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2529 Janelia Publications

Showing 201-210 of 2529 results
Heberlein LabSimpson Lab
09/02/15 | A subset of serotonergic neurons evokes hunger in adult Drosophila.
Albin SD, Kaun KR, Knapp J, Chung P, Heberlein U, Simpson JH
Current Biology : CB. 2015 Sep 2;25(18):2435-40. doi: 10.1016/j.cub.2015.08.005

Hunger is a complex motivational state that drives multiple behaviors. The sensation of hunger is caused by an imbalance between energy intake and expenditure. One immediate response to hunger is increased food consumption. Hunger also modulates behaviors related to food seeking such as increased locomotion and enhanced sensory sensitivity in both insects [1-5] and vertebrates [6, 7]. In addition, hunger can promote the expression of food-associated memory [8, 9]. Although progress is being made [10], how hunger is represented in the brain and how it coordinates these behavioral responses is not fully understood in any system. Here, we use Drosophila melanogaster to identify neurons encoding hunger. We found a small group of neurons that, when activated, induced a fed fly to eat as though it were starved, suggesting that these neurons are downstream of the metabolic regulation of hunger. Artificially activating these neurons also promotes appetitive memory performance in sated flies, indicating that these neurons are not simply feeding command neurons but likely play a more general role in encoding hunger. We determined that the neurons relevant for the feeding effect are serotonergic and project broadly within the brain, suggesting a possible mechanism for how various responses to hunger are coordinated. These findings extend our understanding of the neural circuitry that drives feeding and enable future exploration of how state influences neural activity within this circuit.

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Gonen Lab
06/01/14 | A suite of software for processing MicroED data of extremely small protein crystals.
Iadanza MG, Gonen T
Journal of Applied Crystallography. 2014 Jun 1;47(Pt 3):1140-45. doi: 10.1107/S1600576714008073

Electron diffraction of extremely small three-dimensional crystals (MicroED) allows for structure determination from crystals orders of magnitude smaller than those used for X-ray crystallography. MicroED patterns, which are collected in a transmission electron microscope, were initially not amenable to indexing and intensity extraction by standard software, which necessitated the development of a suite of programs for data processing. The MicroED suite was developed to accomplish the tasks of unit-cell determination, indexing, background subtraction, intensity measurement and merging, resulting in data that can be carried forward to molecular replacement and structure determination. This ad hoc solution has been modified for more general use to provide a means for processing MicroED data until the technique can be fully implemented into existing crystallographic software packages. The suite is written in Python and the source code is available under a GNU General Public License.

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Simpson Lab
08/19/14 | A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila.
Seeds AM, Ravbar P, Chung P, Hampel S, Midgley FM, Mensh BD, Simpson JH
eLife. 2014 Aug 19;3:e02951. doi: 10.7554/eLife.02951

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences.

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10/25/12 | A survey of 6,300 genomic fragments for cis-regulatory activity in the imaginal discs of Drosophila melanogaster.
Jory A, Estella C, Giorgianni MW, Slattery M, Laverty TR, Rubin GM, Mann RS
Cell Reports. 2012 Oct 25;2(4):1014-24. doi: 10.1016/j.celrep.2012.09.010

Over 6,000 fragments from the genome of Drosophila melanogaster were analyzed for their ability to drive expression of GAL4 reporter genes in the third-instar larval imaginal discs. About 1,200 reporter genes drove expression in the eye, antenna, leg, wing, haltere, or genital imaginal discs. The patterns ranged from large regions to individual cells. About 75% of the active fragments drove expression in multiple discs; 20% were expressed in ventral, but not dorsal, discs (legs, genital, and antenna), whereas \~{}23% were expressed in dorsal but not ventral discs (wing, haltere, and eye). Several patterns, for example, within the leg chordotonal organ, appeared a surprisingly large number of times. Unbiased searches for DNA sequence motifs suggest candidate transcription factors that may regulate enhancers with shared activities. Together, these expression patterns provide a valuable resource to the community and offer a broad overview of how transcriptional regulatory information is distributed in the Drosophila genome.

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Eddy/Rivas Lab
01/01/09 | A survey of nematode SmY RNAs.
Jones TA, Otto W, Marz M, Eddy SR, Stadler PF
RNA Biology. 2009 Jan-Mar;6(1):5-8

SmY RNAs are a family of approximately 70-90 nt small nuclear RNAs found in nematodes. In C. elegans, SmY RNAs copurify in a small ribonucleoprotein (snRNP) complex related to the SL1 and SL2 snRNPs that are involved in nematode mRNA trans-splicing. Here we describe a comprehensive computational analysis of SmY RNA homologs found in the currently available genome sequences. We identify homologs in all sequenced nematode genomes in class Chromadorea. We are unable to identify homologs in a more distantly related nematode species, Trichinella spiralis (class: Dorylaimia), and in representatives of non-nematode phyla that use trans-splicing. Using comparative RNA sequence analysis, we infer a conserved consensus SmY RNA secondary structure consisting of two stems flanking a consensus Sm protein binding site. A representative seed alignment of the SmY RNA family, annotated with the inferred consensus secondary structure, has been deposited with the Rfam RNA families database.

