Molecular electron microscopy: state of the art and current challenges

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Molecular vibrational imaging at nanoscale

The demand to visualize the spatial distribution of chemical species based on vibrational spectra is rapidly increasing. Driven by such a need, various Raman and infrared spectro-microscopies with a nanometric spatial resolution have been developed over the last two decades. Despite rapid progress, a large gap still exists between the general needs and what these techniques can achieve. This Perspective highlights the key challenges and recent breakthroughs of the two vibrational nano-imaging techniques, scattering-type scanning near-field optical microscopy and tip-enhanced Raman scattering.

Electrostatically-gated molecular rotors

The ability to control molecular-scale motion using electrostatic interactions was demonstrated using an N-phenylsuccinimide molecular rotor with an electrostatic pyridyl-gate. Protonation of the pyridal-gate forms stabilizing electrostatic interactions in the...

Liquid electron microscopy: then, now and future

Contemporary microscopic imaging at near-atomic resolution of diverse embodiments in liquid environment has gained keen interest. In particular, Electron Microscopy (EM) can provide comprehensive framework on the structural and functional characterization of samples in liquid phase. In the past few decades, liquid based electron microscopic modalities have developed tremendously to provide insights into various backgrounds like biological, chemical, nanoparticle and material researches. It serves to be a promising analytical tool in deciphering unique insights from solvated systems. Here, the basics of liquid electron microscopy with few examples of its applications are summarized in brief. The technical developments made so far and its preference over other approaches is shortly presented. Finally, the experimental limitations and an outlook on the future technical advancement for liquid EM have been discussed.

Archiving and disseminating integrative structure models

Limitations in the applicability, accuracy, and precision of individual structure characterization methods can sometimes be overcome via an integrative modeling approach that relies on information from all available sources, including all available experimental data and prior models. The open-source Integrative Modeling Platform (IMP) is one piece of software that implements all computational aspects of integrative modeling. To maximize the impact of integrative structures, the coordinates should be made publicly available, as is already the case for structures based on X-ray crystallography, NMR spectroscopy, and electron microscopy. Moreover, the associated experimental data and modeling protocols should also be archived, such that the original results can easily be reproduced. Finally, it is essential that the integrative structures are validated as part of their publication and deposition. A number of research groups have already developed software to implement integrative modeling and have generated a number of structures, prompting the formation of an Integrative/Hybrid Methods Task Force. Following the recommendations of this task force, the existing PDBx/mmCIF data representation used for atomic PDB structures has been extended to address the requirements for archiving integrative structural models. This IHM-dictionary adds a flexible model representation, including coarse graining, models in multiple states and/or related by time or other order, and multiple input experimental information sources. A prototype archiving system called PDB-Dev ( https://pdb-dev.wwpdb.org ) has also been created to archive integrative structural models, together with a Python library to facilitate handling of integrative models in PDBx/mmCIF format.

Modeling Biological Complexes Using Integrative Modeling Platform

Integrative structure modeling provides 3D models of macromolecular systems that are based on information from multiple types of experiments, physical principles, statistical inferences, and prior structural models. Here, we provide a hands-on realistic example of integrative structure modeling of the quaternary structure of the actin, tropomyosin, and gelsolin protein assembly based on electron microscopy, solution X-ray scattering, and chemical crosslinking data for the complex as well as excluded volume, sequence connectivity, and rigid atomic X-ray structures of the individual subunits. We follow the general four-stage process for integrative modeling, including gathering the input information, converting the input information into a representation of the system and a scoring function, sampling alternative model configurations guided by the scoring function, and analyzing the results. The computational aspects of this approach are implemented in our open-source Integrative Modeling Platform (IMP), a comprehensive and extensible software package for integrative modeling ( https://integrativemodeling.org ). In particular, we rely on the Python Modeling Interface (PMI) module of IMP that provides facile mixing and matching of macromolecular representations, restraints based on different types of information, sampling algorithms, and analysis including validations of the input data and output models. Finally, we also outline how to deposit an integrative structure and corresponding experimental data into PDB-Dev, the nascent worldwide Protein Data Bank (wwPDB) resource for archiving and disseminating integrative structures ( https://pdb-dev.wwpdb.org ). The example application provides a starting point for a user interested in using IMP for integrative modeling of other biomolecular systems.

