Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states

Advanced optical imaging in living embryos

Developmental biology investigations have evolved from static studies of embryo anatomy and into dynamic studies of the genetic and cellular mechanisms responsible for shaping the embryo anatomy. With the advancement of fluorescent protein fusions, the ability to visualize and comprehend how thousands to millions of cells interact with one another to form tissues and organs in three dimensions (xyz) over time (t) is just beginning to be realized and exploited. In this review, we explore recent advances utilizing confocal and multi-photon time-lapse microscopy to capture gene expression, cell behavior, and embryo development. From choosing the appropriate fluorophore, to labeling strategy, to experimental set-up, and data pipeline handling, this review covers the various aspects related to acquiring and analyzing multi-dimensional data sets. These innovative techniques in multi-dimensional imaging and analysis can be applied across a number of fields in time and space including protein dynamics to cell biology to morphogenesis

Hyperspectral phasor analysis enables multiplexed 5D in vivo imaging

Time-lapse imaging of multiple labels is challenging for biological imaging as noise, photobleaching and phototoxicity compromise signal quality, while throughput can be limited by processing time. Here, we report software called Hyper-Spectral Phasors (HySP) for denoising and unmixing multiple spectrally overlapping fluorophores in a low signal-to-noise regime with fast analysis. We show that HySP enables unmixing of seven signals in time-lapse imaging of living zebrafish embryos

Mutation of pescadillo Disrupts Oligodendrocyte Formation in Zebrafish

Background: In vertebrates, the myelin sheath is essential for efficient propagation of action potentials along the axon shaft. Oligodendrocytes are the cells of the central nervous system that create myelin sheaths. During embryogenesis, ventral neural tube precursors give rise to oligodendrocyte progenitor cells, which divide and migrate throughout the central nervous system. This study aimed to investigate mechanisms that regulate oligodendrocyte progenitor cell formation. Methodology/Principal Findings: By conducting a mutagenesis screen in transgenic zebrafish, we identified a mutation, designated vu166, by an apparent reduction in the number of oligodendrocyte progenitor cells in the dorsal spinal cord. We subsequently determined that vu166 is an allele of pescadillo, a gene known to play a role in ribosome biogenesis and cell proliferation. We found that pescadillo function is required for both the proper number of oligodendrocyte progenitors to form, by regulating cell cycle progression, and for normal levels of myelin gene expression. Conclusions/Significance: Our data provide evidence that neural precursors require pes function to progress through th

A Quantitative Image Cytometry Technique for Time Series or Population Analyses of Signaling Networks

Background: Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. Methodology/Principal Findings: We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. Conclusions/Significance: The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging

Expression of stabilized β-catenin in differentiated neurons of transgenic mice does not result in tumor formation

BACKGROUND: Medulloblastomas, embryonal tumors arising in the cerebellum, commonly contain mutations that activate Wnt signaling. To determine whether increased Wnt signaling in the adult CNS is sufficient to induce tumor formation, we created transgenic mice expressing either wild-type or activated β-catenin in the brain. METHODS: Wild-type and mutant human β-catenin transgenes were expressed under the control of a murine PrP promoter fragment that drives high level postnatal expression in the CNS. Mutant β-catenin was stabilized by a serine to phenylalanine alteration in codon 37. RESULTS: Expression of the mutant transgene resulted in an approximately two-fold increase in β-catenin protein levels in the cortex and cerebellum of adult animals. Immunohistochemical analysis revealed nuclear β-catenin in hippocampal, cortical and cerebellar neurons of transgenic animals but not in non-transgenic controls. Tail kinking was observed in some transgenic animals, but no CNS malformations or tumors were detected. CONCLUSIONS: No tumors or morphologic alterations were detected in the brains of transgenic mice expressing stabilized β-catenin, suggesting that postnatal Wnt signaling in differentiated neurons may not be sufficient to induce CNS tumorigenesis

Multi-Cellular Logistics of Collective Cell Migration

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems

The living microarray: a high-throughput platform for measuring transcription dynamics in single cells

