The application of Graphene as a sample support in Transmission Electron Microscopy

Transmission electron microscopy has witnessed rampant development and surging point resolution over the past few years. The improved imaging performance of modern electron microscopes shifts the bottleneck for image contrast and resolution to sample preparation. Hence, it is increasingly being realized that the full potential of electron microscopy will only be realized with the optimization of current sample preparation techniques. Perhaps the most recognized issues are background signal and noise contributed by sample supports, sample charging and instability. Graphene provides supports of single atom thickness, extreme physical stability, periodic structure, and ballistic electrical conductivity. As an increasing number of applications adapting graphene to their benefit emerge, we discuss the unique capabilities afforded by the use of graphene as a sample support for electron microscopy.Comment: Review, to appear in solid state communication

Fast automated cell phenotype image classification

BACKGROUND: The genomic revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respect, microscope imaging of a protein's sub-cellular localisation is proving invaluable, and recent advances in automated fluorescent microscopy allow protein localisations to be imaged in high throughput. Hence there is a need for large scale automated computational techniques to efficiently quantify, distinguish and classify sub-cellular images. While image statistics have proved highly successful in distinguishing localisation, commonly used measures suffer from being relatively slow to compute, and often require cells to be individually selected from experimental images, thus limiting both throughput and the range of potential applications. Here we introduce threshold adjacency statistics, the essence which is to threshold the image and to count the number of above threshold pixels with a given number of above threshold pixels adjacent. These novel measures are shown to distinguish and classify images of distinct sub-cellular localization with high speed and accuracy without image cropping. RESULTS: Threshold adjacency statistics are applied to classification of protein sub-cellular localization images. They are tested on two image sets (available for download), one for which fluorescently tagged proteins are endogenously expressed in 10 sub-cellular locations, and another for which proteins are transfected into 11 locations. For each image set, a support vector machine was trained and tested. Classification accuracies of 94.4% and 86.6% are obtained on the endogenous and transfected sets, respectively. Threshold adjacency statistics are found to provide comparable or higher accuracy than other commonly used statistics while being an order of magnitude faster to calculate. Further, threshold adjacency statistics in combination with Haralick measures give accuracies of 98.2% and 93.2% on the endogenous and transfected sets, respectively. CONCLUSION: Threshold adjacency statistics have the potential to greatly extend the scale and range of applications of image statistics in computational image analysis. They remove the need for cropping of individual cells from images, and are an order of magnitude faster to calculate than other commonly used statistics while providing comparable or better classification accuracy, both essential requirements for application to large-scale approaches

Rendering graphene supports hydrophilic with non-covalent aromatic functionalization for transmission electron microscopy

Amorphous carbon films have been routinely used to enhance the preparation of frozen-hydrated samples for transmission electron microscopy (TEM), either in retaining protein concentration, providing mechanical stability or dissipating sample charge. However, strong background signal from the amorphous carbon support obstructs that of the sample, and the insulating properties of thin amorphous carbon films preclude any efficiency in dispersing charge. Graphene addresses the limitations of amorphous carbon. Graphene is a crystalline material with virtually no phase or amplitude contrast and unparalleled, high electrical carrier mobility. However, the hydrophobic properties of graphene have prevented its routine application in Cryo-TEM. This Letter reports a method for rendering graphene TEM supports hydrophilic-a convenient approach maintaining graphene's structural and electrical properties based on non-covalent, aromatic functionalization. (C) 2014 AIP Publishing LLC

Preparation of 2D Crystals of Membrane Proteins for High-Resolution Electron Crystallography Data Collection

Electron crystallography is a powerful technique for the structure determination of membrane proteins as well as soluble proteins. Sample preparation for 2D membrane protein crystals is a crucial step, as proteins have to be prepared for electron microscopy at close to native conditions. In this review, we discuss the factors of sample preparation that are key to elucidating the atomic structure of membrane proteins using electron crystallography

Cryoelectron Microscopy Map of Atadenovirus Reveals Cross-Genus Structural Differences from Human Adenovirus▿

A three-dimensional (3D) cryoelectron microscopy reconstruction of the prototype Atadenovirus (OAdV [an ovine adenovirus isolate]) showing information at a 10.6-Å resolution (0.5 Fourier shell correlation) was derived by single-particle analysis. This is the first 3D structure solved for any adenovirus that is not a Mastadenovirus, allowing cross-genus comparisons between structures and the assignment of genus-specific capsid proteins. Viable OAdV mutants that lacked the genus-specific LH3 and p32k proteins in purified virions were also generated. Negatively stained 3D reconstructions of these mutants were used to identify the location of protein LH3 and infer that of p32k within the capsid. The key finding was that LH3 is a critical protein that holds the outer capsid of the virus together. In its absence, the outer viral capsid is unstable. LH3 is located in the same position among the hexon subunits as its protein IX equivalent from mastadenoviruses but sits on top of the hexon trimers, forming prominent “knobs” on the virion surface that visually distinguish OAdV from other known AdVs. Electron density was also assigned to hexon and penton subunits and to proteins IIIa and VIII. There was good correspondence between OAdV density and human AdV hexon structures, which also validated the significant differences that were observed between the penton base protein structures

Preparation of 2D crystals of membrane proteins for high-resolution electron crystallography data collection

Electron crystallography is a powerful technique for the structure determination of membrane proteins as well as soluble proteins. Sample preparation for 2D membrane protein crystals is a crucial step, as proteins have to be prepared for electron microscopy at close to native conditions. In this review, we discuss the factors of sample preparation that are key to elucidating the atomic structure of membrane proteins using electron crystallography

SwarmPS: Rapid, semi-automated single particle selection software

Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that ∼104–105 particle projections are required to attain a 3 Å resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present SwarmPS, a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (∼102), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. SwarmPS is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites

The discriminative bilateral filter: An enhanced denoising filter for electron microscopy data

Advances in three-dimensional (313) electron microscopy (EM) and image processing are providing considerable improvements in the resolution of subcellular volumes, macromolecular assemblies and individual proteins. However, the recovery of high-frequency information from biological samples is hindered by specimen sensitivity to beam damage. Low dose electron cryo-microscopy conditions afford reduced beam damage but typically yield images with reduced contrast and low signal-to-noise ratios (SNRs). Here, we describe the properties of a new discriminative bilateral (DBL) filter that is based upon the bilateral filter implementation of Jiang et al. (Jiang, W., Baker, M.L., Wu, Q., Bajaj, C., Chin, W., 2003. Applications of a bilateral denoising filter in biological electron microscopy. J. Struc. Biol. 128, 82-97.). In contrast to the latter, the DBL filter can distinguish between object edges and high-frequency noise pixels through the use of an additional photometric exclusion function. As a result, high frequency noise pixels are smoothed, yet object edge detail is preserved. In the present study, we show that the DBL filter effectively reduces noise in low SNR single particle data as well as cellular tomograms of stained plastic sections. The properties of the DBL filter are discussed in terms of its usefulness for single particle analysis and for pre-processing cellular tomograms ahead of image segmentation. (c) 2006 Elsevier Inc. All rights reserved