A Polymerizable Photoswitchable Fluorophore for Super-Resolution Imaging of Polymer Self-Assembly and Dynamics

Single-molecule super-resolution microscopy has become a standard imaging tool in the life sciences for visualizing nanostructures in situ, but the application of this technique in polymer science is much less explored. A key bottleneck is the lack of fluorophores and simple covalent attachment strategies onto polymer chains. Here, we report a functional diarylethene-based photoswitchable fluorophore that can be directly incorporated into polymer backbones through copolymerization, which significantly streamlines the labeling strategy, with no further postcoupling reactions or purifications needed. The attachment of fluorophores onto selectively labeled polymers enables super-resolution imaging of a series of model polymer blend systems with different nanostructures and chemical compositions. As each individual fluorophore is able to switch several times on average between its bright and dark state, multiple time-lapse images can be acquired to observe the dynamic nanostructural evolution of polymer blends upon solvent vapor annealing. With this demonstration of a universal, simplified labeling strategy and the ability to image polymer assembly under native conditions, this reported fluorophore may promote the widespread use of super-resolution microscopy in the polymer community.

High resolution subsurface imaging using resonance-enhanced detection in 2nd-harmonic KPFM

Second harmonic Kelvin probe force microscopy is a robust mechanism for subsurface imaging at the nanoscale. Here we exploit resonance-enhanced detection as a way to boost the subsurface contrast with higher force sensitivity using lower bias voltages, in comparison to the traditional off-resonance case. In this mode, the second harmonic signal of the electrostatic force is acquired at one of the eigenmode frequencies of the microcantilever. As a result, high resolution subsurface images are obtained in a variety of nanocomposites. To further understand the subsurface imaging detection upon electrostatic forces, we use a finite element model that approximates the geometry of the probe and sample. This allows the investigation of the contrast mechanism, the depth sensitivity and lateral resolution depending on tip-sample properties.

Integrative structure modeling with the Integrative Modeling Platform

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use.

In Situ Environmental TEM in Imaging Gas and Liquid Phase Chemical Reactions for Materials Research

Gas and liquid phase chemical reactions cover a broad range of research areas in materials science and engineering, including the synthesis of nanomaterials and application of nanomaterials, for example, in the areas of sensing, energy storage and conversion, catalysis, and bio-related applications. Environmental transmission electron microscopy (ETEM) provides a unique opportunity for monitoring gas and liquid phase reactions because it enables the observation of those reactions at the ultra-high spatial resolution, which is not achievable through other techniques. Here, the fundamental science and technology developments of gas and liquid phase TEM that facilitate the mechanistic study of the gas and liquid phase chemical reactions are discussed. Combined with other characterization tools integrated in TEM, unprecedented material behaviors and reaction mechanisms are observed through the use of the in situ gas and liquid phase TEM. These observations and also the recent applications in this emerging area are described. The current challenges in the imaging process are also discussed, including the imaging speed, imaging resolution, and data management.

Development of a bio-analytical strategy for characterization of vaccine particles combining SEC and nanoES GEMMA

Commonly used methods for size and shape analysis of bionanoparticles found in vaccines like X-ray crystallography and cryo-electron microscopy are very time-consuming and cost-intensive. The nano-electrospray (nanoES) gas-phase electrophoretic mobility macromolecular analyzer (GEMMA), belonging to the group of ion mobility spectrometers, was used for size determination of vaccine virus particles because it requires less analysis time and investment (no vacuum system). Size exclusion chromatography (SEC) of viral vaccines and production intermediates turned out to be a good purification/isolation method prior to GEMMA, TEM (transmission electron microscopy) and AFM (atomic force microscopy) investigations, as well as providing a GEMMA analysis-compatible buffer. Column materials and different elution buffers were tested for optimal vaccine particle yield. We used a Superdex 200 column with a 50 mM ammonium acetate buffer. In addition, SEC allowed the removal of process-related impurities from the virions of interest. A sample concentrating step or a detergent addition step was also investigated. As a final step of our strategy SEC-purified or untreated vaccine-nanoparticles were further analyzed: (a) by immunological detection with a specific polyclonal antibody (dot blot) to verify the biological functionality, (b) by GEMMA to provide the size of the particles at atmospheric pressure and (c) by AFM and (d) TEM to obtain both size and shape information. The mean diameter of inactivated tick-borne encephalitis virions (i.e. vaccine particles) determined by GEMMA measurement was 46.6 ± 0.5 nm, in contrast to AFM and TEM images providing diameters of about 58 ± 4 and 52 ± 5 nm, respectively.

