On geometric artifacts in cryo electron tomography

High-confidence 3D template matching for cryo-electron tomography

Visual proteomics attempts to build atlases of the molecular content of cells but the automated annotation of cryo electron tomograms remains challenging. Template matching (TM) and methods based on machine learning detect structural signatures of macromolecules. However, their applicability remains limited in terms of both the abundance and size of the molecular targets. Here we show that the performance of TM is greatly improved by using template-specific search parameter optimization and by including higher-resolution information. We establish a TM pipeline with systematically tuned parameters for the automated, objective and comprehensive identification of structures with confidence 10 to 100-fold above the noise level. We demonstrate high-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, fatty acid synthases, lipid membranes and microtubules, and individual subunits inside crowded eukaryotic cells. We provide software tools for the generic implementation of our method that is broadly applicable towards realizing visual proteomics.

Correlative montage parallel array cryo-tomography for in situ structural cell biology

Imaging large fields of view while preserving high-resolution structural information remains a challenge in low-dose cryo-electron tomography. Here we present robust tools for montage parallel array cryo-tomography (MPACT) tailored for vitrified specimens. The combination of correlative cryo-fluorescence microscopy, focused-ion-beam milling, substrate micropatterning, and MPACT supports studies that contextually define the three-dimensional architecture of cells. To further extend the flexibility of MPACT, tilt series may be processed in their entirety or as individual tiles suitable for sub-tomogram averaging, enabling efficient data processing and analysis.

Correlating cryo-super resolution radial fluctuations and dual-axis cryo-scanning transmission electron tomography to bridge the light-electron resolution gap

Visualization of organelles and their interactions with other features in the native cell remains a challenge in modern biology. We have introduced cryo-scanning transmission electron tomography (CSTET), which can access 3D volumes on the scale of 1 micron with a resolution of nanometers, making it ideal for this task. Here we introduce two relevant advances: (a) we demonstrate the utility of multi-color super-resolution radial fluctuation light microscopy under cryogenic conditions (cryo-SRRF), and (b) we extend the use of deconvolution processing for dual-axis CSTET data. We show that cryo-SRRF nanoscopy is able to reach resolutions in the range of 100 nm, using commonly available fluorophores and a conventional widefield microscope for cryo-correlative light-electron microscopy. Such resolution aids in precisely identifying regions of interest before tomographic acquisition and enhances precision in localizing features of interest within the 3D reconstruction. Dual-axis CSTET tilt series data and application of entropy regularized deconvolution during post-processing results in close-to-isotropic resolution in the reconstruction without averaging. The integration of cryo-SRRF with deconvolved dual-axis CSTET provides a versatile workflow for studying unique objects in a cell.

MDTOMO method for continuous conformational variability analysis in cryo electron subtomograms based on molecular dynamics simulations

Cryo electron tomography (cryo-ET) allows observing macromolecular complexes in their native environment. The common routine of subtomogram averaging (STA) allows obtaining the three-dimensional (3D) structure of abundant macromolecular complexes, and can be coupled with discrete classification to reveal conformational heterogeneity of the sample. However, the number of complexes extracted from cryo-ET data is usually small, which restricts the discrete-classification results to a small number of enough populated states and, thus, results in a largely incomplete conformational landscape. Alternative approaches are currently being investigated to explore the continuity of the conformational landscapes that in situ cryo-ET studies could provide. In this article, we present MDTOMO, a method for analyzing continuous conformational variability in cryo-ET subtomograms based on Molecular Dynamics (MD) simulations. MDTOMO allows obtaining an atomic-scale model of conformational variability and the corresponding free-energy landscape, from a given set of cryo-ET subtomograms. The article presents the performance of MDTOMO on a synthetic ABC exporter dataset and an in situ SARS-CoV-2 spike dataset. MDTOMO allows analyzing dynamic properties of molecular complexes to understand their biological functions, which could also be useful for structure-based drug discovery.

Sampling theory perspective on tomographic tilt increment schemes

Given a limited radiation exposure to be distributed over a discrete number of tilted projections in tomography, the optimal collection of information depends on the tilt increment scheme. Relying on principles of sampling theory, several tilt increment schemes can be compared and quantified. Following reasoning of Saxton, a revised scheme is offered in which the tilt angle increments Δθ_n are proportional to 1/cosθ_n. The revised scheme is preferable according to matrix analysis and simulations of geometrical optics. For thin specimens, applying a cosine sampling grid similar to Hoppe's scheme can improve the results. A realistic case is examined by Dr. Probe simulation of a scanning transmission electron microscope (STEM) for an atomic model adapted from the Ferritin protein molecule. Optimal reconstruction methods that are tested include the direct algebraic method, iterative reconstruction, and a new deconvolution-based weighted back-projection, which resembles the correction filter technique in signal recovery from sub-sampled data. A non-linear correction may be accounted for by iteration of the simulation with an ad-hoc atomic model.

