Novel image processing tools and techniques in cryo-electron microscopy

The software resources in cryo-EM have to deal with stacks of hundreds of “8k” images. To process this amount of data, a fast and efficient software tool is required. For this, a performance oriented C++ toolkit named EMKIT was developed. This toolkit can be used to accomplish fast basic operations using in-built classes and methods. Furthermore, complex features can be conveniently built using the toolkit. After the advent of DEDs the amount of data that comes out of the microscopes has drastically increased. Today, there exists a handful of software which can automate the data collection process on microscopes. Target spots on the grid are selected and the microscope automatically records images on these spots. With some tricks the microscopes can now yield a new image every minute. This allows obtaining more data in the limited microscope-time. But it is quite important that this data can be processed in real time to get an idea if the recording is running as expected. Focus was designed to accomplish this task in a user friendly environment. One of the classical methods in electron microscopy is 2D electron crystallography. Obtaining highly-ordered 2D crystals is difficult and time-consuming. However, 2D crystals diffracting to only 10-12Å can be prepared relatively conveniently in most cases. There is a need to develop image processing algorithms allowing to generate high resolution 3D structure from cryo-EM images of badly ordered crystals. Apart from that, while recording tilted 2D crystals, there is a limitation to the possible extent of tilt. This limitation arises due to considerations such as sample movement, increase in thickness of sample with tilt and varying defocus. The achievable tilt angle is typically 60 degrees. This would mean that in 3D Fourier space, the slices with tilt angle beyond this would be missing. This region in Fourier space turns out to be conical in shape and hence this problem in 2D electron crystallography is known as the “problem of missing cone”. In real space, this makes the densities look elongated in the vertical direction. Apart from the missing cone, data can also be missing in other regions, depending on the tilt sampling. New methods have been developed which can tackle the problems stated above to some extent including (i) movie-mode unbending, which performs frame-wise unbending in the recorded movie frames; (ii) refinement over sub-tiles of the frames in order to locally refine the crystal tilt geometry within different tile locations on the images; (iii) a projective constraint optimisation refinement for approximating the Fourier data in the region of missing cone. All of these methods were applied to MloK1 membrane protein. MloK1, a cyclic nucleotide-modulated potassium channel from Mesorhizobium loti, is a homologue of human HCN (Hyperpolarization-activated Cyclic Nucleotide-gated) channels important for signal transduction and pacemaking. MloK1 in the presence of lipids forms micrometer-large 2D crystals diffracting only up to 10Å. Using newly developed methods, we determined the three-dimensional (3D) map of full-length MloK1 in the presence of cAMP at the resolution of 4.5Å

Performance of Integrated IoT Network with Hybrid mmWave/FSO/THz Backhaul Link

Establishing end-to-end connectivity of Internet of Things (IoT) network with the core for collecting sensing data from remote and hard-to-reach terrains is a challenging task. In this article, we analyze the performance of an IoT network integrated with wireless backhaul link for data collection. We propose a solution that involves a self-configuring protocol for aggregate node (AN) selection in an IoT network, which sends the data packet to an unmanned aerial vehicle (UAV) over radio frequency (RF) channels. We adopt a novel hybrid transmission technique for wireless backhaul employing opportunistic selections combining (OSC) and maximal ratio combining (MRC) that simultaneously transmits the data packet on mmWave (mW), free space optical (FSO), and terahertz (THz) technologies to take advantage of their complementary characteristics. We employ the decode-and-forward (DF) protocol to integrate the IoT and backhaul links and provide physical layer performance assessment using outage probability and average bit-error-rate (BER) under diverse channel conditions. We also develop simplified expressions to gain a better understanding of the system's performance at high signal-to-noise ratio (SNR). We provide computer simulations to compare different wireless backhaul technologies under various channel and SNR scenarios and demonstrate the performance of the data collection using the integrated link.Comment: This work has been submitted to IEEE for possible publicatio

