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Cryogenic electron microscopy

Cryogenic electron microscopy (cryo-EM) is a powerful imaging technique that uses a to visualize biological specimens at cryogenic temperatures, typically by rapidly freezing samples in vitreous to preserve their native hydrated state without the need for or . This method enables the determination of three-dimensional structures of macromolecules, such as proteins and viruses, at resolutions, often better than 3 Å, by collecting and computationally reconstructing multiple two-dimensional images of individual particles. Unlike traditional , cryo-EM minimizes and dehydration artifacts through low-dose imaging under cryogenic conditions, making it particularly suited for studying dynamic and heterogeneous biomolecular assemblies in near-native environments. Developed over decades, cryo-EM's foundational principles trace back to the 1970s and 1980s, with key advancements in sample vitrification by Jacques Dubochet and computational image processing by Joachim Frank, culminating in the 2017 Nobel Prize in Chemistry awarded to Dubochet, Frank, and Richard Henderson for enabling high-resolution structure determination of biomolecules. The technique involves several critical steps: sample preparation via plunge-freezing on electron microscopy grids to form thin films of amorphous ice, low-electron-dose imaging to capture projections from various angles, and single-particle analysis or tomography for 3D reconstruction using algorithms that align and average thousands to millions of particle images. Recent innovations, including direct electron detectors, automated data collection, and improved software for heterogeneity handling, have dramatically increased throughput and resolution, transforming cryo-EM into a mainstream tool in structural biology since the 2010s. Cryo-EM's applications extend beyond isolated proteins to complex cellular structures, membrane proteins in lipid environments, and time-resolved studies of conformational changes, providing insights into molecular mechanisms of diseases, , and cellular processes. For instance, it has elucidated structures of ion channels, ribosomes, and viral spikes, contributing to developments like design. As of 2025, the number of new structures determined annually by cryo-EM is set to exceed those from , underscoring its growing preeminence in the field. While challenges remain in uniformity and for very large complexes, ongoing hardware and algorithmic improvements continue to expand its resolution limits and accessibility, positioning cryo-EM as a complementary method to and NMR in the toolkit.

Fundamentals

Principles of Operation

Cryogenic electron microscopy (cryo-EM) relies on the interactions between a beam of high-energy electrons and the sample to generate structural information. When electrons pass through the specimen, they undergo elastic scattering, where the electron's direction changes without significant energy loss, primarily contributing to image formation by providing phase contrast from the projected electron potential of the sample. Inelastic scattering, involving energy transfer to the specimen (e.g., exciting atomic electrons or phonons), leads to signal loss and beam-induced damage but can be minimized through energy filtering or low-dose imaging strategies. In vitreous ice, the embedding medium for biological samples, contrast arises mainly from these weak scattering events due to the low atomic number elements present, resulting in inherently low amplitude contrast that necessitates advanced imaging techniques for visualization. To preserve the native hydrated state of biomolecules, samples are rapidly frozen to cryogenic temperatures, typically by in cooled to approximately -180°C, followed by storage and imaging at temperatures around -196°C. This ultra-fast cooling prevents the formation of damaging crystals, instead forming amorphous (vitreous) that maintains the sample's shell and three-dimensional structure close to its physiological state, avoiding artifacts common in room-temperature electron microscopy. The low temperatures also reduce molecular motion and slow secondary processes, enabling higher electron doses before structural degradation occurs. Imaging in cryo-EM predominantly uses contrast, as unstained biological specimens act as weak objects with minimal contrast. To enhance visibility, the objective lens is deliberately defocused (typically by 1-3 μm), introducing a shift that converts subtle variations into detectable differences in the . This defocus-based contrast is modeled by the contrast transfer function (CTF), which describes how spatial frequencies are modulated: \text{CTF}(k) = \sin[\chi(k)] where k is the spatial frequency, and \chi(k) = \pi \lambda k^2 \Delta z + \frac{\pi}{2} C_s \lambda^3 k^4 incorporates the defocus \Delta z, electron wavelength \lambda, and spherical aberration coefficient C_s. The oscillatory nature of the CTF leads to alternating regions of enhancement and suppression of different resolution bands, requiring computational correction for high-resolution reconstruction. The achievable resolution in cryo-EM is fundamentally limited by radiation damage, where inelastic scattering events break chemical bonds and denature the sample, restricting the total electron dose to about 20-50 electrons per square to avoid significant structural alterations. This dose constraint results in noisy images, with typically reaching 2-4 for well-behaved proteins under optimal conditions. To mitigate these limits and improve beam control, particularly for beam-sensitive materials, four-dimensional (4D-STEM) records both patterns and scan positions, enabling precise beam positioning, reduced dose per area, and enhanced signal-to-noise through ptychographic .

