Search

© 2021 by the authors. Artículo firmado por más de 10 autores. The project that gave rise to these results received the support of a fellowship from the “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/DI18/11660021. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713673. The work was supported by European Regional Development Fund-Project "CERIT Scientific Cloud" (No.CZ.02.1.01/0.0/0.0/16_013/0001802). The authors would like to acknowledge economic support from: The Spanish Ministry of Economy and Competitiveness through Grants PID2019-104757RB-I00 (AEI/FEDER, UE) and SEV 2017-0712, the “Comunidad Autónoma de Madrid” through Grant: S2017/BMD-3817. European Union (EU) and Horizon 2020 through grants: EOSC Life (Proposal: 824087), HighResCells (Proposal: 810057), IM-paCT (Proposal: 857203), EOSC-Synergy (Proposal: 857647) and iNEXT-Discovery (Proposal: 871037). Authors acknowledge the support and the use of resources of Instruct, a Landmark ESFRI project. J.V thanks economical support from the Spanish Ministry of Science and Innovation through the call 2019 Proyectos de I+D+i–RTI Tipo A (PID2019-108850RA-I00). We acknowledge the support of the French National Research Agency—ANR (ANR-11-BSV8-010-04, ANR-19-CE11-0008-01, and ANR-20-CE11-0020-03 to S.J.), the French National Center for Scientific Research and the Spanish National Research Council (CSIC2009FR0015 and PICS 2011 to S.J. and C.O.S.S.), and access to HPC resources of CINES and IDRIS granted by GENCI (2010-2016 project No. 072174, A0100710998, A0070710998, AP010712190, AD011012188 to S.J.)., Xmipp is an open-source software package consisting of multiple programs for processing data originating from electron microscopy and electron tomography, designed and managed by the Biocomputing Unit of the Spanish National Center for Biotechnology, although with contributions from many other developers over the world. During its 25 years of existence, Xmipp underwent multiple changes and updates. While there were many publications related to new programs and functionality added to Xmipp, there is no single publication on the Xmipp as a package since 2013. In this article, we give an overview of the changes and new work since 2013, describe technologies and techniques used during the development, and take a peek at the future of the package., Europea. Horizonte 2020, European Regional Development Fund-Project, Ministerio de Economía y Competitividad (MINECO)/FEDER, Ministerio de Ciencia e Innovación (MICINN), French National Research Agency (ANR), Comunidad de Madrid, Consejo Superior de Investigaciones Científicas (CSIC), Centre national de la recherche scientifique (CNRS), GENCI, Fundación La Caixa, Depto. de Óptica, Fac. de Ciencias Físicas, TRUE, pub

Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) method was introduced in 2014. HEMNMA computes normal modes of a reference model (an atomic structure or an electron microscopy map) of a molecular complex and uses this model and its normal modes to analyze single‐particle images of the complex to obtain information on its continuous conformational changes, by determining the full distribution of conformational variability from the images. An advantage of HEMNMA is a simultaneous determination of all parameters of each image (particle conformation, orientation, and shift) through their iterative optimization, which allows applications of HEMNMA even when the effects of conformational changes dominate those of orientational changes. HEMNMA was first implemented in Xmipp and was using MATLAB for statistical analysis of obtained conformational distributions and for fitting of underlying trajectories of conformational changes. A HEMNMA implementation independent of MATLAB is now available as part of a plugin of Scipion V2.0 (http://scipion.i2pc.es). This plugin, named ContinuousFlex, can be installed by following the instructions at https://pypi.org/project/scipion-em-continuousflex. In this article, we present this new HEMNMA software, which is user‐friendly, totally free, and open‐source.

[Motivation]: Cryo electron microscopy (EM) is currently one of the main tools to reveal the structural information of biological macromolecules. The re-construction of three-dimensional (3D) maps is typically carried out following an iterative process that requires an initial estimation of the 3D map to be refined in subsequent steps. Therefore, its determination is key in the quality of the final results, and there are cases in which it is still an open issue in single particle analysis (SPA). Small angle X-ray scattering (SAXS) is a well-known technique applied to structural biology. It is useful from small nanostructures up to macromolecular ensembles for its ability to obtain low resolution information of the biological sample measuring its X-ray scattering curve. These curves, together with further analysis, are able to yield information on the sizes, shapes and structures of the analyzed particles. [Results]: In this paper, we show how the low resolution structural information revealed by SAXS is very useful for the validation of EM initial 3D models in SPA, helping the following refinement process to obtain more accurate 3D structures. For this purpose, we approximate the initial map by pseudo-atoms and predict the SAXS curve expected for this pseudo-atomic structure. The match between the predicted and experimental SAXS curves is considered as a good sign of the correctness of the EM initial map.

Single-particle analysis by electron microscopy is a well established technique for analyzing the three-dimensional structures of biological macromolecules. Besides its ability to produce high-resolution structures, it also provides insights into the dynamic behavior of the structures by elucidating their conformational variability. Here, the different image-processing methods currently available to study continuous conformational changes are reviewed.