cryo-em-and-single-particle-analysis-with-scipion

Cryo-EM and Single-Particle Analysis with Scipion

Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at ...

Campus Universidad Autónoma de Madrid

The introduction of direct detection devices in cryo-EM has shown that specimens present beam-induced motion (BIM). Consequently, in this work, we develop a BIM correction method at the image level, resulting in an integrated image in which the in-plane BIM blurring is compensated prior to particle picking. The methodology is based on a robust Optical Flow (OF) approach that can efficiently correct for local movements in a rapid manner. The OF works particularly well if the BIM pattern presents a substantial degree of local movements, which occurs in our data sets for Falcon II data. However, for those cases in which the BIM pattern corresponds to global movements, we have found it advantageous to first run a global motion correction approach and to subsequently apply OF. Additionally, spatial analysis of the Optical Flow allows for quantitative analysis of the BIM pattern. The software that incorporates the new approach is available in XMIPP (http://xmipp.cnb.csic.es). 

Alignment of direct detection device micrographs using a robust Optical Flow approach.

Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although the computational cost of calculating a single PSSM profile is affordable, many statistical studies or machine learning-based methods used thousands of profiles to achieve their goals, thereby leading to a substantial increase of the computational cost. In this work we present a new database compiling PSSM profiles for the proteins of the PDB. Currently, the database contains 333,532 protein chain profiles involving 123,135 different PDB entries.

3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures.

Since the beginning of electron microscopy, resolution has been a critical parameter. In this article, we propose a fully automatic, accurate method for determining the local resolution of a 3D map (MonoRes). The foundation of this algorithm is an extension of the concept of analytic signal, termed monogenic signal. The map is filtered at different frequencies and the amplitude of the monogenic signal is calculated, after which a criterion is applied to determine the resolution at each voxel. MonoRes is fully automatic without compulsory user parameters, with great accuracy in all tests, and is computationally more rapid than existing methods in the field. In addition, MonoRes offers the option of local filtering of the original map based on the calculated local resolution.

MonoRes: Automatic and Accurate Estimation of Local Resolution for Electron Microscopy Maps.

We have used cryo Electron Tomography, proteomics and immunolabeling to study centrosomes isolated from the young lamb thymus, an efficient source of quiescent differentiated cells. We compared the proteome of thymocyte centrosomes to data published for KE37 cells, focusing on proteins associated with centriole disengagement and centrosome separation. The data obtained enhances our understanding of the protein system joining the centrioles, a system comprised of a branched network of fibers linked to an apparently amorphous density that was partially characterized here. A number of proteins were localized to the amorphous density by immunolabeling (C-NAP1, cohesin SMC1, condensin SMC4 and NCAPD2), yet not DNA. In conjuction, these data not only extend our understanding of centrosomes but they will help refine the model that focus on the protein system associated with the centriolar junction.

Cryo-Electron Tomography and Proteomics studies of centrosomes from differentiated quiescent thymocytes.

The introduction of local resolution has enormously helped the understanding of cryo-EM maps. Still, for any given pixel it is a global, aggregated value, that makes impossible the individual analysis of the contribution of the different projection directions. We introduce MonoDir, a fully automatic, parameter-free method that, starting only from the final cryo-EM map, decomposes local resolution into the different projection directions, providing a detailed level of analysis of the final map. Many applications of directional local resolution are possible, and we concentrate here on map quality and validation.

Measuring local-directional resolution and local anisotropy in cryo-EM maps.

The analysis of structure factors in 3D cryo-EM Coulomb potential maps and their "enhancement" at the end of the reconstruction process is a well-established practice, normally referred to as sharpening. The aim is to increase contrast and, in this way, to help tracing the atomic model. The most common way to accomplish this enhancement is by means of the so-called B-factor correction, which applies a global filter to boost high frequencies with some dampening considerations related to noise amplification. The results are maps with a better visual aspect and a quasiflat spectrum at medium and high frequencies. This practice is so widespread that most map depositions in the Electron Microscopy Data Base (EMDB) only contain sharpened maps. Here, the use in cryoEM of global B-factor corrections is theoretically and experimentally analyzed. Results clearly illustrate that protein spectra present a falloff. Thus, spectral quasi-flattening may produce protein spectra with distortions when compared with experimental ones, this fact, combined with the practice of reporting only sharpened maps, generates a sub-optimal situation in terms of data preservation, reuse and reproducibility. Now that the field is more advanced, we put forward two suggestions: (1) to use methods which keep more faithfully the original experimental signal properties of macromolecules when "enhancing" the map, and (2) to further stress the need to deposit the original experimental maps without any postprocessing or sharpening, not only the enhanced maps. In the absence of access to these original maps data is lost, preventing their future analysis with new methods.

Re-examining the spectra of macromolecules. Current practice of spectral quasi B-factor flattening.

In recent years, advances in cryoEM have dramatically increased the resolution of reconstructions and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the quality measure "FSC-Q", and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to detect overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.

FSC-Q: a CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation.

The presence of preferred orientations in single particle analysis (SPA) by cryo-Electron Microscopy (cryoEM) is currently one of the hurdles preventing many structural analyses from yielding high-resolution structures. Although the existence of preferred orientations is mostly related to the grid preparation, in this technical note, we show that some image processing algorithms used for angular assignment and three-dimensional (3D) reconstruction are more robust than others to these detrimental conditions. We exemplify this argument with three different data sets in which the presence of preferred orientations hindered achieving a 3D reconstruction without artifacts or, even worse, a 3D reconstruction could never be achieved.

Algorithmic robustness to preferred orientations in single particle analysis by CryoEM.

Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution. Despite the great development of the techniques involved to solve the biological structures with Cryo-EM in the last years, the reconstructed 3D maps can present lower resolution due to errors committed while processing the information acquired by the microscope. One of the main problems comes from the 3D alignment step, which is an error-prone part of the reconstruction workflow due to the very low signal-to-noise ratio (SNR) common in Cryo-EM imaging. In fact, as we will show in this work, it is not unusual to find a disagreement in the alignment parameters in approximately 20-40% of the processed images, when outputs of different alignment algorithms are compared. In this work, we present a novel method to align sets of single particle images in the 3D space, called DeepAlign. Our proposal is based on deep learning networks that have been successfully used in plenty of problems in image classification. Specifically, we propose to design several deep neural networks on a regionalized basis to classify the particle images in sub-regions and, then, make a refinement of the 3D alignment parameters only inside that sub-region. We show that this method results in accurately aligned images, improving the Fourier shell correlation (FSC) resolution obtained with other state-of-the-art methods while decreasing computational time.

J.M. Carazo

Centro Nacional de Biotecnología

Campus Universidad Autónoma de Madrid

Cryo-EM and Single-Particle Analysis with Scipion

J.M. Carazo

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Campus Universidad Autónoma de Madrid

Cryo-EM and Single-Particle Analysis with Scipion

Centro Nacional de Biotecnología