A two step approach for semi-automated particle selection from low contrast cryo-electron micrographs

Abstract Over recent years advances in cryo-electron microscopy for the study of macromolecular structure have resulted in resolutions in the range 10–15 A becoming routine. With this drive for increased resolution comes the need to collect larger datasets, commonly >10 000 particle images. Manual selection of particles from micrographs is often difficult and with such large numbers of particles now involved it is also laborious and a common bottleneck. Automated methods do exist but are normally restricted to specific samples or data, i.e., spherical particles, no aggregation, high contrast, and low noise. A two step approach has been developed that remains general and can be applied to low contrast, high noise micrographs of small molecules. Specifically, application of the approach is presented using micrographs of Escherichia coli RNA polymerase, which due to low contrast and the relatively small size of the molecule prove difficult to pick manually. To test the automated approach, independent reconstructions of RNA polymerase were carried out using manual and automatically picked data. The two reconstructions are shown to be comparable and the reconstruction from the automatically picked dataset is at a higher resolution, due to an increase in the number of particles picked.