3D reconstruction of two-dimensional crystals

Electron crystallography of two-dimensional (2D) crystals determines the structure of membrane proteins in the lipid bilayer by imaging with cryo-electron microscopy and image processing. Membrane proteins can be packed in regular 2D arrays by their reconstitution in the presence of lipids at low lipid to protein weight-to-weight ratio. The crystal quality depends on the protein purity and homogeneity, its stability, and on the crystallization conditions. A 2D crystal presents the membrane protein in a functional and fully lipidated state. Electron crystallography determines the 3D structure even of small membrane proteins up to atomic resolution, but 3D density maps have a better resolution in the membrane plane than in the vertical direction. This problem can be partly eliminated by applying an iterative algorithm that exploits additional known constraints about the 2D crystal. 2D electron crystallography is particularly attractive for the structural analysis of membrane proteins that are too small for single particle analyses and too unstable to form 3D crystals. With the recent introduction of direct electron detector cameras, the routine determination of the atomic 3D structure of membrane-embedded membrane proteins is in reach. (C) 2015 Published by Elsevier Inc

3D reconstruction of two-dimensional crystals

Electron crystallography of two-dimensional (2D) crystals determines the structure of membrane proteins in the lipid bilayer by imaging with cryo-electron microscopy and image processing. Membrane proteins can be packed in regular 2D arrays by their reconstitution in the presence of lipids at low lipid to protein weight-to-weight ratio. The crystal quality depends on the protein purity and homogeneity, its stability, and on the crystallization conditions. A 2D crystal presents the membrane protein in a functional and fully lipidated state. Electron crystallography determines the 3D structure even of small membrane proteins up to atomic resolution, but 3D density maps have a better resolution in the membrane plane than in the vertical direction. This problem can be partly eliminated by applying an iterative algorithm that exploits additional known constraints about the 2D crystal. 2D electron crystallography is particularly attractive for the structural analysis of membrane proteins that are too small for single particle analyses and too unstable to form 3D crystals. With the recent introduction of direct electron detector cameras, the routine determination of the atomic 3D structure of membrane-embedded membrane proteins is in reach

An analysis of oligomerization interfaces in transmembrane proteins

Background The amount of transmembrane protein (TM) structures solved to date is now large enough to attempt large scale analyses. In particular, extensive studies of oligomeric interfaces in the transmembrane region are now possible. Results We have compiled the first fully comprehensive set of validated transmembrane protein interfaces in order to study their features and assess what differentiates them from their soluble counterparts. Conclusions The general features of TM interfaces do not differ much from those of soluble proteins: they are large, tightly packed and possess many interface core residues. In our set, membrane lipids were not found to significantly mediate protein-protein interfaces. Although no G protein-coupled receptor (GPCR) was included in the validated set, we analyzed the crystallographic dimerization interfaces proposed in the literature. We found that the putative dimer interfaces proposed for class A GPCRs do not show the usual patterns of stable biological interfaces, neither in terms of evolution nor of packing, thus they likely correspond to crystal interfaces. We cannot however rule out the possibility that they constitute transient or weak interfaces. In contrast we do observe a clear signature of biological interface for the proposed dimer of the class F human Smoothened receptor.ISSN:1472-680

Retrieving high-resolution information from disordered 2D crystals by single-particle cryo-EM

Electron crystallography can reveal the structure of membrane proteins within 2D crystals under close-to-native conditions. High-resolution structural information can only be reached if crystals are perfectly flat and highly ordered. In practice, such crystals are difficult to obtain. Available image unbending algorithms correct for disorder, but only perform well on images of non-tilted, flat crystals, while out-of-plane distortions are not addressed. Here, we present an approach that employs single-particle refinement procedures to locally unbend crystals in 3D. With this method, density maps of the MloK1 potassium channel with a resolution of 4 A were obtained from images of 2D crystals that do not diffract beyond 10 A. Furthermore, 3D classification allowed multiple structures to be resolved, revealing a series of MloK1 conformations within a single 2D crystal. This conformational heterogeneity explains the poor diffraction observed and is related to channel function. The approach is implemented in the FOCUS package

