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9 Janelia Publications

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    09/01/23 | OME-Zarr: a cloud-optimized bioimaging file format with international community support.
    Josh Moore , Daniela Basurto-Lozada , Sébastien Besson , John Bogovic , Eva M. Brown , Jean-Marie Burel , Gustavo de Medeiros , Erin E. Diel , David Gault , Satrajit S. Ghosh , Ilan Gold , Yaroslav O. Halchenko , Matthew Hartley , Dave Horsfall , Mark S. Keller , Mark Kittisopikul , Gabor Kovacs , Aybüke Küpcü Yoldaş , Albane le Tournoulx de la Villegeorges , Tong Li , Prisca Liberali , Melissa Linkert , Dominik Lindner , Joel Lüthi , Jeremy Maitin-Shepard , Trevor Manz , Matthew McCormick , Khaled Mohamed , William Moore , Bugra Özdemir , Constantin Pape , Lucas Pelkmans , Martin Prete , Tobias Pietzsch , Stephan Preibisch , Norman Rzepka , David R. Stirling , Jonathan Striebel , Christian Tischer , Daniel Toloudis , Petr Walczysko , Alan M. Watson , Frances Wong , Kevin A. Yamauchi , Omer Bayraktar , Muzlifah Haniffa , Stephan Saalfeld , Jason R. Swedlow
    Histochemistry and Cell Biology. 2023 Feb 25;160(3):223-251. doi: 10.1007/s00418-023-02209-1

    A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the format itself – OME-Zarr – along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain — the file format that underlies so many personal, institutional, and global data management and analysis tasks.

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    06/16/23 | Architecture and dynamics of a desmosome-endoplasmic reticulum complex.
    Bharathan NK, Giang W, Hoffman CL, Aaron JS, Khuon S, Chew T, Preibisch S, Trautman ET, Heinrich L, Bogovic J, Bennett D, Ackerman D, Park W, Petruncio A, Weigel AV, Saalfeld S, COSEM Project Team , Wayne Vogl A, Stahley SN, Kowalczyk AP
    Nature Cell Biology. 2023 Jun 16;25(6):823-835. doi: 10.1038/s41556-023-01154-4

    The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signalling and lipid transfer. Here, 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 nanometre 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, mobility and expression of ER stress transcripts. These findings indicate that desmosomes and the keratin cytoskeleton regulate the distribution, function and dynamics 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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    06/06/23 | A Connectome of the Male Drosophila Ventral Nerve Cord
    Shin-ya Takemura , Kenneth J Hayworth , Gary B Huang , Michal Januszewski , Zhiyuan Lu , Elizabeth C Marin , Stephan Preibisch , C Shan Xu , John Bogovic , Andrew S Champion , Han S J Cheong , Marta Costa , Katharina Eichler , William Katz , Christopher Knecht , Feng Li , Billy J Morris , Christopher Ordish , Patricia K Rivlin , Philipp Schlegel , Kazunori Shinomiya , Tomke Sturner , Ting Zhao , Griffin Badalamente , Dennis Bailey , Paul Brooks , Brandon S Canino , Jody Clements , Michael Cook , Octave Duclos , Christopher R Dunne , Kelli Fairbanks , Siqi Fang , Samantha Finley-May , Audrey Francis , Reed George , Marina Gkantia , Kyle Harrington , Gary Patrick Hopkins , Joseph Hsu , Philip M Hubbard , Alexandre Javier , Dagmar Kainmueller , Wyatt Korff , Julie Kovalyak , Dominik Krzeminski , Shirley A Lauchie , Alanna Lohff , Charli Maldonado , Emily A Manley , Caroline Mooney , Erika Neace , Matthew Nichols , Omotara Ogundeyi , Nneoma Okeoma , Tyler Paterson , Elliott Phillips , Emily M Phillips , Caitlin Ribeiro , Sean M Ryan , Jon Thomson Rymer , Anne K Scott , Ashley L Scott , David Shepherd , Aya Shinomiya , Claire Smith , Alia Suleiman , Satoko Takemura , Iris Talebi , Imaan F M Tamimi , Eric T Trautman , Lowell Umayam , John J Walsh , Tansy Yang , Gerald M Rubin , Louis K Scheffer , Jan Funke , Stephan Saalfeld , Harald F Hess , Stephen M Plaza , Gwyneth M Card , Gregory S X E Jefferis , Stuart Berg
    bioRxiv. 2023 Jun 06:. doi: 10.1101/2023.06.05.543757

    Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.

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    11/01/21 | Whole-cell organelle segmentation in volume electron microscopy.
    Heinrich L, Bennett D, Ackerman D, Park W, Bogovic J, Eckstein N, Petruncio A, Clements J, Pang S, Xu CS, Funke J, Korff W, Hess HF, Lippincott-Schwartz J, Saalfeld S, Weigel AV, COSEM Project Team
    Nature. 2021 Nov 01;599(7883):141-46. doi: 10.1038/s41586-021-03977-3

    Cells contain hundreds of organelles and macromolecular assemblies. Obtaining a complete understanding of their intricate organization requires the nanometre-level, three-dimensional reconstruction of whole cells, which is only feasible with robust and scalable automatic methods. Here, to support the development of such methods, we annotated up to 35 different cellular organelle classes-ranging from endoplasmic reticulum to microtubules to ribosomes-in diverse sample volumes from multiple cell types imaged at a near-isotropic resolution of 4 nm per voxel with focused ion beam scanning electron microscopy (FIB-SEM). We trained deep learning architectures to segment these structures in 4 nm and 8 nm per voxel FIB-SEM volumes, validated their performance and showed that automatic reconstructions can be used to directly quantify previously inaccessible metrics including spatial interactions between cellular components. We also show that such reconstructions can be used to automatically register light and electron microscopy images for correlative studies. We have created an open data and open-source web repository, 'OpenOrganelle', to share the data, computer code and trained models, which will enable scientists everywhere to query and further improve automatic reconstruction of these datasets.