Instrumentation

Cryogenic electron microscopy (cryo-EM) relies on specialized designed to generate, focus, and detect high-energy while maintaining samples at cryogenic temperatures to preserve their native structure. The core hardware includes an source, accelerating column, electromagnetic lenses, systems, cryogenic sample holders, direct electron detectors, filters, aberration correctors, and phase plates, all optimized for low-dose of beam-sensitive biological specimens to achieve near-atomic . The source in modern cryo-EM systems typically employs a (FEG), which produces a high-brightness, coherent electron beam essential for high-resolution . Schottky-type FEGs, operating at elevated temperatures around 1,700–1,800 K, or cold FEGs (cFEGs) at with an energy spread as low as 0.3 , enhance signal-to-noise ratios by minimizing and chromatic effects. These sources have evolved from earlier thermionic emitters to provide the required for prolonged in cryo-EM. Electrons are accelerated to kV in most high-end cryo-EM instruments, such as the Titan Krios or CRYO ARM , striking a balance between through thicker vitrified samples and sufficient for generation. This voltage reduces multiple events compared to lower energies (e.g., 200 kV), enabling resolutions below 2 Å while minimizing sample damage. Electromagnetic lenses then focus the beam, with objective and condenser lenses designed for precise control of illumination and magnification under conditions. Vacuum systems in cryo-EM maintain pressures below 10^{-7} mbar to prevent by residual gas and of frozen-hydrated samples, with dedicated cryopumps and turbo-molecular pumps adapted for cryogenic operation to avoid ice buildup. Specialized cryo-transfer holders, such as Gatan's Model 626 or Elsa series, facilitate sample insertion and positioning, cooling grids to approximately -196°C using while allowing tilt ranges up to 70° for . These holders ensure thermal stability below the point of (around -140°C), preventing structural artifacts during imaging. Direct detectors, a pivotal advancement, replace traditional cameras with monolithic active sensors (MAPS) like the Gatan K2 Summit or Thermo Fisher Falcon series, enabling electron counting and movie-mode acquisition at frame rates exceeding 400 Hz. These detectors achieve detective quantum efficiencies (DQEs) over 0.4 at low spatial frequencies, supporting low-dose strategies (e.g., 1–5 e/Ų per image) to mitigate beam-induced motion and damage. Energy filters, such as the in-column Omega filter in instruments or the Selectris filter in Thermo Fisher systems, remove inelastically scattered electrons, reducing background noise and improving contrast by up to 50% in low-dose images. Aberration correctors, often hexapole-based for spherical () and chromatic () aberrations, further refine beam focus, allowing underfocus-free imaging and resolutions approaching 1.2 Å. Phase plates, exemplified by the Volta phase plate, introduce a π/2 phase shift to the unscattered beam, enhancing low-frequency contrast for weakly scattering biomolecules without requiring defocus, which can distort high-resolution details. This has enabled reconstructions of small complexes (e.g., 64 kDa at 3.2 Å) with fewer particles.

History

Early Development

The foundational development of cryogenic electron microscopy (cryo-EM) began in the 1970s with pioneering efforts in computational image processing to handle noisy electron micrographs of biological specimens. introduced correlation-based algorithms for aligning and averaging low-dose images of unstained or negatively stained macromolecules, enabling the reconstruction of three-dimensional structures from two-dimensional projections without relying on crystalline order. His work, including the development of the software system in the mid-1970s, laid the groundwork for single-particle analysis by improving signal-to-noise ratios in images dominated by . In the early , advanced sample preservation techniques to address and structural artifacts common in traditional electron microscopy. He demonstrated that rapid cooling could form vitreous ice, an amorphous state of water that embeds biological samples without formation, thus maintaining native hydration. This breakthrough culminated in the 1982 invention of the plunge-freezing method, where a thin aqueous suspension is applied to an electron microscopy grid and rapidly immersed in liquid ethane cooled by , vitrifying the sample in milliseconds to prevent beam-induced damage during imaging. A key milestone came in 1984 when Dubochet and colleagues published the first cryo-EM images of unstained viruses, such as Semliki Forest virus, preserved in thin vitrified ice films without support or fixation. These images revealed viral envelopes and internal structures at resolutions sufficient to visualize macromolecular assemblies in their hydrated state, marking the practical application of cryo-EM to non-crystalline biological specimens. Early cryo-EM faced significant technical hurdles, including low image contrast from unstained, hydrated samples and from electron beams, which degraded delicate biomolecules even at cryogenic temperatures. To mitigate beam damage, researchers employed minimal electron doses, resulting in inherently noisy images that demanded sophisticated averaging techniques for interpretable results. Richard Henderson's contributions in the late 1980s and early 1990s demonstrated cryo-EM's potential for high- using two-dimensional protein crystals. In 1990, his team achieved a near-atomic map of at 3.5 Å, the first such structure of a obtained via electron cryo-crystallography of frozen, hydrated crystals, validating the technique's accuracy for atomic modeling. This work highlighted the synergy of , low-dose imaging, and computational reconstruction in overcoming early limitations.

Milestones and Recognition

In 2017, the was awarded jointly to , , and Richard Henderson "for developing cryo-electron microscopy for the visualization of biomolecules." This recognition highlighted their foundational contributions: Dubochet's development of vitreous ice embedding to preserve native biomolecular structures, Frank's invention of computational methods for from 2D projections, and Henderson's demonstration of high-resolution imaging of individual proteins like . The prize underscored cryo-EM's transformation from a niche technique to a dominant method in , enabling atomic-level insights into complex biomolecules without crystallization. Key milestones in the technique's maturation include the achievement of near-atomic resolution for the in 2013, as reported by Scheres and colleagues, who determined structures at approximately 3.6 using single-particle cryo-EM on thousands of particles, marking a breakthrough in resolving large macromolecular assemblies. Another pivotal advance came the same year with the 3.4 structure of the by Liao, Cao, and colleagues, the first near-atomic resolution map of a mammalian obtained solely via cryo-EM, demonstrating the method's potential for challenging targets. These accomplishments built on earlier work, such as Richard Henderson's 2015 review, which forecasted that routine atomic-resolution cryo-EM structures (better than 3 ) would soon be feasible with ongoing improvements in detectors and software. The establishment and growth of public depositories further reflect cryo-EM's impact, with the Electron Microscopy Data Bank (EMDB), founded in 2002 as a repository for 3D EM density maps, and the Protein Data Bank (PDB), which archives associated atomic models, becoming essential for and validation. By 2020, these archives had surpassed cryo-EM-derived entries, a milestone that highlighted the explosion in high-resolution structures following hardware and algorithmic advances. As of November 2025, EMDB contains over 51,000 entries, reflecting sustained growth.