Heat-passing framework for robust interpretation of data in networks

Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transforming this data into knowledge. We develop a new framework, called heat-passing, which exploits intrinsic similarity relationships within noisy and incomplete raw data, and constructs a meaningful map of the data. The proposed framework is able to rank, cluster, and visualize the data all at once. The novelty of this framework is derived from an analogy between the process of data interpretation and that of heat transfer, in which all data points contribute simultaneously and globally to reveal intrinsic similarities between regions of data, meaningful coordinates for embedding the data, and exemplar data points that lie at optimal positions for heat transfer. We demonstrate the effectiveness of the heat-passing framework for robustly partitioning the complex networks, analyzing the globin family of proteins and determining conformational states of macromolecules in the presence of high levels of noise. The results indicate that the methodology is able to reveal functionally consistent relationships in a robust fashion with no reference to prior knowledge. The heat-passing framework is very general and has the potential for applications to a broad range of research fields, for example, biological networks, social networks and semantic analysis of documents.

High-resolution electron microscopy and spectroscopy of ferritin in biocompatible graphene liquid cells and graphene sandwiches

Atomic and electronic structures of hydrated ferritin are characterized using electron microscopy and spectroscopy through encapsulation in single layer graphene in a biocompatible manner. Graphene's ability to reduce radiation damage levels to hydrogen bond breakage is demonstrated. A reduction of iron valence from 3+ to 2+ is measured at nanometer-resolution in ferritin, showing initial stages of iron release by ferritin.

Liquid scanning transmission electron microscopy: imaging protein complexes in their native environment in whole eukaryotic cells

Scanning transmission electron microscopy (STEM) of specimens in liquid, so-called Liquid STEM, is capable of imaging the individual subunits of macromolecular complexes in whole eukaryotic cells in liquid. This paper discusses this new microscopy modality within the context of state-of-the-art microscopy of cells. The principle of operation and equations for the resolution are described. The obtained images are different from those acquired with standard transmission electron microscopy showing the cellular ultrastructure. Instead, contrast is obtained on specific labels. Images can be recorded in two ways, either via STEM at 200 keV electron beam energy using a microfluidic chamber enclosing the cells, or via environmental scanning electron microscopy at 30 keV of cells in a wet environment. The first series of experiments involved the epidermal growth factor receptor labeled with gold nanoparticles. The labels were imaged in whole fixed cells with nanometer resolution. Since the cells can be kept alive in the microfluidic chamber, it is also feasible to detect the labels in unfixed, live cells. The rapid sample preparation and imaging allows studies of multiple whole cells.

Modeling protein assemblies in the proteome

Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high- and low-resolution scales. Existing computational methods have made substantial progress toward this aim; however, current approaches are still limited. Some involve manual adjustment of experimental data; some are automated docking methods, which are computationally expensive and not applicable to large-scale proteome studies; and still others exploit the symmetry of the complexes and thus are not applicable to nonsymmetrical complexes. Our study aims to take steps toward overcoming these limitations. We have developed a strategy for the construction of protein assemblies computationally based on binary interactions predicted by a motif-based protein interaction prediction tool, PRISM (Protein Interactions by Structural Matching). Previously, we have shown its power in predicting pairwise interactions. Here we take a step toward multimolecular assemblies, reflecting the more prevalent cellular scenarios. With this method we are able to construct homo-/hetero-complexes and symmetric/asymmetric complexes without a limitation on the number of components. The method considers conformational changes and is applicable to large-scale studies. We also exploit electron microscopy density maps to select a solution from among the predictions. Here we present the method, illustrate its results, and highlight its current limitations.

Growth of large and highly ordered 2D crystals of a K⁺ channel, structural role of lipidic environment

2D crystallography has proven to be an excellent technique to determine the 3D structure of membrane proteins. Compared to 3D crystallography, it has the advantage of visualizing the protein in an environment closer to the native one. However, producing good 2D crystals is still a challenge and little statistical knowledge can be gained from literature. Here, we present a thorough screening of 2D crystallization conditions for a prokaryotic inwardly rectifying potassium channel (>130 different conditions). Key parameters leading to very large and well-organized 2D crystals are discussed. In addition, the problem of formation of multilayers during the growth of 2D crystals is also addressed. An intermediate resolution projection map of KirBac3.1 at 6 Å is presented, which sheds (to our knowledge) new light on the structure of this channel in a lipid environment.

Combinatorial approach for large-scale identification of linked peptides from tandem mass spectrometry spectra

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein-protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides.

Correlative fluorescence and electron microscopy of quantum dot labeled proteins on whole cells in liquid

Correlative fluorescence microscopy and scanning transmission electron microscopy (STEM) of cells fully immersed in liquid is a new methodology with many application areas. Proteins, in live cells immobilized on microchips, are labeled with fluorescent quantum dot (QD) nanoparticles. In this protocol, the epidermal growth factor receptor (EGFR) is labeled. The cells are fixed after a selected labeling time, for example, 5 min as needed to form EGFR dimers. The microchip with cells is then imaged with fluorescence microscopy. Thereafter, the microchip with the labeled cells and one with a spacer are assembled in a special microfluidic device and imaged with STEM.

