Automated particle picking for low-contrast macromolecules in cryo-electron microscopy

J Struct Biol. 2014 Apr;186(1):1-7. doi: 10.1016/j.jsb.2014.03.001. Epub 2014 Mar 6.

Abstract

Cryo-electron microscopy is an increasingly popular tool for studying the structure and dynamics of biological macromolecules at high resolution. A crucial step in automating single-particle reconstruction of a biological sample is the selection of particle images from a micrograph. We present a novel algorithm for selecting particle images in low-contrast conditions; it proves more effective than the human eye on close-to-focus micrographs, yielding improved or comparable resolution in reconstructions of two macromolecular complexes.

Keywords: Automation; Cryo-EM; High-resolution; Machine-learning; Particle selection.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence
  • Bacterial Proteins / ultrastructure
  • Cryoelectron Microscopy / methods*
  • Escherichia coli
  • Imaging, Three-Dimensional*
  • Ribosome Subunits, Large, Bacterial / ultrastructure
  • Ribosome Subunits, Small, Bacterial / ultrastructure
  • Software
  • Thermus thermophilus
  • Vacuolar Proton-Translocating ATPases / ultrastructure

Substances

  • Bacterial Proteins
  • Vacuolar Proton-Translocating ATPases