Cryo-tomography tilt-series alignment with consideration of the beam-induced sample motion.
ABSTRACT: Recent evidence suggests that the beam-induced motion of the sample during tilt-series acquisition is a major resolution-limiting factor in electron cryo-tomography (cryoET). It causes suboptimal tilt-series alignment and thus deterioration of the reconstruction quality. Here we present a novel approach to tilt-series alignment and tomographic reconstruction that considers the beam-induced sample motion through the tilt-series. It extends the standard fiducial-based alignment approach in cryoET by introducing quadratic polynomials to model the sample motion. The model can be used during reconstruction to yield a motion-compensated tomogram. We evaluated our method on various datasets with different sample sizes. The results demonstrate that our method could be a useful tool to improve the quality of tomograms and the resolution in cryoET.
Project description:Recently, it has been shown that the resolution in cryo-tomography could be improved by considering the sample motion in tilt-series alignment and reconstruction, where a set of quadratic polynomials were used to model this motion. One requirement of this polynomial method is the optimization of a large number of parameters, which may limit its practical applicability. In this work, we propose an alternative method for modeling the sample motion. Starting from the standard fiducial-based tilt-series alignment, the method uses the alignment residual as local estimates of the sample motion at the 3D fiducial positions. Then, a scattered data interpolation technique characterized by its smoothness and a closed-form solution is applied to model the sample motion. The motion model is then integrated in the tomographic reconstruction. The new method improves the tomogram quality similar to the polynomial one, with the important advantage that the determination of the motion model is greatly simplified, thereby overcoming one of the major limitations of the polynomial model. Therefore, the new method is expected to make the beam-induced motion correction methodology more accessible to the cryoET community.
Project description:Bsoft offers many tools for the processing of tomographic tilt series and the interpretation of tomograms. Since I introduced tomography into Bsoft almost two decades ago, the field has advanced significantly, requiring refinement of old algorithms and development of new ones. The current direct detectors allow us to collect data more efficiently and with better quality, progressing towards automation. The goal is then to also automate alignment of tilt series and reconstruction. I added an estimation of the specimen thickness as well as fiducialless alignment, to augment the existing fiducial-based alignment. High-resolution work requires correction for the contrast transfer function, in tomography complicated by the tilted specimen. For this, I developed a method to generate a power spectrum using the whole micrograph, compensating for tilting. This is followed by routine determination of the contrast transfer function, and correction for it during reconstruction. The next steps involve interpretation of the tomogram, either by subtomogram averaging where possible, or by segmentation and modeling otherwise. Such interpretation actually constitutes the main time-consuming part of tomography and is less amenable to automation compared to the initial reconstruction.
Project description:Cryo-electron tomography (cryo-ET) is an emerging technique that can elucidate the architecture of macromolecular complexes and cellular ultrastructure in a near-native state. Some important sample parameters, such as thickness and tilt, are needed for 3-D reconstruction. However, these parameters can currently only be determined using trial 3-D reconstructions. Accurate electron mean free path plays a significant role in modeling image formation process essential for simulation of electron microscopy images and model-based iterative 3-D reconstruction methods; however, their values are voltage and sample dependent and have only been experimentally measured for a limited number of sample conditions. Here, we report a computational method, tomoThickness, based on the Beer-Lambert law, to simultaneously determine the sample thickness, tilt and electron inelastic mean free path by solving an overdetermined nonlinear least square optimization problem utilizing the strong constraints of tilt relationships. The method has been extensively tested with both stained and cryo datasets. The fitted electron mean free paths are consistent with reported experimental measurements. The accurate thickness estimation eliminates the need for a generous assignment of Z-dimension size of the tomogram. Interestingly, we have also found that nearly all samples are a few degrees tilted relative to the electron beam. Compensation of the intrinsic sample tilt can result in horizontal structure and reduced Z-dimension of tomograms. Our fast, pre-reconstruction method can thus provide important sample parameters that can help improve performance of tomographic reconstruction of a wide range of samples.
Project description:Cryo-electron tomography combined with subtomogram averaging (StA) has yielded high-resolution structures of macromolecules in their native context. However, high-resolution StA is not commonplace due to beam-induced sample drift, images with poor signal-to-noise ratios (SNR), challenges in CTF correction, and limited particle number. Here we address these issues by collecting tilt series with a higher electron dose at the zero-degree tilt. Particles of interest are then located within reconstructed tomograms, processed by conventional StA, and then re-extracted from the high-dose images in 2D. Single particle analysis tools are then applied to refine the 2D particle alignment and generate a reconstruction. Use of our hybrid StA (hStA) workflow improved the resolution for tobacco mosaic virus from 7.2 to 4.4?Å and for the ion channel RyR1 in crowded native membranes from 12.9 to 9.1?Å. These resolution gains make hStA a promising approach for other StA projects aimed at achieving subnanometer resolution.