Modeling of proteins and their assemblies with the Integrative Modeling Platform

To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resolution structural characterization of these assemblies is frequently beyond the reach of current experimental methods, such as X-ray crystallography, NMR spectroscopy, electron microscopy, footprinting, chemical cross-linking, FRET spectroscopy, small angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build models of the assembly structures that are consistent with all of the available datasets, and therefore more accurate, precise, and complete. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as well as possible. These generated models can then potentially inform about the precision and accuracy of structure determination, the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific use cases.

Visualization of two distinct states of disassembly in the bacterial V-ATPase from Thermus thermophilus

V-ATPases are multisubunit, membrane-bound, energy-converting, cellular machines whose assembly and disassembly is innately connected to their activity in vivo. In vitro V-ATPases show a propensity for disassembly that greatly complicates their functional, and, in particular, structural characterization. Direct structural evidence for early stages of their disassembly has not been reported yet. We analyzed the structure of the V-ATPase from Thermus thermophilus in a single negatively stained two-dimensional (2-D) crystal both by electron tomography and by electron crystallography. Our analysis demonstrated that for 2-D crystals of fragile macromolecular complexes, which are too heterogenous or too few for the merging of image data from many crystals, single-crystal 3-D reconstructions by electron tomography and electron crystallography are expedient tools of analysis. The asymmetric unit in the 2-D crystal lattice contains two different V-ATPase complexes that appear to be in an early stage of disassembly and with either one or both peripheral stalks not being visualized, suggesting the involvement of the peripheral stalks in early stages of disassembly.

A method for integrative structure determination of protein-protein complexes

MOTIVATION

Structural characterization of protein interactions is necessary for understanding and modulating biological processes. On one hand, X-ray crystallography or NMR spectroscopy provide atomic resolution structures but the data collection process is typically long and the success rate is low. On the other hand, computational methods for modeling assembly structures from individual components frequently suffer from high false-positive rate, rarely resulting in a unique solution.

RESULTS

Here, we present a combined approach that computationally integrates data from a variety of fast and accessible experimental techniques for rapid and accurate structure determination of protein-protein complexes. The integrative method uses atomistic models of two interacting proteins and one or more datasets from five accessible experimental techniques: a small-angle X-ray scattering (SAXS) profile, 2D class average images from negative-stain electron microscopy micrographs (EM), a 3D density map from single-particle negative-stain EM, residue type content of the protein-protein interface from NMR spectroscopy and chemical cross-linking detected by mass spectrometry. The method is tested on a docking benchmark consisting of 176 known complex structures and simulated experimental data. The near-native model is the top scoring one for up to 61% of benchmark cases depending on the included experimental datasets; in comparison to 10% for standard computational docking. We also collected SAXS, 2D class average images and 3D density map from negative-stain EM to model the PCSK9 antigen-J16 Fab antibody complex, followed by validation of the model by a subsequently available X-ray crystallographic structure.

A portable cryo-plunger for on-site intact cryogenic microscopy sample preparation in natural environments

We present a modern, light portable device specifically designed for environmental samples for cryogenic transmission-electron microscopy (cryo-TEM) by on-site cryo-plunging. The power of cryo-TEM comes from preparation of artifact-free samples. However, in many studies, the samples must be collected at remote field locations, and the time involved in transporting samples back to the laboratory for cryogenic preservation can lead to severe degradation artifacts. Thus, going back to the basics, we developed a simple mechanical device that is light and easy to transport on foot yet effective. With the system design presented here we are able to obtain cryo-samples of microbes and microbial communities not possible to culture, in their near-intact environmental conditions as well as in routine laboratory work, and in real time. This methodology thus enables us to bring the power of cryo-TEM to microbial ecology.

Optimized deconvolution for maximum axial resolution in three-dimensional aberration-corrected scanning transmission electron microscopy

Three-dimensional (3D) datasets were recorded of gold nanoparticles placed on both sides of silicon nitride membranes using focal series aberration-corrected scanning transmission electron microscopy (STEM). Deconvolution of the 3D datasets was applied to obtain the highest possible axial resolution. The deconvolution involved two different point spread functions, each calculated iteratively via blind deconvolution. Supporting membranes of different thicknesses were tested to study the effect of beam broadening on the deconvolution. It was found that several iterations of deconvolution was efficient in reducing the imaging noise. With an increasing number of iterations, the axial resolution was increased, and most of the structural information was preserved. Additional iterations improved the axial resolution by maximal a factor of 4 to 6, depending on the particular dataset, and up to 8 nm maximal, but also led to a reduction of the lateral size of the nanoparticles in the image. Thus, the deconvolution procedure optimized for the highest axial resolution is best suited for applications where one is interested in the 3D locations of nanoparticles only.

