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31 Janelia Publications

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    Cardona LabSaalfeld LabFetter Lab
    07/01/12 | Elastic volume reconstruction from series of ultra-thin microscopy sections.
    Saalfeld S, Fetter RD, Cardona A, Tomancak P
    Nature Methods. 2012 Jul;9(7):717-20. doi: 10.1038/nmeth.2072

    Anatomy of large biological specimens is often reconstructed from serially sectioned volumes imaged by high-resolution microscopy. We developed a method to reassemble a continuous volume from such large section series that explicitly minimizes artificial deformation by applying a global elastic constraint. We demonstrate our method on a series of transmission electron microscopy sections covering the entire 558-cell Caenorhabditis elegans embryo and a segment of the Drosophila melanogaster larval ventral nerve cord.

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    08/02/13 | Electron microscopy reconstruction of brain structure using sparse representations over learned dictionaries.
    Hu T, Nunez-Iglesias J, Vitaladevuni S, Scheffer L, Xu S, Bolorizadeh M, Hess H, Fetter R, Chklovskii D
    IEEE Transactions on Medical Imaging. 2013 Aug 2;32(12):2179-88. doi: 10.1109/TMI.2013.2276018

    A central problem in neuroscience is reconstructing neuronal circuits on the synapse level. Due to a wide range of scales in brain architecture such reconstruction requires imaging that is both high-resolution and high-throughput. Existing electron microscopy (EM) techniques possess required resolution in the lateral plane and either high-throughput or high depth resolution but not both. Here, we exploit recent advances in unsupervised learning and signal processing to obtain high depth-resolution EM images computationally without sacrificing throughput. First, we show that the brain tissue can be represented as a sparse linear combination of localized basis functions that are learned using high-resolution datasets. We then develop compressive sensing-inspired techniques that can reconstruct the brain tissue from very few (typically 5) tomographic views of each section. This enables tracing of neuronal processes and, hence, high throughput reconstruction of neural circuits on the level of individual synapses.

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    Cardona LabTruman LabFetter Lab
    10/21/15 | Even-Skipped(+) interneurons are core components of a sensorimotor circuit that maintains left-right symmetric muscle contraction amplitude.
    Heckscher ES, Zarin AA, Faumont S, Clark MQ, Manning L, Fushiki A, Schneider-Mizell CM, Fetter RD, Truman JW, Zwart MF, Landgraf M, Cardona A, Lockery SR, Doe CQ
    Neuron. 2015 Oct 21;88(2):314-29. doi: 10.1016/j.neuron.2015.09.009

    Bilaterally symmetric motor patterns-those in which left-right pairs of muscles contract synchronously and with equal amplitude (such as breathing, smiling, whisking, and locomotion)-are widespread throughout the animal kingdom. Yet, surprisingly little is known about the underlying neural circuits. We performed a thermogenetic screen to identify neurons required for bilaterally symmetric locomotion in Drosophila larvae and identified the evolutionarily conserved Even-skipped(+) interneurons (Eve/Evx). Activation or ablation of Eve(+) interneurons disrupted bilaterally symmetric muscle contraction amplitude, without affecting the timing of motor output. Eve(+) interneurons are not rhythmically active and thus function independently of the locomotor CPG. GCaMP6 calcium imaging of Eve(+) interneurons in freely moving larvae showed left-right asymmetric activation that correlated with larval behavior. TEM reconstruction of Eve(+) interneuron inputs and outputs showed that the Eve(+) interneurons are at the core of a sensorimotor circuit capable of detecting and modifying body wall muscle contraction.

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    Fetter Lab
    02/07/08 | GFP Reconstitution Across Synaptic Partners (GRASP) defines cell contacts and synapses in living nervous systems.
    Feinberg EH, Vanhoven MK, Bendesky A, Wang G, Fetter RD, Shen K, Bargmann CI
    Neuron. 2008 Feb 7;57(3):353-63. doi: 10.1016/j.neuron.2007.11.030

    The identification of synaptic partners is challenging in dense nerve bundles, where many processes occupy regions beneath the resolution of conventional light microscopy. To address this difficulty, we have developed GRASP, a system to label membrane contacts and synapses between two cells in living animals. Two complementary fragments of GFP are expressed on different cells, tethered to extracellular domains of transmembrane carrier proteins. When the complementary GFP fragments are fused to ubiquitous transmembrane proteins, GFP fluorescence appears uniformly along membrane contacts between the two cells. When one or both GFP fragments are fused to synaptic transmembrane proteins, GFP fluorescence is tightly localized to synapses. GRASP marks known synaptic contacts in C. elegans, correctly identifies changes in mutants with altered synaptic specificity, and can uncover new information about synaptic locations as confirmed by electron microscopy. GRASP may prove particularly useful for defining connectivity in complex nervous systems.

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    01/01/11 | High resolution segmentation of neuronal tissues from low depth-resolution EM imagery.
    Glasner D, Hu T, Nunez-Iglesias J, Scheffer L, Xu C, Hess H, Fetter R, Chklovskii D, Basri R
    8th International Conference of Energy Minimization Methods in Computer Vision and Pattern Recognition Energy Minimization Methods in Computer Vision and Pattern Recognition. 2011;6819:261-72

    The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack of EM images into the individual neurons is difficult, due to the low depth-resolution in existing high-throughput EM technology, such as serial section Transmission EM (ssTEM). In this paper we propose methods for detecting the high resolution locations of membranes from low depth-resolution images. We approach this problem using both a method that learns a discriminative, over-complete dictionary and a kernel SVM. We test this approach on tomographic sections produced in simulations from high resolution Focused Ion Beam (FIB) images and on low depth-resolution images acquired with ssTEM and evaluate our results by comparing it to manual labeling of this data.

