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175 Janelia Publications

Showing 71-80 of 175 results
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    07/21/22 | NeuronBridge: an intuitive web application for neuronal morphology search across large data sets
    Jody Clements , Cristian Goina , Philip M. Hubbard , Takashi Kawase , Donald J. Olbris , Hideo Otsuna , Robert Svirskas , Konrad Rokicki
    bioRxiv. 2022 Jul 21:. doi: 10.1101/2022.07.20.500311

    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. In order to exploit this knowledge base, researchers target individual neurons and study their function. Therefore, vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM). However, creating a fly line for driving gene expression within a single neuron found in the EM connectome remains a challenge, as it typically requires identifying a pair of fly 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. Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large datasets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly GUI, data model, serverless cloud architecture, and massively parallel image search engine. NeuronBridge is openly accessible at http://neuronbridge.janelia.org/.

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    07/20/22 | Print: An open access tool for EM connectomics.
    Plaza SM, Clements J, Dolafi T, Umayam L, Neubarth NN, Scheffer LK, Berg S
    Frontiers in Neuroinformatics. 2022 Jul 20;16:896292. doi: 10.3389/fninf.2022.896292

    Due to advances in electron microscopy and deep learning, it is now practical to reconstruct a connectome, a description of neurons and the chemical synapses between them, for significant volumes of neural tissue. Smaller past reconstructions were primarily used by domain experts, could be handled by downloading data, and performance was not a serious problem. But new and much larger reconstructions upend these assumptions. These networks now contain tens of thousands of neurons and tens of millions of connections, with yet larger reconstructions pending, and are of interest to a large community of non-specialists. Allowing other scientists to make use of this data needs more than publication-it requires new tools that are publicly available, easy to use, and efficiently handle large data. We introduce neuPrint to address these data analysis challenges. Neuprint contains two major components-a web interface and programmer APIs. The web interface is designed to allow any scientist worldwide, using only a browser, to quickly ask and answer typical biological queries about a connectome. The neuPrint APIs allow more computer-savvy scientists to make more complex or higher volume queries. NeuPrint also provides features for assessing reconstruction quality. Internally, neuPrint organizes connectome data as a graph stored in a neo4j database. This gives high performance for typical queries, provides access though a public and well documented query language Cypher, and will extend well to future larger connectomics databases. Our experience is also an experiment in open science. We find a significant fraction of the readers of the article proceed to examine the data directly. In our case preprints worked exactly as intended, with data inquiries and PDF downloads starting immediately after pre-print publication, and little affected by formal publication later. From this we deduce that many readers are more interested in our data than in our analysis of our data, suggesting that data-only papers can be well appreciated and that public data release can speed up the propagation of scientific results by many months. We also find that providing, and keeping, the data available for online access imposes substantial additional costs to connectomics research.

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    07/15/22 | Binding partners regulate unfolding of myosin VI to activate the molecular motor.
    Dos Santos Á, Fili N, Hari-Gupta Y, Gough RE, Wang L, Martin-Fernandez M, Arron J, Wait E, Chew TL, Toseland C
    The Biochemical Journal. 2022 Jul 15;479(13):1409-1428. doi: 10.1042/BCJ20220025

    Myosin VI is the only minus-end actin motor and is coupled to various cellular processes ranging from endocytosis to transcription. This multi-potent nature is achieved through alternative isoform splicing and interactions with a network of binding partners. There is a complex interplay between isoforms and binding partners to regulate myosin VI. Here, we have compared the regulation of two myosin VI splice isoforms by two different binding partners. By combining biochemical and single-molecule approaches, we propose that myosin VI regulation follows a generic mechanism, independently of the spliced isoform and the binding partner involved. We describe how myosin VI adopts an autoinhibited backfolded state which is released by binding partners. This unfolding activates the motor, enhances actin binding and can subsequently trigger dimerization. We have further expanded our study by using single molecule imaging to investigate the impact of binding partners upon myosin VI molecular organisation and dynamics.

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    07/14/22 | Using Simulated Training Data of Voxel-Level Generative Models to Improve 3D Neuron Reconstruction.
    Liu C, Wang D, Zhang H, Wu W, Sun W, Zhao T, Zheng N
    IEEE Transactions on Medical Imaging. 2022 Jul 14;PP:. doi: 10.1109/TMI.2022.3191011

    Reconstructing neuron morphologies from fluorescence microscope images plays a critical role in neuroscience studies. It relies on image segmentation to produce initial masks either for further processing or final results to represent neuronal morphologies. This has been a challenging step due to the variation and complexity of noisy intensity patterns in neuron images acquired from microscopes. Whereas progresses in deep learning have brought the goal of accurate segmentation much closer to reality, creating training data for producing powerful neural networks is often laborious. To overcome the difficulty of obtaining a vast number of annotated data, we propose a novel strategy of using two-stage generative models to simulate training data with voxel-level labels. Trained upon unlabeled data by optimizing a novel objective function of preserving predefined labels, the models are able to synthesize realistic 3D images with underlying voxel labels. We showed that these synthetic images could train segmentation networks to obtain even better performance than manually labeled data. To demonstrate an immediate impact of our work, we further showed that segmentation results produced by networks trained upon synthetic data could be used to improve existing neuron reconstruction methods.