Macromolecular assembly structures by comparative modeling and electron microscopy

Advances in electron microscopy allow for structure determination of large biological machines at increasingly higher resolutions. A key step in this process is fitting component structures into the electron microscopy-derived density map of their assembly. Comparative modeling can contribute by providing atomic models of the components, via fold assignment, sequence-structure alignment, model building, and model assessment. All four stages of comparative modeling can also benefit from consideration of the density map. In this chapter, we describe numerous types of modeling problems restrained by a density map and available protocols for finding solutions. In particular, we provide detailed instructions for density map-guided modeling using the Integrative Modeling Platform (IMP), MODELLER, and UCSF Chimera.

Three-dimensional morphology of iron oxide nanoparticles with reactive concave surfaces. A compressed sensing-electron tomography (CS-ET) approach

In this paper, we apply electron tomography (ET) to the study of the three-dimensional (3D) morphology of iron oxide nanoparticles (NPs) with reactive concave surfaces. The ability to determine quantitatively the volume and shape of the NP concavity is essential for understanding the key-lock mechanism responsible for the destabilization of gold nanocrystals within the iron oxide NP concavity. We show that quantitative ET is enhanced greatly by the application of compressed sensing (CS) techniques to the tomographic reconstruction. High-fidelity tomograms using a new CS-ET algorithm reveal with clarity the concavities of the particle and enable 3D nanometrology studies to be undertaken with confidence. In addition, the robust performance of the CS-ET algorithm with undersampled data should allow rapid progress with time-resolved 3D nanoscale studies, 3D atomic resolution imaging, and cryo-tomography of nanoscale cellular structures.

Electron microscopy of specimens in liquid

Imaging samples in liquids with electron microscopy can provide unique insights into biological systems, such as cells containing labelled proteins, and into processes of importance in materials science, such as nanoparticle synthesis and electrochemical deposition. Here we review recent progress in the use of electron microscopy in liquids and its applications. We examine the experimental challenges involved and the resolution that can be achieved with different forms of the technique. We conclude by assessing the potential role that electron microscopy of liquid samples can play in areas such as energy storage and bioimaging.

Oxidative doping renders graphene hydrophilic, facilitating its use as a support in biological TEM

Graphene represents the first practical realization of crystalline supports in biological transmission electron microscopy (TEM) since their introduction over 30 years ago. The high transparency, minimal inelastic cross-section, and electrical conductivity of graphene are highly desirable characteristics for a TEM support. However, without a suitable method for rendering graphene supports, hydrophilic applications are limited. This work describes the in situ functionalization of graphene with minimal structural degradation, rendering TEM supports sufficiently hydrophilic for the mounting of biological samples.

Fully hydrated yeast cells imaged with electron microscopy

We demonstrate electron microscopy of fully hydrated eukaryotic cells with nanometer resolution. Living Schizosaccharomyces pombe cells were loaded in a microfluidic chamber and imaged in liquid with scanning transmission electron microscopy (STEM). The native intracellular (ultra)structures of wild-type cells and three different mutants were studied without prior labeling, fixation, or staining. The STEM images revealed various intracellular components that were identified on the basis of their shape, size, location, and mass density. The maximal achieved spatial resolution in this initial study was 32 ± 8 nm, an order of magnitude better than achievable with light microscopy on pristine cells. Light-microscopy images of the same samples were correlated with the corresponding electron-microscopy images. Achieving synergy between the capabilities of light and electron microscopy, we anticipate that liquid STEM will be broadly applied to explore the ultrastructure of live cells.

Imaging Specific Protein Labels on Eukaryotic Cells in Liquid with Scanning Transmission Electron Microscopy

Understanding the structure and dynamics of the protein complexes that underlie cellular function is a central scientific challenge. Biochemical techniques used to identify such complexes would be enhanced by the imaging of specific molecular positions in the context of intact cells, with protein-scale resolution (on the order of a few nanometers). Currently, though, nanometer resolution can only be achieved at the cost of less-direct imaging of the unperturbed cell. Cellular ultrastructure is traditionally studied by transmission electron microscopy (TEM), which yields nanometer resolution on embedded and stained sections, or cryo sections. These cellular samples are neither intact nor in their native liquid state. Light microscopy is used to image protein distributions in fluorescently labeled cells in liquid to investigate cellular function, but even recent improvements in resolution by nanoscopy techniques are still insufficient to resolve the individual constituents of protein complexes. Thus, development of techniques capable of high-resolution imaging in native cellular states would contribute significantly to our understanding of cellular function at the molecular level. The development of liquid compartments that include electron-transparent silicon nitride membrane windows has led to the introduction of a novel concept to achieve nanometer resolution on tagged proteins in cells.