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    01/01/10 | Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction.
    Veeraraghavan A, Genkin AV, Vitaladevuni S, Scheffer L, Xu C, Hess H, Fetter R, Cantoni M, Knott G, Chklovskii DB
    Computer Vision and Pattern Recognition (CVPR). 2010:1767-74. doi: 10.1109/CVPR.2010.5539846
    Hess LabFetter Lab
    03/03/09 | Interferometric fluorescent super-resolution microscopy resolves 3D cellular ultrastructure.
    Shtengel G, Galbraith JA, Galbraith CG, Lippincott-Schwartz J, Gillette JM, Manley S, Sougrat R, Waterman CM, Kanchanawong P, Davidson MW, Fetter RD, Hess HF
    Proceedings of the National Academy of Sciences of the United States of America. 2009 Mar 3;106:3125-30. doi: 10.1073/pnas.0813131106

    Understanding molecular-scale architecture of cells requires determination of 3D locations of specific proteins with accuracy matching their nanometer-length scale. Existing electron and light microscopy techniques are limited either in molecular specificity or resolution. Here, we introduce interferometric photoactivated localization microscopy (iPALM), the combination of photoactivated localization microscopy with single-photon, simultaneous multiphase interferometry that provides sub-20-nm 3D protein localization with optimal molecular specificity. We demonstrate measurement of the 25-nm microtubule diameter, resolve the dorsal and ventral plasma membranes, and visualize the arrangement of integrin receptors within endoplasmic reticulum and adhesion complexes, 3D protein organization previously resolved only by electron microscopy. iPALM thus closes the gap between electron tomography and light microscopy, enabling both molecular specification and resolution of cellular nanoarchitecture.

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    Cardona LabFetter Lab
    08/02/18 | MDN brain descending neurons coordinately activate backward and inhibit forward locomotion.
    Carreira-Rosario A, Zarin AA, Clark MQ, Manning L, Fetter RD, Cardona A, Doe CQ
    eLife. 2018 Aug 02;7:. doi: 10.7554/eLife.38554

    Command-like descending neurons can induce many behaviors, such as backward locomotion, escape, feeding, courtship, egg-laying, or grooming (we define 'command-like neuron' as a neuron whose activation elicits or 'commands' a specific behavior). In most animals it remains unknown how neural circuits switch between antagonistic behaviors: via top-down activation/inhibition of antagonistic circuits or via reciprocal inhibition between antagonistic circuits. Here we use genetic screens, intersectional genetics, circuit reconstruction by electron microscopy, and functional optogenetics to identify a bilateral pair of larval 'mooncrawler descending neurons' (MDNs) with command-like ability to coordinately induce backward locomotion and block forward locomotion; the former by stimulating a backward-active premotor neuron, and the latter by disynaptic inhibition of a forward-specific premotor neuron. In contrast, direct monosynaptic reciprocal inhibition between forward and backward circuits was not observed. Thus, MDNs coordinate a transition between antagonistic larval locomotor behaviors. Interestingly, larval MDNs persist into adulthood, where they can trigger backward walking. Thus, MDNs induce backward locomotion in both limbless and limbed animals.

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    Fetter Lab
    01/01/14 | Nanometer-resolution fluorescence electron microscopy (nano-EM) in cultured cells.
    Watanabe S, Lehmann M, Hujber E, Fetter RD, Richards J, Söhl-Kielczynski B, Felies A, Rosenmund C, Schmoranzer J, Jorgensen EM
    Methods in Molecular Biology. 2014;1117:503-26. doi: 10.1007/978-1-62703-776-1_22

    Nano-resolution fluorescence electron microscopy (nano-fEM) pinpoints the location of individual proteins in electron micrographs. Plastic sections are first imaged using a super-resolution fluorescence microscope and then imaged on an electron microscope. The two images are superimposed to correlate the position of labeled proteins relative to subcellular structures. Here, we describe the method in detail and present five technical advancements: the use of uranyl acetate during the freeze-substitution to enhance the contrast of tissues and reduce the loss of fluorescence, the use of ground-state depletion instead of photoactivation for temporal control of fluorescence, the use of organic fluorophores instead of fluorescent proteins to obtain brighter fluorescence signals, the use of tissue culture cells to broaden the utility of the method, and the use of a transmission electron microscope to achieve sharper images of ultrastructure.

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    Fetter LabTruman LabZlatic LabCardona Lab
    08/08/17 | Organization of the drosophila larval visual circuit.
    Larderet I, Fritsch PM, Gendre N, Neagu-Maier GL, Fetter RD, Schneider-Mizell CM, Truman JW, Zlatic M, Cardona A, Sprecher SG
    eLife. 2017 Aug 8:e28387. doi: 10.7554/eLife.28387

    Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on photoreceptor neuron types (PR) present, organization of the eye and wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create two converging pathways potentially underlying the computation of ambient light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the larval optic neuropil (LON) suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors.

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