NeuronBridge: an intuitive web application for neuronal morphology search across large data sets.

BACKGROUND: Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome's structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. RESULTS: Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine. CONCLUSIONS: NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org .

Neural circuit mechanisms for transforming learned olfactory valences into wind-oriented movement.

How memories are used by the brain to guide future action is poorly understood. In olfactory associative learning in Drosophila, multiple compartments of the mushroom body act in parallel to assign a valence to a stimulus. Here, we show that appetitive memories stored in different compartments induce different levels of upwind locomotion. Using a photoactivation screen of a new collection of split-GAL4 drivers and EM connectomics, we identified a cluster of neurons postsynaptic to the mushroom body output neurons (MBONs) that can trigger robust upwind steering. These UpWind Neurons (UpWiNs) integrate inhibitory and excitatory synaptic inputs from MBONs of appetitive and aversive memory compartments, respectively. After formation of appetitive memory, UpWiNs acquire enhanced response to reward-predicting odors as the response of the inhibitory presynaptic MBON undergoes depression. Blocking UpWiNs impaired appetitive memory and reduced upwind locomotion during retrieval. Photoactivation of UpWiNs also increased the chance of returning to a location where activation was terminated, suggesting an additional role in olfactory navigation. Thus, our results provide insight into how learned abstract valences are gradually transformed into concrete memory-driven actions through divergent and convergent networks, a neuronal architecture that is commonly found in the vertebrate and invertebrate brains.

Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster.

To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their function. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse driver lines targeting 198 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neural circuits and connectivity of premotor circuits while linking them to behavioral outputs.

A searchable image resource of Drosophila GAL4 driver expression patterns with single neuron resolution.

Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here, we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end, we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.

Rapid reconstruction of neural circuits using tissue expansion and light sheet microscopy.

Brain function is mediated by the physiological coordination of a vast, intricately connected network of molecular and cellular components. The physiological properties of neural network components can be quantified with high throughput. The ability to assess many animals per study has been critical in relating physiological properties to behavior. By contrast, the synaptic structure of neural circuits is presently quantifiable only with low throughput. This low throughput hampers efforts to understand how variations in network structure relate to variations in behavior. For neuroanatomical reconstruction, there is a methodological gulf between electron microscopic (EM) methods, which yield dense connectomes at considerable expense and low throughput, and light microscopic (LM) methods, which provide molecular and cell-type specificity at high throughput but without synaptic resolution. To bridge this gulf, we developed a high-throughput analysis pipeline and imaging protocol using tissue expansion and light sheet microscopy (ExLLSM) to rapidly reconstruct selected circuits across many animals with single-synapse resolution and molecular contrast. Using Drosophila to validate this approach, we demonstrate that it yields synaptic counts similar to those obtained by EM, enables synaptic connectivity to be compared across sex and experience, and can be used to correlate structural connectivity, functional connectivity, and behavior. This approach fills a critical methodological gap in studying variability in the structure and function of neural circuits across individuals within and between species.

Classification and genetic targeting of cell types in the primary taste and premotor center of the adult Drosophila brain.

Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. Here, we generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult Drosophila melanogaster, comprising approximately one third of all SEZ neurons. We characterize the single-cell anatomy of these neurons and find that they cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. We find that the majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior.

An unbiased template of the Drosophila brain and ventral nerve cord.

The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individual neurons and neural subtypes. Brain templates are essential for comparative biological studies because they enable analyzing many individuals in a common reference space. Several central brain templates exist for Drosophila, but every one is either biased, uses sub-optimal tissue preparation, is imaged at low resolution, or does not account for artifacts. No publicly available Drosophila ventral nerve cord template currently exists. In this work, we created high-resolution templates of the Drosophila brain and ventral nerve cord using the best-available technologies for imaging, artifact correction, stitching, and template construction using groupwise registration. We evaluated our central brain template against the four most competitive, publicly available brain templates and demonstrate that ours enables more accurate registration with fewer local deformations in shorter time.

A connectome and analysis of the adult Drosophila central brain.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain.

Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons ­ compared to some 86 billion in humans ­ the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map ­ or connectome ­ the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Conservation and divergence of related neuronal lineages in the Drosophila central brain.

Wiring a complex brain requires many neurons with intricate cell specificity, generated by a limited number of neural stem cells. Drosophila central brain lineages are a predetermined series of neurons, born in a specific order. To understand how lineage identity translates to neuron morphology, we mapped 18 Drosophila central brain lineages. While we found large aggregate differences between lineages, we also discovered shared patterns of morphological diversification. Lineage identity plus Notch-mediated sister fate govern primary neuron trajectories, whereas temporal fate diversifies terminal elaborations. Further, morphological neuron types may arise repeatedly, interspersed with other types. Despite the complexity, related lineages produce similar neuron types in comparable temporal patterns. Different stem cells even yield two identical series of dopaminergic neuron types, but with unrelated sister neurons. Together, these phenomena suggest that straightforward rules drive incredible neuronal complexity, and that large changes in morphology can result from relatively simple fating mechanisms.