The power of correlative microscopy: multi-modal, multi-scale, multi-dimensional

Correlative microscopy is a sophisticated approach that combines the capabilities of typically separate, but powerful microscopy platforms: often including, but not limited, to conventional light, confocal and super-resolution microscopy, atomic force microscopy, transmission and scanning electron microscopy, magnetic resonance imaging and micro/nano CT (computed tomography). When targeting rare or specific events within large populations or tissues, correlative microscopy is increasingly being recognized as the method of choice. Furthermore, this multi-modal assimilation of technologies provides complementary and often unique information, such as internal and external spatial, structural, biochemical and biophysical details from the same targeted sample. The development of a continuous stream of cutting-edge applications, probes, preparation methodologies, hardware and software developments will enable realization of the full potential of correlative microscopy.

Silicon nitride windows for electron microscopy of whole cells

Silicon microchips with thin, electron transparent silicon nitride windows provide a sample support that accommodates both light-, and electron microscopy of whole eukaryotic cells in vacuum or liquid, with minimum sample preparation steps. The windows are robust enough that cellular samples can be cultured directly onto them, with no addition of a supporting film, and there is no need to embed or section the sample, as is typically required in electron microscopy. By combining two microchips, a microfluidic chamber can be constructed for the imaging of samples in liquid in the electron microscope. We provide microchip design specifications, a fabrication outline, instructions on how to prepare the microchips for biological samples, and examples of images obtained using different light and electron microscopy modalities. The use of these microchips is particularly advantageous for correlative light and electron microscopy.

Three-dimensional locations of gold-labeled proteins in a whole mount eukaryotic cell obtained with 3nm precision using aberration-corrected scanning transmission electron microscopy

Three-dimensional (3D) maps of proteins within the context of whole cells are important for investigating cellular function. However, 3D reconstructions of whole cells are challenging to obtain using conventional transmission electron microscopy (TEM). We describe a methodology to determine the 3D locations of proteins labeled with gold nanoparticles on whole eukaryotic cells. The epidermal growth factor receptors on COS7 cells were labeled with gold nanoparticles, and critical-point dried whole-mount cell samples were prepared. 3D focal series were obtained with aberration-corrected scanning transmission electron microscopy (STEM), without tilting the specimen. The axial resolution was improved with deconvolution. The vertical locations of the nanoparticles in a whole-mount cell were determined with a precision of 3nm. From the analysis of the variation of the axial positions of the labels we concluded that the cellular surface was ruffled. To achieve sufficient stability of the sample under electron beam irradiation during the recording of the focal series, the sample was carbon coated. A quantitative method was developed to analyze the stability of the ultrastructure after electron beam irradiation using TEM. The results of this study demonstrate the feasibility of using aberration-corrected STEM to study the 3D nanoparticle distribution in whole cells.

Exploring the spatial and temporal organization of a cell's proteome

To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and spatial distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome's spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome's organization into a spatially explicit, predictive model of cellular processes.

Modeling of proteins and their assemblies with the integrative modeling platform

To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resolution structural characterization of these assemblies is frequently beyond the reach of current experimental methods, such as X-ray crystallography, NMR spectroscopy, electron microscopy, footprinting, chemical cross-linking, FRET spectroscopy, small-angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build computational models of the assembly structures that are consistent with all of the available datasets. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as much as possible. These generated models can then potentially inform about the precision and accuracy of structure determination, the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific-use cases.

Determining macromolecular assembly structures by molecular docking and fitting into an electron density map

Structural models of macromolecular assemblies are instrumental for gaining a mechanistic understanding of cellular processes. Determining these structures is a major challenge for experimental techniques, such as X-ray crystallography, NMR spectroscopy and electron microscopy (EM). Thus, computational modeling techniques, including molecular docking, are required. The development of most molecular docking methods has so far been focused on modeling of binary complexes. We have recently introduced the MultiFit method for modeling the structure of a multisubunit complex by simultaneously optimizing the fit of the model into an EM density map of the entire complex and the shape complementarity between interacting subunits. Here, we report algorithmic advances of the MultiFit method that result in an efficient and accurate assembly of the input subunits into their density map. The successful predictions and the increasing number of complexes being characterized by EM suggests that the CAPRI challenge could be extended to include docking-based modeling of macromolecular assemblies guided by EM.

