Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead

Electron cryomicroscopy (cryo-EM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize molecules such as ribosomes, viruses, and ion channels, for example. Obtaining structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryo-EM a scientific rebirth. Because of imaging improvements, image processing and analysis of the resultant images have increased the resolution such that molecular structures can be resolved at the atomic level. Cryo-EM is ripe with stimulating image processing challenges. In this article, we will touch on the most essential in order to build an accurate structural three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. With this review, however, we will highlight fresh approaches from new and varied angles for each image processing sub-problem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking. Keywords: Cryo-electron microscopy, Single Particle Analysis, Image processing algorithms

Flexible workflows for on-the-fly electronmicroscopy single-particle image processing using Scipion

Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Å resolution β-galactosidase data setThe authors would like to acknowledge financial support from The Spanish Ministry of Economy and Competitiveness through the BIO2016-76400-R (AEI/FEDER, UE) grant, the Comunidad Auto´noma de Madrid through grant S2017/BMD3817, the Instituto de Salud Carlos III (PT17/0009/0010), the European Union (EU) and Horizon 2020 through the CORBEL grant (INFRADEV-1-2014-1, Proposal 654248), the ‘la Caixa’ Foundation (ID 100010434, Fellow LCF/BQ/ IN18/11660021), Elixir–EXCELERATE (INFRADEV-3- 2015, Proposal 676559), iNEXT (INFRAIA-1-2014-2015, Proposal 653706), EOSCpilot (INFRADEV-04-2016, Proposal 739563) and INSTRUCT–ULTRA (INFRADEV03-2016-2017, Proposal 731005

Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy

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 reviewedThe authors would like to acknowledge support from the Spanish Ministry of Economy and Competitiveness through grants BIO2013-44647-R and BIO2016-76400-R (AEI/ FEDER, UE), Comunidad Autonoma de Madrid through grant S2017/BMD-3817, Instituto de Salud Carlos III through grants PT13 /0001/0009 and PT17/0009/0010,the European Union (EU) and Horizon 2020 through West-Life (EINFRA- 2015-1, Proposal 675858), CORBEL (INFRADEV-1-2014-1, Proposal 654248), ELIXIR–EXCELERATE (INFRADEV-3- 2015, Proposal 676559), iNEXT (INFRAIA-1-2014-2015, Proposal 653706), EOSCpilot (INFRADEV-04-2016, Proposal 739563) and the National Institutes of Health (P41 GM 103712) (IB

Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead.

Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.Spanish Ministry of Economy and Competitiveness (BIO2013-44647-R, BIO2016-76400-R)Comunidad Autonoma de Madrid (S2017/BMD-3817)Instituto de Salud Carlos III, (PT13/0001/ 0009, PT17/0009/0010)European Union (EU) (EINFRA-2015-1)Peer reviewe

Validation of electron microscopy initial models via small angle X-ray scattering curves

[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.This work was supported by the Spanish Ministry of Economy and Competitiveness through Grants BIO2016-76400-R(AEI/FEDER, UE), Comunidad Autonoma de Madrid through Grant: S2017/BMD-3817, Instituto de Salud Carlos III, PT13/0001/0009, PT17/0009/0010 and European Union (EU) and Horizon 2020 through Grants: Elixir—EXCELERATE (INFRADEV-3-2015, Proposal: 676559), iNEXT (INFRAIA-1-2014-2015, Proposal: 653706) and INSTRUCT—ULTRA (INFRADEV-03-2016-2017, Proposal: 731005)

Flexible workflows for on-the-fly electron-microscopy single-particle image processing using Scipion

Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 angstrom resolution beta-galactosidase data set.Spanish Ministry of Economy and Competitiveness through the BIO2016-76400-R (AEI/FEDER, UE) grant, the Comunidad Auto ´noma de Madrid through grant S2017/BMD3817, the Instituto de Salud Carlos III (PT17/0009/0010), the European Union (EU) and Horizon 2020 through the CORBE

Using Scipion for stream image processing at Cryo-EM facilities

Three dimensional electron microscopy is becoming a very data-intensive field in which vast amounts of experimental images are acquired at high speed. To manage such large-scale projects, we had previously developed a modular workflow system called Scipion (de la Rosa-Trevín et al., 2016). We present here a major extension of Scipion that allows processing of EM images while the data is being acquired. This approach helps to detect problems at early stages, saves computing time and provides users with a detailed evaluation of the data quality before the acquisition is finished. At present, Scipion has been deployed and is in production mode in seven Cryo-EM facilities throughout the world.Spanish Ministry of Economy and Competitiveness through Grants BIO2016-76400R(AEI/FEDER, UE) and AEI/FEDER BFU 2016 74868P, the Comunidad Autónoma de Madrid through Grant: S2017/BMD-3817, European Union (EU) and Horizon 2020 through grant Corbel (INFRADEV-1-2014-1, Proposal: 654248). The “Knut & Alice Wallenberg Foundation”, and “A Pilot Facility development grant from Science for Life Laboratory”. European Union (EU) and Horizon 2020 through grant EOSCpilot (INFRADEV-04-2016, Proposal: 739563).This work used the EGI Infrastructure and is co-funded by the EGIEngage project (Horizon 2020) under Grant No. 654142. European Union (EU) and Horizon 2020 through grant West-Life (EINFRA-2015-1, Proposal: 675858) European Union (EU) and Horizon 2020 through grant Elixir - EXCELERATE (INFRADEV-3-2015, Proposal: 676559) European Union (EU) and Horizon 2020 through grant iNEXT (INFRAIA-1-2014-2015, Proposal: 653706).Peer reviewe