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249 Publications

Showing 21-30 of 249 results
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    Cardona LabFunke LabFlyEM
    11/18/15 | Who is talking to whom: Synaptic partner detection in anisotropic volumes of insect brain.
    Kreshuk A, Funke J, Cardona A, Hamprecht FA
    Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015:661-8. doi: 10.1007/978-3-319-24553-9_81

    Automated reconstruction of neural connectivity graphs from electron microscopy image stacks is an essential step towards large-scale neural circuit mapping. While significant progress has recently been made in automated segmentation of neurons and detection of synapses, the problem of synaptic partner assignment for polyadic (one-to-many) synapses, prevalent in the Drosophila brain, remains unsolved. In this contribution, we propose a method which automatically assigns pre- and postsynaptic roles to neurites adjacent to a synaptic site. The method constructs a probabilistic graphical model over potential synaptic partner pairs which includes factors to account for a high rate of one-to-many connections, as well as the possibility of the same neuron to be pre-synaptic in one synapse and post-synaptic in another. The algorithm has been validated on a publicly available stack of ssTEM images of Drosophila neural tissue and has been shown to reconstruct most of the synaptic relations correctly.

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    11/16/15 | Propagation of homeostatic sleep signals by segregated synaptic microcircuits of the Drosophila mushroom body.
    Sitaraman D, Aso Y, Jin X, Chen N, Felix M, Rubin GM, Nitabach MN
    Current Biology : CB. 2015 Nov 16;25(22):2915-27. doi: 10.1016/j.cub.2015.09.017

    The Drosophila mushroom body (MB) is a key associative memory center that has also been implicated in the control of sleep. However, the identity of MB neurons underlying homeostatic sleep regulation, as well as the types of sleep signals generated by specific classes of MB neurons, has remained poorly understood. We recently identified two MB output neuron (MBON) classes whose axons convey sleep control signals from the MB to converge in the same downstream target region: a cholinergic sleep-promoting MBON class and a glutamatergic wake-promoting MBON class. Here, we deploy a combination of neurogenetic, behavioral, and physiological approaches to identify and mechanistically dissect sleep-controlling circuits of the MB. Our studies reveal the existence of two segregated excitatory synaptic microcircuits that propagate homeostatic sleep information from different populations of intrinsic MB "Kenyon cells" (KCs) to specific sleep-regulating MBONs: sleep-promoting KCs increase sleep by preferentially activating the cholinergic MBONs, while wake-promoting KCs decrease sleep by preferentially activating the glutamatergic MBONs. Importantly, activity of the sleep-promoting MB microcircuit is increased by sleep deprivation and is necessary for homeostatic rebound sleep (i.e., the increased sleep that occurs after, and in compensation for, sleep lost during deprivation). These studies reveal for the first time specific functional connections between subsets of KCs and particular MBONs and establish the identity of synaptic microcircuits underlying transmission of homeostatic sleep signals in the MB.

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    11/13/15 | Dynamics of CRISPR-Cas9 genome interrogation in living cells.
    Knight SC, Xie L, Deng W, Guglielmi B, Witkowsky LB, Bosanac L, Zhang ET, El Beheiry M, Masson J, Dahan M, Liu Z, Doudna JA, Tjian R
    Science (New York, N.Y.). 2015 Nov 13;350(6262):823-6. doi: 10.1126/science.aac6572

    The RNA-guided CRISPR-associated protein Cas9 is used for genome editing, transcriptional modulation, and live-cell imaging. Cas9-guide RNA complexes recognize and cleave double-stranded DNA sequences on the basis of 20-nucleotide RNA-DNA complementarity, but the mechanism of target searching in mammalian cells is unknown. Here, we use single-particle tracking to visualize diffusion and chromatin binding of Cas9 in living cells. We show that three-dimensional diffusion dominates Cas9 searching in vivo, and off-target binding events are, on average, short-lived (<1 second). Searching is dependent on the local chromatin environment, with less sampling and slower movement within heterochromatin. These results reveal how the bacterial Cas9 protein interrogates mammalian genomes and navigates eukaryotic chromatin structure.

