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

Electron microscopy is a valuable tool for elucidating the three-dimensional structures of macromolecular complexes. As the field matures and the number of solved structures increases, the existence of infrastructures that keep this information organized and accessible is crucial. At the same time, standards and clearly described conventions facilitate software maintenance, benefit interoperability with other packages and allow data interchange. This work describes three developments promoting integrative biology, standardization and workflow processing, namely PeppeR, the EMX initiative and Scipion.

On the development of three new tools for organizing and sharing information in three-dimensional electron microscopy.

Image formation in bright field electron microscopy can be described with the help of the contrast transfer function (CTF). In this work the authors describe the "CTF Estimation Challenge", called by the Madrid Instruct Image Processing Center (I2PC) in collaboration with the National Center for Macromolecular Imaging (NCMI) at Houston. Correcting for the effects of the CTF requires accurate knowledge of the CTF parameters, but these have often been difficult to determine. In this challenge, researchers have had the opportunity to test their ability in estimating some of the key parameters of the electron microscope CTF on a large micrograph data set produced by well-known laboratories on a wide set of experimental conditions. This work presents the first analysis of the results of the CTF Estimation Challenge, including an assessment of the performance of the different software packages under different conditions, so as to identify those areas of research where further developments would be desirable in order to achieve high-resolution structural information. 

CTF Challenge: Result summary.

Three-dimensional electron microscopy (3DEM) of ice-embedded samples allows the structural analysis of large biological macromolecules close to their native state. Different techniques have been developed during the last forty years to process cryo-electron microscopy (cryo-EM) data. Not surprisingly, success in analysis and interpretation is highly correlated with the continuous development of image processing packages. The field has matured to the point where further progress in data and methods sharing depends on an agreement between the packages on how to describe common image processing tasks. Such standardization will facilitate the use of software as well as seamless collaboration, allowing the sharing of rich information between different platforms. Our aim here is to describe the Electron Microscopy eXchange (EMX) initiative, launched at the 2012 Instruct Image Processing Center Developer Workshop, with the intention of developing a first set of standard conventions for the interchange of information for single-particle analysis (EMX version 1.0). These conventions cover the specification of the metadata for micrograph and particle images, including contrast transfer function (CTF) parameters and particle orientations. EMX v1.0 has already been implemented in the Bsoft, EMAN, Xmipp and Scipion image processing packages. It has been and will be used in the CTF and EMDataBank Validation Challenges respectively. It is also being used in EMPIAR, the Electron Microscopy Pilot Image Archive, which stores raw image data related to the 3DEM reconstructions in EMDB. 

Article	Year
On the development of three new tools for organizing and sharing information in three-dimensional electron microscopy. Acta crystallographica. Section D, Biological crystallography\| PubMed ID: 23633578	2013
CTF Challenge: Result summary. Journal of structural biology\| PubMed ID: 25913484	2015
The Electron Microscopy eXchange (EMX) initiative. Journal of structural biology\| PubMed ID: 26873784	2016

R. Marabini

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