Alternative automatic alignment method for specimen tilt-series images based on back-projected volume data cross-correlations

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

We 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.

Optimization-based simultaneous alignment and reconstruction in multi-element tomography

As x-ray microscopy is pushed into the nanoscale with the advent of more bright and coherent x-ray sources, associated improvement in spatial resolution becomes highly vulnerable to geometrical errors and uncertainties during data collection. We address a form of error in tomography experiments, namely, the drift between projections during the tomographic scan. Our proposed method can simultaneously recover the drift, while tomographically reconstructing the specimen based on a joint iterative optimization scheme. This approach utilizes the correlation provided from different view angles and different signals. While generally applicable, we demonstrate our method on x-ray fluorescence tomography from a tissue specimen and compare the reconstruction quality with conventional methods.

Tomographic Collection of Block-Based Sparse STEM Images: Practical Implementation and Impact on the Quality of the 3D Reconstructed Volume

The reduction of the electron dose in electron tomography of biological samples is of high significance to diminish radiation damages. Simulations have shown that sparse data collection can perform efficient electron dose reduction. Frameworks based on compressive-sensing or inpainting algorithms have been proposed to accurately reconstruct missing information in sparse data. The present work proposes a practical implementation to perform tomographic collection of block-based sparse images in scanning transmission electron microscopy. The method has been applied on sections of chemically-fixed and resin-embedded Trypanosoma brucei cells. There are 3D reconstructions obtained from various amounts of downsampling, which are compared and eventually the limits of electron dose reduction using this method are explored.

A nuclear membrane-derived structure associated with Atg8 is involved in the sequestration of selective cargo, the Cvt complex, during autophagosome formation in yeast

Macroautophagy (hereafter autophagy) is a conserved intracellular degradation mechanism required for cell survival. A double-membrane structure, the phagophore, is generated to sequester cytosolic cargos destined for degradation in the vacuole. The mechanism involved in the biogenesis of the phagophore is still an open question. We focused on 4 autophagy-related (Atg) proteins (Atg2, Atg9, Atg14, and Atg18), which are involved in the formation of the phagophore in order to gain a more complete understanding of the membrane dynamics that occur during formation of the autophagosome. The corresponding mutants, while defective in autophagy, nonetheless generate the membrane-bound form of Atg8, allowing us to use this protein as a marker for the nascent autophagosome precursor membrane. Using electron microscopy (EM), we discovered in these atg mutants a novel single-membrane structure (~120 to 150 nm in size). Electron tomography revealed that this structure originates from a part of the nuclear membrane, and we have named it the alphasome. Our data suggest that the alphasome is associated with Atg8, and sequesters selective cargo, the Cvt complex, during autophagy. Abbreviations: 3D: three-dimensional; AB: autophagic body; AP: autophagosome; Atg: autophagy-related; Cvt: cytoplasm-to-vacuole targeting; EM: electron microscopy; IEM: immunoelectron microscopy; L: lipid droplet; N: nucleus; NM: nuclear membrane; PAS: phagophore assembly site; PE: phosphatidylethanolamine; prApe1: precursor aminopeptidase I; rER: rough endoplasmic reticulum; TEM: transmission electron microscopy; V: vacuole; VLP: virus-like particle.

Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection

As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography.

A new field-of-view autotracking method based on back-projected ray image cross-correlation for online tomography reconstruction

In general, a tomogram cannot be observed immediately after the acquisition of a series of specimen tilt images, but is instead observed after the post-processing of the tilt series alignment, which often requires a substantial amount of time. Moreover, for general specimens, the automatic acquisition of the tilt series is difficult because field-of-view tracking frequently fails as the tilt angle or specimen thickness increases.In this study, we focus on the improvement of the field-of-view autotracking technique for the purpose of online tomography reconstruction and propose a new alternative technique [1,2]. The method we proposed uses a so-called 'back-projected ray image' instead of a specimen tilt image. The back-projected ray image is a cross-section image calculated from each projection image only during reconstruction. As a result of a study on 'ray images', the quality and accuracy of the cross-correlation between a pair of neighboring ray images among the tilt series were observed to be very high compared with those between a pair of projection images. We observed that a back projected ray image reliably cross-correlates with other neighboring ray images at the position of an existing three-dimensional object. The proposed method can therefore consistently track the field-of-view, overcoming the weakness of a conventional image-matching-based method. In addition, the present method is simple, and high speed processing is expected to be achieved because fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT) algorithms can be used.We applied this method to real specimens in online experiments using a TEM and thereby demonstrated its successful performance. Online autotracking experiments with thin-section samples were used to demonstrate the effectiveness of the proposed method. The field-of-view was automatically tracked with high accuracy through a tilt angle range. Furthermore, online tomograms were obtained immediately after the last specimen tilting. With increases in the tracking speed, in situ tomographic observations for analyzing the dynamic behavior might become feasible in the future.jmicro;63/suppl_1/i23-a/DFU058F1F1DFU058F1Fig. 1.Comparison of the proposed autotracking method with the conventional PCF based alignment method using the yeast cell thin-section. a and b: Reconstructed X-Y cross-section images from tracking results at 8° increment angle with the PCF method and with the proposed method. N, nucleus; V, vacuole; NVJ, nucleus-vacuole junction. c: A reconstructed cross-section image from autotracking result at 1° increment angle with the proposed method. (scale bar: 100 nm).

A new field-of-view autotracking method for online tomography reconstruction based on back-projected ray image cross-correlation

We devised a new field-of-view autotracking method for online tomography reconstruction based on a cross-correlation between a pair of neighbours, called back-projected ray images, among a specimen tilt sequence. One ray image is calculated through normal filtered back-projection only in the cross-sectional plane from each projection image. This ray-image matching can reliably track the field-of-view because a pair of neighbouring ray images mostly cross-correlates at the existing three-dimensional object position. Online experiments using real specimens resulted in successful autotracking performance with high accuracy, and online tomograms were obtained immediately after the final tracking at the last tilting angle.