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    11/09/15 | Control of sleep by dopaminergic inputs to the Drosophila mushroom body.
    Sitaraman D, Aso Y, Rubin GM, Nitabach MN
    Frontiers in Neural Circuits. 2015 Nov 09;9:73. doi: 10.3389/fncir.2015.00073

    The Drosophila mushroom body (MB) is an associative learning network that is important for the control of sleep. We have recently identified particular intrinsic MB Kenyon cell (KC) classes that regulate sleep through synaptic activation of particular MB output neurons (MBONs) whose axons convey sleep control signals out of the MB to downstream target regions. Specifically, we found that sleep-promoting KCs increase sleep by preferentially activating cholinergic sleep-promoting MBONs, while wake-promoting KCs decrease sleep by preferentially activating glutamatergic wake-promoting MBONs. Here we use a combination of genetic and physiological approaches to identify wake-promoting dopaminergic neurons (DANs) that innervate the MB, and show that they activate wake-promoting MBONs. These studies reveal a dopaminergic sleep control mechanism that likely operates by modulation of KC-MBON microcircuits.

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    11/06/15 | Imaging fictive locomotor patterns in larval Drosophila.
    Pulver SR, Bayley TG, Taylor AL, Berni J, Bate M, Hedwig B
    Journal of Neurophysiology. 2015 Nov 06;114(5):2564-77. doi: 10.1152/jn.00731.2015

    We have established a preparation in larval Drosophila to monitor fictive locomotion simultaneously across abdominal and thoracic segments of the isolated CNS with genetically encoded Ca(2+) indicators. The Ca(2+) signals closely followed spiking activity measured electrophysiologically in nerve roots. Three motor patterns are analyzed. Two comprise waves of Ca(2+) signals that progress along the longitudinal body axis in a posterior-to-anterior or anterior-to-posterior direction. These waves had statistically indistinguishable intersegmental phase delays compared with segmental contractions during forward and backward crawling behavior, despite being ∼10 times slower. During these waves, motor neurons of the dorsal longitudinal and transverse muscles were active in the same order as the muscle groups are recruited during crawling behavior. A third fictive motor pattern exhibits a left-right asymmetry across segments and bears similarities with turning behavior in intact larvae, occurring equally frequently and involving asymmetry in the same segments. Ablation of the segments in which forward and backward waves of Ca(2+) signals were normally initiated did not eliminate production of Ca(2+) waves. When the brain and subesophageal ganglion (SOG) were removed, the remaining ganglia retained the ability to produce both forward and backward waves of motor activity, although the speed and frequency of waves changed. Bilateral asymmetry of activity was reduced when the brain was removed and abolished when the SOG was removed. This work paves the way to studying the neural and genetic underpinnings of segmentally coordinated motor pattern generation in Drosophila with imaging techniques.

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    11/06/15 | Mitochondrial transcription factor A (TFAM) binds to RNA containing 4-way junctions and mitochondrial tRNA.
    Brown TA, Tkachuk AN, Clayton DA
    PloS one. 2015 nov 6;10(11):e0142436. doi: 10.1371/journal.pone.0142436

    Mitochondrial DNA (mtDNA) is maintained within nucleoprotein complexes known as nucleoids. These structures are highly condensed by the DNA packaging protein, mitochondrial Transcription Factor A (TFAM). Nucleoids also include RNA, RNA:DNA hybrids, and are associated with proteins involved with RNA processing and mitochondrial ribosome biogenesis. Here we characterize the ability of TFAM to bind various RNA containing substrates in order to determine their role in TFAM distribution and function within the nucleoid. We find that TFAM binds to RNA-containing 4-way junctions but does not bind appreciably to RNA hairpins, internal loops, or linear RNA:DNA hybrids. Therefore the RNA within nucleoids largely excludes TFAM, and its distribution is not grossly altered with removal of RNA. Within the cell, TFAM binds to mitochondrial tRNAs, consistent with our RNA 4-way junction data. Kinetic binding assays and RNase-insensitive TFAM distribution indicate that DNA remains the preferred substrate within the nucleoid. However, TFAM binds to tRNA with nanomolar affinity and these complexes are not rare. TFAM-immunoprecipitated tRNAs have processed ends, suggesting that binding is not specific to RNA precursors. The amount of each immunoprecipitated tRNA is not well correlated with tRNA celluar abundance, indicating unequal TFAM binding preferences. TFAM-mt-tRNA interaction suggests potentially new functions for this protein.

