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Routine determination of ice thickness for cryo-EM grids.
Rice, William J; Cheng, Anchi; Noble, Alex J; Eng, Edward T; Kim, Laura Y; Carragher, Bridget; Potter, Clinton S.
Afiliação
  • Rice WJ; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States.
  • Cheng A; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States.
  • Noble AJ; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States.
  • Eng ET; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States.
  • Kim LY; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States.
  • Carragher B; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, United States.
  • Potter CS; National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, New York, United States; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, United States.
J Struct Biol ; 204(1): 38-44, 2018 10.
Article em En | MEDLINE | ID: mdl-29981485
Recent advances in instrumentation and automation have made cryo-EM a popular method for producing near-atomic resolution structures of a variety of proteins and complexes. Sample preparation is still a limiting factor in collecting high quality data. Thickness of the vitreous ice in which the particles are embedded is one of the many variables that need to be optimized for collection of the highest quality data. Here we present two methods, using either an energy filter or scattering outside the objective aperture, to measure ice thickness for potentially every image collected. Unlike geometrical or tomographic methods, these can be implemented directly in the single particle collection workflow without interrupting or significantly slowing down data collection. We describe the methods as implemented into the Leginon/Appion data collection workflow, along with some examples from test cases. Routine monitoring of ice thickness should prove helpful for optimizing sample preparation, data collection, and data processing.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microscopia Crioeletrônica Limite: Animals Idioma: En Revista: J Struct Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microscopia Crioeletrônica Limite: Animals Idioma: En Revista: J Struct Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos