ABSTRACT
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 2.2â Å resolution ß-galactosidase data set.
Subject(s)
Image Processing, Computer-Assisted/methods , Microscopy, Electron/methods , Single Molecule Imaging/methods , Software , Automation , beta-Galactosidase/chemistryABSTRACT
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.
Subject(s)
Electrons , Image Processing, Computer-Assisted/statistics & numerical data , Imaging, Three-Dimensional/statistics & numerical data , Macromolecular Substances/ultrastructure , Microscopy, Electron/methods , Proteins/ultrastructure , Algorithms , Humans , Macromolecular Substances/chemistry , Microscopy, Electron/instrumentation , Molecular Conformation , Molecular Dynamics Simulation , Principal Component Analysis , Proteins/chemistry , ThermodynamicsABSTRACT
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.
