Combined scanning probe and total internal reflection fluorescence microscopy

Combining scanning probe and optical microscopy represents a powerful approach for investigating structure-function relationships and dynamics of biomolecules and biomolecular assemblies, often in situ and in real-time. This platform technology allows us to obtain three-dimensional images of individual molecules with nanometer resolution, while simultaneously characterizing their structure and interactions though complementary techniques such as optical microscopy and spectroscopy. We describe herein the practical strategies for the coupling of scanning probe and total internal reflection fluorescence microscopy along with challenges and the potential applications of such platforms, with a particular focus on their application to the study of biomolecular interactions at membrane surfaces.     

Difficult macromolecular structures determined using X-ray diffraction techniques

Macromolecular crystallography has been, for the last few decades, the main source of structural information of biological macromolecular systems and it is one of the most powerful techniques for the analysis of enzyme mechanisms and macromolecular interactions at the atomic level. In addition, it is also an extremely powerful tool for drug design. Recent technological and methodological developments in macromolecular X-ray crystallography have allowed solving structures that until recently were considered difficult or even impossible, such as structures at atomic or subatomic resolution or large macromolecular complexes and assemblies at low resolution. These developments have also helped to solve the 3D-structure of macromolecules from twin crystals. Recently, this technique complemented with cryo-electron microscopy and neutron crystallography has provided the structure of large macromolecular machines with great precision allowing understanding of the mechanisms of their function.     

Correlative light-electron microscopy reveals the tubular-saccular ultrastructure of carriers operating between Golgi apparatus and plasma membrane

Transport intermediates (TIs) have a central role in intracellular traffic, and much effort has been directed towards defining their molecular organization. Unfortunately, major uncertainties remain regarding their true structure in living cells. To address this question, we have developed an approach based on the combination of the green fluorescent protein technology and correlative light-electron microscopy, by which it is possible to monitor an individual carrier in vivo and then take a picture of its ultrastructure at any moment of its life-cycle. We have applied this technique to define the structure of TIs operating from the Golgi apparatus to the plasma membrane, whose in vivo dynamics have been characterized recently by light microscopy. We find that these carriers are large (ranging from 0.3-1.7 microm in maximum diameter, nearly half the size of a Golgi cisterna), comprise almost exclusively tubular-saccular structures, and fuse directly with the plasma membrane, sometimes minutes after docking to the fusion site.     

Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins.     

Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins.     

Subdiffraction‐resolution live‐cell imaging for visualizing thylakoid membranes

The chloroplast is the chlorophyll‐containing organelle that produces energy through photosynthesis. Within the chloroplast is an intricate network of thylakoid membranes containing photosynthetic membrane proteins that mediate electron transport and generate chemical energy. Historically, electron microscopy (EM) has been a powerful tool for visualizing the macromolecular structure and organization of thylakoid membranes. However, an understanding of thylakoid membrane dynamics remains elusive because EM requires fixation and sectioning. To improve our knowledge of thylakoid membrane dynamics we need to consider at least two issues: (i) the live‐cell imaging conditions needed to visualize active processes in vivo; and (ii) the spatial resolution required to differentiate the characteristics of thylakoid membranes. Here, we utilize three‐dimensional structured illumination microscopy (3D‐SIM) to explore the optimal imaging conditions for investigating the dynamics of thylakoid membranes in living plant and algal cells. We show that 3D‐SIM is capable of examining broad characteristics of thylakoid structures in chloroplasts of the vascular plant Arabidopsis thaliana and distinguishing the structural differences between wild‐type and mutant strains. Using 3D‐SIM, we also visualize thylakoid organization in whole cells of the green alga Chlamydomonas reinhardtii. These data reveal that high light intensity changes thylakoid membrane structure in C. reinhardtii. Moreover, we observed the green alga Chromochloris zofingiensis and the moss Physcomitrella patens to show the applicability of 3D‐SIM. This study demonstrates that 3D‐SIM is a promising approach for studying the dynamics of thylakoid membranes in photoautotrophic organisms during photoacclimation processes.     