A PDB-wide, evolution-based assessment of protein–protein interfaces

Background Thanks to the growth in sequence and structure databases, more than 50 million sequences are now available in UniProt and 100,000 structures in the PDB. Rich information about protein-protein interfaces can be obtained by a comprehensive study of protein contacts in the PDB, their sequence conservation and geometric features. Results An automated computational pipeline was developed to run our Evolutionary protein-protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces. This allows the analysis of interface data on a PDB-wide scale. Two large benchmark datasets of biological interfaces and crystal contacts, each containing about 3000 entries, were automatically generated based on criteria thought to be strong indicators of interface type. The BioMany set of biological interfaces includes NMR dimers solved as crystal structures and interfaces that are preserved across diverse crystal forms, as catalogued by the Protein Common Interface Database (ProtCID) from Xu and Dunbrack. The second dataset, XtalMany, is derived from interfaces that would lead to infinite assemblies and are therefore crystal contacts. BioMany and XtalMany were used to benchmark the EPPIC approach. The performance of EPPIC was also compared to classifications from the Protein Interfaces, Surfaces, and Assemblies (PISA) program on a PDB-wide scale, finding that the two approaches give the same call in about 88% of PDB interfaces. By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB. Additionally, we developed a PyMOL plugin for direct download and easy visualization of EPPIC interfaces for any PDB entry. Both the datasets and the PyMOL plugin are available at http://www.eppic-web.org/ewui/#downloads. Conclusions Our computational pipeline allows us to analyze protein-protein contacts and their sequence conservation across the entire PDB. Two new benchmark datasets are provided, which are over an order of magnitude larger than existing manually curated ones. These tools enable the comprehensive study of several aspects of protein-protein contacts in the PDB and represent a basis for future, even larger scale studies of protein-protein interactions.ISSN:1472-680

Theoretical and Computational Analysis of Static and Dynamic Anomalies in Water-DMSO Binary Mixture at Low DMSO Concentrations

Experiments have repeatedly observed both thermodynamic and dynamic anomalies in aqueous binary mixtures, surprisingly at low solute concentration. Examples of such binary mixtures include water-DMSO, water-ethanol, water-tertiary butyl alcohol (TBA), and water-dioxane, to name a few. The anomalies have often been attributed to the onset of a structural transition, whose nature, however, has been left rather unclear. Here we study the origin of such anomalies using large scale computer simulations and theoretical analysis in water-DMSO binary mixture. At very low DMSO concentration (below 10%), small aggregates of DMSO are solvated by water through the formation of DMSO-(H2O)(2) moieties. As the concentration is increased beyond 10-12% of DMSO, spanning clusters comprising the same moieties appear in the system. Those clusters are formed and stabilized not only through H-bonding but also through the association of CH3 groups of DMSO. We attribute the experimentally observed anomalies to a continuum percolation-like transition at DMSO concentration X-DMSO approximate to 12-15%. The largest cluster size of CH3-CH3 aggregation clearly indicates the formation of such percolating clusters. As a result, a significant slowing down is observed in the decay of associated rotational auto time correlation functions (of the S = O bond vector of DMSO and O-H bond vector of water). Markedly unusual behavior in the mean square fluctuation of total dipole moment again suggests a structural transition around the same concentration range. Furthermore, we map our findings to an interacting lattice model which substantiates the continuum percolation model as the reason for low concentration anomalies in binary mixtures where the solutes involved have both hydrophilic and hydrophobic moieties

Image processing techniques for high-resolution structure determination from badly ordered 2D crystals

2D electron crystallography can be used to study small membrane proteins in their native environment. Obtaining highly ordered 2D crystals is difficult and time-consuming. However, 2D crystals diffracting to only 10–12 Å can be prepared relatively conveniently in most cases. We have developed image-processing algorithms allowing to generate a high resolution 3D structure from cryo-electron crystallography images of badly ordered crystals. These include movie-mode unbending, refinement over sub-tiles of the images in order to locally refine the sample tilt geometry, implementation of different CTF correction schemes, and an iterative method to apply known constraints in the real and reciprocal space to approximate amplitudes and phases in the so-called missing cone regions. These algorithms applied to a dataset of the potassium channel MloK1 show significant resolution improvements to better than 5 Å.ISSN:1047-8477ISSN:1095-865