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Optimized cryo‐EM data‐acquisition workflow by sample‐thickness determination
Author(s) -
Rheinberger Jan,
Oostergetel Gert,
Resch Guenter P.,
Paulino Cristina
Publication year - 2021
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.374
H-Index - 138
ISSN - 2059-7983
DOI - 10.1107/s205979832100334x
Subject(s) - data acquisition , computer science , sample (material) , data set , workflow , software , bottleneck , resolution (logic) , data collection , cryo electron microscopy , microscope , data quality , computer data storage , identification (biology) , data mining , artificial intelligence , computer vision , computer hardware , optics , database , chemistry , mathematics , statistics , engineering , physics , embedded system , operations management , metric (unit) , biology , operating system , biochemistry , chromatography , programming language , botany
Sample thickness is a known key parameter in cryo‐electron microscopy (cryo‐EM) and can affect the amount of high‐resolution information retained in the image. Yet, common data‐acquisition approaches in single‐particle cryo‐EM do not take it into account. Here, it is demonstrated how the sample thickness can be determined before data acquisition, allowing the identification of optimal regions and the restriction of automated data collection to images with preserved high‐resolution details. This quality‐over‐quantity approach almost entirely eliminates the time‐ and storage‐consuming collection of suboptimal images, which are discarded after a recorded session or during early image processing due to a lack of high‐resolution information. It maximizes the data‐collection efficiency and lowers the electron‐microscopy time required per data set. This strategy is especially useful if the speed of data collection is restricted by the microscope hardware and software, or if microscope access time, data transfer, data storage and computational power are a bottleneck.