Topological and modality-specific representation of somatosensory information in the fly brain.

Insects and mammals share similarities of neural organization underlying the perception of odors, taste, vision, sound, and gravity. We observed that insect somatosensation also corresponds to that of mammals. In Drosophila, the projections of all the somatosensory neuron types to the insect's equivalent of the spinal cord segregated into modality-specific layers comparable to those in mammals. Some sensory neurons innervate the ventral brain directly to form modality-specific and topological somatosensory maps. Ascending interneurons with dendrites in matching layers of the nerve cord send axons that converge to respective brain regions. Pathways arising from leg somatosensory neurons encode distinct qualities of leg movement information and play different roles in ground detection. Establishment of the ground pattern and genetic tools for neuronal manipulation should provide the basis for elucidating the mechanisms underlying somatosensation.

FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis.

BACKGROUND: Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations. RESULTS: Here, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender. CONCLUSION: The redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques.

Stem Cell-Intrinsic, Seven-up-Triggered Temporal Factor Gradients Diversify Intermediate Neural Progenitors.

Building a sizable, complex brain requires both cellular expansion and diversification. One mechanism to achieve these goals is production of multiple transiently amplifying intermediate neural progenitors (INPs) from a single neural stem cell. Like mammalian neural stem cells, Drosophila type II neuroblasts utilize INPs to produce neurons and glia. Within a given lineage, the consecutively born INPs produce morphologically distinct progeny, presumably due to differential inheritance of temporal factors. To uncover the underlying temporal fating mechanisms, we profiled type II neuroblasts' transcriptome across time. Our results reveal opposing temporal gradients of Imp and Syp RNA-binding proteins (descending and ascending, respectively). Maintaining high Imp throughout serial INP production expands the number of neurons and glia with early temporal fate at the expense of cells with late fate. Conversely, precocious upregulation of Syp reduces the number of cells with early fate. Furthermore, we reveal that the transcription factor Seven-up initiates progression of the Imp/Syp gradients. Interestingly, neuroblasts that maintain initial Imp/Syp levels can still yield progeny with a small range of early fates. We therefore propose that the Seven-up-initiated Imp/Syp gradients create coarse temporal windows within type II neuroblasts to pattern INPs, which subsequently undergo fine-tuned subtemporal patterning.

A toolbox to study epidermal cell types in zebrafish.

Epithelia provide a crucial protective barrier for our organs and are also the sites where the majority of carcinomas form. Most studies on epithelia and carcinomas use cell culture or organisms where high-resolution live imaging is inaccessible without invasive techniques. Here, we introduce the developing zebrafish epidermis as an excellent in vivo model system for studying a living epithelium. We developed tools to fluorescently tag specific epithelial cell types and express genes in a mosaic fashion using five Gal4 lines identified from an enhancer trap screen. When crossed to a variety of UAS effector lines, we can now track, ablate or monitor single cells at sub-cellular resolution. Using photo-cleavable morpholino oligonucleotides that target gal4, we can also express genes in a mosaic fashion at specific times during development. Together, this system provides an excellent in vivo alternative to tissue culture cells, without the intrinsic concerns of culture conditions or transformation, and enables the investigation of distinct cell types within living epithelial tissues.

The RNA Binding Protein Igf2bp1 Is Required for Zebrafish RGC Axon Outgrowth In Vivo.

Attractive growth cone turning requires Igf2bp1-dependent local translation of ß-actin mRNA in response to external cues in vitro. While in vivo studies have shown that Igf2bp1 is required for cell migration and axon terminal branching, a requirement for Igf2bp1 function during axon outgrowth has not been demonstrated. Using a timelapse assay in the zebrafish retinotectal system, we demonstrate that the ß-actin 3'UTR is sufficient to target local translation of the photoconvertible fluorescent protein Kaede in growth cones of pathfinding retinal ganglion cells (RGCs) in vivo. Igf2bp1 knockdown reduced RGC axonal outgrowth and tectal coverage and retinal cell survival. RGC-specific expression of a phosphomimetic Igf2bp1 reduced the density of axonal projections in the optic tract while sparing RGCs, demonstrating for the first time that Igf2bp1 is required during axon outgrowth in vivo. Therefore, regulation of local translation mediated by Igf2bp proteins may be required at all stages of axon development.

High-resolution analysis of central nervous system expression patterns in zebrafish Gal4 enhancer-trap lines.

BACKGROUND: The application of the Gal4/UAS system to enhancer and gene trapping screens in zebrafish has greatly increased the ability to label and manipulate cell populations in multiple tissues, including the central nervous system (CNS). However the ability to select existing lines for specific applications has been limited by the lack of detailed expression analysis. RESULTS: We describe a Gal4 enhancer trap screen in which we used advanced image analysis, including three-dimensional confocal reconstructions and documentation of expression patterns at multiple developmental time points. In all, we have created and annotated 98 lines exhibiting a wide range of expression patterns, most of which include CNS expression. Expression was also observed in nonneural tissues such as muscle, skin epithelium, vasculature, and neural crest derivatives. All lines and data are publicly available from the Zebrafish International Research Center (ZIRC) from the Zebrafish Model Organism Database (ZFIN). CONCLUSIONS: Our detailed documentation of expression patterns, combined with the public availability of images and fish lines, provides a valuable resource for researchers wishing to study CNS development and function in zebrafish. Our data also suggest that many existing enhancer trap lines may have previously uncharacterized expression in multiple tissues and cell types.