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05/01/24 | A survival-critical role for Drosophila giant interneurons during predation
Cynthia M. Chai , Carmen Morrow , Dhyey D. Parikh , Catherine R. von Reyn , Anthony Leonardo , Gwyneth M Card
bioRxiv. 2024 May 1:. doi: 10.1101/2024.04.30.591368

Large axon-diameter descending neurons are metabolically costly but transmit information rapidly from sensory neurons in the brain to motor neurons in the nerve cord. They have thus endured as a common feature of escape circuits in many animal species where speed is paramount. Though often considered isolated command neurons triggering fast-reaction-time, all-or-none escape responses, giant neurons are just one of multiple parallel pathways enabling selection between behavioral alternatives. Such degeneracy among escape circuits makes it unclear if and how giant neurons benefit prey fitness. Here we competed Drosophila melanogaster flies with genetically-silenced Giant Fibers (GFs) against flies with functional GFs in an arena with wild-caught damselfly predators and find that GF silencing decreases prey survival. Kinematic analysis of damselfly attack trajectories shows that decreased prey survival fitness results from GF-silenced flies failing to escape during predator attack speeds and approach distances that would normally elicit successful escapes. When challenged with a virtual looming predator, fly GFs promote survival by enforcing selection of a short-duration takeoff sequence as opposed to reducing reaction time. Our findings support a role for the GFs in promoting prey survival by influencing action selection as a means to enhance escape performance during realistically complex predation scenarios.

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09/09/20 | A systematic nomenclature for the Drosophila ventral nerve cord.
Court R, Namiki S, Armstrong JD, Borner J, Card G, Costa M, Dickinson M, Duch C, Korff W, Mann R, Merritt D, Murphey RK, Seeds AM, Shirangi T, Simpson JH, Truman JW, Tuthill JC, Williams DW, Shepherd D
Neuron. 2020 Sep 14;107(6):1071-79. doi: 10.1016/j.neuron.2020.08.005

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

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04/26/17 | A systematic nomenclature for the Drosophila ventral nervous system.
Court RC, Armstrong JD, Borner J, Card GM, Costa M, Dickinson MH, Duch C, Korff W, Mann RS, Merritt D, Murphey RK, Namiki S, Seeds AM, Shepherd D, Shirangi TR, Simpson JH, Truman JW, Tuthill JC, Williams DW
bioRxiv. 2017 Apr 26:. doi: 10.1101/122952

Insect nervous systems are proven and powerful model systems for neuroscience research with wide relevance in biology and medicine. However, descriptions of insect brains have suffered from a lack of a complete and uniform nomenclature. Recognising this problem the Insect Brain Name Working Group produced the first agreed hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other insect taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Ito et al. (2014) purposely focused on the gnathal regions that account for approximately 50% of the adult CNS. We extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system to provide a nomenclature of the so-called ventral nervous system (VNS), which includes the thoracic and abdominal neuromeres that was not included in the original work and contains the neurons that play critical roles underpinning most fly behaviours.

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Simpson LabRubin Lab
02/19/14 | A systematic nomenclature for the insect brain.
Ito K, Shinomiya K, Ito M, Armstrong JD, Boyan G, Hartenstein V, Harzsch S, Heisenberg M, Homberg U, Jenett A, Keshishian H, Restifo LL, Rössler W, Simpson JH, Strausfeld NJ, Strauss R, Vosshall LB
Neuron. 2014 Feb 19;81:755-65. doi: 10.1016/j.neuron.2013.12.017

Despite the importance of the insect nervous system for functional and developmental neuroscience, descriptions of insect brains have suffered from a lack of uniform nomenclature. Ambiguous definitions of brain regions and fiber bundles have contributed to the variation of names used to describe the same structure. The lack of clearly determined neuropil boundaries has made it difficult to document precise locations of neuronal projections for connectomics study. To address such issues, a consortium of neurobiologists studying arthropod brains, the Insect Brain Name Working Group, has established the present hierarchical nomenclature system, using the brain of Drosophila melanogaster as the reference framework, while taking the brains of other taxa into careful consideration for maximum consistency and expandability. The following summarizes the consortium’s nomenclature system and highlights examples of existing ambiguities and remedies for them. This nomenclature is intended to serve as a standard of reference for the study of the brain of Drosophila and other insects.

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Singer Lab
08/21/15 | A three-camera imaging microscope for high-speed single-molecule tracking and super-resolution imaging in living cells.
English BP, Singer RH
Proceedings of SPIE. 2015 Aug 21;9550:955008 . doi: 10.1117/12.2190246

Our aim is to develop quantitative single-molecule assays to study when and where molecules are interacting inside living cells and where enzymes are active. To this end we present a three-camera imaging microscope for fast tracking of multiple interacting molecules simultaneously, with high spatiotemporal resolution. The system was designed around an ASI RAMM frame using three separate tube lenses and custom multi-band dichroics to allow for enhanced detection efficiency. The frame times of the three Andor iXon Ultra EMCCD cameras are hardware synchronized to the laser excitation pulses of the three excitation lasers, such that the fluorophores are effectively immobilized during frame acquisitions and do not yield detections that are motion-blurred. Stroboscopic illumination allows robust detection from even rapidly moving molecules while minimizing bleaching, and since snapshots can be spaced out with varying time intervals, stroboscopic illumination enables a direct comparison to be made between fast and slow molecules under identical light dosage. We have developed algorithms that accurately track and co-localize multiple interacting biomolecules. The three-color microscope combined with our co-movement algorithms have made it possible for instance to simultaneously image and track how the chromosome environment affects diffusion kinetics or determine how mRNAs diffuse during translation. Such multiplexed single-molecule measurements at a high spatiotemporal resolution inside living cells will provide a major tool for testing models relating molecular architecture and biological dynamics.

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