scholarly journals A novel constrained reconstruction model towards high-resolution subtomogram averaging

2019 ◽  
Author(s):  
Renmin Han ◽  
Lun Li ◽  
Peng Yang ◽  
Fa Zhang ◽  
Xin Gao
Keyword(s):  
Averaging Method ◽  
Electron Tomography ◽  
Solution Space ◽  
Supplementary Information ◽  
Reconstruction Technique ◽  
Constrained Reconstruction ◽  
Kaczmarz Algorithm ◽  
Reconstruction Quality ◽  
Subtomogram Averaging ◽  
Reconstruction Model

Abstract Motivation Electron tomography (ET) offers a unique capacity to image biological structures in situ. However, the resolution of ET reconstructed tomograms is not comparable to that of the single-particle cryo-EM. If many copies of the object of interest are present in the tomograms, their structures can be reconstructed in the tomogram, picked, aligned and averaged to increase the signal-to-noise ratio and improve the resolution, which is known as the subtomogram averaging. To date, the resolution improvement of the subtomogram averaging is still limited because each reconstructed subtomogram is of low reconstruction quality due to the missing wedge issue. Results In this article, we propose a novel computational model, the constrained reconstruction model (CRM), to better recover the information from the multiple subtomograms and compensate for the missing wedge issue in each of them. CRM is supposed to produce a refined reconstruction in the final turn of subtomogram averaging after alignment, instead of directly taking the average. We first formulate the averaging method and our CRM as linear systems, and prove that the solution space of CRM is no larger, and in practice much smaller, than that of the averaging method. We then propose a sparse Kaczmarz algorithm to solve the formulated CRM, and further extend the solution to the simultaneous algebraic reconstruction technique (SART). Experimental results demonstrate that CRM can significantly alleviate the missing wedge issue and improve the final reconstruction quality. In addition, our model is robust to the number of images in each tilt series, the tilt range and the noise level. Availability and implementation The codes of CRM-SIRT and CRM-SART are available at https://github.com/icthrm/CRM. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A joint method for marker-free alignment of tilt series in electron tomography

2019 ◽  
Vol 35 (14) ◽  
pp. i249-i259 ◽  
Author(s):  
Renmin Han ◽  
Zhipeng Bao ◽  
Xiangrui Zeng ◽  
Tongxin Niu ◽  
Fa Zhang ◽  
...  
Keyword(s):  
State Of The Art ◽  
Electron Tomography ◽  
Supplementary Information ◽  
Intensity Change ◽  
Projection Model ◽  
Reconstruction Quality ◽  
Marker Free ◽  
Tilt Series ◽  
Geometric Changes ◽  
Joint Method

Abstract Motivation Electron tomography (ET) is a widely used technology for 3D macro-molecular structure reconstruction. To obtain a satisfiable tomogram reconstruction, several key processes are involved, one of which is the calibration of projection parameters of the tilt series. Although fiducial marker-based alignment for tilt series has been well studied, marker-free alignment remains a challenge, which requires identifying and tracking the identical objects (landmarks) through different projections. However, the tracking of these landmarks is usually affected by the pixel density (intensity) change caused by the geometry difference in different views. The tracked landmarks will be used to determine the projection parameters. Meanwhile, different projection parameters will also affect the localization of landmarks. Currently, there is no alignment method that takes interrelationship between the projection parameters and the landmarks. Results Here, we propose a novel, joint method for marker-free alignment of tilt series in ET, by utilizing the information underlying the interrelationship between the projection model and the landmarks. The proposed method is the first joint solution that combines the extrinsic (track-based) alignment and the intrinsic (intensity-based) alignment, in which the localization of landmarks and projection parameters keep refining each other until convergence. This iterative approach makes our solution robust to different initial parameters and extreme geometric changes, which ensures a better reconstruction for marker-free ET. Comprehensive experimental results on three real datasets show that our new method achieved a significant improvement in alignment accuracy and reconstruction quality, compared to the state-of-the-art methods. Availability and implementation The main program is available at https://github.com/icthrm/joint-marker-free-alignment. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A guided approach for subtomogram averaging of challenging macromolecular assemblies

