bims-lances Biomed News
on Landscapes from Cryo-EM and Simulations
Issue of 2024–08–18
two papers selected by
James M. Krieger, National Centre for Biotechnology
  1. DynaMight: estimating molecular motions with improved reconstruction from cryo-EM images.
  2. Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit.
  1. Nat Methods. 2024 Aug 09.
    DynaMight: estimating molecular motions with improved reconstruction from cryo-EM images.
    Johannes Schwab, Dari Kimanius, Alister Burt, Tom Dendooven, Sjors H W Scheres.
      How to deal with continuously flexing molecules is one of the biggest outstanding challenges in single-particle analysis of proteins from cryogenic-electron microscopy (cryo-EM) images. Here, we present DynaMight, a software tool that estimates a continuous space of conformations in a cryo-EM dataset by learning three-dimensional deformations of a Gaussian pseudo-atomic model of a consensus structure for every particle image. Inversion of the learned deformations is then used to obtain an improved reconstruction of the consensus structure. We illustrate the performance of DynaMight for several experimental cryo-EM datasets. We also show how error estimates on the deformations may be obtained by independently training two variational autoencoders on half sets of the cryo-EM data, and how regularization of the three-dimensional deformations through the use of atomic models may lead to important artifacts due to model bias. DynaMight is distributed as free, open-source software, as part of RELION-5.
    DOI:  https://doi.org/10.1038/s41592-024-02377-5
  2. SIAM J Imaging Sci. 2023 ;16(2): 886-910
    Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit.
    Tamir Bendory, Nicolas Boumal, William Leeb, Eitan Levin, Amit Singer.
      Single-particle cryo-electron microscopy (cryo-EM) has recently joined X-ray crystallography and NMR spectroscopy as a high-resolution structural method to resolve biological macromolecules. In a cryo-EM experiment, the microscope produces images called micrographs. Projections of the molecule of interest are embedded in the micrographs at unknown locations, and under unknown viewing directions. Standard imaging techniques first locate these projections (detection) and then reconstruct the 3-D structure from them. Unfortunately, high noise levels hinder detection. When reliable detection is rendered impossible, the standard techniques fail. This is a problem, especially for small molecules. In this paper, we pursue a radically different approach: we contend that the structure could, in principle, be reconstructed directly from the micrographs, without intermediate detection. The aim is to bring small molecules within reach for cryo-EM. To this end, we design an autocorrelation analysis technique that allows one to go directly from the micrographs to the sought structures. This involves only one pass over the micrographs, allowing online, streaming processing for large experiments. We show numerical results and discuss challenges that lay ahead to turn this proof-of-concept into a complementary approach to state-of-the-art algorithms.
    Keywords:  62F10; 94A12; autocorrelation analysis; cryo-electron microscopy; detection
    DOI:  https://doi.org/10.1137/22m1503828
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