Recent Advancements

Since the late 2010s, has transformed particle picking in cryo-EM workflows, with models enabling automated detection of protein particles in noisy micrographs. CryoSPARC introduced its Deep Picker module in 2019, leveraging convolutional neural networks trained on diverse datasets to achieve higher accuracy and speed compared to traditional template-matching methods, reducing manual intervention in high-throughput processing. Subsequent integrations, such as approaches like cryo-EMMAE in 2025, have further generalized particle picking across unseen samples without extensive annotations, streamlining automated pipelines for single-particle analysis. Advancements in detector technology during the have enhanced dose efficiency, particularly for beam-sensitive biological samples. Energy-filtered transmission electron microscopy (EFTEM) implementations, combined with direct electron detectors, have improved signal-to-noise ratios by selectively removing events, achieving up to 3-5 times better dose utilization in thick specimens like bacterial cells. These pixelated detectors, with high (DQE), support lower electron doses while maintaining resolution, as demonstrated in 100 kV cryo-EM systems optimized for routine high-resolution imaging by 2025. Time-resolved cryo-EM has seen significant progress in 2025, enabling visualization of protein dynamics on millisecond timescales. Techniques like "mix-and-freeze" protocols have captured transient states in assemblies, revealing conformational changes during processes with sub-nanometer precision. Extensions to time-resolved cryo-electron tomography (cryo-ET) in 2024 have allowed observation of cellular transients, such as cytoskeletal rearrangements, by synchronizing mixing devices with rapid . In the early 2020s, resolutions below 2.5 became more common in cryo-EM, exemplified by numerous high-resolution structures that resolved details of and receptor-binding interfaces, aiding design for pathogens like SARS-CoV-2. This milestone reflects broader hardware and software synergies, with over 600 spike-related cryo-EM entries in the by 2024, many below 3 . In 2025, efforts have shifted toward cryo-ET to contextualize these high-resolution structures within native cellular environments, mapping molecular architectures in tissues like the mouse hippocampus at near- scales. Cryo-EM has expanded into , with 2024 workflows tailored for beam-sensitive systems like electrolytes. Operando freezing techniques preserve native interphase structures during electrochemical cycling, revealing ion depletion zones and solid-electrolyte interfaces at the nanoscale without artifacts from drying. These methods, integrating air-controlled transfer and cryogenic imaging, have optimized analysis of evolution in solid-state batteries. Machine learning integration for map sharpening has advanced through tools like EMReady from 2023 onward, incorporating to refine anisotropic resolutions and enhance high-frequency details. The 2023 EMReady tool used neural networks for local and non-local modification, improving quality for model building in challenging datasets. A 2024 review highlighted ongoing developments in such tools for addressing preferred orientation biases and boosting interpretability of dynamic protein assemblies. Further advancements as of 2024 apply generative models for automated sharpening, reducing noise while preserving biological features. In 2024, practical guides emerged for applying cryo-EM to specialized biological imaging, including protozoan parasites and dermatological contexts. Cryo-ET protocols detailed sample preparation for invasion mechanisms, achieving sub-nanometer views of host-parasite interfaces to inform antimalarial therapies. Complementary workflows for skin-associated pathogens, such as in dermatological research, adapted techniques for thin-sectioned tissues, enabling correlative studies of microbial biofilms.

Sample Preparation

Biological Specimens

Biological specimens in cryogenic electron microscopy (cryo-EM) are prepared to preserve their native hydrated state, preventing structural damage from formation or chemical fixatives. The primary goal is to vitrify into , maintaining biomolecules like proteins, viruses, and cellular components in their functional conformations. This involves rapid cooling techniques that achieve rates exceeding 10^6 K/s, typically around 6.4 × 10^6 K/s for pure , to suppress crystallization, as slower rates lead to hexagonal or cubic phases that disrupt delicate structures. Plunge-freezing is the most common method for preparing thin samples, such as purified proteins or small cellular assemblies. In this technique, a microliter droplet of the specimen is applied to an electron microscopy grid, blotted to form a (typically 50-200 nm thick), and rapidly plunged into liquid cooled to approximately -180°C, embedding the sample in vitreous ice. This process vitrifies the aqueous suspension within milliseconds, preserving proteins in without additives in many cases, though challenges like preferred particle orientation in the 2D film can arise due to interactions at the air-water interface. For thicker biological samples, such as tissues or multicomponent cellular systems up to 200 µm, high-pressure freezing (HPF) is employed to achieve uniform . HPF applies hydrostatic of about 2,100 during cooling to -196°C, inhibiting and allowing deeper of the cooling front compared to plunge-freezing, which is limited to ~10 µm. Post-HPF, samples may undergo freeze-substitution to replace with resins for room-temperature sectioning if needed, though direct imaging of vitreous samples is preferred for native-state preservation. Vitreous sectioning via cryo-ultramicrotomy enables analysis of bulk tissue blocks by producing ultrathin sections (50-100 nm) from vitrified samples. The frozen block is mounted on a cryo-ultramicrotome at temperatures around -100°C to -140°C, and diamond knives slice ribbons of that are collected on grids for direct cryo-EM imaging, revealing native without artifacts. To facilitate correlative imaging, fiducial markers such as fluorescent microspheres are often incorporated into samples during preparation, serving as reference points for aligning fluorescence microscopy data with cryo-EM images and improving spatial correlation in complex biological contexts. Cryoprotectants like (typically 5-10% v/v) can be added to stabilize fragile complexes, reducing denaturation during freezing without significantly impairing resolution or increasing beam-induced motion.

