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Unbend: Correction of local beam-induced sample motion in cryo-EM images using a 3D spline model

Kong, L.; Zottig, X.; Elferich, J.; Grigorieff, N.

2025-09-06 biophysics
10.1101/2025.09.05.674398 bioRxiv
Show abstract

The exposure of frozen biological samples to the high-energy electron beam in a cryo-electron microscope commonly leads to beam-induced sample motion and distortions. Previously, we described Unblur, which is part of our cisTEM software to correct for beam-induced motion based on the alignment of full frames in a movie collected during the beam exposure (Grant et al., 2015). However, Unblur cannot accommodate motion due to more localized sample bending and distortions. Here, we present Unbend, extending Unblur by incorporating local motion correction using a three-dimensional cubic spline model. The 3D spline model is constructed using cubic B-splines along the exposure time axis, and bicubic B-splines within movie frames. Unbend is integrated into our cisTEM software with a new local motion visualization panel within the cisTEM graphical user interface. We processed movie frames from various in-situ sample types, including whole cells, lamellae, and cell lysates, to analyze motion behavior across different specimen types. To quantify the improvement in high-resolution signal, we utilized the 2D template matching method, which operates independently of the motion correction process, to search large ribosomal subunits from the motion-corrected micrographs. Overall, the signal-to-noise ratio of detected particles improved by 3-8% across different samples compared with full-frame aligned micrographs, while the number of detected target particles increased by up to [~]300%. The total and Von Mises equivalent strain shows a deformation scale of less than 1% in most of the samples, confirming that our model induces minimal additional distortion. Furthermore, we processed micrograph montages to study motion patterns across an entire sample, revealing considerable variance in distortion scale within the same sample, suggesting a complex underlying mechanism.

Published in eLife (predicted rank #4) · training set

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