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    Turaga LabCardona Lab
    11/05/15 | Crowdsourcing the creation of image segmentation algorithms for connectomics.
    Arganda-Carreras I, Turaga SC, Berger DR, Ciresan D, Giusti A, Gambardella LM, Schmidhuber J, Laptev D, Dwivedi S, Buhmann JM
    Frontiers in Neuroanatomy. 2015 Nov 05;9:142. doi: 10.3389/fnana.2015.00142

    To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This “deep learning” approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge.

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    11/05/15 | Histone H3 threonine phosphorylation regulates asymmetric histone inheritance in the Drosophila male germline.
    Xie J, Wooten M, Tran V, Chen B, Pozmanter C, Simbolon C, Betzig E, Chen X
    Cell. 2015 Nov 5;163(4):920-33. doi: 10.1016/j.cell.2015.10.002

    A long-standing question concerns how stem cells maintain their identity through multiple divisions. Previously, we reported that pre-existing and newly synthesized histone H3 are asymmetrically distributed during Drosophila male germline stem cell (GSC) asymmetric division. Here, we show that phosphorylation at threonine 3 of H3 (H3T3P) distinguishes pre-existing versus newly synthesized H3. Converting T3 to the unphosphorylatable residue alanine (H3T3A) or to the phosphomimetic aspartate (H3T3D) disrupts asymmetric H3 inheritance. Expression of H3T3A or H3T3D specifically in early-stage germline also leads to cellular defects, including GSC loss and germline tumors. Finally, compromising the activity of the H3T3 kinase Haspin enhances the H3T3A but suppresses the H3T3D phenotypes. These studies demonstrate that H3T3P distinguishes sister chromatids enriched with distinct pools of H3 in order to coordinate asymmetric segregation of "old" H3 into GSCs and that tight regulation of H3T3 phosphorylation is required for male germline activity.

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    Sternson Lab
    11/04/15 | Applying the brakes: when to stop eating.
    Betley JN, Sternson SM
    Neuron. 2015 Nov 4;88(3):440-1. doi: 10.1016/j.neuron.2015.10.034

    The nucleus accumbens regulates consummatory behaviors, such as eating. In this issue of Neuron, O'Connor et al. (2015) identify dopamine receptor 1-expressing neurons that project to the lateral hypothalamus as mediating rapid control over feeding behavior.

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    Pastalkova Lab
    11/03/15 | Clique topology reveals intrinsic geometric structure in neural correlations.
    Giusti C, Pastalkova E, Curto C, Itskov V
    Proceedings of the National Academy of Sciences of the United States of America. 2015 Nov 3;112(44):13455-60. doi: 10.1073/pnas.1506407112

    Detecting meaningful structure in neural activity and connectivity data is challenging in the presence of hidden nonlinearities, where traditional eigenvalue-based methods may be misleading. We introduce a novel approach to matrix analysis, called clique topology, that extracts features of the data invariant under nonlinear monotone transformations. These features can be used to detect both random and geometric structure, and depend only on the relative ordering of matrix entries. We then analyzed the activity of pyramidal neurons in rat hippocampus, recorded while the animal was exploring a 2D environment, and confirmed that our method is able to detect geometric organization using only the intrinsic pattern of neural correlations. Remarkably, we found similar results during nonspatial behaviors such as wheel running and rapid eye movement (REM) sleep. This suggests that the geometric structure of correlations is shaped by the underlying hippocampal circuits and is not merely a consequence of position coding. We propose that clique topology is a powerful new tool for matrix analysis in biological settings, where the relationship of observed quantities to more meaningful variables is often nonlinear and unknown.

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