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169 Janelia Publications

Showing 71-80 of 169 results
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    07/27/22 | Actin nano-architecture of phagocytic podosomes
    J. Cody Herron , Shiqiong Hu , Takashi Watanabe , Ana T. Nogueira , Bei Liu , Megan Kern , Jesse Aaron , Aaron Taylor , Michael Pablo , Teng-Leong Chew , Timothy C. Elston , Klaus M. Hahn
    Nature Communications. 2022 Jul 27;13(1):4363. doi: 10.1101/2022.05.04.490675

    Podosomes are actin-enriched adhesion structures important for multiple cellular processes, including migration, bone remodeling, and phagocytosis. Here, we characterized the structure and organization of phagocytic podosomes using interferometric photoactivated localization microscopy (iPALM), a super-resolution microscopy technique capable of 15-20 nm resolution, together with structured illumination microscopy (SIM) and localization-based superresolution microscopy. Phagocytic podosomes were observed during frustrated phagocytosis, a model in which cells attempt to engulf micro-patterned IgG antibodies. For circular patterns, this resulted in regular arrays of podosomes with well-defined geometry. Using persistent homology, we developed a pipeline for semi-automatic identification and measurement of podosome features. These studies revealed an "hourglass" shape of the podosome actin core, a protruding "knob" at the bottom of the core, and two actin networks extending from the core. Additionally, the distributions of paxillin, talin, myosin II, α-actinin, cortactin, and microtubules relative to actin were characterized.

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    07/27/22 | Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation
    Kevin J. Cutler , Carsen Stringer , Paul A. Wiggins , Joseph D. Mougous
    bioRxiv. 2022 Jul 27:. doi: 10.1101/2021.11.03.467199

    Advances in microscopy hold great promise for allowing quantitative and precise readouts of morphological and molecular phenomena at the single cell level in bacteria. However, the potential of this approach is ultimately limited by the availability of methods to perform unbiased cell segmentation, defined as the ability to faithfully identify cells independent of their morphology or optical characteristics. In this study, we present a new algorithm, Omnipose, which accurately segments samples that present significant challenges to current algorithms, including mixed bacterial cultures, antibiotic-treated cells, and cells of extended or branched morphology. We show that Omnipose achieves generality and performance beyond leading algorithms and its predecessor, Cellpose, by virtue of unique neural network outputs such as the gradient of the distance field. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism and on the segmentation of non-bacterial objects. Our results distinguish Omnipose as a uniquely powerful tool for answering diverse questions in bacterial cell biology.

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    07/26/22 | A scalable and modular automated pipeline for stitching of large electron microscopy datasets.
    Mahalingam G, Torres R, Kapner D, Trautman ET, Fliss T, Seshamani S, Perlman E, Young R, Kinn S, Buchanan J, Takeno MM, Yin W, Bumbarger DJ, Gwinn RP, Nyhus J, Lein E, Smith SJ, Reid RC, Khairy KA, Saalfeld S, Collman F, Macarico da Costa N
    eLife. 2022 Jul 26;11:. doi: 10.7554/eLife.76534

    Serial-section electronmicroscopy (ssEM) is themethod of choice for studyingmacroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. In order to use this data, consisting of up to 10 individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render (27) services used in the volume assembly of the brain of adult Drosophilamelanogaster (30). It achieves high throughput by operating on themeta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP ismodular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (28; 8) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

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    07/22/22 | Brain structure and synaptic protein expression alterations after antidepressant treatment in a Wistar-Kyoto rat model of depression.
    Li Q, Gao Y, Li H, Liu H, Wang D, Pan W, Liu S, Xu Y
    Journal of Affective Disorders. 2022 Jul 22;314:293-302. doi: 10.1016/j.jad.2022.07.037

    BACKGROUND: Structural MRI has demonstrated brain alterations in depression pathology and antidepressants treatment. While synaptic plasticity has been previously proposed as the potential underlying mechanism of MRI findings at a cellular and molecular scale, there is still insufficient evidence to link the MRI findings and synaptic plasticity mechanisms in depression pathology.

    METHODS: In this study, a Wistar-Kyoto (WKY) depression rat model was treated with antidepressants (citalopram or Jie-Yu Pills) and tested in a series of behavioral tests and a 7.0 MRI scanner. We then measured dendritic spine density within altered brain regions. We also examined expression of synaptic marker proteins (PSD-95 and SYP).

    RESULTS: WKY rats exhibited depression-like behaviors in the sucrose preference test (SPT) and forced swim test (FST), and anxiety-like behaviors in the open field test (OFT). Both antidepressants reversed behavioral changes in SPT and OFT but not in FST. We found a correlation between SPT performance and brain volumes as detected by MRI. All structural changes were consistent with alterations of the corpus callosum (white matter), dendritic spine density, as well as PSD95 and SYP expression at different levels. Two antidepressants similarly reversed these macro- and micro-changes.

    LIMITATIONS: The single dose of antidepressants was the major limitation of this study. Further studies should focus on the white matter microstructure changes and myelin-related protein alterations, in addition to comparing the effects of ketamine.

    CONCLUSION: Translational evidence links structural MRI changes and synaptic plasticity alterations, which promote our understanding of SPT mechanisms and antidepressant response in WKY rats.

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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

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    07/20/22 | neuPrint: 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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