Material Specimens

In cryogenic electron microscopy (cryo-EM) for specimens, sample preparation emphasizes preserving the native of inorganic and materials, such as electrolytes, nanoparticles, and thin films, by them in vitreous to minimize beam-induced artifacts. Unlike biological samples that require ultrathin ice layers for high-resolution of hydrated proteins, specimens often tolerate thicker ice embeddings, around 100-300 , to accommodate denser or less beam-sensitive structures while ensuring sufficient penetration. Vitrification of liquids and solutions, such as battery electrolytes, employs plunge-freezing techniques adapted from biological protocols but with modifications to the vitrification agents, including non-aqueous solvents or additives to stabilize reactive components like lithium salts without crystallization. This rapid freezing into amorphous ice captures transient states, such as solid-electrolyte interphases (SEI) in lithium-metal batteries, preserving nanoscale interfaces that would otherwise degrade under ambient conditions. For instance, electrolytes are blotted onto EM grids and frozen in liquid ethane at -180°C, enabling direct visualization of metastable phases. Cryo-focused ion beam (FIB) milling is a key method for preparing site-specific sections of bulk inorganic materials, such as electrodes or photovoltaic layers, by milling thin lamellae (typically 50-100 thick) at cryogenic temperatures around -170°C to -180°C. This technique uses liquid nitrogen-cooled stages and ions (e.g., Xe⁺ or Ar⁺) instead of to avoid contamination in beam-sensitive samples, thereby preserving delicate nanoscale features like growth in deposits or boundaries in perovskites. The process involves protective deposition followed by targeted milling, resulting in electron-transparent sections suitable for (TEM) analysis. For beam-sensitive inorganic materials, such as and metal oxide , preparation involves embedding in vitreous ice to study buried interfaces, like those in hybrid solar cells, where the ice layer shields against and heating during imaging. thin films or dispersions are vitrified on holey carbon grids, often with air-tight transfer systems to prevent oxidation, allowing atomic-scale of defects and surface reconstructions. , dispersed in solvents like or , are plunge-frozen to form thin ice films that embed aggregates without aggregation-induced distortions, facilitating interface studies in applications. Recent advancements as of 2025, including microfluidic platforms like for minimal sample use and magnetic bead methods like cryo-EM to reduce sample loss, have further improved preparation efficiency for both biological and material specimens. These methods highlight improved protocols for ice layers in materials, contrasting with the thinner requirements for biological specimens to maintain native . Key challenges in preparing material specimens include stringent contamination control, addressed through handling and vacuum transfers to avoid hydrocarbon buildup on ice surfaces, and leveraging the higher electron dose tolerance of inorganics—often 10-100 times that of proteins—to enable of thicker or denser samples without rapid degradation. Despite these advantages, issues like unintended icing during transfer or reactivity with residual persist, necessitating standardized workflows for reproducible results.

Core Techniques

Cryogenic Transmission Electron Microscopy

Cryogenic transmission electron microscopy (cryo-TEM) utilizes a parallel beam of electrons transmitted through ultrathin, vitrified specimens to generate high-contrast, two-dimensional images that reveal internal structures at near-native conditions. This mode relies on the interaction of electrons with the sample, where unscattered and weakly scattered electrons contribute to phase contrast imaging under defocus conditions, enabling visualization of biological macromolecules without or artifacts. Accelerating voltages typically range from 200 to 300 kV to balance and while reducing chromatic aberrations in cryogenic environments. The workflow in cryo-TEM emphasizes low-dose imaging to mitigate beam-induced damage, with electron doses limited to approximately 20-50 per square across the exposure. Electrons pass through the frozen-hydrated sample, producing projections that capture density variations; for single-particle analysis, thousands to millions of such projections from randomly oriented particles are acquired in a single session on a direct electron detector. This approach exploits the random orientations inherent in vitrified suspensions, allowing computational averaging to enhance signal-to-noise ratios and reconstruct three-dimensional density maps. Dose fractionation divides the total exposure into sequential frames, where the cumulative dose D = \sum d_i (with d_i as the dose per frame) facilitates post-acquisition motion correction, thereby preserving structural integrity by aligning frames to counteract specimen drift and conformational changes. Cryo-TEM operates predominantly in bright-field mode, selecting unscattered electrons to form images that map mass density through interference effects, ideal for phase-sensitive structures like proteins. Dark-field mode, which collects scattered electrons, provides complementary contrast for highlighting differences or specific density features but is less common due to lower signal efficiency in low-dose regimes. Single-particle cryo-EM, a cornerstone technique, excels for symmetric assemblies such as icosahedral viruses, where imposed accelerates convergence and routinely achieves resolutions of 3-10 Å, sufficient for secondary structure tracing and ligand identification. Pioneered in the , cryo-TEM was first applied to unstained suspensions, including icosahedral examples like adenovirus, enabling unprecedented views of hydrated capsids without support films. This breakthrough, building on methods, marked the shift from to native-state imaging. Today, it serves as the standard for structures, circumventing challenges and yielding atomic models for over half of new entries in structural databases.

