Multi-particle cryo-EM refinement with M visualizes ribosome-antibiotic complex at 3.5 Å in cells

Cryo-electron microscopy (cryo-EM) enables macromolecular structure determination in vitro and in situ. In addition to aligning individual particles, accurate registration of sample motion and 3D deformation during exposures is crucial for achieving high resolution. Here we describe M, a software tool that establishes a reference-based, multi-particle refinement framework for cryo-EM data and improves the results of structure determination. M provides a unified optimization framework for both in vitro frame series and in situ tomographic tilt series data. We show that tilt series data can provide the same resolution as frame series, indicating that the alignment step no longer limits the resolution obtainable from tomographic data. In combination with Warp and RELION, M improves upon previous methods, and resolves a 70S ribosome bound to an antibiotic inside bacterial cells at a nominal resolution of 3.7 Å. Thus, computational tools are now available to resolve structures from tomographic in situ cryo-EM data at residue level.

[1]  J Frank,et al.  Reconstruction of glutamine synthetase using computer averaging. , 1978, Ultramicroscopy.

[2]  J. Nocedal Updating Quasi-Newton Matrices With Limited Storage , 1980 .

[3]  W. O. Saxton,et al.  The correlation averaging of a regularly arranged bacterial cell envelope protein , 1982, Journal of microscopy.

[4]  J. Dubochet,et al.  Electron microscopy of frozen water and aqueous solutions , 1982 .

[5]  W Hoppe,et al.  Three-dimensional reconstruction and averaging of 50 S ribosomal subunits of Escherichia coli from electron micrographs. , 1983, Journal of molecular biology.

[6]  W Hoppe,et al.  Three-dimensional reconstruction and averaging of 30 S ribosomal subunits of Escherichia coli from electron micrographs. , 1983, Journal of molecular biology.

[7]  J R Kremer,et al.  Computer visualization of three-dimensional image data using IMOD. , 1996, Journal of structural biology.

[8]  D. DeRosier Correction of high-resolution data for curvature of the Ewald sphere. , 2000, Ultramicroscopy.

[9]  R. Henderson,et al.  Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy. , 2003, Journal of molecular biology.

[10]  David N Mastronarde,et al.  Automated electron microscope tomography using robust prediction of specimen movements. , 2005, Journal of structural biology.

[11]  Sjors H.W. Scheres,et al.  RELION: Implementation of a Bayesian approach to cryo-EM structure determination , 2012, Journal of structural biology.

[12]  A. Cheng,et al.  Beam-induced motion of vitrified specimen on holey carbon film. , 2012, Journal of structural biology.

[13]  Yuxiang Chen,et al.  PyTom: a python-based toolbox for localization of macromolecules in cryo-electron tomograms and subtomogram analysis. , 2012, Journal of structural biology.

[14]  Shaoxia Chen,et al.  Prevention of overfitting in cryo-EM structure determination , 2012, Nature Methods.

[15]  Guillermo Sapiro,et al.  Protein secondary structure determination by constrained single-particle cryo-electron tomography. , 2012, Structure.

[16]  D. Agard,et al.  Electron counting and beam-induced motion correction enable near atomic resolution single particle cryoEM , 2013, Nature Methods.

[17]  A. Steven,et al.  One number does not fit all: mapping local variations in resolution in cryo-EM reconstructions. , 2013, Journal of structural biology.

[18]  Nikolaus Grigorieff,et al.  Measuring the optimal exposure for single particle cryo-EM using a 2.6 Å reconstruction of rotavirus VP6 , 2015, eLife.

[19]  N. Grigorieff,et al.  Automatic estimation and correction of anisotropic magnification distortion in electron microscopes. , 2015, Journal of structural biology.

[20]  S. Scheres,et al.  Advances in Single-Particle Electron Cryomicroscopy Structure Determination applied to Sub-tomogram Averaging , 2015, Structure.

[21]  A. Hyman,et al.  Visualizing the molecular sociology at the HeLa cell nuclear periphery , 2016, Science.

[22]  S H W Scheres,et al.  Processing of Structurally Heterogeneous Cryo-EM Data in RELION. , 2016, Methods in enzymology.

