National Institutes of Health/National Heart, Lung, and Blood Institute (NIH/NHLBI)
R01-CA-221289
米国
引用
ジャーナル: Structure / 年: 2020 タイトル: High-Throughput Cryo-EM Enabled by User-Free Preprocessing Routines. 著者: Yilai Li / Jennifer N Cash / John J G Tesmer / Michael A Cianfrocco / 要旨: Single-particle cryoelectron microscopy (cryo-EM) continues to grow into a mainstream structural biology technique. Recent developments in data collection strategies alongside new sample preparation ...Single-particle cryoelectron microscopy (cryo-EM) continues to grow into a mainstream structural biology technique. Recent developments in data collection strategies alongside new sample preparation devices herald a future where users will collect multiple datasets per microscope session. To make cryo-EM data processing more automatic and user-friendly, we have developed an automatic pipeline for cryo-EM data preprocessing and assessment using a combination of deep-learning and image-analysis tools. We have verified the performance of this pipeline on a number of datasets and extended its scope to include sample screening by the user-free assessment of the qualities of a series of datasets under different conditions. We propose that our workflow provides a decision-free solution for cryo-EM, making data preprocessing more generalized and robust in the high-throughput era as well as more convenient for users from a range of backgrounds.