Scanning Electron Cryomicroscopy

Scanning electron cryomicroscopy (cryo-SEM) operates by raster-scanning a focused beam of across the surface of a frozen-hydrated sample, detecting secondary and backscattered to generate high-resolution images of and . This surface-sensitive technique preserves the native state of samples through rapid , typically via plunge freezing in liquid or high-pressure freezing, followed by maintenance at cryogenic temperatures (around -170°C) using a specialized cold stage within the vacuum. The method achieves resolutions of approximately 10 for biological structures, enabling detailed visualization of surface features without the artifacts common in traditional . Adaptations for cryogenic conditions include the integration of environmental scanning electron microscopy (ESEM) features, such as low-vacuum modes and Peltier-cooled stages, which allow of hydrated or partially hydrated samples by controlling chamber pressure and temperature to prevent ice . Samples are often prepared via cryofracture to expose internal surfaces or to sublimate surface , revealing underlying topography, and coated with a thin layer (1-30 nm) of conductive material like or to enhance signal and stability. Cryo-SEM was developed in the specifically for biological surfaces in their frozen state, building on earlier freeze-fracture techniques to study hydrated specimens. In applications, cryo-SEM excels at surface reconstruction of cells, such as plant-microbe interactions or cellular organelles like thylakoid membranes, and materials like emulsions, providing insights into native architectures at the nanoscale. For instance, fracture-etched samples of biological tissues reveal detailed topography, such as macrofibrils in cell walls at 25 nm resolution, aiding studies in and . A primary challenge is electron beam-induced charging in non-conductive frozen samples, which can distort images; this is mitigated through metal coatings or low accelerating voltages (<1 kV) to distribute charge evenly.

Data Processing

Image Acquisition and Preprocessing

Image acquisition in cryogenic electron microscopy (cryo-EM) employs low-dose strategies to minimize beam-induced damage to radiation-sensitive biological specimens while capturing sufficient signal for structural analysis. Typically, the total electron dose per micrograph is limited to 20-50 electrons per square angstrom (e/Ų), distributed across multiple frames in movie mode to allow subsequent motion correction. This dose fractionation, often involving 20-50 frames per exposure, enables the recording of dynamic specimen movements caused by beam heating and charging effects. Automated collection software, such as SerialEM, facilitates high-throughput acquisition by systematically navigating grid squares, focusing, and exposing areas with suitable ice thickness and particle distribution. In the 2020s, advancements like SmartScope have shifted toward fully automated screening, integrating deep learning for real-time evaluation of specimen quality to optimize data collection efficiency. Beam tilting and image-shift techniques further enhance dose efficiency during acquisition, particularly for single-particle analysis (SPA). By introducing controlled beam tilts of up to 2-3 degrees, these methods reduce astigmatism and coma aberrations without stage movement, allowing multiple micrographs to be collected from a single position and increasing throughput by factors of 3-5. Movie acquisition in low-dose mode records dose-fractionated videos at pixel sizes of 0.8-1.5 Å, typically yielding thousands of micrographs per dataset—often 1,000 to 10,000—to ensure statistical robustness for particle picking and 3D reconstruction. These strategies balance resolution, contrast, and specimen preservation, with defocus ranges set from -0.5 to -3.0 μm to capture phase contrast in vitreous ice. Preprocessing begins with frame alignment to correct beam-induced motion, a critical step that restores high-frequency signal lost to specimen drift and bubbling. Algorithms like Unblur perform per-frame alignment using cross-correlation, estimating local displacements to generate motion-corrected, dose-weighted sums. The motion model approximates displacement as \delta(x,y) = f(\mathbf{b}), where \delta(x,y) is the shift at pixel coordinates (x,y) and f(\mathbf{b}) represents beam-induced movement parameters, often refined iteratively across patches for anisotropic effects. Following alignment, contrast transfer function (CTF) estimation and correction address microscope-induced phase shifts. Tools such as analyze power spectra of motion-corrected micrographs to fit defocus values with sub-angstrom accuracy, enabling per-micrograph CTF parameters for downstream refinement. Correction involves phase reversal or Wiener filtering to recover amplitude information, improving signal-to-noise ratios by 20-50% in high-resolution regimes. These initial steps, handling datasets of thousands of micrographs, prepare particle images for 3D processing while discarding low-quality data based on metrics like .