Conformational changes studied by cryo-electron microscopy

Biological processes involving movement, such as muscle contraction or the opening of an ion channel through a membrane, are mediated through conformational changes. These changes often occur in large and flexible macromolecular complexes. Cryo-electron microscopy provides a means of capturing different conformational states of such assemblies. Even if the resulting density maps are at low resolution, they can be combined with atomic structures of subcomplexes or isolated components determined by X-ray crystallography or NMR. This review presents a brief summary of the principles and recent advances in macromolecular structure determination by cryo-electron microscopy.     

Probing the Machinery of Intracellular Trafficking with the Atomic Force Microscope

Atomic force microscopy has emerged as a powerful tool for characterizing single biological macromolecules, macromolecular assemblies, and whole cells in aqueous buffer, in real time, and at molecular-scale spatial and force resolution. Many of the central elements of intracellular transport are tens to hundreds of nanometers in size and highly dynamic. Thus, atomic force microscopy provides a valuable means of addressing questions of structure and mechanism in intracellular transport. We begin this review of recent efforts to apply atomic force microscopy to problems in intracellular transport by discussing the technical principles behind atomic force microscopy. We then turn to three specific areas in which atomic force microscopy has been applied to problems with direct implications for intracellular trafficking: cytoskeletal structure and dynamics, vesicular transport, and receptor–ligand interactions. In each case, we discuss studies which use both intact cellular elements and reconstituted models. While many technical challenges remain, these studies point to several areas where atomic force microscopy can be used to provide valuable insight into intracellular transport at exquisite spatial and energetic resolution.     

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Single particle analysis for structure determination in cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are not designed to handle heterogeneous mixtures of structures from many distinct macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. The feasibility of this approach is first demonstrated on a large set of synthetic reprojections from 35 unique macromolecular structures spanning a mass range of hundreds to thousands of kilodaltons. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort single particle cryo-EM data from extremely heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.     

A core-weighted fitting method for docking atomic structures into low-resolution maps: application to cryo-electron microscopy

Cryo-electron microscopy of "single particles" is a powerful method to analyze structures of large macromolecular assemblies that are not amenable to investigation by traditional X-ray crystallographic methods. A key step in these studies is to obtain atomic interpretations of multiprotein complexes by fitting atomic structures of individual components into maps obtained from electron microscopic data. Here, we report the use of a "core-weighting" method, combined with a grid-threading Monte Carlo (GTMC) approach for this purpose. The "core" of an individual structure is defined to represent the part where the density distribution is least likely to be altered by other components that comprise the macromolecular assembly of interest. The performance of the method has been evaluated by its ability to determine the correct fit of (i) the alpha-chain of the T-cell receptor variable domain into a simulated map of the alphabeta complex at resolutions between 5 and 40 A, and (ii) the E2 catalytic domain of the pyruvate dehydrogenase into an experimentally determined map, at 14 A resolution, of the icosahedral complex formed by 60 copies of this enzyme. Using the X-ray structures of the two test cases as references, we demonstrate that, in contrast to more traditional methods, the combination of the core-weighting method and the grid-threading Monte Carlo approach can identify the correct fit reliably and rapidly from the low-resolution maps that are typical of structures determined with the use of single-particle electron microscopy.     

How to minimize dye-induced perturbations while studying biomembrane structure and dynamics: PEG linkers as a rational alternative

