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Current outcomes when optimizing ‘standard’ sample preparation for single‐particle cryo‐EM
Author(s) -
CARRAGHER B.,
CHENG Y.,
FROST A.,
GLAESER R.M.,
LANDER G.C.,
NOGALES E.,
WANG H.W.
Publication year - 2019
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12834
Subject(s) - homogeneous , computer science , nanotechnology , cryo electron microscopy , variety (cybernetics) , field (mathematics) , sample (material) , resolution (logic) , particle (ecology) , sample preparation , range (aeronautics) , current (fluid) , biochemical engineering , data science , materials science , physics , chemistry , artificial intelligence , statistical physics , biology , mathematics , engineering , chromatography , nuclear magnetic resonance , pure mathematics , composite material , thermodynamics , ecology
Summary Although high‐resolution single‐particle cryo‐electron microscopy (cryo‐EM) is now producing a rapid stream of breakthroughs in structural biology, it nevertheless remains the case that the preparation of suitable frozen‐hydrated samples on electron microscopy grids is often quite challenging. Purified samples that are intact and structurally homogeneous – while still in the test tube – may not necessarily survive the standard methods of making extremely thin, aqueous films on grids. As a result, it is often necessary to try a variety of experimental conditions before finally finding an approach that is optimal for the specimen at hand. Here, we summarize some of our collective experiences to date in optimizing sample preparation, in the hope that doing so will be useful to others, especially those new to the field. We also hope that an open discussion of these common challenges will encourage the development of more generally applicable methodology. Our collective experiences span a diverse range of biochemical samples and most of the commonly used variations in how grids are currently prepared. Unfortunately, none of the currently used optimization methods can be said, in advance, to be the one that ultimately will work when a project first begins. Nevertheless, there are some preferred first steps to explore when facing specific problems that can be more generally recommended, based on our experience and that of many others in the cryo‐EM field.