3D Reconstruction and Analysis

In (cryo-EM), 3D reconstruction and analysis transform thousands to millions of 2D projection images of biological macromolecules into high-resolution 3D density maps, primarily through (SPA). SPA assumes that individual particles are identical but randomly oriented and translated in the ice, allowing computational alignment of projections to infer their 3D orientations and generate a consistent volume via or Fourier methods. This process begins with preprocessed images, where particle coordinates have been picked and motion-corrected, enabling focus on orientation determination and density averaging. The core of SPA involves angular reconstitution, where initial low-resolution 3D models are built from subsets of 2D class averages, followed by iterative refinement to optimize particle orientations and the 3D map. A key algorithm is projection matching, which minimizes the difference between observed images I and simulated projections P(\theta) of a 3D model over estimated orientations \theta, formulated as \sum ||P(\theta) - I||^2. This is implemented in software like , which uses a Bayesian approach with an empirical prior on orientations to regularize the likelihood and prevent overfitting during maximum a posteriori refinement. RELION's iterative algorithm alternates between aligning particles to projections and updating the 3D map, achieving resolutions often below 3 Å for well-behaved samples. Heterogeneity in particle conformations or compositions poses a major challenge, addressed through 3D classification to sort particles into distinct structural states. In RELION, this employs a Bayesian framework to assign particles to multiple 3D classes simultaneously, revealing conformational ensembles without prior knowledge. For beam-induced motion and decay, Bayesian polishing refines per-particle trajectories using Gaussian process regression on aligned movie frames, effectively correcting B-factors (temperature factors) that model resolution variation across the map and improving overall reconstruction quality. These steps enable separation of dynamic states, as seen in studies of ribosomal complexes where multiple conformations are resolved at near-atomic detail. Reconstructed maps require validation and post-processing for interpretability. Resolution is assessed using the Fourier shell correlation (FSC) between half-maps from independent refinements, with the "gold standard" cutoff of 0.143 FSC determining the point where signal equals noise, providing a conservative estimate unbiased by overfitting. Map sharpening enhances high-frequency details by applying inverse B-factor weighting or local filters that adapt to spatially varying resolution, often guided by atomic models or estimated local FSC. Tools like LocScale perform this local sharpening by optimizing a likelihood target per voxel, yielding maps suitable for model building. Prominent software suites facilitate these workflows: cryoSPARC employs stochastic gradient descent for rapid ab initio modeling, generating initial 3D volumes from random subsets without templates via common-lines detection in Fourier space. RELION complements this with robust refinement and classification. By 2025, machine learning integrations have advanced de novo structure prediction, such as multimodal deep learning models combining cryo-EM maps with AlphaFold3 predictions to refine atomic models directly, achieving sub-2 Å accuracy for novel proteins without homology. These reconstructed models underpin applications in structural biology, elucidating mechanisms like enzyme catalysis.

Applications

Structural Biology

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of high-resolution structures of biomolecular complexes that are often too large, flexible, or heterogeneous for traditional methods like . This technique preserves proteins in near-native states, revealing atomic details of macromolecular assemblies involved in cellular processes such as translation, signaling, and viral infection. By 2025, cryo-EM-derived structures account for over 29,000 entries in the , underscoring its dominance in elucidating biomolecular architectures. In the study of large biomolecular complexes, cryo-EM has provided landmark insights into ribosomes and ion channels. For instance, the bacterial ribosome has been resolved at 1.55 Å resolution, highlighting the intricate RNA-protein interactions critical for . Similarly, the structure of the TRPV1 ion channel, determined at 3.4 Å in 2013, marked an early breakthrough in visualizing mammalian transient receptor potential channels, with subsequent studies capturing conformational changes during activation. Viral envelopes, such as that of the , have been mapped at 3.8 Å resolution, revealing the arrangement of envelope glycoproteins that facilitate host cell entry and informing antiviral strategies. Cryo-EM plays a pivotal role in drug discovery, particularly for G protein-coupled receptors (GPCRs), by capturing conformational dynamics essential for ligand binding. Structures of GPCRs in various states, often stabilized with nanobodies or G proteins, have exposed allosteric sites and activation mechanisms, accelerating the design of selective modulators. In vaccine development, cryo-EM structures of the SARS-CoV-2 spike protein, resolved at resolutions up to 3.2 Å in the prefusion conformation, have guided the engineering of immunogens that elicit neutralizing antibodies, contributing to mRNA and subunit vaccines. The technique's impact on COVID-19 research is profound, with over 100 cryo-EM structures of viral components deposited by 2023, enabling rapid iteration on therapeutics and prophylactics. For cellular insights, hybrid approaches combining cryo-EM with electron tomography (cryo-ET) yield in situ structures of organelles, preserving their native context within cells. Cryo-ET has visualized mitochondrial cristae and endoplasmic reticulum membranes at near-atomic resolution, disclosing protein organization and lipid interactions that underpin organelle function. However, challenges persist with flexible regions in biomolecules, where heterogeneity blurs reconstructions; focused classification and refinement strategies mitigate this by isolating rigid domains and modeling dynamics, enhancing interpretability of states like loop movements in enzymes.