Organic dye-tagged lipid analogs are essential for many fluorescence-based investigations of complex membrane structures, especially when using advanced microscopy approaches. However, lipid analogs may interfere with membrane structure and dynamics, and it is not obvious that the properties of lipid analogs would match those of non-labeled host lipids. In this work, we bridged atomistic simulations with super-resolution imaging experiments and biomimetic membranes to assess the performance of commonly used sphingomyelin-based lipid analogs. The objective was to compare, on equal footing, the relative strengths and weaknesses of acyl chain labeling, headgroup labeling, and labeling based on poly-ethyl-glycol (PEG) linkers in determining biomembrane properties. We observed that the most appropriate strategy to minimize dye-induced membrane perturbations and to allow consideration of Brownian-like diffusion in liquid-ordered membrane environments is to decouple the dye from a membrane by a PEG linker attached to a lipid headgroup. Yet, while the use of PEG linkers may sound a rational and even an obvious approach to explore membrane dynamics, the results also suggest that the dyes exploiting PEG linkers interfere with molecular interactions and their dynamics. Overall, the results highlight the great care needed when using fluorescent lipid analogs, in particular accurate controls.     

Markov state modeling of membrane transport proteins

The flux of ions and molecules in and out of the cell is vital for maintaining the basis of various biological processes. The permeation of substrates across the cellular membrane is mediated through the function of specialized integral membrane proteins commonly known as membrane transporters. These proteins undergo a series of structural rearrangements that allow a primary substrate binding site to be accessed from either side of the membrane at a given time. Structural insights provided by experimentally resolved structures of membrane transporters have aided in the biophysical characterization of these important molecular drug targets. However, characterizing the transitions between conformational states remains challenging to achieve both experimentally and computationally. Though molecular dynamics simulations are a powerful approach to provide atomistic resolution of protein dynamics, a recurring challenge is its ability to efficiently obtain relevant timescales of large conformational transitions as exhibited in transporters. One approach to overcome this difficulty is to adaptively guide the simulation to favor exploration of the conformational landscape, otherwise known as adaptive sampling. Furthermore, such sampling is greatly benefited by the statistical analysis of Markov state models. Historically, the use of Markov state models has been effective in quantifying slow dynamics or long timescale behaviors such as protein folding. Here, we review recent implementations of adaptive sampling and Markov state models to not only address current limitations of molecular dynamics simulations, but to also highlight how Markov state modeling can be applied to investigate the structure–function mechanisms of large, complex membrane transporters.     

细菌分泌系统的结构及作用机制研究进展

细菌分泌系统（bacterial secretion systems）是一类存在于细菌细胞膜上的大分子复合物，是结构复杂的跨膜分子机器，可为多种细菌的效应物提供分泌途径。目前已经发现了9种细菌分泌系统，即T1SS~T9SS，在细菌的生存及致病力方面发挥着重要作用。随着X射线晶体学（X-ray crystallography）、核磁共振（nuclear magnetic resonance，NMR）及冷冻电镜（cryo-electron microscopy，Cryo-EM）等技术手段的发展与应用，这些大分子复合物的三维结构也得到了一定程度的解析，极大增强了人类对于细菌分泌系统转运底物复杂机制的理解。因此，本文结合近年来关于细菌T1SS~T9SS的研究进展，对各分泌系统的结构信息进行了系统整合，总结了这些分泌系统的分子作用机制，并对其未来的发展方向进行了展望，以期为与细菌蛋白质分泌相关的致病、耐药、环境适应性等机制的研究奠定理论基础，为进一步开发以分泌系统结构为基础的小分子抑菌物质提供精准的三维靶标。     

TROSY and CRINEPT: NMR with large molecular and supramolecular structures in solution

TROSY and CRINEPT are new techniques for solution NMR studies of molecular and supramolecular structures. They allow the collection of high-resolution spectra of structures with molecular weights >100 kDa, significantly extending the range of macromolecular systems that can be studied by NMR in solution. TROSY has already been used to map protein-protein interfaces, to conduct structural studies on membrane proteins and to study nucleic acid conformations in multimolecular assemblies. These techniques will help us to investigate the conformational states of individual macromolecular components and will support de novo protein structure determination in large supramolecular structures.     

