Cryo‐Electron Tomography for Structural Characterization of Macromolecular Complexes

Conical Fourier shell correlation applied to electron tomograms.

Cryogenic single-particle photoluminescence (PL) spectroscopy has been used with great success to directly observe the heterogeneous photophysical states present in a population of luminescent particles. Cryogenic electron tomography provides complementary nanometer scale structural information to PL spectroscopy, but the two techniques have not been correlated due to technical challenges. Here, we present a method for correlating single-particle information from these two powerful microscopy modalities. We simultaneously observe PL brightness, emission spectrum, and in-plane excitation dipole orientation of CdSSe/ZnS quantum dots suspended in vitreous ice. Stable and fluctuating emitters were observed, as well as a surprising splitting of the PL spectrum into two bands with an average energy separation of 80 meV. In some cases, the onset of the splitting corresponded to changes in the in-plane excitation dipole orientation. These dynamics were assigned to structures of individual quantum dots and the excitation dipoles were visualized in the context of structural features.

With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities.

Electron Tomography of Ice-Embedded Prokaryotic Cells

As cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) continue to advance, the ability to visualize cellular and organismal structures with unprecedented clarity is redefining the landscape of structural biology. Breakthroughs in imaging technology, sample preparation and image processing now enable the detailed elucidation of cellular architecture, macromolecular organization, and dynamic biological processes at sub-nanometer resolution. Recent methodological advances have propelled the field to new frontiers, facilitating the investigation of complex biological questions across scales-from macromolecular complexes to organism-wide structural insights. This review explores rapidly emerging trends, highlights key innovations that are pushing the boundaries of in situ structural biology, and addresses persistent challenges in expanding the applicability of cryo-EM and cryo-ET across diverse biological systems.

Air-water interface (AWI) interactions during cryo-electron microscopy (cryo-EM) sample preparation cause significant sample loss, hindering structural biology research. Organisms like nematodes and tardigrades produce Late Embryogenesis Abundant (LEA) proteins to withstand desiccation stress. Here we show that these LEA proteins, when used as additives during plunge freezing, effectively mitigate AWI damage to fragile multi-subunit molecular samples. The resulting high-resolution cryo-EM maps are comparable to or better than those obtained using existing AWI damage mitigation methods. Cryogenic electron tomography reveals that particles are localized at specific interfaces, suggesting LEA proteins form a barrier at the AWI. This interaction may explain the observed sample-dependent preferred orientation of particles. LEA proteins offer a simple, cost-effective, and adaptable approach for cryo-EM structural biologists to overcome AWI-related sample damage, potentially revitalizing challenging projects and advancing the field of structural biology.

Cryo-electron microscopy (cryo-EM) allows the imaging of intact macromolecular complexes in the context of whole cells. The biological samples for cryo-EM are kept in a near-native state by flash freezing, without the need for any additional sample preparation or fixation steps. Since transmission electron microscopy only generates 2D projections of the samples, the specimen has to be tilted in order to recover its 3D structural information. This is done by collecting images of the sample with various tilt angles in respect to the electron beam. The acquired tilt series can then be computationally back-projected. This technique is called electron cryotomography (ECT), and has been instrumental in unraveling the architecture of chemoreceptor arrays. Here we describe the method of visualizing in vivo bacterial chemoreceptor arrays in three main steps: immobilization of bacterial cells on EM grids by plunge-freezing; 2D image acquisition in tilt series; and 3D tomogram reconstruction.

Cellular processes are governed by macromolecular complexes inside the cell. Study of the native structures of macromolecular complexes has been extremely difficult due to lack of data. With recent breakthroughs in Cellular Electron Cryo-Tomography (CECT) 3D imaging technology, it is now possible for researchers to gain accesses to fully study and understand the macro-molecular structures single cells. However, systematic recovery of macromolecular structures from CECT is very difficult due to high degree of structural complexity and practical imaging limitations. Specifically, we proposed a deep learning-based image classification approach for large-scale systematic macromolecular structure separation from CECT data. However, our previous work was only a very initial step toward exploration of the full potential of deep learning-based macromolecule separation. In this paper, we focus on improving classification performance by proposing three newly designed individual CNN models: an extended version of (Deep Small Receptive Field) DSRF3D, donated as DSRF3D-v2, a 3D residual block-based neural network, named as RB3D, and a convolutional 3D (C3D)-based model, CB3D. We compare them with our previously developed model (DSRF3D) on 12 datasets with different SNRs and tilt angle ranges. The experiments show that our new models achieved significantly higher classification accuracies. The accuracies are not only higher than 0.9 on normal datasets, but also demonstrate potentials to operate on datasets with high levels of noises and missing wedge effects presented.

Advances in cryogenic electron microscopy (cryoEM) single particle analysis have revolutionized structural biology by facilitating the in vitro determination of atomic- and near-atomic-resolution structures for fully hydrated macromolecular complexes exhibiting compositional and conformational heterogeneity across a wide range of sizes. Cryogenic electron tomography (cryoET) and subtomogram averaging are rapidly progressing toward delivering similar insights for macromolecular complexes in situ, without requiring tags or harsh biochemical purification. Furthermore, cryoET enables the visualization of cellular and tissue phenotypes directly at molecular, nanometric resolution without chemical fixation or staining artifacts. This forward-looking review covers recent developments in cryoEM/ET and related technologies such as cryogenic focused ion beam milling scanning electron microscopy and correlative light microscopy, increasingly enhanced and supported by artificial intelligence algorithms. Their potential application to emerging concepts is discussed, primarily the prospect of complementing medical histopathology analysis. Machine learning solutions are poised to address current challenges posed by "big data" in cryoET of tissues, cells, and macromolecules, offering the promise of enabling novel, quantitative insights into disease processes, which may translate into the clinic and lead to improved diagnostics and targeted therapeutics.

Solving the structures of macromolecular complexes.

Single particle and molecular assembly analysis of polyribosomes by single- and double-tilt cryo electron tomography

Electron tomography is the most widely applicable method for obtaining three-dimensional information by electron microscopy. It is, in fact, the only method suitable for investigating pleomorphic structures, such as many supramolecular assemblies, organelles and cells. With the recent development of automated low-dose data-acquisition schemes, it is now possible to study molecules and cells embedded in vitreous ice. This opens up new horizons for investigating the functional organization of cellular components with minimal perturbation of the cellular context. In the present study we used automated electron tomography in conjunction with cryomicroscopy to reveal the internal organization and ultrastructure of mitochondria. The whole isolated cell organelles from Neurospora crassa were quick-frozen and examined in vitrified ice. Single-axis tilt series were recorded with a Philips CM 120 Biotwin under low-dose conditions; the estimated total exposure was 10,000 e−nm−2. The tilt increment was 1° and the tilt series ranged from −65° to +65°. In order to enhance the contrast of the rather thick samples zero-loss energy filtering was employed. The images were recorded with a Ik × Ik CCD camera. The experimental setup has been described by Koster et al2 Three-dimensional reconstructions were performed by weighted backprojection. Prior to the three-dimensional visualization of 3-D data sets a denoising technique based on nonlinear anisotropic diffusion was applied (Figs. 2, 3).

Dose tolerance at helium and nitrogen temperatures for whole cell electron tomography

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d23514e125">Biology is intrinsically multiscale, interactions of molecules such as proteins on the nanoscale drive microscale behavior across cells, between cells and even whole organisms. Techniques that can image at nanometer resolutions whilst also providing a field of view capable of taking in the microscale assist in understanding this complex interplay. Electron cryo-tomography is capable of studying biology in its native context with resolutions up to a few nanometers. In the technique, a three-dimensional volume is reconstructed from a tilt series of transmission electron microscopy (TEM) images of a biological sample frozen in vitreous (amorphous) ice. A ceiling on the resolution of the technique is the camera pixel size in the image plane of the electron microscope – higher magnifications will result in a smaller image pixel size but the number of pixels available of modern electron cameras (typically 16 million or so) will mean that there is always a trade-off between resolution and field of view. Recording a grid of overlapping images and stitching the images together to form a montage allows us to transcend the constraints of camera size. In cryo-TEM is that samples are typically beam sensitive and only permit a few tens of electrons per square Ångstrom before the sample is damaged and high-resolution information is lost. The standard TEM has circular condenser (probe-forming) apertures and thus round beams and rectangular cameras so there is typically a mismatch between the illuminated area and the camera. This makes montage imaging challenging as if the beam is expanded to fully illuminate the camera it will also illuminate regions outside the camera, damaging them and preventing future acquisition.

Cryo-electron tomography: The power of seeing the whole picture