Materials Science

Cryogenic electron microscopy (cryo-EM) has emerged as a vital tool for characterizing the nanoscale structure and dynamics of materials, enabling the visualization of beam-sensitive samples in their native or near-native states without the artifacts introduced by dehydration or staining. In materials science, cryo-EM excels at resolving atomic-scale features in functional materials, such as interfaces and defects, which are critical for understanding performance in energy storage and conversion devices. By vitrifying samples in vitreous ice, this technique preserves hydrated or liquid-like environments, allowing researchers to probe properties that are otherwise inaccessible under ambient conditions.01373-0) A key application lies in imaging battery materials, where cryo-EM reveals the atomic-scale structure of electrolyte interfaces and formation in lithium-ion cells. For instance, studies have shown that dendrites in carbonate-based electrolytes grow as faceted, single-crystalline nanowires along preferred crystallographic directions like <111>, <110>, or <211>, providing insights into failure mechanisms and strategies for dendrite suppression. In solid-state batteries, cryo-EM has elucidated atomic-scale interface structures in garnet-type electrolytes, identifying pathways to design dendrite-free systems by mitigating polarization and void formation at interfaces. These observations, achieved at resolutions approaching levels, highlight how cryo-EM captures the sensitive morphology of metal anodes during electrochemical cycling. Cryo-EM also advances the study of nanoparticles and catalysts, particularly vitrified alloys used in surface reactions, and extends to perovskites in photovoltaics. Vitrified metallic alloys and catalysts have been imaged to uncover mechanisms, such as the dynamic restructuring of copper nanocatalysts during CO2 reduction, where operando-freezing preserves transient intermediates like electrowetted surfaces. In perovskites for solar cells, 2024 studies have leveraged cryo-EM to examine defects and strains, revealing boundaries and ionic migrations that impact photovoltaic efficiency and stability. Resolutions down to approximately 2 have been achieved for inorganic s, as demonstrated in metal-organic frameworks, enabling precise mapping of atomic surfaces and host-guest interactions.30053-0) For polymers and composites, cryo-EM visualizes hydrated states to investigate phase transitions, such as the coil-to-globule transformations in thermoresponsive polymers above the , where captures entropically driven assemblies without disrupting their native . In ion-conducting polymers like , cryo-EM shows how induces a shift from isolated hydrophilic clusters to interconnected branched networks, informing designs for membranes. The 2024 expansion of cryo-EM to renewables, including defect analysis, underscores its growing role in sustainable materials. Overall, a primary benefit is the ability to capture transient states in functional materials, such as evolving interfaces during operation, which traditional methods alter through drying or heating.

Comparisons and Limitations

Versus X-ray Crystallography

Cryogenic electron microscopy (cryo-EM) and X-ray crystallography represent two cornerstone techniques in structural biology, each with distinct methodological approaches that influence their applicability to different types of samples. A primary difference lies in sample preparation requirements: cryo-EM does not necessitate crystallization and can accommodate native, heterogeneous samples in a frozen-hydrated state, typically requiring only microliters of purified protein at concentrations of 0.1–1 mg/mL. In contrast, X-ray crystallography demands the production of highly ordered, diffraction-quality crystals, often from milligrams of protein, which can be challenging for flexible or membrane-embedded macromolecules due to the need for extensive optimization of crystallization conditions. This crystallization bottleneck in X-ray methods preserves the sample in a crystalline lattice but may induce conformational artifacts not present in solution. Regarding resolution and molecular size suitability, cryo-EM has advanced to routinely achieve sub-3 resolutions for large macromolecular complexes exceeding 100 , enabling atomic model building even for dynamic assemblies. It particularly excels with flexible or large (>500 ) structures, such as multi-subunit complexes or viruses, where direct visualization of heterogeneity is possible without averaging out conformational states. , however, remains superior for smaller, rigid proteins (<100 ), often yielding resolutions below 2 due to the high-order from , though it struggles with or heterogeneity that disrupts formation. Cryo-EM's ability to image samples in near-native further supports its strength in capturing physiological states, unlike methods where may exclude solvent layers. Throughput and workflow timelines also differ significantly. Cryo-EM enables structure determination in hours to days once samples are vitrified, bypassing prolonged trials and allowing rapid assessment of through multiple conformational captures. , while efficient for data collection at sources—essential for sufficient flux in macromolecular studies—often requires weeks to months for and optimization, with the problem addressed via methods like multiple anomalous dispersion () adding further steps. access, typically needed for high-resolution X-ray data, introduces scheduling constraints not faced by cryo-EM, which uses laboratory-based microscopes. Since 2018, cryo-EM has dramatically increased its impact, with annual releases of new structures in the rising from 882 in 2018 to 4,576 in 2023, 5,791 in 2024, and approximately 6,032 as of November 2025, continuing to grow rapidly and rival in certain ranges (e.g., 3.5–5 Å), with cryo-EM comprising a significant portion of new annual deposits as of 2025. Hybrid approaches combining both techniques are increasingly common for validation, where cryo-EM provides overall and refines local details, enhancing accuracy for complex systems like G-protein coupled receptors.

Advantages and Challenges

Cryogenic electron microscopy (cryo-EM) offers significant advantages in by enabling the imaging of biological macromolecules in their native, hydrated state without the need for or chemical fixation, thereby preserving functional conformations and interactions that might be lost in other techniques.01078-9) This approach allows for the study of large macromolecular complexes with no upper size limit, unlike (NMR) spectroscopy, which is constrained to smaller proteins typically below 50 . Additionally, cryo-EM facilitates the capture of through particle classification methods during , revealing conformational heterogeneity and transient states in solution. Despite these strengths, cryo-EM faces substantial challenges related to instrumentation and data handling. High-end cryo-transmission electron microscopes (cryo-TEMs) required for atomic-resolution imaging cost between $5 million and $7 million, limiting accessibility to well-funded laboratories. Data acquisition generates terabyte-scale volumes due to the need for thousands of images per dataset, demanding significant computational resources for processing and storage. Beam-induced radiation damage necessitates low-dose imaging strategies, which reduce signal-to-noise ratios and complicate data collection, often requiring prolonged exposure times or specialized detectors. Key limitations include the potential for preferred particle orientations on the EM grid, which can bias 3D reconstructions and lead to anisotropic or incomplete maps. Cryo-EM traditionally struggles with small molecules or proteins below 50 kDa due to low contrast and insufficient scattering signal, though advances such as nanobody scaffolds have enabled high- structures as small as 14 kDa as of 2025. As of 2025, sample heterogeneity remains a persistent issue, arising from conformational variability or impurities that complicate particle and in heterogeneous datasets. Emerging solutions, such as AI-driven denoising algorithms, are addressing these by enhancing map quality through and artifact correction, enabling better from imperfect . Looking forward, cost reductions are anticipated through innovations like lower-voltage microscopes and miniaturized designs, potentially bringing high-performance systems to more labs at a fraction of current prices. Shared facilities and national centers are expanding access by providing subsidized instrumentation and expertise, democratizing cryo-EM for broader research communities.