Advances in mass spectrometry-based footprinting of membrane proteins

Structural biology is entering an exciting time where many new high-resolution structures of large complexes and membrane proteins (MPs) are determined regularly. These advances have been driven by over 15 years of technological improvements, first in macromolecular crystallography, and recently in cryo-electron microscopy. Obtaining information about MP higher order structure and interactions is also a frontier, important but challenging owing to their unique properties and the need to choose suitable detergents/lipids for their study. The development of mass spectrometry (MS), both instruments and methodology in the past 10 years, has also advanced it as a complementary method to study MP structure and interactions. In this review, we discuss advances in MS-based footprinting for MPs and highlight recent methodologies that offer new promise for MP study by chemical footprinting and mass spectrometry.     

108 Individual-particle electron tomography: a method for studying macromolecule dynamics

In solution, macromolecules are naturally flexible and dynamic. Dynamic personalities and structural heterogeneities of macromolecules are essential to understanding their proper function (Karplus & Kuriyan, 2005). However, structural determination of dynamic/heterogeneous macromolecules is limited by current technology such as: X-ray crystallography, nuclear magnetic resonance spectrum, small angle scattering, and electron microscopy single-particle reconstruction. A common weakness of all current techniques is requiring an averaged signal from thousands to millions of different macromolecules. Using averaged “signal” must involve in an assumption that macromolecules remain in identical structures or few identical conformations. This assumption is a good estimate for some macromolecule that have a rigid body, but not for most macromolecules that have “soft”, flexible, and dynamic body, such as lipoproteins and antibodies. An ideal approach for structure determination regardless of macromolecular dynamics is to use non-averaged signal, i.e. the signal from a single macromolecule itself. We developed a ‘‘focused electron tomography reconstruction’’ (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance macromolecule (Zhang & Ren, 2012). FETR can tolerate certain levels of image distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. Since this approach can obtain the structure of a single-instance macromolecule, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single ‘‘snapshot’’ of molecule structure determination (Zhang & Ren, 2012). FETR/IPET provides a completely new opportunity for a single-macromolecule structure determination, and could be used to study the dynamic character, equilibrium fluctuation, to reveal macromolecular mechanism, and even to track the intermediate state of the reaction of macromolecules (Zhang et al., 2010; Zhang & Ren, 2010).     

Normal mode based flexible fitting of high-resolution structure into low-resolution experimental data from cryo-EM

A new method for the flexible fitting of high-resolution structures into low-resolution maps of macromolecular complexes from electron microscopy has been recently described in applications to simulated electron density maps. This method uses a linear combination of low-frequency normal modes in an iterative manner to deform the structure optimally to conform to the low-resolution electron density map. Gradient-following techniques in the coordinate space of collective normal modes are used to optimize the overall correlation coefficient between computed and measured electron densities. With this approach, multi-scale flexible fitting can be performed using all-atoms or Calpha atoms. In this paper, illustrative studies of normal mode based flexible fitting to experimental cryo-EM maps are presented for three different systems. Large, functionally relevant conformational changes for elongation factor G bound to the ribosome, Escherichia coli RNA polymerase and cowpea chlorotic mottle virus are elucidated as the result of the application of NMFF from high-resolution structures to cryo-electron microscopy maps.     

Nuclear egress of herpesviruses

Herpesviruses assemble and fill their capsids in the infected cell nucleus,and must then move this enormous macromolecular assembly across the nuclear membrane and into the cytoplasm.Doing so is a complex,multi-step process that involves envelopment of the capsid at the inner nuclear membrane and de-envelopment by fusion with the outer nuclear membrane.This process is orchestrated by viral proteins,but requires the modification of cellular structures and mechanisms including the nuclear lamina.In this review I summarize recent research on the mechanism of nuclear envelopment and the viral and cellular systems involved in its execution.     

Computational studies of membrane channels

The determination of the structure of several members of the K+ channel and aquaporin family represents a unique opportunity to explain the mechanism of these biomolecular systems. With their ability to go beyond static structures, molecular dynamics simulations offer a unique route for relating functional properties to membrane channel structure. The recent progress in this area is reviewed.     

Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins

One of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures.