AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction.

Motivation: Dual-axis electron tomography is an important 3 D macro-molecular structure reconstruction technology, which can reduce artifacts and suppress the effect of missing wedge. However, the fully automatic data process for dual-axis electron tomography still remains a challenge due to three difficulties: (i) how to track the mass of fiducial markers automatically; (ii) how to integrate the information from the two different tilt series; and (iii) how to cope with the inconsistency between the two different tilt series. Results: Here we develop a toolkit for fully automatic alignment of dual-axis electron tomography, with a simultaneous reconstruction procedure. The proposed toolkit and its workflow carries out the following solutions: (i) fully automatic detection and tracking of fiducial markers under large-field datasets; (ii) automatic combination of two different tilt series and global calibration of projection parameters; and (iii) inconsistency correction based on distortion correction parameters and the consequently simultaneous reconstruction. With all of these features, the presented toolkit can achieve accurate alignment and reconstruction simultaneously and conveniently under a single global coordinate system. Availability and implementation: The toolkit AuTom-dualx (alignment module dualxmauto and reconstruction module volrec_mltm) are accessible for general application at http://ear.ict.ac.cn, and the key source code is freely available under request. Supplementary information: Supplementary data are available at Bioinformatics online.

Iron-specific Signal Separation from within Heavy Metal Stained Biological Samples Using X-Ray Microtomography with Polychromatic Source and Energy-Integrating Detectors.

Biological samples are frequently stained with heavy metals in preparation for examining the macro, micro and ultra-structure using X-ray microtomography and electron microscopy. A single X-ray microtomography scan reveals detailed 3D structure based on staining density, yet it lacks both material composition and functional information. Using a commercially available polychromatic X-ray source, energy integrating detectors and a two-scan configuration labelled by their energy- "High" and "Low", we demonstrate how a specific element, here shown with iron, can be detected from a mixture with other heavy metals. With proper selection of scan configuration, achieving strong overlap of source characteristic emission lines and iron K-edge absorption, iron absorption was enhanced enabling K-edge imaging. Specifically, iron images were obtained by scatter plot material analysis, after selecting specific regions within scatter plots generated from the "High" and "Low" scans. Using this method, we identified iron rich regions associated with an iron staining reaction that marks the nodes of Ranvier along nerve axons within mouse spinal roots, also stained with osmium metal commonly used for electron microscopy.

Monomeric C-Reactive Protein Binds and Neutralizes Receptor Activator of NF-κB Ligand-Induced Osteoclast Differentiation.

C-reactive protein (CRP) is an established marker of rheumatoid arthritis (RA) but with ill-defined actions in the pathogenesis. Here, we show that CRP regulates the differentiation of osteoclasts, a central mediator of joint inflammation and bone erosion in RA, in a conformation- and receptor activator of NF-κB ligand (RANKL)-dependent manner. CRP in the native conformation is ineffective, whereas the monomeric conformation (mCRP) actively modulates osteoclast differentiation through NF-κB and phospholipase C signaling. Moreover, mCRP can bind RANKL, the major driver of osteoclast differentiation, and abrogate its activities. The binding and inhibition of RANKL are mediated by the cholesterol binding sequence (CBS) of mCRP. Corroborating the in vitro results, CRP knockout exacerbates LPS-induced bone resorption in mice. These results suggest that mCRP may be protective in joint inflammation by inhibiting pathological osteoclast differentiation and that the CBS peptide could be exploited as a potential RANKL inhibitor.

Electron tomography simulator with realistic 3D phantom for evaluation of acquisition, alignment and reconstruction methods.

Because of the significance of electron microscope tomography in the investigation of biological structure at nanometer scales, ongoing improvement efforts have been continuous over recent years. This is particularly true in the case of software developments. Nevertheless, verification of improvements delivered by new algorithms and software remains difficult. Current analysis tools do not provide adaptable and consistent methods for quality assessment. This is particularly true with images of biological samples, due to image complexity, variability, low contrast and noise. We report an electron tomography (ET) simulator with accurate ray optics modeling of image formation that includes curvilinear trajectories through the sample, warping of the sample and noise. As a demonstration of the utility of our approach, we have concentrated on providing verification of the class of reconstruction methods applicable to wide field images of stained plastic-embedded samples. Accordingly, we have also constructed digital phantoms derived from serial block face scanning electron microscope images. These phantoms are also easily modified to include alignment features to test alignment algorithms. The combination of more realistic phantoms with more faithful simulations facilitates objective comparison of acquisition parameters, alignment and reconstruction algorithms and their range of applicability. With proper phantoms, this approach can also be modified to include more complex optical models, including distance-dependent blurring and phase contrast functions, such as may occur in cryotomography.

3D reconstruction of biological structures: automated procedures for alignment and reconstruction of multiple tilt series in electron tomography.

Transmission electron microscopy allows the collection of multiple views of specimens and their computerized three-dimensional reconstruction and analysis with electron tomography. Here we describe development of methods for automated multi-tilt data acquisition, tilt-series processing, and alignment which allow assembly of electron tomographic data from a greater number of tilt series, yielding enhanced data quality and increasing contrast associated with weakly stained structures. This scheme facilitates visualization of nanometer scale details of fine structure in volumes taken from plastic-embedded samples of biological specimens in all dimensions. As heavy metal-contrasted plastic-embedded samples are less sensitive to the overall dose rather than the electron dose rate, an optimal resampling of the reconstruction space can be achieved by accumulating lower dose electron micrographs of the same area over a wider range of specimen orientations. The computerized multiple tilt series collection scheme is implemented together with automated advanced procedures making collection, image alignment, and processing of multi-tilt tomography data a seamless process. We demonstrate high-quality reconstructions from samples of well-described biological structures. These include the giant Mimivirus and clathrin-coated vesicles, imaged in situ in their normal intracellular contexts. Examples are provided from samples of cultured cells prepared by high-pressure freezing and freeze-substitution as well as by chemical fixation before epoxy resin embedding.

BSIRT: a block-iterative SIRT parallel algorithm using curvilinear projection model.

Large-field high-resolution electron tomography enables visualizing detailed mechanisms under global structure. As field enlarges, the distortions of reconstruction and processing time become more critical. Using the curvilinear projection model can improve the quality of large-field ET reconstruction, but its computational complexity further exacerbates the processing time. Moreover, there is no parallel strategy on GPU for iterative reconstruction method with curvilinear projection. Here we propose a new Block-iterative SIRT parallel algorithm with the curvilinear projection model (BSIRT) for large-field ET reconstruction, to improve the quality of reconstruction and accelerate the reconstruction process. We also develop some key techniques, including block-iterative method with the curvilinear projection, a scope-based data decomposition method and a page-based data transfer scheme to implement the parallelization of BSIRT on GPU platform. Experimental results show that BSIRT can improve the reconstruction quality as well as the speed of the reconstruction process.

EPiK-a Workflow for Electron Tomography in Kepler.

Scientific workflows integrate data and computing interfaces as configurable, semi-automatic graphs to solve a scientific problem. Kepler is such a software system for designing, executing, reusing, evolving, archiving and sharing scientific workflows. Electron tomography (ET) enables high-resolution views of complex cellular structures, such as cytoskeletons, organelles, viruses and chromosomes. Imaging investigations produce large datasets. For instance, in Electron Tomography, the size of a 16 fold image tilt series is about 65 Gigabytes with each projection image including 4096 by 4096 pixels. When we use serial sections or montage technique for large field ET, the dataset will be even larger. For higher resolution images with multiple tilt series, the data size may be in terabyte range. Demands of mass data processing and complex algorithms require the integration of diverse codes into flexible software structures. This paper describes a workflow for Electron Tomography Programs in Kepler (EPiK). This EPiK workflow embeds the tracking process of IMOD, and realizes the main algorithms including filtered backprojection (FBP) from TxBR and iterative reconstruction methods. We have tested the three dimensional (3D) reconstruction process using EPiK on ET data. EPiK can be a potential toolkit for biology researchers with the advantage of logical viewing, easy handling, convenient sharing and future extensibility.

TxBR montage reconstruction for large field electron tomography.

Electron tomography (ET) has been proven an essential technique for imaging the structure of cells beyond the range of the light microscope down to the molecular level. Large-field high-resolution views of biological specimens span more than four orders of magnitude in spatial scale, and, as a consequence, are rather difficult to generate directly. Various techniques have been developed towards generating those views, from increasing the sensor array size to implementing serial sectioning and montaging. Datasets and reconstructions obtained by the latter techniques generate multiple three-dimensional (3D) reconstructions, that need to be combined together to provide all the multiscale information. In this work, we show how to implement montages within TxBR, a tomographic reconstruction software package. This work involves some new application of mathematical concepts related to volume preserving transformations and issues of gauge ambiguity, which are essential problems arising from the nature of the observation in an electron microscope. The purpose of TxBR is to handle those issues as generally as possible in order to correct for most distortions in the 3D reconstructions and allow for a seamless recombination of ET montages.

