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206 Janelia Publications

Showing 201-206 of 206 results
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    Gonen Lab
    01/15/18 | Sub-ångström cryo-EM structure of a prion protofibril reveals a polar clasp.
    Gallagher-Jones M, Glynn C, Boyer DR, Martynowycz MW, Hernandez E, Miao J, Zee C, Novikova IV, Goldschmidt L, McFarlane HT, Helguera GF, Evans JE, Sawaya MR, Cascio D, Eisenberg DS, Gonen T, Rodriguez JA
    Nature Structural & Molecular Biology. 2018 Jan 15:. doi: 10.1038/s41594-017-0018-0

    The atomic structure of the infectious, protease-resistant, β-sheet-rich and fibrillar mammalian prion remains unknown. Through the cryo-EM method MicroED, we reveal the sub-ångström-resolution structure of a protofibril formed by a wild-type segment from the β2-α2 loop of the bank vole prion protein. The structure of this protofibril reveals a stabilizing network of hydrogen bonds that link polar zippers within a sheet, producing motifs we have named 'polar clasps'.

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    01/11/18 | Persistent activity in a recurrent circuit underlies courtship memory in Drosophila.
    Zhao X, Lenek D, Dag U, Dickson B, Keleman K
    eLife. 2018 Jan 11;7:. doi: 10.7554/eLife.31425

    Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBg), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBγ>M6 neurons. M6 neurons in turn provide input to aSP13 neurons, prolonging potentiation of MBγ>M6 synapses over time periods that match short-term memory. These data support a model in which persistent aSP13 activity within a recurrent circuit lays the foundation for a short-term memory.

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    Zlatic LabTruman Lab
    01/08/18 | Neural substrates of navigational decision-making in Drosophila larva anemotaxis.
    Jovanic T, Truman JW, Gershow M, Zlatic M
    bioRxiv. 2018 Jan 08:244608. doi: 10.1101/244608

    Small animals navigate in the environment as a function of varying sensory information in order to reach more favorable environmental conditions. To achieve this Drosophila larvae alternate periods of runs and turns in gradients of light, temperature, odors and CO2. While the sensory neurons that mediate the navigation behaviors in the different sensory gradients have been described, where and how are these navigational strategies are implemented in the central nervous system and controlled by neuronal circuit elements is not well known. Here we characterize for the first time the navigational strategies of Drosophila larvae in gradients of air-current speeds using high-throughput behavioral assays and quantitative behavioral analysis. We find that larvae extend runs when facing favorable conditions and increase turn rate when facing unfavorable direction, a strategy they use in other sensory modalities as well. By silencing the activity of individual neurons and very sparse expression patterns (2 or 3 neuron types), we further identify the sensory neurons and circuit elements in the ventral nerve cord and brain of the larva required for navigational decisions during anemotaxis. The phenotypes of these central neurons are consistent with a mechanism where the increase of the turning rate in unfavorable conditions and decrease in turning rate in favorable conditions are independently controlled.

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    01/08/18 | Simple integration of fast excitation and offset, delayed inhibition computes directional selectivity in Drosophila.
    Gruntman E, Romani S, Reiser MB
    Nature Neuroscience. 2018 Jan 08;21(2):250-7. doi: 10.1038/s41593-017-0046-4

    A neuron that extracts directionally selective motion information from upstream signals lacking this selectivity must compare visual responses from spatially offset inputs. Distinguishing among prevailing algorithmic models for this computation requires measuring fast neuronal activity and inhibition. In the Drosophila melanogaster visual system, a fourth-order neuron-T4-is the first cell type in the ON pathway to exhibit directionally selective signals. Here we use in vivo whole-cell recordings of T4 to show that directional selectivity originates from simple integration of spatially offset fast excitatory and slow inhibitory inputs, resulting in a suppression of responses to the nonpreferred motion direction. We constructed a passive, conductance-based model of a T4 cell that accurately predicts the neuron's response to moving stimuli. These results connect the known circuit anatomy of the motion pathway to the algorithmic mechanism by which the direction of motion is computed.

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    01/04/18 | Robust model-based analysis of single-particle tracking experiments with Spot-On.
    Hansen AS, Woringer M, Grimm JB, Lavis LD, Tjian R, Darzacq X
    eLife. 2018 Jan 04;7:. doi: 10.7554/eLife.33125

    Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants.

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    01/01/18 | larvalign: Aligning gene expression patterns from the larval brain of Drosophila melanogaster.
    Muenzing SE, Strauch M, Truman JW, Bühler K, Thum AS, Merhof D
    Neuroinformatics. 2018 Jan 1;16(1):65-80. doi: 10.1007/s12021-017-9349-6

    The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neuroscience. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expression patterns from different larvae into a reference space defined by the standard template. We provide a manually annotated gold standard that serves for evaluation of the registration framework involved in template generation and mapping. A method for registration quality assessment enables the automatic detection of registration errors, and a semi-automatic registration method allows one to correct registrations, which is a prerequisite for a high-quality, curated database of expression patterns. All computational methods are available within the larvalign software package: https://github.com/larvalign/larvalign/releases/tag/v1.0.

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