[23]  J. Briggs,et al.  An atomic model of HIV-1 capsid-SP1 reveals structures regulating assembly and maturation , 2016, Science.

[24]  S J Ludtke,et al.  Single-Particle Refinement and Variability Analysis in EMAN2.1. , 2016, Methods in enzymology.

[25]  F. Förster,et al.  Subtomogram analysis using the Volta phase plate. , 2017, Journal of structural biology.

[26]  D. Agard,et al.  MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy , 2017, Nature Methods.

[27]  Beata Turoňová,et al.  Efficient 3D-CTF correction for cryo-electron tomography using NovaCTF improves subtomogram averaging resolution to 3.4 Å , 2017, Journal of structural biology.

[28]  J. Briggs,et al.  Implementation of a cryo-electron tomography tilt-scheme optimized for high resolution subtomogram averaging , 2017, Journal of structural biology.

[29]  D. Tegunov,et al.  Structures of transcription pre-initiation complex with TFIIH and Mediator , 2017, Nature.

[30]  Benjamin A Himes,et al.  emClarity: Software for High Resolution Cryo-electron Tomography and Sub-tomogram Averaging , 2018, Nature Methods.

[31]  Jaakko Lehtinen,et al.  Noise2Noise: Learning Image Restoration without Clean Data , 2018, ICML.

[32]  Erik Lindahl,et al.  New tools for automated high-resolution cryo-EM structure determination in RELION-3 , 2018, eLife.

[33]  Alexis Rohou,et al.  cisTEM: User-friendly software for single-particle image processing , 2018 .

[34]  Alexis Rohou,et al.  cisTEM: User-friendly software for single-particle image processing , 2017, bioRxiv.

[35]  R. Henderson,et al.  Ewald sphere correction using a single side-band image processing algorithm , 2018, Ultramicroscopy.

[36]  L. Dijkhuizen,et al.  Structural and functional characterization of a family GH53 β-1,4-galactanase from Bacteroides thetaiotaomicron that facilitates degradation of prebiotic galactooligosaccharides. , 2019, Journal of structural biology.

[37]  David A Agard,et al.  Consideration of sample motion in cryo-tomography based on alignment residual interpolation. , 2019, Journal of structural biology.

[38]  Ron O. Dror,et al.  Structure of a Signaling Cannabinoid Receptor 1-G Protein Complex , 2019, Cell.

[39]  Muyuan Chen,et al.  A complete data processing workflow for CryoET and subtomogram averaging , 2019, Nature Methods.

[40]  Florian Jug,et al.  Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data , 2018, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

[41]  Kailash Ramlaul,et al.  Mitigating local over-fitting during single particle reconstruction with SIDESPLITTER , 2019, bioRxiv.

[42]  M. Kudryashev,et al.  Subtomogram averaging from cryo-electron tomograms. , 2019, Methods in cell biology.

[43]  Dmitry Lyumkis,et al.  Challenges and opportunities in cryo-EM single-particle analysis , 2019, The Journal of Biological Chemistry.

[44]  David J. Fleet,et al.  Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction , 2019, Nature Methods.

[45]  Radostin Danev,et al.  Cryo-Electron Microscopy Methodology: Current Aspects and Future Directions. , 2019, Trends in biochemical sciences.

[46]  K. Namba,et al.  CryoTEM with a Cold Field Emission Gun That Moves Structural Biology into a New Stage , 2019, Microscopy and Microanalysis.

[47]  Dimitry Tegunov,et al.  Real-time cryo–EM data pre-processing with Warp , 2019, Nature Methods.

[48]  Radostin Danev,et al.  Improved applicability and robustness of fast cryo-electron tomography data acquisition , 2019, Journal of structural biology.

[49]  Jasenko Zivanov,et al.  Estimation of high-order aberrations and anisotropic magnification from cryo-EM data sets in RELION-3.1 , 2019, bioRxiv.

[50]  D. Tegunov,et al.  In-cell architecture of an actively transcribing-translating expressome , 2020, Science.

[51]  Sjors H W Scheres,et al.  Estimation of high-order aberrations and anisotropic magnification from cryo-EM data sets in RELION-3.1 , 2020, IUCrJ.