Recent improvements in spatial resolution and measurement sensitivity for high-resolution digital image correlation (HR-DIC) now provide an avenue for the quantitative measurement of deformation events and capturing the physical nature of deformation mechanisms. However, HR-DIC measurements require significant time due to scanning electron image acquisition; such a limitation prevents the widespread use of HR-DIC for material characterization. Apply a novel SEM acquisition technology to enhance HR-DIC measurements for high throughput applications. Multi-beam SEM technology is employed to image an entire gauge length at once at high resolution and at nearly a hundredfold acceleration of typical HR-DIC image acquisition, even when automated stage movement and image acquisition are employed. These images were fed into a discontinuity-tolerant HR-DIC software to determine slip localization induced by non-metallic inclusions and grain structure. Slip localization was able to be analyzed to an unprecedented level, with over 210,000 slip bands able to be investigated, with the most intense slip localizing near and parallel to twin boundaries and in the vicinity of non-metallic inclusion clusters. Additionally, secondary slip activation and grain boundary shearing by intense dislocation pileups are observed to reduce slip amplitude near and parallel to twin boundaries. By performing HR-DIC in conjunction with a multi-beam SEM, high-throughput measurements of large field-of-view, high-resolution images were able to be performed in a timely manner. These measurements provided an immense number of slip events for statistical analysis to be performed on to relate to microstructural features.

Journal Article A 331-Beam Scanning Electron Microscope Get access Stephan Nickell, Stephan Nickell Carl Zeiss Microscopy GmbH, Carl-Zeiss-Str. 22, D-73447 Oberkochen, Germany Search for other works by this author on: Oxford Academic Google Scholar Dirk Zeidler Dirk Zeidler Carl Zeiss Microscopy GmbH, Carl-Zeiss-Str. 22, D-73447 Oberkochen, Germany Corresponding author: dirk.zeidler@zeiss.com Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 25, Issue S2, 1 August 2019, Pages 568–569, https://doi.org/10.1017/S143192761900357X Published: 01 August 2019

Journal Article Towards Fast and Direct Memory Read-out by Multi-beam Scanning Electron Microscopy and Deep Learning Image Classification Get access Kyle Crosby, Kyle Crosby Carl Zeiss Microscopy LLC, Business Development mSEM, One Zeiss Drive, Thornwood, USA Search for other works by this author on: Oxford Academic Google Scholar Tomasz Garbowski, Tomasz Garbowski Carl Zeiss Microscopy GmbH, Business Development mSEM, Oberkochen, Germany Search for other works by this author on: Oxford Academic Google Scholar Stephan Nickell Stephan Nickell Carl Zeiss Microscopy GmbH, Business Development mSEM, Oberkochen, Germany Corresponding author: Stephan.Nickell@Zeiss.com Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 25, Issue S2, 1 August 2019, Pages 192–193, https://doi.org/10.1017/S1431927619001697 Published: 01 August 2019

Abstract Reverse engineering of today’s integrated circuits requires proper sample preparation, high speed imaging and data processing capabilities. The electron-optical design and the data handling architecture of our multi-beam scanning electron microscopes are scalable over a large range of beam numbers, providing sufficient imaging speed - also for the foreseeable future. A first step in data processing for reverse engineering on images acquired with a multi-beam scanning electron microscope has been successfully shown in preliminary tests.

Cytosolic, globular droplets with an average diameter of 50 nm were observed in vitrified Thermoplasma acidophilum cells by means of cryo-electron tomography. These droplets were isolated by column chromatography and immunoprecipitation protein purification methods. Subsequent chemical and biochemical analyses identified lipid and protein components, respectively. Two major lipid components, comigrating menaquinones at the solvent front and the slower migrating Thermoplasma polar lipid U4, were detected by TLC experiments. The major protein component was identified as the 153 amino acid long Ta0547 vitellogenin-N domain protein. This domain has been found so far exclusively in large lipid transport proteins of vertebrates and non-vertebrates. Blast protein database homology searches with Ta0547 did not return any eukaryal hits; homologous sequences were found only in thermo-acidophilic archaeons. However, a profile-sequence domain search performed with the vitellogenin-N domain (PF01347) hmm-profile against the T. acidophilum proteome returned Ta0547 as hit. Electron microscopy appearance of isolated droplets resembled to lipoprotein particles. However, no (tetraether) lipid layer could be detected on the droplets surface, rather hydrophobic compounds of the electron dense lumen were surrounded by a denser discontinuous protein boundary. Based on described features, these particles qualify for a novel lipoprotein particle category, what we nominated Thermoplasma Quinone Droplet.

