Cryo-electron Microscopy Analysis of Structurally Heterogeneous Macromolecular Complexes

AbstractCryo-electron microscopy (cryo-EM) has for a long time been a technique of choice for determining structure of large and flexible macromolecular complexes that were difficult to study by other experimental techniques such as X-ray crystallography or nuclear magnetic resonance. However, a fast development of instruments and software for cryo-EM in the last decade has allowed that a large range of complexes can be studied by cryo-EM, and that their structures can be obtained at near-atomic resolution, including the structures of small complexes (e.g., membrane proteins) whose size was earlier an obstacle to cryo-EM. Image analysis to identify multiple coexisting structures in the same specimen (multiconformation reconstruction) is now routinely done both to solve structures at near-atomic resolution and to study conformational dynamics. Methods for multiconformation reconstruction and latest examples of their applications are the focus of this review

A methodology using Gaussian-based density map approximation to assess sets of cryo-electron microscopy density maps

International audienceThis article presents a methodology to assess a set of density maps, as used in the Blind Assessment Phase of the 2015/2016 Map Challenge (EMDataBank Validation Challenges). The synthetic and experimental cryo-electron microscopy (cryo-EM) density maps obtained by different single particle analysis protocols and by different participants, submitted in the Challenge Phase for assessment, were analyzed with this methodology and the obtained results are presented and discussed here. The goal of using such a methodology was to blindly identify the density maps with globally similar structural information, meaning the maps with the structural information mostly “reproduced” by different protocols. To this end, the density maps are “coarsened” using Gaussian-based approximations, with the same input approximation parameters for all maps of the target biological complex. The approximated maps are then represented in a common reduced-dimension (here, 3D) space of their correlation-coefficient-based distances, in which close maps mean similar maps. The distance analysis allows identifying maps with the most “reproduced” structural information by different protocols. The obtained results are also discussed taking into account the detailed information about the protocols that has been released after the end of the Blind Assessment Phase

MDTOMO method for continuous conformational variability analysis in cryo electron subtomograms based on molecular dynamics simulations

International audienceCryo electron tomography (cryo-ET) allows observing macromolecular complexes in their native environment. The common routine of subtomogram averaging (STA) allows obtaining the threedimensional (3D) structure of abundant macromolecular complexes, and can be coupled with discrete classification to reveal conformational heterogeneity of the sample. However, the number of complexes extracted from cryo-ET data is usually small, which restricts the discrete-classification results to a small number of enough populated states and, thus, results in a largely incomplete conformational landscape. Alternative approaches are currently being investigated to explore the continuity of the conformational landscapes that in situ cryo-ET studies could provide. In this article, we present MDTOMO, a method for analyzing continuous conformational variability in cryo-ET subtomograms based on Molecular Dynamics (MD) simulations. MDTOMO allows obtaining an atomic-scale model of conformational variability and the corresponding free-energy landscape, from a given set of cryo-ET subtomograms. The article presents the performance of MDTOMO on a synthetic ABC exporter dataset and an in situ SARS-CoV-2 spike dataset. MDTOMO allows analyzing dynamic properties of molecular complexes to understand their biological functions, which could also be useful for structure-based drug discovery

Coarse-Graining of Volumes for Modeling of Structure and Dynamics in Electron Microscopy: Algorithm to Automatically Control Accuracy of Approximation

International audienceCoarse-graining (or granularization) of structures from transmission electron microscopy (EM volumes) has been shown to be useful for a variety of structural analysis applications. Several methods perform coarse-graining of EM volumes using hard spheres or 3D Gaussian functions but they do not allow controlling automatically the volume approximation accuracy. To tackle this problem, we recently developed such a method. It is currently used by 3DEM Loupe web server and HEMNMA software to study macromolecular dynamics based on coarse-grained representations of EM volumes. In this paper, we give a detailed description of the implemented algorithm and fully analyze its performance, which was out of scope of our previous papers. The performance is analyzed in a controlled environment, in the context of studying structure and dynamics of macromolecular complexes. We show that this technique allows computing structures that are similar to atomic structures, by analyzing intermediate-resolution volumes. Additionally, we show that it allows sharpening of intermediate-resolution volumes. The full algorithm description allows its implementation in any other software package