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    09/07/20 | A connectome and analysis of the adult Drosophila central brain.
    Scheffer LK, Xu CS, Januszewski M, Lu Z, Takemura S, Hayworth KJ, Huang GB, Shinomiya K, Maitlin-Shepard J, Berg S, Clements J, Hubbard PM, Katz WT, Umayam L, Zhao T, Ackerman D, Blakely T, Bogovic J, Dolafi T, Kainmueller D, Kawase T, Khairy KA, Leavitt L, Li PH, Lindsey L, Neubarth N, Olbris DJ, Otsuna H, Trautman ET, Ito M, Bates AS, Goldammer J, Wolff T, Svirskas R, Schlegel P, Neace E, Knecht CJ, Alvarado CX, Bailey DA, Ballinger S, Borycz JA, Canino BS, Cheatham N, Cook M, Dreher M, Duclos O, Eubanks B, Fairbanks K, Finley S, Forknall N, Francis A, Hopkins GP, Joyce EM, Kim S, Kirk NA, Kovalyak J, Lauchie SA, Lohff A, Maldonado C, Manley EA, McLin S, Mooney C, Ndama M, Ogundeyi O, Okeoma N, Ordish C, Padilla N, Patrick CM, Paterson T, Phillips EE, Phillips EM, Rampally N, Ribeiro C, Robertson MK, Rymer JT, Ryan SM, Sammons M, Scott AK, Scott AL, Shinomiya A, Smith C, Smith K, Smith NL, Sobeski MA, Suleiman A, Swift J, Takemura S, Talebi I, Tarnogorska D, Tenshaw E, Tokhi T, Walsh JJ, Yang T, Horne JA, Li F, Parekh R, Rivlin PK, Jayaraman V, Costa M, Jefferis GS, Ito K, Saalfeld S, George R, Meinertzhagen IA, Rubin GM, Hess HF, Jain V, Plaza SM
    Elife. 2020 Sep 07;9:. doi: 10.7554/eLife.57443

    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 . 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.

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    07/25/18 | An unbiased template of the Drosophila brain and ventral nerve cord.
    Bogovic JA, Otsuna H, Heinrich L, Ito M, Jeter J, Meissner GW, Nern A, Colonell J, Malkesman O, Saalfeld S
    bioRxiv. 2018 Jul 25:. doi: 10.1101/376384

    The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individuals 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.

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    07/12/18 | A complete electron microscopy volume of the brain of adult Drosophila melanogaster.
    Zheng Z, Lauritzen JS, Perlman E, Robinson CG, Nichols M, Milkie DE, Torrens O, Price J, Fisher CB, Sharifi N, Calle-Schuler SA, Kmecova L, Ali IJ, Karsh B, Trautman ET, Bogovic JA, Hanslovsky P, Jefferis GS, Kazhdan M, Khairy K
    Cell. 2018 Jul 12;174(3):730-43. doi: 10.1016/j.cell.2018.06.019

    Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly at synaptic resolution. To validate the dataset, we traced brain-spanning circuitry involving the mushroom body (MB), which has been extensively studied for its role in learning. All inputs to Kenyon cells (KCs), the intrinsic neurons of the MB, were mapped, revealing a previously unknown cell type, postsynaptic partners of KC dendrites, and unexpected clustering of olfactory projection neurons. These reconstructions show that this freely available EM volume supports mapping of brain-spanning circuits, which will significantly accelerate Drosophila neuroscience..

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    04/26/18 | Joint deformable registration of large EM image volumes: a matrix solver approach.
    Khairy K, Denisov G, Saalfeld S
    arXiv. 2018 Apr 26:

    Large electron microscopy image datasets for connectomics are typically composed of thousands to millions of partially overlapping two-dimensional images (tiles), which must be registered into a coherent volume prior to further analysis. A common registration strategy is to find matching features between neighboring and overlapping image pairs, followed by a numerical estimation of optimal image deformation using a so-called solver program. 
    Existing solvers are inadequate for large data volumes, and inefficient for small-scale image registration. 
    In this work, an efficient and accurate matrix-based solver method is presented. A linear system is constructed that combines minimization of feature-pair square distances with explicit constraints in a regularization term. In absence of reliable priors for regularization, we show how to construct a rigid-model approximation to use as prior. The linear system is solved using available computer programs, whose performance on typical registration tasks we briefly compare, and to which future scale-up is delegated. Our method is applied to the joint alignment of 2.67 million images, with more than 200 million point-pairs and has been used for successfully aligning the first full adult fruit fly brain.

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    03/18/16 | Quantitative neuroanatomy for connectomics in Drosophila.
    Schneider-Mizell CM, Gerhard S, Longair M, Kazimiers T, Li F, Zwart M, Champion A, Midgley F, Fetter RD, Saalfeld S, Cardona A
    eLife. 2016 Mar 18:e12059. doi: 10.7554/eLife.12059

    Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.

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