Conformational heterogeneity and probability distributions from single-particle cryo-electron microscopy

• Published in: Current opinion in structural biology 2023-08, Vol.81, p.102626-102626, Article 102626
• Main Authors: Tang, Wai Shing, Zhong, Ellen D., Hanson, Sonya M., Thiede, Erik H., Cossio, Pilar
• Format: Article
• Language: English
• Subjects: Cryoelectron Microscopy - methods; Electrons; Molecular Conformation; Single Molecule Imaging
• ISSN: 0959-440X; 1879-033X
• DOI: 10.1016/j.sbi.2023.102626

Single-particle cryo-electron microscopy (cryo-EM) is a technique that takes projection images of biomolecules frozen at cryogenic temperatures. A major advantage of this technique is its ability to image single biomolecules in heterogeneous conformations. While this poses a challenge for data analysis, recent algorithmic advances have enabled the recovery of heterogeneous conformations from the noisy imaging data. Here, we review methods for the reconstruction and heterogeneity analysis of cryo-EM images, ranging from linear-transformation-based methods to nonlinear deep generative models. We overview the dimensionality-reduction techniques used in heterogeneous 3D reconstruction methods and specify what information each method can infer from the data. Then, we review the methods that use cryo-EM images to estimate probability distributions over conformations in reduced subspaces or predefined by atomistic simulations. We conclude with the ongoing challenges for the cryo-EM community. [Display omitted] •Cryo-EM captures images of biomolecules in heterogeneous conformations.•Dimensionality-reduction techniques can aid the discovery of conformational changes.•Machine learning algorithms have advanced conformational variability analysis.•Cryo-EM data can reveal the probability distribution of conformations.