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    07/08/22 | Architecture and dynamics of a novel desmosome-endoplasmic reticulum organelle
    Navaneetha Krishnan Bharathan , William Giang , Jesse S. Aaron , Satya Khuon , Teng-Leong Chew , Stephan Preibisch , Eric T. Trautman , Larissa Heinrich , John Bogovic , Davis Bennett , David Ackerman , Woohyun Park , Alyson Petruncio , Aubrey V. Weigel , Stephan Saalfeld , COSEM Project Team , A. Wayne Vogl , Sara N. Stahley , Andrew P. Kowalczyk
    bioRxiv. 2022 Jul 08:. doi: 10.1101/2022.07.07.499185

    The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signaling, and lipid transfer. Using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometer proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization and mobility. These findings indicate that desmosomes and the keratin cytoskeleton pattern the distribution of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction.

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    07/08/22 | Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience.
    Kumar P, Lavis LD
    Annual Review Neuroscience. 2022 Jul 08;45:131-150. doi: 10.1146/annurev-neuro-110520-030031

    Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems.

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    Romani LabSvoboda Lab
    07/08/22 | Neural Algorithms and Circuits for Motor Planning.
    Inagaki HK, Chen S, Daie K, Finkelstein A, Fontolan L, Romani S, Svoboda K
    Annual Review Neuroscience. 2022 Jul 08;45:249-271. doi: 10.1146/annurev-neuro-092021-121730

    The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

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    08/22/22 | Neuronal circuits integrating visual motion information in Drosophila melanogaster.
    Shinomiya K, Nern A, Meinertzhagen IA, Plaza SM, Reiser MB
    Current Biology. 2022 Aug 22;32(16):3529-3544. doi: 10.1016/j.cub.2022.06.061

    The detection of visual motion enables sophisticated animal navigation, and studies on flies have provided profound insights into the cellular and circuit bases of this neural computation. The fly's directionally selective T4 and T5 neurons encode ON and OFF motion, respectively. Their axons terminate in one of the four retinotopic layers in the lobula plate, where each layer encodes one of the four directions of motion. Although the input circuitry of the directionally selective neurons has been studied in detail, the synaptic connectivity of circuits integrating T4/T5 motion signals is largely unknown. Here, we report a 3D electron microscopy reconstruction, wherein we comprehensively identified T4/T5's synaptic partners in the lobula plate, revealing a diverse set of new cell types and attributing new connectivity patterns to the known cell types. Our reconstruction explains how the ON- and OFF-motion pathways converge. T4 and T5 cells that project to the same layer connect to common synaptic partners and comprise a core motif together with bilayer interneurons, detailing the circuit basis for computing motion opponency. We discovered pathways that likely encode new directions of motion by integrating vertical and horizontal motion signals from upstream T4/T5 neurons. Finally, we identify substantial projections into the lobula, extending the known motion pathways and suggesting that directionally selective signals shape feature detection there. The circuits we describe enrich the anatomical basis for experimental and computations analyses of motion vision and bring us closer to understanding complete sensory-motor pathways.

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    07/06/22 | Taste quality interactions and transformations in a sensorimotor circuit
    Philip K. Shiu , Gabriella R. Sterne , Stefanie Engert , Barry J. Dickson , Kristin Scott
    eLife. 2022 Jul 06:. doi: 10.1101/2022.03.06.483180

    Taste detection and hunger state dynamically regulate the decision to initiate feeding. To study how context-appropriate feeding decisions are generated, we combined synaptic resolution circuit reconstruction with targeted genetic access to specific neurons to elucidate a gustatory sensorimotor circuit for feeding initiation in Drosophila melanogaster. This circuit connects gustatory sensory neurons to proboscis motor neurons through three intermediate layers. Most of the neurons in this pathway are necessary and sufficient for proboscis extension, a feeding initiation behavior, and respond selectively to sugar taste detection. Hunger signals act at select second-order neurons to increase feeding initiation in food-deprived animals. In contrast, a bitter taste pathway inhibits premotor neurons, illuminating a central mechanism that weighs sugar and bitter tastes to promote or inhibit feeding. Together, these studies reveal the neural circuit basis for the integration of external taste detection and internal nutritive state to flexibly execute a critical feeding decision.

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    07/04/22 | Visualizing Synaptic Dopamine Efflux with a 2D Nanofilm.
    Chandima Bulumulla , Andrew T. Krasley , Deepika Walpita , Abraham G. Beyene
    eLife. 2022 Jul 04:. doi: 10.1101/2022.01.19.476937

    Chemical neurotransmission constitutes one of the fundamental modalities of communication between neurons. Monitoring release of these chemicals has traditionally been difficult to carry out at spatial and temporal scales relevant to neuron function. To understand chemical neurotransmission more fully, we need to improve the spatial and temporal resolutions of measurements for neurotransmitter release. To address this, we engineered a chemi-sensitive, two-dimensional nanofilm that facilitates subcellular visualization of the release and diffusion of the neurochemical dopamine with synaptic resolution, quantal sensitivity, and simultaneously from hundreds of release sites. Using this technology, we were able to monitor the spatiotemporal dynamics of dopamine release in dendritic processes, a poorly understood phenomenon. We found that dopamine release is broadcast from a subset of dendritic processes as hotspots that have a mean spatial spread of ≈3.2 µm (full width at half maximum) and are observed with a mean spatial frequency of 1 hotspot per ≈7.5 µm of dendritic length. Major dendrites of dopamine neurons and fine dendritic processes, as well as dendritic arbors and dendrites with no apparent varicose morphology participated in dopamine release. Remarkably, these release hotspots colocalized with Bassoon, suggesting that Bassoon may contribute to organizing active zones in dendrites, similar to its role in axon terminals.

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