Conical Fourier shell correlation applied to electron tomograms.

BackgroundCryo-electron tomography is an important tool to study structures of macromolecular complexes in close to native states. A whole cell cryo electron tomogram contains structural information of all its macromolecular complexes. However, extracting this information remains challenging, and relies on sophisticated image processing, in particular for template-free particle extraction, classification and averaging. To develop these methods it is crucial to realistically simulate tomograms of crowded cellular environments, which can then serve as ground truth models for assessing and optimizing methods for detection of complexes in cell tomograms.ResultsWe present a framework to generate crowded mixtures of macromolecular complexes for realistically simulating cryo electron tomograms including noise and image distortions due to the missing-wedge effects. Simulated tomograms are then used for assessing the template-free Difference-of-Gaussian (DoG) particle-picking method to detect complexes of different shapes and sizes under various crowding and noise levels. We identified DoG parameter settings that maximize precision and recall for detecting particles over a wide range of sizes and shapes. We observed that medium sized DoG scaling factors showed the overall best performance. To further improve performance, we propose a combination strategy for integrating results from multiple parameter settings. With increasing macromolecular crowding levels, the precision of particle picking remained relatively high, while the recall was dramatically reduced, which limits the detection of sufficient copy numbers of complexes in a crowded environment. Over a wide range of increasing noise levels, the DoG particle picking performance remained stable, but dramatically reduced beyond a specific noise threshold.ConclusionsAutomatic and reference-free particle picking is an important first step in a visual proteomics analysis of cell tomograms. However, cell cytoplasm is highly crowded, which makes particle detection challenging. It is therefore important to test particle-picking methods in a realistic crowded setting. Here, we present a framework for simulating tomograms of cellular environments at high crowding levels and assess the DoG particle picking method. We determined optimal parameter settings to maximize the performance of the DoG particle-picking method.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1283-3) contains supplementary material, which is available to authorized users.

Nanofabrication of a gold fiducial array on specimen support for electron tomography

Cryo-electron tomography (cryo-ET) is an emerging 3-D reconstruction technology that combines the principles of tomographic 3-D reconstruction with the unmatched structural preservation of biological matter embedded in vitreous ice. Cryo-ET is particularly suited to investigating cell-biological samples and large macromolecular structures that are too polymorphic to be reconstructed by classical averaging-based 3-D reconstruction procedures. This unit aims to make cryo-ET accessible to newcomers and discusses the specialized equipment required, as well as relevant advantages and hurdles associated with sample preparation by vitrification and cryo-ET. Protocols describe specimen preparation, data recording and 3-D data reconstruction for cryo-ET, with a special focus on macromolecular complexes. A step-by-step procedure for specimen vitrification by plunge freezing is provided, followed by the general practicalities of tilt-series acquisition for cryo-ET, including advice on how to select an area appropriate for acquiring a tilt series. A brief introduction to the underlying computational reconstruction principles applied in tomography is described, along with instructions for reconstructing a tomogram from cryo-tilt series data. Finally, a method is detailed for extracting small subvolumes containing identical macromolecular structures from tomograms for alignment and averaging as a means to increase the signal-to-noise ratio and eliminate missing wedge effects inherent in tomographic reconstructions.

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

Structural features of the salivary gland hypertrophy virus of the tsetse fly revealed by cryo-electron microscopy and tomography

In the recent years, cryo-electron microscopy (cryo-EM) single-particle analysis (SPA) has greatly benefited from a multitude of technological advances cumulating in breaking the atomic-resolution barrier for biological macromolecules. Since then, structural insights by cryo-EM have led to driving rational design of new vaccines and therapeutics due to high throughput and high-resolution screening and data collection technologies. Additionally, cryo-electron tomography (cryo-ET) has become an indispensable tool for structural cell biology. In this presentation we elaborate on the latest Thermo Fisher Scientific innovations for 300kV cryo electron microscopy for SPA and cryo-ET to advance more workflow efficiency and performance. Our ongoing mission is to further improve the connectivity between the cryo-FIB and cryo-TEM for an even more streamlined tomography workflow that is safer, faster and cleaner. Data acquisition and processing can be a significant cryo-ET bottleneck. Our integrated solution, combining Thermo Scientific Tomography 5 and Tomo Live, automates pre-acquisition tasks, enhances productivity with predictive tracking and enables rapid quality assessment. Robust and optimized motion correction helps produce crisp tomograms and image quality needed for sub-tomogram averaging. Results are displayed with new quality metrics on a web platform, making the workflow user-friendly and facilitating structural biology advancements.

Advances in electron microscopy: A qualitative view of instrumentation development for macromolecular imaging and tomography

Modeling of magnetic Barkhausen noise in single and dual easy axis systems in steel

Tracking is important in a system that harnesses solar energy. Single axis tracking mechanism is cheaper and simple to develop but because of the limitation of tracking axis, this system is less efficient than dual axis. Dual-axis tracking systems necessitate a large number of equipment, sensors, motors, and a lengthy computer program to function properly. Therefore, in the present study, a novel method of solar tracking has been discussed where each tracking point has the impact of both the azimuth and altitude angle at a single point. This method is an average axis tracking method (AATM). HelioScope software was used to extract the hourly solar altitude and azimuth angles for each day and month for the site of Bhopal, India. The average method was then used to get the hourly average solar tracking angle (ASTA) for each month. The parabolic dish concentrator was designed in SolidWorks to apply and simulate the newly developed tracking points on SolTrace software. The graphical analysis was presented along with proper validation of the proposed method, and the single and dual axes were compared with AATM. The graphical study shows that the average axis tracking points have a smoother slop of wave than the single axis. From June to September, the proposed method's error was estimated between 0.85 and 0.95. It can be concluded that by making slight adjustments to the seasonal angle, this error could be minimized and the concept could be successfully applied to a parabolic dish or a solar PV system.

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

Software for automated acquisition of electron tomography tilt series.

To solve three-dimensional structures of biological macromolecules in situ, large numbers of particles often need to be picked from cryo-electron tomograms. However, adoption of automated particle-picking methods remains limited because of their technical limitations. To overcome the limitations, we develop DeepETPicker, a deep learning model for fast and accurate picking of particles from cryo-electron tomograms. Training of DeepETPicker requires only weak supervision with low numbers of simplified labels, reducing the burden of manual annotation. The simplified labels combined with the customized and lightweight model architecture of DeepETPicker and accelerated pooling enable substantial performance improvement. When tested on simulated and real tomograms, DeepETPicker outperforms the competing state-of-the-art methods by achieving the highest overall accuracy and speed, which translate into higher authenticity and coordinates accuracy of picked particles and higher resolutions of final reconstruction maps. DeepETPicker is provided in open source with a user-friendly interface to support cryo-electron tomography in situ.

Superior mobility of knee parts with dual-versus single-axis hinge for extravehicular activity without prebreathing

Design of rural photovoltaic water pumping systems and the potential of manual array tracking for a West-African village

Biochemical and structural characterization of the capsid-bound tegument proteins of human cytomegalovirus