Automatic alignment of stacks of filament data

We present a fast and robust method for the alignment of image stacks containing filamentous structures. Such stacks are usually obtained by physical sectioning a specimen, followed by an optical sectioning of each slice. For reconstruction, the filaments have to be traced and the sub-volumes aligned. Our algorithm takes traced filaments as input and matches their endpoints to find the optimal transform. We show that our method is able to quickly and accurately align sub-volumes containing neuronal processes, acquired using brightfield microscopy. Our method also makes it possible to align traced microtubuli, obtained from electron tomography data, which are extremely difficult to align manually

Index to NASA Tech Briefs, January - June 1966

Index to NASA technological innovations for January-June 196

Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection

In the field of connectomics, neuroscientists seek to identify cortical connectivity comprehensively. Neuronal boundary detection from the Electron Microscopy (EM) images is often done to assist the automatic reconstruction of neuronal circuit. But the segmentation of EM images is a challenging problem, as it requires the detector to be able to detect both filament-like thin and blob-like thick membrane, while suppressing the ambiguous intracellular structure. In this paper, we propose multi-stage multi-recursive-input fully convolutional networks to address this problem. The multiple recursive inputs for one stage, i.e., the multiple side outputs with different receptive field sizes learned from the lower stage, provide multi-scale contextual boundary information for the consecutive learning. This design is biologically-plausible, as it likes a human visual system to compare different possible segmentation solutions to address the ambiguous boundary issue. Our multi-stage networks are trained end-to-end. It achieves promising results on two public available EM segmentation datasets, the mouse piriform cortex dataset and the ISBI 2012 EM dataset.Comment: Accepted by ICCV201

4-D single particle tracking of synthetic and proteinaceous microspheres reveals preferential movement of nuclear particles along chromatin – poor tracks

BACKGROUND: The dynamics of nuclear organization, nuclear bodies and RNPs in particular has been the focus of many studies. To understand their function, knowledge of their spatial nuclear position and temporal translocation is essential. Typically, such studies generate a wealth of data that require novel methods in image analysis and computational tools to quantitatively track particle movement on the background of moving cells and shape changing nuclei. RESULTS: We developed a novel 4-D image processing platform (TIKAL) for the work with laser scanning and wide field microscopes. TIKAL provides a registration software for correcting global movements and local deformations of cells as well as 2-D and 3-D tracking software. With this new tool, we studied the dynamics of two different types of nuclear particles, namely nuclear bodies made from GFP-NLS-vimentin and microinjected 0.1 μm – wide polystyrene beads, by live cell time-lapse microscopy combined with single particle tracking and mobility analysis. We now provide a tool for the automatic 3-D analysis of particle movement in parallel with the acquisition of chromatin density data. CONCLUSIONS: Kinetic analysis revealed 4 modes of movement: confined obstructed, normal diffusion and directed motion. Particle tracking on the background of stained chromatin revealed that particle movement is directly related to local reorganization of chromatin. Further a direct comparison of particle movement in the nucleoplasm and the cytoplasm exhibited an entirely different kinetic behaviour of vimentin particles in both compartments. The kinetics of nuclear particles were slightly affected by depletion of ATP and significantly disturbed by disruption of actin and microtubule networks. Moreover, the hydration state of the nucleus had a strong impact on the mobility of nuclear bodies since both normal diffusion and directed motion were entirely abolished when cells were challenged with 0.6 M sorbitol. This effect correlated with the compaction of chromatin. We conclude that alteration in chromatin density directly influences the mobility of protein assemblies within the nucleus

The metabolic enzyme CTP synthase forms cytoskeletal filaments

Filament-forming cytoskeletal proteins are essential for the structure and organization of all cells. Bacterial homologues of the major eukaryotic cytoskeletal families have now been discovered, but studies suggest that yet more remain to be identified. We demonstrate that the metabolic enzyme CTP synthase (CtpS) forms filaments in Caulobacter crescentus. CtpS is bifunctional, as the filaments it forms regulate the curvature of C. crescentus cells independently of its catalytic function. The morphogenic role of CtpS requires its functional interaction with the intermediate filament, crescentin (CreS). Interestingly, the Escherichia coli CtpS homologue also forms filaments both in vivo and in vitro, suggesting that CtpS polymerization may be widely conserved. E. coli CtpS can replace the enzymatic and morphogenic functions of C. crescentus CtpS, indicating that C. crescentus has adapted a conserved filament-forming protein for a secondary role. These results implicate CtpS as a novel bifunctional member of the bacterial cytoskeleton and suggest that localization and polymerization may be important properties of metabolic enzymes

The Correlation-Based Method for the Movement Compensation in the Analysis of the Results of FRAP Experiments

This paper presents a computational algorithm for the detection and compensation for intracellular movement in the FRAP experiments with focal adhesions in living cells. The developed approach is based on the calculation of correlation coefficient. It was validated on the series of the experimental datasets and shows the successful results in the comparison with other widelyestablished methods

3D immuno-confocal image reconstruction of fibroblast cytoskeleton and nucleus architecture

Computational models of cellular structures generally rely on simplifying approximations and assumptions that limit biological accuracy. This study presents a comprehensive image processing pipeline for creating unified three‐dimensional (3D) reconstructions of the cell cytoskeletal networks and nuclei. Confocal image stacks of these cellular structures were reconstructed to 3D isosurfaces (Imaris), then tessellations were simplified to reduce the number of elements in initial meshes by applying quadric edge collapse decimation with preserved topology boundaries (MeshLab). Geometries were remeshed to ensure uniformity (Instant Meshes) and the resulting 3D meshes exported (ABAQUS) for downstream application. The protocol has been applied successfully to fibroblast cytoskeletal reorganisation in the scleral connective tissue of the eye, under mechanical load that mimics internal eye pressure. While the method herein is specifically employed to reconstruct immunofluorescent confocal imaging data, it is also more widely applicable to other biological imaging modalities where accurate 3D cell structures are required