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Cryogenic electron microscopy (cryo-EM) is an important tool for determining the molecular structure of proteins and protein assemblies, including helical assemblies such as amyloid fibrils. In reconstruction of amyloid fibril structures from cryo-EM images, an important early step is the selection of fibril locations. This fibril picking step is typically done by hand, a tedious process when thousands of images need to be analyzed. Here we present a computer program called FibrilFinder that identifies the locations and directions of fibril segments in cryo-EM images, by using the properties that the fibrils should be linear objects and have widths within a specified range. The program outputs the fibril locations in text files compatible with the RELION density reconstruction program. After RELION is used to extract the particle image boxes contained in the fibril segments identified by FibrilFinder, a second program called FibrilFixer removes boxes that contain more than one fibril, for instance because two fibrils cross each other. As concrete and realistic examples, we describe the application of the two programs to cryo-EM images of two different amyloid fibrils, namely 40-residue amyloid-β fibrils derived from human brain tissue by seeded growth and fibrils formed by the C-terminal half of the low-complexity domain of the RNA-binding protein FUS. Both examples of amyloid fibrils can be picked from cryo-EM images using the same set of FibrilFinder and FibrilFixer parameters, showing that this software does not require re-optimization for each sample. A set of 1337 cryo-EM images was analyzed in 17 min with one multi-core computer. The new fibril picking software should enable the rapid analysis and comparison of more helical structures using cryo-EM, and perhaps serve as part of the greater automation of the entire structure determination process.

More information Original publication

DOI

10.1016/j.jsb.2021.107736

Type

Journal article

Publication Date

2021-06-01T00:00:00+00:00

Volume

213

Keywords

Amyloid fibril, Automated particle picking, Electron microscopy, cryo-EM, Algorithms, Amyloid, Amyloid beta-Peptides, Cryoelectron Microscopy, Humans, Image Processing, Computer-Assisted, Peptide Fragments, RNA-Binding Protein FUS, Signal-To-Noise Ratio, Software, Time Factors