Advanced Techniques

Cryo-Electron Tomography

Cryo-electron tomography (cryo-ET) enables the three-dimensional imaging of cellular structures in their native environment by acquiring a series of two-dimensional projection images of a frozen-hydrated sample tilted over a range of angles. The workflow begins with tilt-series acquisition, typically spanning ±60° to ±70° in increments of 2° to 3°, using a dose-symmetric scheme to minimize beam-induced damage while ensuring even distribution of electron dose across projections. These tilt series are then aligned, often using fiducial markers such as gold nanoparticles to correct for specimen drift and achieve precise registration, followed by tomographic reconstruction via weighted back-projection to generate a 3D density map, or tomogram. The weighted back-projection method computes the reconstructed volume f(\mathbf{x}) by integrating projections p(\theta, s) weighted by a function w(\theta, s - \mathbf{x} \cdot \mathbf{n}_\theta), formalized as: f(\mathbf{x}) = \int p(\theta, s) \, w(\theta, s - \mathbf{x} \cdot \mathbf{n}_\theta) \, ds where \theta denotes the tilt angle, s the projection coordinate, and \mathbf{n}_\theta the projection direction. A key strength of cryo-ET lies in subtomogram averaging, which enhances for repeating cellular structures by extracting sub-volumes (subtomograms) from multiple tomograms and aligning and averaging them to reduce noise. This approach has been particularly effective for studying macromolecular complexes , such as bacterial ribosomes, where averaging reveals functional states and interactions within the crowded cellular context at resolutions supporting molecular interpretation. For structures, resolutions typically range from 5 to 10 , allowing visualization of secondary structure elements and interfaces without isolating complexes. Recent advances in have extended these capabilities to protozoan parasites, enabling high-resolution imaging of infection machinery, such as the polar tube apparatus in microsporidians, to uncover native ultrastructures critical for host invasion. In November , cryo-EM revealed the helical filament structure of AAA+ Thorase at 4 , providing insights into nucleotide-dependent assembly. Despite these achievements, cryo-ET faces challenges inherent to limited tilt ranges, including the missing wedge artifact, which arises from incomplete angular sampling and manifests as anisotropic and distortions in the reconstructed tomogram, particularly elongating features along the . Fiducial markers mitigate alignment errors but require careful placement to avoid obscuring biological features, and ongoing developments in marker-free alignment and computational compensation continue to address these limitations.

Correlative and Time-Resolved Methods

Correlative light-electron microscopy (CLEM) combines fluorescence microscopy with cryo-EM to identify and target specific cellular regions for high-resolution while preserving the native hydrated state of samples. In cryo-CLEM workflows, live-cell guides the localization of proteins or structures of interest, followed by rapid and EM imaging to overlay optical and electron data for precise correlation. This approach has been enhanced by cryo-super-resolution techniques, such as structured illumination microscopy (SIM), to achieve sub-100 nm localization accuracy compatible with subsequent cryo-EM. Genetic tags like (GFP) are commonly integrated into CLEM for correlative imaging, enabling the visualization of tagged proteins in before correlating their positions in cryo-EM densities. For instance, fixation-resistant GFP variants maintain post-vitrification, facilitating the identification of dynamic cellular components such as viral entry sites or interactions. Advanced variants, including mini-Singlet Oxygen Generator (miniSOG) fused to GFP, allow photo-oxidation for electron-dense labeling, improving overlay precision in 3D reconstructions. Time-resolved cryo-EM employs microfluidic mixing devices to capture transient molecular states by initiating reactions and vitrifying samples on millisecond timescales, revealing intermediates in processes like enzymatic cycles. On-grid and in-flow mixing methods enable rapid diffusion of reactants, such as ATP, to synchronize conformational changes in proteins, with examples including the hydrolysis cycles of V/A-ATPases where structures of activation intermediates were resolved at 3.2 . These techniques have achieved resolutions around 3-4 for transient states. Recent advancements in 2025 have extended time-resolved methods to cryo-electron (cryo-ET), incorporating the time dimension to visualize cellular dynamics , such as protein rearrangements during bacterial . These developments include correlative voltage with cryo-ET (CoVET) for probing electrophysiological changes alongside structural snapshots, achieving resolutions around 7-8 Å for dynamic membrane processes using a cryo-electron pipeline for membranes. Pump-probe setups further enable the study of light-induced states, where pulses trigger photochemical reactions in photosensitive proteins, followed by cryogenic trapping to resolve photointermediates at sub-second delays. A key challenge in these methods is synchronizing biochemical reactions across millisecond-to-second timescales with , as manual mixing limits resolution to slower events while microfluidic delay lines introduce variability in times (e.g., 0–40 distributions). Biochemical processes must remain synchronized throughout , which is hindered by sample heterogeneity and beam-induced motion in cryo-EM. Ongoing innovations, such as spray-based plunging under 30 , address these issues but require optimization for low sample volumes and high-throughput.

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