<p>Abstract</p> <p>Background</p> <p>Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation and Systems Biology. However, endpoint measurements obtained from methods that pool populations of cells are not amenable to studying time-dependent processes that show cell heterogeneity.</p> <p>Results</p> <p>Here we describe a high-throughput platform for measuring transcriptional changes in real time in single mammalian cells. By using reverse transfection microarrays we are able to transfect fluorescent reporter plasmids into 600 independent clusters of cells plated on a single microscope slide and image these clusters every 20 minutes. We use a fast-maturing, destabilized and nuclear-localized reporter that is suitable for automated segmentation to accurately measure promoter activity in single cells. We tested this platform with synthetic drug-inducible promoters that showed robust induction over 24 hours. Automated segmentation and tracking of over 11 million cell images during this period revealed that cells display substantial heterogeneity in their responses to the applied treatment, including a large proportion of transfected cells that do not respond at all.</p> <p>Conclusions</p> <p>The results from our single-cell analysis suggest that methods that measure average cellular responses, such as DNA microarrays, RT-PCR and chromatin immunoprecipitation, characterize a response skewed by a subset of cells in the population. Our method is scalable and readily adaptable to studying complex systems, including cell proliferation, differentiation and apoptosis.</p

A Novel Function of DELTA-NOTCH Signalling Mediates the Transition from Proliferation to Neurogenesis in Neural Progenitor Cells

A complete account of the whole developmental process of neurogenesis involves understanding a number of complex underlying molecular processes. Among them, those that govern the crucial transition from proliferative (self-replicating) to neurogenic neural progenitor (NP) cells remain largely unknown. Due to its sequential rostro-caudal gradients of proliferation and neurogenesis, the prospective spinal cord of the chick embryo is a good experimental system to study this issue. We report that the NOTCH ligand DELTA-1 is expressed in scattered cycling NP cells in the prospective chick spinal cord preceding the onset of neurogenesis. These Delta-1-expressing progenitors are placed in between the proliferating caudal neural plate (stem zone) and the rostral neurogenic zone (NZ) where neurons are born. Thus, these Delta-1-expressing progenitors define a proliferation to neurogenesis transition zone (PNTZ). Gain and loss of function experiments carried by electroporation demonstrate that the expression of Delta-1 in individual progenitors of the PNTZ is necessary and sufficient to induce neuronal generation. The activation of NOTCH signalling by DELTA-1 in the adjacent progenitors inhibits neurogenesis and is required to maintain proliferation. However, rather than inducing cell cycle exit and neuronal differentiation by a typical lateral inhibition mechanism as in the NZ, DELTA-1/NOTCH signalling functions in a distinct manner in the PNTZ. Thus, the inhibition of NOTCH signalling arrests proliferation but it is not sufficient to elicit neuronal differentiation. Moreover, after the expression of Delta-1 PNTZ NP continue cycling and induce the expression of Tis21, a gene that is upregulated in neurogenic progenitors, before generating neurons. Together, these experiments unravel a novel function of DELTA–NOTCH signalling that regulates the transition from proliferation to neurogenesis in NP cells. We hypothesize that this novel function is evolutionary conserved

Systematic NMR Analysis of Stable Isotope Labeled Metabolite Mixtures in Plant and Animal Systems: Coarse Grained Views of Metabolic Pathways

BACKGROUND: Metabolic phenotyping has become an important 'bird's-eye-view' technology which can be applied to higher organisms, such as model plant and animal systems in the post-genomics and proteomics era. Although genotyping technology has expanded greatly over the past decade, metabolic phenotyping has languished due to the difficulty of 'top-down' chemical analyses. Here, we describe a systematic NMR methodology for stable isotope-labeling and analysis of metabolite mixtures in plant and animal systems. METHODOLOGY/PRINCIPAL FINDINGS: The analysis method includes a stable isotope labeling technique for use in living organisms; a systematic method for simultaneously identifying a large number of metabolites by using a newly developed HSQC-based metabolite chemical shift database combined with heteronuclear multidimensional NMR spectroscopy; Principal Components Analysis; and a visualization method using a coarse-grained overview of the metabolic system. The database contains more than 1000 (1)H and (13)C chemical shifts corresponding to 142 metabolites measured under identical physicochemical conditions. Using the stable isotope labeling technique in Arabidopsis T87 cultured cells and Bombyx mori, we systematically detected >450 HSQC peaks in each (13)C-HSQC spectrum derived from model plant, Arabidopsis T87 cultured cells and the invertebrate animal model Bombyx mori. Furthermore, for the first time, efficient (13)C labeling has allowed reliable signal assignment using analytical separation techniques such as 3D HCCH-COSY spectra in higher organism extracts. CONCLUSIONS/SIGNIFICANCE: Overall physiological changes could be detected and categorized in relation to a critical developmental phase change in B. mori by coarse-grained representations in which the organization of metabolic pathways related to a specific developmental phase was visualized on the basis of constituent changes of 56 identified metabolites. Based on the observed intensities of (13)C atoms of given metabolites on development-dependent changes in the 56 identified (13)C-HSQC signals, we have determined the changes in metabolic networks that are associated with energy and nitrogen metabolism