Project description:Cryo-electron tomography (Cryo-ET) is a powerful three-dimensional (3-D) imaging technique for visualizing macromolecular complexes in their native context at a molecular level. The technique involves initially preserving the sample in its native state by rapidly freezing the specimen in vitreous ice, then collecting a series of micrographs from different angles at high magnification, and finally computationally reconstructing a 3-D density map. The frozen-hydrated specimen is extremely sensitive to the electron beam and so micrographs are collected at very low electron doses to limit the radiation damage. As a result, the raw cryo-tomogram has a very low signal to noise ratio characterized by an intrinsically noisy image. To better visualize subjects of interest, conventional imaging analysis and sub-tomogram averaging in which sub-tomograms of the subject are extracted from the initial tomogram and aligned and averaged are utilized to improve both contrast and resolution. Large datasets of tilt-series are essential to understanding and resolving the complexes at different states, conditions, or mutations as well as obtaining a large enough collection of sub-tomograms for averaging and classification. Collecting and processing this data can be a major obstacle preventing further analysis. Here we describe a high-throughput cryo-ET protocol based on a computer-controlled 300kV cryo-electron microscope, a direct detection device (DDD) camera and a highly effective, semi-automated image-processing pipeline software wrapper library tomoauto developed in-house. This protocol has been effectively utilized to visualize the intact type III secretion system (T3SS) in Shigella flexneri minicells. It can be applicable to any project suitable for cryo-ET.
Project description:Myosin interacting-heads (MIH) motifs are visualized in 3D-reconstructions of thick filaments from striated muscle. These reconstructions are calculated by averaging methods using images from electron micrographs of grids prepared using numerous filament preparations. Here we propose an alternative method to calculate the 3D-reconstruction of a single thick filament using only a tilt series images recorded by electron tomography. Relaxed thick filaments, prepared from tarantula leg muscle homogenates, were negatively stained. Single-axis tilt series of single isolated thick filaments were obtained with the electron microscope at a low electron dose, and recorded on a CCD camera by electron tomography. An IHRSR 3D-recontruction was calculated from the tilt series images of a single thick filament. The reconstruction was enhanced by including in the search stage dual tilt image segments while only single tilt along the filament axis is usually used, as well as applying a band pass filter just before the back projection. The reconstruction from a single filament has a 40 Å resolution and clearly shows the presence of MIH motifs. In contrast, the electron tomogram 3D-reconstruction of the same thick filament - calculated without any image averaging and/or imposition of helical symmetry - only reveals MIH motifs infrequently. This is - to our knowledge - the first application of the IHRSR method to calculate a 3D reconstruction from tilt series images. This single filament IHRSR reconstruction method (SF-IHRSR) should provide a new tool to assess structural differences between well-ordered thick (or thin) filaments in a grid by recording separately their electron tomograms.
Project description:In electron tomography, accurate alignment of tilt series is an essential step in attaining high-resolution 3D reconstructions. Nevertheless, quantitative assessment of alignment quality has remained a challenging issue, even though many alignment methods have been reported. Here, we report a fast and accurate method, tomoAlignEval, based on the Beer-Lambert law, for the evaluation of alignment quality. Our method is able to globally estimate the alignment accuracy by measuring the goodness of log-linear relationship of the beam intensity attenuations at different tilt angles. Extensive tests with experimental data demonstrated its robust performance with stained and cryo samples. Our method is not only significantly faster but also more sensitive than measurements of tomogram resolution using Fourier shell correlation method (FSCe/o). From these tests, we also conclude that while current alignment methods are sufficiently accurate for stained samples, inaccurate alignments remain a major limitation for high resolution cryo-electron tomography.
Project description: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.
Project description:Cryo-electron tomography (cryo-ET) provides three-dimensional (3D) structural information of bacteria preserved in a native, frozen-hydrated state. The typical low contrast of tilt-series images, a result of both the need for a low electron dose and the use of conventional defocus phase-contrast imaging, is a challenge for high-quality tomograms. We show that Zernike phase-contrast imaging allows the electron dose to be reduced. This limits movement of gold fiducials during the tilt series, which leads to better alignment and a higher-resolution reconstruction. Contrast is also enhanced, improving visibility of weak features. The reduced electron dose also means that more images at more tilt angles could be recorded, further increasing resolution.
Project description:Cryo electron tomography (CryoET) produces 3D density maps of biological specimen in its near native states. Applied to small cells, cryoET produces 3D snapshots of the cellular distributions of large complexes. However, retrieving this information is non-trivial due to the low resolution and low signal-to-noise ratio in tomograms. Current pattern recognition methods identify complexes by matching known structures to the cryo electron tomogram. However, so far only a small fraction of all protein complexes have been structurally resolved. It is, therefore, of great importance to develop template-free methods for the discovery of previously unknown protein complexes in cryo electron tomograms.Here, we have developed an inference method for the template-free discovery of frequently occurring protein complexes in cryo electron tomograms. We provide a first proof-of-principle of the approach and assess its applicability using realistically simulated tomograms, allowing for the inclusion of noise and distortions due to missing wedge and electron optical factors. Our method is a step toward the template-free discovery of the shapes, abundance and spatial distributions of previously unknown macromolecular complexes in whole cell firstname.lastname@example.org