Two canonical subunits of the 26S proteasome, Rpn10 and Rpn13, function as ubiquitin (Ub) receptors. The mutual arrangement of these subunits—and all other non-ATPase subunits—in the regulatory particle is unknown. Using electron cryomicroscopy, we calculated difference maps between wild-type 26S proteasome from Saccharomyces cerevisiae and deletion mutants (rpn10Δ, rpn13Δ, and rpn10Δrpn13Δ). These maps allowed us to localize the two Ub receptors unambiguously. Rpn10 and Rpn13 mapped to the apical part of the 26S proteasome, above the N-terminal coiled coils of the AAA-ATPase heterodimers Rpt4/Rpt5 and Rpt1/Rpt2, respectively. On the basis of the mutual positions of Rpn10 and Rpn13, we propose a model for polyubiquitin binding to the 26S proteasome.

— Cryo-electron microscopy (CEM) in combination with single particle analysis (SPA) is a widely used technique for elucidating structural details of macromolecular assemblies at close-to-atomic resolutions. However, development of automated software for SPA processing is still vital since thousands to millions of individual particle images need to be processed. Here, we present our workflow for automated particle picking. Our approach integrates peak shape analysis to the classical correlation and an iterative approach to separate macromolecules and background by classification. This particle selection workflow furthermore provides a robust means for SPA with little user interaction. Processing simulated and experimental data assesses performance of the presented tools.

We report a simple and generic method for the direct transfer of protein complexes separated by native gel electrophoresis to electron microscopy grids. After transfer, sufficient material remains in the gel for identification and characterization by mass spectrometry. The method should facilitate higher-throughput single-particle analysis by substantially reducing the time needed for protein purification, as demonstrated for three complexes from Thermoplasma acidophilum.

Cryo-electron tomography in combination with subtomogram averaging allows to investigate the structure of protein assemblies in their natural environment in a close to live state. To make full use of the structural information contained in tomograms it is necessary to analyze the contrast transfer function (CTF) of projections and to restore the phases of higher spatial frequencies. CTF correction is however hampered by the difficulty of determining the actual defocus values from tilt series data, which is due to the low signal-to-noise ratio of electron micrographs. In this study, an extended acquisition scheme is introduced that enables an independent CTF determination. Two high-dose images are recorded along the tilt axis on both sides of each projection, which allow an accurate determination of the defocus values of these images. These values are used to calculate the CTF for each image of the tilt series. We applied this scheme to the mycobacterial outer membrane protein MspA reconstituted in lipid vesicles and tested several variants of CTF estimation in combination with subtomogram averaging and correction of the modulation transfer function (MTF). The 3D electron density map of MspA was compared with a structure previously determined by X-ray crystallography. We were able to demonstrate that structural information up to a resolution of 16.8Å can be recovered using our CTF correction approach, whereas the uncorrected 3D map had a resolution of only 26.2Å.

The 26S proteasome operates at the executive end of the ubiquitin-proteasome pathway. Here, we present a cryo-EM structure of the Saccharomyces cerevisiae 26S proteasome at a resolution of 7.4 Å or 6.7 Å (Fourier-Shell Correlation of 0.5 or 0.3, respectively). We used this map in conjunction with molecular dynamics-based flexible fitting to build a near-atomic resolution model of the holocomplex. The quality of the map allowed us to assign α-helices, the predominant secondary structure element of the regulatory particle subunits, throughout the entire map. We were able to determine the architecture of the Rpn8/Rpn11 heterodimer, which had hitherto remained elusive. The MPN domain of Rpn11 is positioned directly above the AAA-ATPase N-ring suggesting that Rpn11 deubiquitylates substrates immediately following commitment and prior to their unfolding by the AAA-ATPase module. The MPN domain of Rpn11 dimerizes with that of Rpn8 and the C-termini of both subunits form long helices, which are integral parts of a coiled-coil module. Together with the C-terminal helices of the six PCI-domain subunits they form a very large coiled-coil bundle, which appears to serve as a flexible anchoring device for all the lid subunits.