2020 ◽  
Author(s):  
Danielle Grotjahn ◽  
Saikat Chowdhury ◽  
Gabriel C. Lander
Keyword(s):  
Electron Tomography ◽  
A Priori ◽  
Three Dimensional ◽  
Structural Heterogeneity ◽  
Dimensional Structure ◽  
Diverse Range ◽  
Macromolecular Assemblies ◽  
Cryo Electron Tomography ◽  
Subtomogram Averaging

AbstractCryo-electron tomography is a powerful biophysical technique enabling three-dimensional visualization of complex biological systems. Macromolecular targets of interest identified within cryo-tomograms can be computationally extracted, aligned, and averaged to produce a better-resolved structure through a process called subtomogram averaging (STA). However, accurate alignment of macromolecular machines that exhibit extreme structural heterogeneity and conformational flexibility remains a significant challenge with conventional STA approaches. To expand the applicability of STA to a broader range of pleomorphic complexes, we developed a user-guided, focused refinement approach that can be incorporated into the standard STA workflow to facilitate the robust alignment of particularly challenging samples. We demonstrate that it is possible to align visually recognizable portions of multi-subunit complexes by providing a priori information regarding their relative orientations within cryo-tomograms, and describe how this strategy was applied to successfully elucidate the first three-dimensional structure of the dynein-dynactin motor protein complex bound to microtubules. Our approach expands the application of STA for solving a more diverse range of heterogeneous biological structures, and establishes a conceptual framework for the development of automated strategies to deconvolve the complexity of crowded cellular environments and improve in situ structure determination technologies.

scholarly journals Nuclear pores constrict upon energy depletion

2020 ◽  
Author(s):  
Christian E Zimmerli ◽  
Matteo Allegretti ◽  
Vasileios Rantos ◽  
Sara K Goetz ◽  
Agnieszka Obarska-Kosinska ◽  
...  
Keyword(s):  
Conformational Changes ◽  
Large Scale ◽  
Electron Tomography ◽  
Nuclear Pore ◽  
Nuclear Pore Complexes ◽  
Energy Status ◽  
Energy Depletion ◽  
Time Variations ◽  
Subtomogram Averaging ◽  
Pore Complexes

Nuclear pore complexes (NPCs) fuse the inner and outer nuclear membranes and mediate nucleocytoplasmic exchange. They are made of 30 different nucleoporins that form an intricate cylindrical architecture around an aqueous central channel. This architecture is highly dynamic in space and time. Variations in NPC diameter were reported, but the physiological circumstances and the molecular details remain unknown. Here we combined cryo-electron tomography and subtomogram averaging with integrative structural modeling to capture a molecular movie of the respective large-scale conformational changes in cellulo. While actively transporting NPCs adopt a dilated conformation, they strongly constrict upon cellular energy depletion. Fluorescence recovery after photo bleaching experiments show that NPC constriction is concomitant with reduced diffusion and active transport across the nuclear envelope. Our data point to a model where the energy status of cells is linked to the conformation of NPC architecture.

scholarly journals The Dynamo Software Package for Cryo-electron Tomography and Subtomogram Averaging

2020 ◽  
Vol 26 (S2) ◽  
pp. 3142-3145
Author(s):  
Paula Navarro ◽  
Stefano Scaramuzza ◽  
Henning Stahlberg ◽  
Daniel Castaño-Díez
Keyword(s):  
Software Package ◽  
Electron Tomography ◽  
Cryo Electron Tomography ◽  
Subtomogram Averaging

Progressive Stochastic Reconstruction Technique (PSRT) for cryo electron tomography

2015 ◽  
Vol 189 (3) ◽  
pp. 195-206 ◽  
Author(s):  
Beata Turoňová ◽  
Lukas Marsalek ◽  
Tomáš Davidovič ◽  
Philipp Slusallek
Keyword(s):  
Electron Tomography ◽  
Reconstruction Technique ◽  
Stochastic Reconstruction ◽  
Cryo Electron Tomography

scholarly journals Summarizing the solution space in tumor phylogeny inference by multiple consensus trees

2019 ◽  
Vol 35 (14) ◽  
pp. i408-i416 ◽  
Author(s):  
Nuraini Aguse ◽  
Yuanyuan Qi ◽  
Mohammed El-Kebir
Keyword(s):  
Solution Space ◽  
Simulated Data ◽  
Exact Algorithm ◽  
Real Data ◽  
Supplementary Information ◽  
Mixed Integer ◽  
Consensus Tree ◽  
Large Solution ◽  
Consensus Trees ◽  
Topological Features