Structural and Elastic Properties of Empty-Pore Metalattices Extracted via Nondestructive Coherent Extreme UV Scatterometry and Electron Tomography

Semiconductor metalattices consisting of a linked network of three-dimensional nanostructures with periodicities on a length scale <100 nm can enable tailored functional properties due to their complex nanostructuring. For example, by controlling both the porosity and pore size, thermal transport in these phononic metalattices can be tuned, making them promising candidates for efficient thermoelectrics or thermal rectifiers. Thus, the ability to characterize the porosity, and other physical properties, of metalattices is critical but challenging, due to their nanoscale structure and thickness. To date, only metalattices with high porosities, close to the close-packing fraction of hard spheres, have been studied experimentally. Here, we characterize the porosity, thickness, and elastic properties of a low-porosity, empty-pore silicon metalattice film (∼500 nm thickness) with periodic spherical pores (∼tens of nanometers), for the first time. We use laser-driven nanoscale surface acoustic waves probed by extreme ultraviolet scatterometry to nondestructively measure the acoustic dispersion in these thin silicon metalattice layers. By comparing the data to finite element models of the metalattice sample, we can extract Young's modulus and porosity. Moreover, by controlling the acoustic wave penetration depth, we can also determine the metalattice layer thickness and verify the substrate properties. Additionally, we utilize electron tomography images of the metalattice to verify the geometry and validate the porosity extracted from scatterometry. These advanced characterization techniques are critical for informed and iterative fabrication of energy-efficient devices based on nanostructured metamaterials.

Capturing actin assemblies in cells using in situ cryo-electron tomography

Actin contributes to an exceptionally wide range of cellular processes through the assembly and disassembly of highly dynamic and ordered structures. Visualizing these structures in cells can help us understand how the molecular players of the actin machinery work together to produce force-generating systems. In recent years, cryo-electron tomography (cryo-ET) has become the method of choice for structural analysis of the cell interior at the molecular scale. Here we review advances in cryo-ET workflows that have enabled this transformation, especially the automation of sample preparation procedures, data collection, and processing. We discuss new structural analyses of dynamic actin assemblies in cryo-preserved cells, which have provided mechanistic insights into actin assembly and function at the nanoscale. Finally, we highlight the latest visual proteomics studies of actin filaments and their interactors reaching sub-nanometer resolutions in cells.

Cryogenic electron microscopy approaches that combine images and tilt series

Cryogenic electron microscopy can be widely applied to biological specimens from the molecular to the cellular scale. In single-particle analysis, 3D structures may be obtained in high resolution by averaging 2D images of single particles in random orientations. For pleomorphic specimens, structures may be obtained by recording the tilt series of a single example of the specimen and calculating tomograms. Where many copies of a single structure such as a protein or nucleic acid assembly are present within the tomogram, averaging of the sub-volumes (subtomogram averaging) has been successfully applied. The choice of data collection method for any given specimen may depend on the structural question of interest and is determined by the radiation sensitivity of the specimen. Here, we survey some recent developments on the use of hybrid methods for recording and analysing data from radiation-sensitive biological specimens. These include single-particle reconstruction from 2D images where additional views are recorded at a single tilt angle of the specimen and methods where image tilt series, initially used for tomogram reconstruction, are processed as individual single-particle images. There is a continuum of approaches now available to maximize structural information obtained from the specimen.

Algorithmic robustness to preferred orientations in single particle analysis by CryoEM

The presence of preferred orientations in single particle analysis (SPA) by cryo-Electron Microscopy (cryoEM) is currently one of the hurdles preventing many structural analyses from yielding high-resolution structures. Although the existence of preferred orientations is mostly related to the grid preparation, in this technical note, we show that some image processing algorithms used for angular assignment and three-dimensional (3D) reconstruction are more robust than others to these detrimental conditions. We exemplify this argument with three different data sets in which the presence of preferred orientations hindered achieving a 3D reconstruction without artifacts or, even worse, a 3D reconstruction could never be achieved.

From 2D STXM to 3D Imaging: Soft X-ray Laminography of Thin Specimens

X-ray tomography has become an indispensable tool for studying complex 3D interior structures with high spatial resolution. Three-dimensional imaging using soft X-rays offers powerful contrast mechanisms but has seen limited success with tomography due to the restrictions imposed by the much lower energy of the probe beam. The generalized geometry of laminography, characterized by a tilted axis of rotation, provides nm-scale 3D resolution for the investigation of extended (mm range) but thin (μm to nm) samples that are well suited to soft X-ray studies. This work reports on the implementation of soft X-ray laminography (SoXL) at the scanning transmission X-ray spectromicroscope of the PolLux beamline at the Swiss Light Source, Paul Scherrer Institut, which enables 3D imaging of extended specimens from 270 to 1500 eV. Soft X-ray imaging provides contrast mechanisms for both chemical sensitivity to molecular bonds and oxidation states and magnetic dichroism due to the much stronger attenuation of X-rays in this energy range. The presented examples of applications range from functionalized nanomaterials to biological photonic crystals and sophisticated nanoscaled magnetic domain patterns, thus illustrating the wide fields of research that can benefit from SoXL.