Nanometer-resolution electron microscopy through micrometers-thick water layers

Scanning transmission electron microscopy (STEM) was used to image gold nanoparticles on top of and below saline water layers of several micrometers thickness. The smallest gold nanoparticles studied had diameters of 1.4 nm and were visible for a liquid thickness of up to 3.3 microm. The imaging of gold nanoparticles below several micrometers of liquid was limited by broadening of the electron probe caused by scattering of the electron beam in the liquid. The experimental data corresponded to analytical models of the resolution and of the electron probe broadening as function of the liquid thickness. The results were also compared with Monte Carlo simulations of the STEM imaging on modeled specimens of similar geometry and composition as used for the experiments. Applications of STEM imaging in liquid can be found in cell biology, e.g., to study tagged proteins in whole eukaryotic cells in liquid and in materials science to study the interaction of solid:liquid interfaces at the nanoscale.

Correlative fluorescence microscopy and scanning transmission electron microscopy of quantum-dot-labeled proteins in whole cells in liquid

Correlative fluorescence microscopy and transmission electron microscopy (TEM) is a state-of-the-art microscopy methodology to study cellular function, combining the functionality of light microscopy with the high resolution of electron microscopy. However, this technique involves complex sample preparation procedures due to its need for either thin sections or frozen samples for TEM imaging. Here, we introduce a novel correlative approach capable of imaging whole eukaryotic cells in liquid with fluorescence microscopy and with scanning transmission electron microscopy (STEM); there is no additional sample preparation necessary for the electron microscopy. Quantum dots (QDs) were bound to epidermal growth factor (EGF) receptors of COS7 fibroblast cells. Fixed whole cells in saline water were imaged with fluorescence microscopy and subsequently with STEM. The STEM images were correlated with fluorescence images of the same cellular regions. QDs of dimensions 7x12 nm were visible in a 5 microm thick layer of saline water, consistent with calculations. A spatial resolution of 3 nm was achieved on the QDs.

Integrative structure modeling of macromolecular assemblies from proteomics data

Proteomics techniques have been used to generate comprehensive lists of protein interactions in a number of species. However, relatively little is known about how these interactions result in functional multiprotein complexes. This gap can be bridged by combining data from proteomics experiments with data from established structure determination techniques. Correspondingly, integrative computational methods are being developed to provide descriptions of protein complexes at varying levels of accuracy and resolution, ranging from complex compositions to detailed atomic structures.

Averaging of electron subtomograms and random conical tilt reconstructions through likelihood optimization

The reference-free averaging of three-dimensional electron microscopy (3D-EM) reconstructions with empty regions in Fourier space represents a pressing problem in electron tomography and single-particle analysis. We present a maximum likelihood algorithm for the simultaneous alignment and classification of subtomograms or random conical tilt (RCT) reconstructions, where the Fourier components in the missing data regions are treated as hidden variables. The behavior of this algorithm was explored using tests on simulated data, while application to experimental data was shown to yield unsupervised class averages for subtomograms of groEL/groES complexes and RCT reconstructions of p53. The latter application served to obtain a reliable de novo structure for p53 that may resolve uncertainties about its quaternary structure.

Three-dimensional scanning transmission electron microscopy of biological specimens

A three-dimensional (3D) reconstruction of the cytoskeleton and a clathrin-coated pit in mammalian cells has been achieved from a focal-series of images recorded in an aberration-corrected scanning transmission electron microscope (STEM). The specimen was a metallic replica of the biological structure comprising Pt nanoparticles 2-3 nm in diameter, with a high stability under electron beam radiation. The 3D dataset was processed by an automated deconvolution procedure. The lateral resolution was 1.1 nm, set by pixel size. Particles differing by only 10 nm in vertical position were identified as separate objects with greater than 20% dip in contrast between them. We refer to this value as the axial resolution of the deconvolution or reconstruction, the ability to recognize two objects, which were unresolved in the original dataset. The resolution of the reconstruction is comparable to that achieved by tilt-series transmission electron microscopy. However, the focal-series method does not require mechanical tilting and is therefore much faster. 3D STEM images were also recorded of the Golgi ribbon in conventional thin sections containing 3T3 cells with a comparable axial resolution in the deconvolved dataset.