Versatility of Approximating Single-Particle Electron Microscopy Density Maps Using Pseudoatoms and Approximation-Accuracy Control

Three-dimensional Gaussian functions have been shown useful in representing electron microscopy (EM) density maps for studying macromolecular structure and dynamics. Methods that require setting a desired number of Gaussian functions or a maximum number of iterations may result in suboptimal representations of the structure. An alternative is to set a desired error of approximation of the given EM map and then optimize the number of Gaussian functions to achieve this approximation error. In this article, we review different applications of such an approach that uses spherical Gaussian functions of fixed standard deviation, referred to as pseudoatoms. Some of these applications use EM-map normal mode analysis (NMA) with elastic network model (ENM) (applications such as predicting conformational changes of macromolecular complexes or exploring actual conformational changes by normal-mode-based analysis of experimental data) while some other do not use NMA (denoising of EM density maps). In applications based on NMA and ENM, the advantage of using pseudoatoms in EM-map coarse-grain models is that the ENM springs are easily assigned among neighboring grains thanks to their spherical shape and uniformed size. EM-map denoising based on the map coarse-graining was so far only shown using pseudoatoms as grains

Methods for studying the localization of mitochondrial complexes III and IV by immunofluorescent and immunogold microscopy

The localization of proteins within a cell is very important for studying protein colocalization and subsequently understanding protein-protein interactions at the subcellular level. Using mitochondrial protein localization as a model, we established methods to study the localization of electron transport chain complexes (ETCCs), specifically complexes III and IV, in brown adipose tissue (BAT) and mitochondria. Immunofluorescent and immunogold techniques were applied to BAT paraffin sections and thin Araldite sections of mitochondria-enriched fractions, respectively. Microscopic analysis clearly showed mitochondrial localization of complexes III and IV, as well their colocalization. In addition, 10 and 20 nm gold particles were capable of identifying the localization of complexes within mitochondrial cristae. The methods described in this study may be a beneficial addition to currently utilized methods for accurately identifying the localization of ETCCs, their colocalization with other proteins and their distribution inside the cell and cellular compartments. Lastly, this method can also be used to study the molecular architecture of BAT mitochondria by analyzing fixed and postfixed thin plastic sections with electron microscopy (EM). [Projekat Ministarstva nauke Republike Srbije, br. 173054 i br.173055

Hybrid Electron Microscopy Normal Mode Analysis graphical interface and protocol

International audienceThis article presents an integral graphical interface to the Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) approach that was developed for capturing continuous motions of large macromolecular complexes from single-particle EM images. HEMNMA was shown to be a good approach to analyze multiple conformations of a macromolecular complex but it could not be widely used in the EM field due to a lack of an integral interface. In particular, its use required switching among different software sources as well as selecting modes for image analysis was difficult without the graphical interface. The graphical interface was thus developed to simplify the practical use of HEMNMA. It is implemented in the open-source software package Xmipp 3.1 (http://xmipp.cnb.csic.es) and only a small part of it relies on MATLAB that is accessible through the main interface. Such integration provides the user with an easy way to perform the analysis of macromolecular dynamics and forms a direct connection to the single-particle reconstruction process. A step-by-step HEMNMA protocol with the graphical interface is given in full details in Supplementary material. The graphical interface will be useful to experimentalists who are interested in studies of continuous conformational changes of macromolecular complexes beyond the modeling of continuous heterogeneity in single particle reconstruction

StructMap: Elastic Distance Analysis of Electron Microscopy Maps for Studying Conformational Changes

International audienceSingle-particle electron microscopy (EM) has been shown to be very powerful for studying structures and associated conformational changes of macromolecular complexes. In the context of analyzing conformational changes of complexes, distinct EM density maps obtained by image analysis and three-dimensional (3D) reconstruction are usually analyzed in 3D for interpretation of structural differences. However, graphic visualization of these differences based on a quantitative analysis of elastic transformations (deformations) among density maps has not been done yet due to a lack of appropriate methods. Here, we present an approach that allows such visualization. This approach is based on statistical analysis of distances among elastically aligned pairs of EM maps (one map is deformed to fit the other map), and results in visualizing EM maps as points in a lower-dimensional distance space. The distances among points in the new space can be analyzed in terms of clusters or trajectories of points related to potential conformational changes. The results of the method are shown with synthetic and experimental EM maps at different resolutions