Abstract Motivation Cancer phylogenies are key to studying tumorigenesis and have clinical implications. Due to the heterogeneous nature of cancer and limitations in current sequencing technology, current cancer phylogeny inference methods identify a large solution space of plausible phylogenies. To facilitate further downstream analyses, methods that accurately summarize such a set T of cancer phylogenies are imperative. However, current summary methods are limited to a single consensus tree or graph and may miss important topological features that are present in different subsets of candidate trees. Results We introduce the Multiple Consensus Tree (MCT) problem to simultaneously cluster T and infer a consensus tree for each cluster. We show that MCT is NP-hard, and present an exact algorithm based on mixed integer linear programming (MILP). In addition, we introduce a heuristic algorithm that efficiently identifies high-quality consensus trees, recovering all optimal solutions identified by the MILP in simulated data at a fraction of the time. We demonstrate the applicability of our methods on both simulated and real data, showing that our approach selects the number of clusters depending on the complexity of the solution space T. Availability and implementation https://github.com/elkebir-group/MCT. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Novel nonlinear reconstruction method with grey-level quantisation units for electron tomography

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Norio Baba ◽  
Kenji Kaneko ◽  
Misuzu Baba
Keyword(s):  
Cross Section ◽  
Electron Tomography ◽  
Three Dimensional ◽  
Reconstruction Technique ◽  
Reconstruction Method ◽  
Back Projection ◽  
Grey Level ◽  
Discrete Processing ◽  
Structural Image ◽  
Tomography Reconstruction

AbstractWe report a new computed tomography reconstruction method, named quantisation units reconstruction technique (QURT), applicable to electron and other fields of tomography. Conventional electron tomography methods such as filtered back projection, weighted back projection, simultaneous iterative reconstructed technique, etc. suffer from the ‘missing wedge’ problem due to the limited tilt-angle range. QURT demonstrates improvements to solve this problem by recovering a structural image blurred due to the missing wedge and substantially reconstructs the structure even if the number of projection images is small. QURT reconstructs a cross-section image by arranging grey-level quantisation units (QU pieces) in three-dimensional image space via unique discrete processing. Its viability is confirmed by model simulations and experimental results. An important difference from recently developed methods such as discrete algebraic reconstruction technique (DART), total variation regularisation—DART, and compressed sensing is that prior knowledge of the conditions regarding the specimen or the expected cross-section image is not necessary.

scholarly journals Proteasomes tether to two distinct sites at the nuclear pore complex

2017 ◽  
Vol 114 (52) ◽  
pp. 13726-13731 ◽  
Author(s):  
Sahradha Albert ◽  
Miroslava Schaffer ◽  
Florian Beck ◽  
Shyamal Mosalaganti ◽  
Shoh Asano ◽  
...  
Keyword(s):  
Nuclear Pore Complex ◽  
Binding Sites ◽  
Electron Tomography ◽  
Nuclear Pore ◽  
Cellular Environment ◽  
Subtomogram Averaging ◽  
Substrate Processing ◽  
Cellular Components ◽  
Transport Of Macromolecules

The partitioning of cellular components between the nucleus and cytoplasm is the defining feature of eukaryotic life. The nuclear pore complex (NPC) selectively gates the transport of macromolecules between these compartments, but it is unknown whether surveillance mechanisms exist to reinforce this function. By leveraging in situ cryo-electron tomography to image the native cellular environment of Chlamydomonas reinhardtii, we observed that nuclear 26S proteasomes crowd around NPCs. Through a combination of subtomogram averaging and nanometer-precision localization, we identified two classes of proteasomes tethered via their Rpn9 subunits to two specific NPC locations: binding sites on the NPC basket that reflect its eightfold symmetry and more abundant binding sites at the inner nuclear membrane that encircle the NPC. These basket-tethered and membrane-tethered proteasomes, which have similar substrate-processing state frequencies as proteasomes elsewhere in the cell, are ideally positioned to regulate transcription and perform quality control of both soluble and membrane proteins transiting the NPC.

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