Classification and averaging of sub-tomograms can improve the fidelity and resolution of structures obtained by electron tomography. Here we present a three-dimensional (3D) maximum likelihood algorithm – MLTOMO – which is characterized by integrating 3D alignment and classification into a single, unified processing step. The novelty of our approach lies in the way we calculate the probability of observing an individual sub-tomogram for a given reference structure. We assume that the reference structure is affected by a ‘compound wedge’, resulting from the summation of many individual missing wedges in distinct orientations. The distance metric underlying our probability calculations effectively down-weights Fourier components that are observed less frequently. Simulations demonstrate that MLTOMO clearly outperforms the ‘constrained correlation’ approach and has advantages over existing approaches in cases where the sub-tomograms adopt preferred orientations. Application of our approach to cryo-electron tomographic data of ice-embedded thermosomes revealed distinct conformations that are in good agreement with results obtained by previous single particle studies.

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011.

Proteasomes execute the degradation of most cellular proteins. Although the 20S core particle (CP) has been studied in great detail, the structure of the 19S regulatory particle (RP), which prepares ubiquitylated substrates for degradation, has remained elusive. Here, we report the crystal structure of one of the RP subunits, Rpn6, and we describe its integration into the cryo-EM density map of the 26S holocomplex at 9.1 Å resolution. Rpn6 consists of an α-solenoid-like fold and a proteasome COP9/signalosome eIF3 (PCI) module in a right-handed suprahelical configuration. Highly conserved surface areas of Rpn6 interact with the conserved surfaces of the Pre8 (alpha2) and Rpt6 subunits from the alpha and ATPase rings, respectively. The structure suggests that Rpn6 has a pivotal role in stabilizing the otherwise weak interaction between the CP and the RP.

An automatic particle picking algorithm for processing electron micrographs of a large molecular complex, the 26S proteasome, is described. The algorithm makes use of a coherence enhancing diffusion filter to denoise the data, and a random forest classifier for removing false positives. It does not make use of a 3D reference model, but uses a training set of manually picked particles instead. False positive and false negative rates of around 25% to 30% are achieved on a testing set. The algorithm was developed for a specific particle, but contains steps that should be useful for developing automatic picking algorithms for other particles.

Automated data acquisition expedites structural studies by electron microscopy and it allows to collect data sets of unprecedented size and consistent quality. In electron tomography it greatly facilitates the systematic exploration of large cellular landscapes and in single particle analysis it allows to generate data sets for an exhaustive classification of coexisting molecular states. Here we describe a novel software philosophy and architecture that can be used for a great variety of automated data acquisition scenarios. Based on our original software package TOM, the new TOM2 package has been designed in an object-oriented way. The whole program can be seen as a collection of self-sufficient modules with defined relationships acting in a concerted manner. It subdivides data acquisition into a set of hierarchical tasks, bonding data structure and the operations to be performed tightly together. To demonstrate its capacity for high-throughput data acquisition it has been used in conjunction with instrumentation combining the latest technological achievements in electron optics, cryogenics and robotics. Its performance is demonstrated with a single particle analysis case study and with a batch tomography application.

The structure of the 26S proteasome from Schizosaccharomyces pombe has been determined to a resolution of 9.1 Å by cryoelectron microscopy and single particle analysis. In addition, chemical cross-linking in conjunction with mass spectrometry has been used to identify numerous residue pairs in close proximity to each other, providing an array of spatial restraints. Taken together these data clarify the topology of the AAA-ATPase module in the 19S regulatory particle and its spatial relationship to the α-ring of the 20S core particle. Image classification and variance analysis reveal a belt of high “activity” surrounding the AAA-ATPase module which is tentatively assigned to the reversible association of proteasome interacting proteins and the conformational heterogeneity among the particles. An integrated model is presented which sheds light on the early steps of protein degradation by the 26S complex.