Automated segmentation of molecular subunits in electron cryomicroscopy density maps.
Electron cryomicroscopy (cryoEM) is capable of imaging large macromolecular machines composed of multiple components. However, it is currently only possible to achieve moderate resolution at which it may be possible to computationally extract the individual components in the machine. In this work, we present application details of an automated method for detecting and segmenting the components of a large machine in an experimentally determined density map. This method is applicable to object with and without symmetry and takes advantage of global and local symmetry axes if present. We have applied this segmentation algorithm to several cryoEM data sets already deposited in EMDB with various complexities, symmetries and resolutions and validated the results using manually segmented density and available structures of the components in the PDB. As such, automated segmentation could become a useful tool for the analysis of the ever-increasing number of structures of macromolecular machines derived from cryoEM.
Baker
Matthew L
ML
National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA. mbaker@bcm.edu
Yu
Zeyun
Z
Chiu
Wah
W
Bajaj
Chandrajit
C
D017100:Bacteriophage P22 / Q000648:ultrastructure; D018834:Chaperonin 60 / Q000648:ultrastructure; D020285:Cryoelectron Microscopy / Q000379:methods*; D018360:Crystallography, X-Ray; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D012087:Reoviridae / Q000648:ultrastructure; D015203:Reproducibility of Results
D018834:Chaperonin 60