Nanoscale imaging of whole cells using a liquid enclosure and a scanning transmission electron microscope

Nanoscale imaging techniques are needed to investigate cellular function at the level of individual proteins and to study the interaction of nanomaterials with biological systems. We imaged whole fixed cells in liquid state with a scanning transmission electron microscope (STEM) using a micrometer-sized liquid enclosure with electron transparent windows providing a wet specimen environment. Wet-STEM images were obtained of fixed E. coli bacteria labeled with gold nanoparticles attached to surface membrane proteins. Mammalian cells (COS7) were incubated with gold-tagged epidermal growth factor and fixed. STEM imaging of these cells resulted in a resolution of 3 nm for the gold nanoparticles. The wet-STEM method has several advantages over conventional imaging techniques. Most important is the capability to image whole fixed cells in a wet environment with nanometer resolution, which can be used, e.g., to map individual protein distributions in/on whole cells. The sample preparation is compatible with that used for fluorescent microscopy on fixed cells for experiments involving nanoparticles. Thirdly, the system is rather simple and involves only minimal new equipment in an electron microscopy (EM) laboratory.

Single particle electron microscopy

Electron microscopy (EM) in combination with image analysis is a powerful technique to study protein structures at low, medium, and high resolution. Since electron micrographs of biological objects are very noisy, improvement of the signal-to-noise ratio by image processing is an integral part of EM, and this is performed by averaging large numbers of individual projections. Averaging procedures can be divided into crystallographic and non-crystallographic methods. The crystallographic averaging method, based on two-dimensional (2D) crystals of (membrane) proteins, yielded in solving atomic protein structures in the last century. More recently, single particle analysis could be extended to solve atomic structures as well. It is a suitable method for large proteins, viruses, and proteins that are difficult to crystallize. Because it is also a fast method to reveal the low-to-medium resolution structures, the impact of its application is growing rapidly. Technical aspects, results, and possibilities are presented.

Advances in imaging secondary ion mass spectrometry for biological samples

Imaging mass spectrometry combines the power of mass spectrometry to identify complex molecules based on mass with sample imaging. Recent advances in secondary ion mass spectrometry have improved sensitivity and spatial resolution, so that these methods have the potential to bridge between high-resolution structures obtained by X-ray crystallography and cyro-electron microscopy and ultrastructure visualized by conventional light microscopy. Following background information on the method and instrumentation, we address the key issue of sample preparation. Because mass spectrometry is performed in high vacuum, it is essential to preserve the lateral organization of the sample while removing bulk water, and this has been a major barrier for applications to biological systems. Recent applications of imaging mass spectrometry to cell biology, microbial communities, and biosynthetic pathways are summarized briefly, and studies of biological membrane organization are described in greater depth.

FitEM2EM--tools for low resolution study of macromolecular assembly and dynamics

Studies of the structure and dynamics of macromolecular assemblies often involve comparison of low resolution models obtained using different techniques such as electron microscopy or atomic force microscopy. We present new computational tools for comparing (matching) and docking of low resolution structures, based on shape complementarity. The matched or docked objects are represented by three dimensional grids where the value of each grid point depends on its position with regard to the interior, surface or exterior of the object. The grids are correlated using fast Fourier transformations producing either matches of related objects or docking models depending on the details of the grid representations. The procedures incorporate thickening and smoothing of the surfaces of the objects which effectively compensates for differences in the resolution of the matched/docked objects, circumventing the need for resolution modification. The presented matching tool FitEM2EMin successfully fitted electron microscopy structures obtained at different resolutions, different conformers of the same structure and partial structures, ranking correct matches at the top in every case. The differences between the grid representations of the matched objects can be used to study conformation differences or to characterize the size and shape of substructures. The presented low-to-low docking tool FitEM2EMout ranked the expected models at the top.

Flexible fitting of high-resolution x-ray structures into cryoelectron microscopy maps using biased molecular dynamics simulations

A methodology for flexible fitting of all-atom high-resolution structures into low-resolution cryoelectron microscopy (cryo-EM) maps is presented. Flexibility of the modeled structure is simulated by classical molecular dynamics and an additional effective potential is introduced to enhance the fitting process. The additional potential is proportional to the correlation coefficient between the experimental cryo-EM map and a synthetic map generated for an all-atom structure being fitted to the map. The additional forces are calculated as a gradient of the correlation coefficient. During the molecular dynamics simulations under the additional forces, the molecule undergoes a conformational transition that maximizes the correlation coefficient, which results in a high-accuracy fit of all-atom structure into a cryo-EM map. Using five test proteins that exhibit structural rearrangement during their biological activity, we demonstrate performance of our method. We also test our method on the experimental cryo-EM of elongation factor G and show that the model obtained is comparable to previous studies. In addition, we show that overfitting can be avoided by assessing the quality of the fitted model in terms of correlation coefficient and secondary structure preservation.