Measurement of local resolution in electron tomography

Resolution (global and local) is one of the most reported metrics of quality measurement in Single Particle Analysis (SPA). However, in electron tomography, the situation is different and its computation is not straightforward. Typically, resolution estimation is global and, therefore, reduces the assessment of a whole tomogram to a single number. However, it is known that tomogram quality is spatially variant. Still, up to our knowledge, a method to estimate local quality metrics in tomography is lacking. This work introduces MonoTomo, a method developed to estimate locally in a tomogram the highest reliable frequency component, expressed as a form of local resolution. The fundamentals lie in a local analysis of the density map via monogenic signals, which, in analogy to MonoRes, allows for local estimations. Results with experimental data show that the local resolution range that MonoTomo casts agrees with reported resolution values for experimental data sets, with the advantage of providing a local estimation. A range of applications of MonoTomo are suggested for further exploration.

Toward high-resolution in situ structural biology with cryo-electron tomography and subtomogram averaging

Cryo-electron tomography (cryo-ET) provides unprecedented insights into the molecular constituents of biological environments. In combination with an image processing method called subtomogram averaging (STA), detailed 3D structures of biological molecules can be obtained in large, irregular macromolecular assemblies or in situ, without the need for purification. The contextual meta-information these methods also provide, such as a protein's location within its native environment, can then be combined with functional data. This allows the derivation of a detailed view on the physiological or pathological roles of proteins from the molecular to cellular level. Despite their tremendous potential in in situ structural biology, cryo-ET and STA have been restricted by methodological limitations, such as the low obtainable resolution. Exciting progress now allows one to reach unprecedented resolutions in situ, ranging in optimal cases beyond the nanometer barrier. Here, I review current frontiers and future challenges in routinely determining high-resolution structures in in situ environments using cryo-ET and STA.

Efficient 3D-CTF correction for cryo-electron tomography using NovaCTF improves subtomogram averaging resolution to 3.4Å

Cryo-electron tomography (cryo-ET) allows cellular ultrastructures and macromolecular complexes to be imaged in three-dimensions in their native environments. Cryo-electron tomograms are reconstructed from projection images taken at defined tilt-angles. In order to recover high-resolution information from cryo-electron tomograms, it is necessary to measure and correct for the contrast transfer function (CTF) of the microscope. Most commonly, this is performed using protocols that approximate the sample as a two-dimensional (2D) plane. This approximation accounts for differences in defocus and therefore CTF across the tilted sample. It does not account for differences in defocus of objects at different heights within the sample; instead, a 3D approach is required. Currently available approaches for 3D-CTF correction are computationally expensive and have not been widely implemented. Here we simulate the benefits of 3D-CTF correction for high-resolution subtomogram averaging, and present a user-friendly, computationally-efficient 3D-CTF correction tool, NovaCTF, that is compatible with standard tomogram reconstruction workflows in IMOD. We validate the approach on synthetic data and test it using subtomogram averaging of real data. Consistent with our simulations, we find that 3D-CTF correction allows high-resolution structures to be obtained with much smaller subtomogram averaging datasets than are required using 2D-CTF. We also show that using equivalent dataset sizes, 3D-CTF correction can be used to obtain higher-resolution structures. We present a 3.4 Å resolution structure determined by subtomogram averaging.

Cryo-Electron Tomography and Subtomogram Averaging

Cryo-electron tomography (cryo-ET) allows 3D volumes to be reconstructed from a set of 2D projection images of a tilted biological sample. It allows densities to be resolved in 3D that would otherwise overlap in 2D projection images. Cryo-ET can be applied to resolve structural features in complex native environments, such as within the cell. Analogous to single-particle reconstruction in cryo-electron microscopy, structures present in multiple copies within tomograms can be extracted, aligned, and averaged, thus increasing the signal-to-noise ratio and resolution. This reconstruction approach, termed subtomogram averaging, can be used to determine protein structures in situ. It can also be applied to facilitate more conventional 2D image analysis approaches. In this chapter, we provide an introduction to cryo-ET and subtomogram averaging. We describe the overall workflow, including tomographic data collection, preprocessing, tomogram reconstruction, subtomogram alignment and averaging, classification, and postprocessing. We consider theoretical issues and practical considerations for each step in the workflow, along with descriptions of recent methodological advances and remaining limitations.