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 2.2 Å resolution β-galactosidase data set.

Highlights

  • Electron microscopy (EM) has become an established technique to define the three-dimensional structure of biological macromolecules (Frank, 2017)

  • The stream processing described in the previous section used to be the only stream processing performed at the EM facility, and as such it can be regarded as a characterization and monitoring of the ‘functioning’ of the machine

  • We have presented the possibilities that Scipion offers to design on-the-fly image-processing workflows

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Summary

Introduction

Electron microscopy (EM) has become an established technique to define the three-dimensional structure of biological macromolecules (Frank, 2017). Added intelligence and flexibility relative to the third-generation workflows As such (1) the algorithm for a specific task is not ‘hardwired’ into a script but can be selected from a variety of options, (2) the imageprocessing pipeline can be tailored to the specific needs of a project or user, (3) several programs can be executed in parallel to perform the same task and a consensus output can be selected and (4) automatic decision algorithms participate in the workflow so that different actions are taken depending on the quality of the micrograph and its particles.

From movies to micrographs
From micrographs to particles
From particles to 2D classes
Resources and time consumption
Creating and launching stream workflows
Conclusions
Findings
Funding information
Full Text
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