Embryo Cell Membranes Reconstruction by Tensor Voting

International audienceImage-based studies of developing organs or embryos produce a huge quantity of data. To handle such high-throughput experimental protocols, automated computer-assisted methods are highly desirable. This article aims at designing an efficient cell segmentation method from microscopic images. The proposed approach is twofold: first, cell membranes are enhanced or extracted by the means of structure-based filters, and then perceptual grouping (i.e. tensor voting) allows to correct for segmentation gaps. To decrease the computational cost of this last step, we propose different methodologies to reduce the number of voters. Assessment on real data allows us to deduce the most efficient approach

ACME: Automated Cell Morphology Extractor for Comprehensive Reconstruction of Cell Membranes

The quantification of cell shape, cell migration, and cell rearrangements is important for addressing classical questions in developmental biology such as patterning and tissue morphogenesis. Time-lapse microscopic imaging of transgenic embryos expressing fluorescent reporters is the method of choice for tracking morphogenetic changes and establishing cell lineages and fate maps in vivo. However, the manual steps involved in curating thousands of putative cell segmentations have been a major bottleneck in the application of these technologies especially for cell membranes. Segmentation of cell membranes while more difficult than nuclear segmentation is necessary for quantifying the relations between changes in cell morphology and morphogenesis. We present a novel and fully automated method to first reconstruct membrane signals and then segment out cells from 3D membrane images even in dense tissues. The approach has three stages: 1) detection of local membrane planes, 2) voting to fill structural gaps, and 3) region segmentation. We demonstrate the superior performance of the algorithms quantitatively on time-lapse confocal and two-photon images of zebrafish neuroectoderm and paraxial mesoderm by comparing its results with those derived from human inspection. We also compared with synthetic microscopic images generated by simulating the process of imaging with fluorescent reporters under varying conditions of noise. Both the over-segmentation and under-segmentation percentages of our method are around 5%. The volume overlap of individual cells, compared to expert manual segmentation, is consistently over 84%. By using our software (ACME) to study somite formation, we were able to segment touching cells with high accuracy and reliably quantify changes in morphogenetic parameters such as cell shape and size, and the arrangement of epithelial and mesenchymal cells. Our software has been developed and tested on Windows, Mac, and Linux platforms and is available publicly under an open source BSD license (https://github.com/krm15/ACME)

Cell Pairings for Ascidian Embryo Registration

International audienceRecent microscopy techniques allow imaging temporal 3D stacks of developing organs or embryos with a cellular level of resolution and with a sufficient acquisition frequency to accurately track cell lineages. Imaging multiple organs or embryos in different experimental conditions may help decipher the impact of genetic backgrounds and environmental inputs on the developmental pro-gram. For this, we need to precisely compare distinct individuals and to compute population statistics. The first step of this procedure is to develop methods to register individuals. From a previous work of cell segmentation from microscopy im-ages, we here demonstrate how to extract the symmetry plane of em-bryos at early stages, and how to use this information as a geometri-cal constraint to both register these embryos and obtain a cell-to-cell mapping

Observing the Cell in Its Native State: Imaging Subcellular Dynamics in Multicellular Organisms

True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments

Doctor of Philosophy

dissertationElectron microscopy can visualize synapses at nanometer resolution, and can thereby capture the fine structure of these contacts. However, this imaging method lacks three key elements: temporal information, protein visualization, and large volume reconstruction. For my dissertation, I developed three methods in electron microscopy that overcame these limitations. First, I developed a method to freeze neurons at any desired time point after a stimulus to study synaptic vesicle cycle. Second, I developed a method to couple super-resolution fluorescence microscopy and electron microscopy to pinpoint the location of proteins in electron micrographs at nanometer resolution. Third, I collaborated with computer scientists to develop methods for semi-automated reconstruction of nervous system. I applied these techniques to answer two fundamental questions in synaptic biology. Which vesicles fuse in response to a stimulus? How are synaptic vesicles recovered at synapses after fusion? Only vesicles that are in direct contact with plasma membrane fuse upon stimulation. The active zone in C. elegans is broad, but primed vesicles are concentrated around the dense projection. Following exocytosis of synaptic vesicles, synaptic vesicle membrane was recovered rapidly at two distinct locations at a synapse: the dense projection and adherens junctions. These studies suggest that there may be a novel form of ultrafast endocytosis

New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced datasets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present thesis introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images.Comment: 218 pages, 58 figures, PhD thesis, Department of Mechanical Engineering, Karlsruhe Institute of Technology, published online with KITopen (License: CC BY-SA 3.0, http://dx.doi.org/10.5445/IR/1000057821

Observing the Cell in Its Native State: Imaging Subcellular Dynamics in Multicellular Organisms

True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments

Meshing Meristems - An Iterative Mesh Optimization Method for Modeling Plant Tissue at Cell Resolution

International audienceWe address in this paper the problem of reconstructing a mesh representation of plant cells in a complex, multi-layered tissue structure, based on segmented images obtained from confocal microscopy of shoot apical meristem of model plant Arabidopsis thaliana. The construction of such mesh structures for plant tissues is currently a missing step in the existing image analysis pipelines. We propose a method for optimizing the surface triangular meshes representing the tissue simultaneously along several criteria, based on an initial low-quality mesh. The mesh geometry is deformed by iteratively minimizing an energy functional defined over this discrete surface representation. This optimization results in a light discrete representation of the cell surfaces that enables fast visualization, and quantitative analysis, and gives way to in silico physical and mechanical simulations on real-world data. We provide a framework for evaluating the quality of the cell tissue reconstruction, that underlines the ability of our method to fit multiple optimization criteria

New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty

Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images

In situ architecture of neuronal α-Synuclein inclusions

The molecular architecture of α-Synuclein (α-Syn) inclusions, pathognomonic of various neurodegenerative disorders, remains unclear. α-Syn inclusions were long thought to consist mainly of α-Syn fibrils, but recent reports pointed to intracellular membranes as the major inclusion component. Here, we use cryo-electron tomography (cryo-ET) to image neuronal α-Syn inclusions in situ at molecular resolution. We show that inclusions seeded by α-Syn aggregates produced recombinantly or purified from patient brain consist of α-Syn fibrils crisscrossing a variety of cellular organelles. Using gold-labeled seeds, we find that aggregate seeding is predominantly mediated by small α-Syn fibrils, from which cytoplasmic fibrils grow unidirectionally. Detailed analysis of membrane interactions revealed that α-Syn fibrils do not contact membranes directly, and that α-Syn does not drive membrane clustering. Altogether, we conclusively demonstrate that neuronal α-Syn inclusions consist of α-Syn fibrils intermixed with membranous organelles, and illuminate the mechanism of aggregate seeding and cellular interaction