Parallel neural pathways in higher visual centers of the Drosophila brain that mediate wavelength-specific behavior.

Compared with connections between the retinae and primary visual centers, relatively less is known in both mammals and insects about the functional segregation of neural pathways connecting primary and higher centers of the visual processing cascade. Here, using the Drosophila visual system as a model, we demonstrate two levels of parallel computation in the pathways that connect primary visual centers of the optic lobe to computational circuits embedded within deeper centers in the central brain. We show that a seemingly simple achromatic behavior, namely phototaxis, is under the control of several independent pathways, each of which is responsible for navigation towards unique wavelengths. Silencing just one pathway is enough to disturb phototaxis towards one characteristic monochromatic source, whereas phototactic behavior towards white light is not affected. The response spectrum of each demonstrable pathway is different from that of individual photoreceptors, suggesting subtractive computations. A choice assay between two colors showed that these pathways are responsible for navigation towards, but not for the detection itself of, the monochromatic light. The present study provides novel insights about how visual information is separated and processed in parallel to achieve robust control of an innate behavior.

Wnt signaling regulates postembryonic hypothalamic progenitor differentiation.

Previous studies have raised the possibility that Wnt signaling may regulate both neural progenitor maintenance and neuronal differentiation within a single population. Here we investigate the role of Wnt/ß-catenin activity in the zebrafish hypothalamus and find that the pathway is first required for the proliferation of unspecified hypothalamic progenitors in the embryo. At later stages, including adulthood, sequential activation and inhibition of Wnt activity is required for the differentiation of neural progenitors and negatively regulates radial glia differentiation. The presence of Wnt activity is conserved in hypothalamic progenitors of the adult mouse, where it plays a conserved role in inhibiting the differentiation of radial glia. This study establishes the vertebrate hypothalamus as a model for Wnt-regulated postembryonic neural progenitor differentiation and defines specific roles for Wnt signaling in neurogenesis.

Crowding induces live cell extrusion to maintain homeostatic cell numbers in epithelia.

For an epithelium to provide a protective barrier, it must maintain homeostatic cell numbers by matching the number of dividing cells with the number of dying cells. Although compensatory cell division can be triggered by dying cells, it is unknown how cell death might relieve overcrowding due to proliferation. When we trigger apoptosis in epithelia, dying cells are extruded to preserve a functional barrier. Extrusion occurs by cells destined to die signalling to surrounding epithelial cells to contract an actomyosin ring that squeezes the dying cell out. However, it is not clear what drives cell death during normal homeostasis. Here we show in human, canine and zebrafish cells that overcrowding due to proliferation and migration induces extrusion of live cells to control epithelial cell numbers. Extrusion of live cells occurs at sites where the highest crowding occurs in vivo and can be induced by experimentally overcrowding monolayers in vitro. Like apoptotic cell extrusion, live cell extrusion resulting from overcrowding also requires sphingosine 1-phosphate signalling and Rho-kinase-dependent myosin contraction, but is distinguished by signalling through stretch-activated channels. Moreover, disruption of a stretch-activated channel, Piezo1, in zebrafish prevents extrusion and leads to the formation of epithelial cell masses. Our findings reveal that during homeostatic turnover, growth and division of epithelial cells on a confined substratum cause overcrowding that leads to their extrusion and consequent death owing to the loss of survival factors. These results suggest that live cell extrusion could be a tumour-suppressive mechanism that prevents the accumulation of excess epithelial cells.

A complex choreography of cell movements shapes the vertebrate eye.

Optic cup morphogenesis (OCM) generates the basic structure of the vertebrate eye. Although it is commonly depicted as a series of epithelial sheet folding events, this does not represent an empirically supported model. Here, we combine four-dimensional imaging with custom cell tracking software and photoactivatable fluorophore labeling to determine the cellular dynamics underlying OCM in zebrafish. Although cell division contributes to growth, we find it dispensable for eye formation. OCM depends instead on a complex set of cell movements coordinated between the prospective neural retina, retinal pigmented epithelium (RPE) and lens. Optic vesicle evagination persists for longer than expected; cells move in a pinwheel pattern during optic vesicle elongation and retinal precursors involute around the rim of the invaginating optic cup. We identify unanticipated movements, particularly of central and peripheral retina, RPE and lens. From cell tracking data, we generate retina, RPE and lens subdomain fate maps, which reveal novel adjacencies that might determine corresponding developmental signaling events. Finally, we find that similar movements also occur during chick eye morphogenesis, suggesting that the underlying choreography is conserved among vertebrates.

Interactive Extraction of Neural Structures with User-Guided Morphological Diffusion.

Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ine ective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.