Alignment of cryo-electron tomography datasets.

Data acquisition of cryo-electron tomography (CET) samples described in previous chapters involves relatively imprecise mechanical motions: the tilt series has shifts, rotations, and several other distortions between projections. Alignment is the procedure of correcting for these effects in each image and requires the estimation of a projection model that describes how points from the sample in three-dimensions are projected to generate two-dimensional images. This estimation is enabled by finding corresponding common features between images. This chapter reviews several software packages that perform alignment and reconstruction tasks completely automatically (or with minimal user intervention) in two main scenarios: using gold fiducial markers as high contrast features or using relevant biological structures present in the image (marker-free). In particular, we emphasize the key decision points in the process that users should focus on in order to obtain high-resolution reconstructions.

Serial reconstruction and montaging from large-field electron microscope tomograms.

Electron microscope tomography [1] has been proven as an essential technique for imaging the structure of cells beyond the range of the light microscope down to the molecular level. However, because of the extreme difference in spatial scales, there is a large gap to be bridged between light and electron microscopy. Various techniques have been developed, including increasing size of the sensor arrays, serial sectioning and montaging. Data sets and reconstructions obtained by the latter techniques generate many 3D reconstructions that need to be glued together to provide information at a larger spatial scale. However, during the course of data acquisition, thin slices may become warped in optical and electron microscope preparations. We review some procedures for de-warping sections and reassembling them into larger reconstructions, and present some data from electron microscopy.

Transform-based backprojection for volume reconstruction of large format electron microscope tilt series.

Alignment of the individual images of a tilt series is a critical step in obtaining high-quality electron microscope reconstructions. We report on general methods for producing good alignments, and utilizing the alignment data in subsequent reconstruction steps. Our alignment techniques utilize bundle adjustment. Bundle adjustment is the simultaneous calculation of the position of distinguished markers in the object space and the transforms of these markers to their positions in the observed images, along the bundle of particle trajectories along which the object is projected to each EM image. Bundle adjustment techniques are general enough to encompass the computation of linear, projective or nonlinear transforms for backprojection, and can compensate for curvilinear trajectories through the object, sample warping, and optical aberration. We will also report on new reconstruction codes and describe our results using these codes.

Automated most-probable loss tomography of thick selectively stained biological specimens with quantitative measurement of resolution improvement.

We describe the technique and application of energy filtering, automated most-probable loss (MPL) tomography to intermediate voltage electron microscopy (IVEM). We show that for thick, selectively stained biological specimens, this method produces a dramatic increase in resolution of the projections and the computed volumes versus standard unfiltered transmission electron microscopy (TEM) methods. This improvement in resolution is attributed to the reduction of chromatic aberration, which results from the large percentage of inelastic electron-scattering events for thick specimens. These improvements are particularly evident at the large tilt angles required to improve tomographic resolution in the z-direction. This method effectively increases the usable thickness of selectively stained samples that can be imaged at a given accelerating voltage by dramatically improving resolution versus unfiltered TEM and increasing signal-to-noise versus zero-loss imaging, thereby expanding the utility of the IVEM to deliver information from within specimens up to 3 microm thick.

High-performance electron tomography of complex biological specimens.

We have evaluated reconstruction methods using smooth basis functions in the electron tomography of complex biological specimens. In particular, we have investigated series expansion methods, with special emphasis on parallel computation. Among the methods investigated, the component averaging techniques have proven to be most efficient and have generally shown fast convergence rates. The use of smooth basis functions provides the reconstruction algorithms with an implicit regularization mechanism, very appropriate for noisy conditions. Furthermore, we have applied high-performance computing (HPC) techniques to address the computational requirements demanded by the reconstruction of large volumes. One of the standard techniques in parallel computing, domain decomposition, has yielded an effective computational algorithm which hides the latencies due to interprocessor communication. We present comparisons with weighted back-projection (WBP), one of the standard reconstruction methods in the areas of computational demand and reconstruction quality under noisy conditions. These techniques yield better results, according to objective measures of quality, than the weighted backprojection techniques after a very few iterations. As a consequence, the combination of efficient iterative algorithms and HPC techniques has proven to be well suited to the reconstruction of large biological specimens in electron tomography, yielding solutions in reasonable computation times.