes can be purified from mitochondrial detergent lysates. They likely represent RNA editing complexes at different assembly stages or at different functional stages of the processing reaction. Due to their low cellular abundance, single-particle electron microscopy (EM) represents the method of choice for their structural characterization. This chapter describes a set of techniques suitable for the purification and structural characterization of RNA editing complexes by single-particle EM. The RNA editing complexes are isolated from the endogenous pool of mitochondrial complexes by tandem-affinity purification (TAP). Since the TAP procedure results in the isolation of a mixture of different RNA editing complexes, the isolates are further subjected to an isokinetic ultracentrifugation step to separate the complexes based on their sedimentation behavior. The use of the "GraFix" protocol is presented that combines mild chemical cross-linking with ultracentrifugation. Different sample preparation protocols including negative staining, cryo-negative staining, and unstained cryotechniques as well as the single-particle image processing of electron microscopical images are described.

Accurate modeling of single-particle cryo-EM images quantitates the benefits expected from using Zernike phase contrast

The use of a Zernike-type phase plate in biologic cryo-electron microscopy allows the imaging, without using defocus, of what are predominantly phase objects. It is thought that such phase-plate implementations might result in higher quality images, free from the problems of CTF correction that occur when images must be recorded at extremely high values of defocus. In single-particle cryo-electron microscopy it is hoped that these improvements in image quality will facilitate work on structures that have proved difficult to study, either because of their relatively small size or because the structures are not completely homogeneous. There is still a need, however, to quantitate how much improvement can be gained by using a phase plate for single-particle cryo-electron microscopy. We present a method for quantitatively modeling the images recorded with 200keV electrons, for single particles embedded in vitreous ice. We then investigate what difference the use of a phase-plate device could have on the processing of single-particle data. We confirm that using a phase plate results in single-particle datasets in which smaller molecules can be detected, particles can be more accurately aligned and problems of heterogeneity can be more easily addressed.

An approach for de novo structure determination of dynamic molecular assemblies by electron cryomicroscopy

Single-particle electron cryomicroscopy is a powerful method for three-dimensional (3D) structure determination of macromolecular assemblies. Here we address the challenge of determining a 3D structure in the absence of reference models. The 3D structures are determined by alignment and weighted averaging of densities obtained by native cryo random conical tilt (RCT) reconstructions including consideration of missing data. Our weighted averaging scheme (wRCT) offers advantages for potentially heterogeneous 3D densities of low signal-to-noise ratios. Sets of aligned RCT structures can also be analyzed by multivariate statistical analysis (MSA) to provide insights into snapshots of the assemblies. The approach is used to compute 3D structures of the Escherichia coli 70S ribosome and the human U4/U6.U5 tri-snRNP under vitrified unstained cryo conditions, and to visualize by 3D MSA the L7/L12 stalk of the 70S ribosome and states of tri-snRNP. The approach thus combines de novo 3D structure determination with an analysis of compositional and conformational heterogeneity.

Structure and function of eukaryotic fatty acid synthases

In all organisms, fatty acid synthesis is achieved in variations of a common cyclic reaction pathway by stepwise, iterative elongation of precursors with two-carbon extender units. In bacteria, all individual reaction steps are carried out by monofunctional dissociated enzymes, whereas in eukaryotes the fatty acid synthases (FASs) have evolved into large multifunctional enzymes that integrate the whole process of fatty acid synthesis. During the last few years, important advances in understanding the structural and functional organization of eukaryotic FASs have been made through a combination of biochemical, electron microscopic and X-ray crystallographic approaches. They have revealed the strikingly different architectures of the two distinct types of eukaryotic FASs, the fungal and the animal enzyme system. Fungal FAS is a 2·6 MDa α₆β₆ heterododecamer with a barrel shape enclosing two large chambers, each containing three sets of active sites separated by a central wheel-like structure. It represents a highly specialized micro-compartment strictly optimized for the production of saturated fatty acids. In contrast, the animal FAS is a 540 kDa X-shaped homodimer with two lateral reaction clefts characterized by a modular domain architecture and large extent of conformational flexibility that appears to contribute to catalytic efficiency.

Automated multi-model reconstruction from single-particle electron microscopy data

Biological macromolecules can adopt multiple conformational and compositional states due to structural flexibility and alternative subunit assemblies. This structural heterogeneity poses a major challenge in the study of macromolecular structure using single-particle electron microscopy. We propose a fully automated, unsupervised method for the three-dimensional reconstruction of multiple structural models from heterogeneous data. As a starting reference, our method employs an initial structure that does not account for any heterogeneity. Then, a multi-stage clustering is used to create multiple models representative of the heterogeneity within the sample. The multi-stage clustering combines an existing approach based on Multivariate Statistical Analysis to perform clustering within individual Euler angles, and a newly developed approach to sort out class averages from individual Euler angles into homogeneous groups. Structural models are computed from individual clusters. The whole data classification is further refined using an iterative multi-model projection-matching approach. We tested our method on one synthetic and three distinct experimental datasets. The tests include the cases where a macromolecular complex exhibits structural flexibility and cases where a molecule is found in ligand-bound and unbound states. We propose the use of our approach as an efficient way to reconstruct distinct multiple models from heterogeneous data.

3-D structures of macromolecules using single-particle analysis in EMAN

Single-particle reconstruction is a methodology whereby transmission electron microscopy (TEM) is used to record images of individual monodisperse molecules or macromolecular assemblies, then sets of images of individual particles are computationally combined to produce a 3-D volumetric reconstruction. Ideally the TEM specimen will be prepared in vitreous ice (electron cryomicroscopy), but negative stain preparations may be used for lower resolution work. This technique has been demonstrated to produce structures at resolutions as high as ∼ 4 A, though this is not yet typical. The reconstruction process is quite computationally intensive, and several software packages are available for this task. EMAN is one of the easier to master software suites for single-particle analysis. This protocol explains how to perform an initial low-resolution reconstruction using EMAN.

The advent of near-atomic resolution in single-particle electron microscopy

Single-particle electron microscopy (EM) can provide structural information for a large variety of biological molecules, ranging from small proteins to large macromolecular assemblies, without the need to produce crystals. The year 2008 has become a landmark year for single-particle EM as for the first time density maps have been produced at a resolution that made it possible to trace protein backbones or even to build atomic models. In this review, we highlight some of the recent successes achieved by single-particle EM and describe the individual steps involved in producing a density map by this technique. We also discuss some of the remaining challenges and areas, in which further advances would have a great impact on the results that can be achieved by single-particle EM.