77 research outputs found
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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)
A versatile gene trap to visualize and interrogate the function of the vertebrate proteome
We report a multifunctional gene-trapping approach, which generates full-length Citrine fusions with endogenous proteins and conditional mutants from a single integration event of the FlipTrap vector. We identified 170 FlipTrap zebrafish lines with diverse tissue-specific expression patterns and distinct subcellular localizations of fusion proteins generated by the integration of an internal citrine exon. Cre-mediated conditional mutagenesis is enabled by heterotypic lox sites that delete Citrine and “flip” in its place mCherry with a polyadenylation signal, resulting in a truncated fusion protein. Inducing recombination with Cerulean-Cre results in fusion proteins that often mislocalize, exhibit mutant phenotypes, and dramatically knock down wild-type transcript levels. FRT sites in the vector enable targeted genetic manipulation of the trapped loci in the presence of Flp recombinase. Thus, the FlipTrap captures the functional proteome, enabling the visualization of full-length fluorescent fusion proteins and interrogation of function by conditional mutagenesis and targeted genetic manipulation
Attenuation of Notch and Hedgehog Signaling Is Required for Fate Specification in the Spinal Cord
During the development of the spinal cord, proliferative neural progenitors differentiate into postmitotic neurons with distinct fates. How cells switch from progenitor states to differentiated fates is poorly understood. To address this question, we studied the differentiation of progenitors in the zebrafish spinal cord, focusing on the differentiation of Kolmer-Agduhr″ (KA″) interneurons from lateral floor plate (LFP) progenitors. In vivo cell tracking demonstrates that KA″ cells are generated from LFP progenitors by both symmetric and asymmetric cell divisions. A photoconvertible reporter of signaling history (PHRESH) reveals distinct temporal profiles of Hh response: LFP progenitors continuously respond to Hh, while KA″ cells lose Hh response upon differentiation. Hh signaling is required in LFP progenitors for KA″ fate specification, but prolonged Hh signaling interferes with KA″ differentiation. Notch signaling acts permissively to maintain LFP progenitor cells: activation of Notch signaling prevents differentiation, whereas inhibition of Notch signaling results in differentiation of ectopic KA″ cells. These results indicate that neural progenitors depend on Notch signaling to maintain Hh responsiveness and rely on Hh signaling to induce fate identity, whereas proper differentiation depends on the attenuation of both Notch and Hh signaling
Towards a Synthetic Chloroplast
The evolution of eukaryotic cells is widely agreed to have proceeded through a series of endosymbiotic events between larger cells and proteobacteria or cyanobacteria, leading to the formation of mitochondria or chloroplasts, respectively. Engineered endosymbiotic relationships between different species of cells are a valuable tool for synthetic biology, where engineered pathways based on two species could take advantage of the unique abilities of each mutualistic partner.We explored the possibility of using the photosynthetic bacterium Synechococcus elongatus PCC 7942 as a platform for studying evolutionary dynamics and for designing two-species synthetic biological systems. We observed that the cyanobacteria were relatively harmless to eukaryotic host cells compared to Escherichia coli when injected into the embryos of zebrafish, Danio rerio, or taken up by mammalian macrophages. In addition, when engineered with invasin from Yersinia pestis and listeriolysin O from Listeria monocytogenes, S. elongatus was able to invade cultured mammalian cells and divide inside macrophages.Our results show that it is possible to engineer photosynthetic bacteria to invade the cytoplasm of mammalian cells for further engineering and applications in synthetic biology. Engineered invasive but non-pathogenic or immunogenic photosynthetic bacteria have great potential as synthetic biological devices
Digitizing life at the level of the cell: high-performance laser-scanning microscopy and image analysis for in toto imaging of development
The field of biological imaging is progressing at an amazing rate. Advances in both laser-scanning microscopy and green fluorescent protein (GFP) technology are combining to make possible imaging-based approaches for studying developmental mechanisms that were previously impossible. Modern confocal and multi-photon microscopes are pushing the envelope of speed, sensitivity, spectral resolution, and depth resolution to allow in vivo imaging of whole, live embryos at cellular resolution over extended periods of time. In toto imaging, in which nearly every cell in an embryo or tissue can be tracked through space and time during development, may become a standard technique for small transparent embryos such as zebrafish and early stage chick and mouse embryos. GFP and its spectral variants can be used to mark a wide range of in vivo biological information for in toto imaging including gene expression patterns, mutant phenotypes, and protein subcellular localization patterns. Combining in toto imaging and GFP transgenic approaches on a large scale may usher in an explosion of in vivo, developmental data as has happened in the past several years with genomic data. There are significant challenges that must be met to reach these goals. This paper will discuss the current state-of-the-art, the challenges, and the prospects of in toto imaging in the areas of imaging, image analysis, and informatics
Imaging in Systems Biology
Most systems biology approaches involve determining the structure of biological circuits using genomewide “-omic” analyses. Yet imaging offers the unique advantage of watching biological circuits function over time at single-cell resolution in the intact animal. Here, we discuss the power of integrating imaging tools with more conventional -omic approaches to analyze the biological circuits of microorganisms, plants, and animals
An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs
In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK) v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse) and grid representations (point, mesh, and image-based). Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a flexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g. gradient and Hessians) across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a developing zebrafish embryo
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