1
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Cooney PC, Huang Y, Li W, Perera DM, Hormigo R, Tabachnik T, Godage IS, Hillman EMC, Grueber WB, Zarin AA. Neuromuscular basis of Drosophila larval rolling escape behavior. Proc Natl Acad Sci U S A 2023; 120:e2303641120. [PMID: 38096410 PMCID: PMC10743538 DOI: 10.1073/pnas.2303641120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 10/06/2023] [Indexed: 12/18/2023] Open
Abstract
When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larva's circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression leads to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.
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Affiliation(s)
- Patricia C. Cooney
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Neuroscience, Columbia University, New York, NY10027
| | - Yuhan Huang
- Department of Biology, Texas A&M University, College Station, TX77843
- Zarin Laboratory, Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX77843
| | - Wenze Li
- Laboratory for Functional Optical Imaging, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Electrical Engineering, Columbia University, New York, NY10027
| | - Dulanjana M. Perera
- Department of Multidisciplinary Engineering, Texas A&M University, College Station, TX77843
| | - Richard Hormigo
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
| | - Tanya Tabachnik
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
| | - Isuru S. Godage
- Department of Multidisciplinary Engineering, Texas A&M University, College Station, TX77843
- Department of Engineering Technology and Industrial Distribution, Texas A&M University, College Station, TX77843
- J. Mike Walker ‘66 Department of Mechanical Engineering, Texas A&M University, College Station, TX77843
| | - Elizabeth M. C. Hillman
- Laboratory for Functional Optical Imaging, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Biomedical Engineering, Columbia University, New York, NY10027
- Laboratory for Functional Optical Imaging, Kavli Institute for Brain Science, Columbia University, New York, NY10032
| | - Wesley B. Grueber
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Neuroscience, Columbia University, New York, NY10027
- Department of Physiology and Cellular Biophysics, Jerome L. Greene Science Center, New York, NY10027
| | - Aref A. Zarin
- Department of Biology, Texas A&M University, College Station, TX77843
- Zarin Laboratory, Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX77843
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2
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Jetti SK, Crane AB, Akbergenova Y, Aponte-Santiago NA, Cunningham KL, Whittaker CA, Littleton JT. Molecular logic of synaptic diversity between Drosophila tonic and phasic motoneurons. Neuron 2023; 111:3554-3569.e7. [PMID: 37611584 DOI: 10.1016/j.neuron.2023.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/22/2023] [Accepted: 07/28/2023] [Indexed: 08/25/2023]
Abstract
Although neuronal subtypes display unique synaptic organization and function, the underlying transcriptional differences that establish these features are poorly understood. To identify molecular pathways that contribute to synaptic diversity, single-neuron Patch-seq RNA profiling was performed on Drosophila tonic and phasic glutamatergic motoneurons. Tonic motoneurons form weaker facilitating synapses onto single muscles, while phasic motoneurons form stronger depressing synapses onto multiple muscles. Super-resolution microscopy and in vivo imaging demonstrated that synaptic active zones in phasic motoneurons are more compact and display enhanced Ca2+ influx compared with their tonic counterparts. Genetic analysis identified unique synaptic properties that mapped onto gene expression differences for several cellular pathways, including distinct signaling ligands, post-translational modifications, and intracellular Ca2+ buffers. These findings provide insights into how unique transcriptomes drive functional and morphological differences between neuronal subtypes.
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Affiliation(s)
- Suresh K Jetti
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Andrés B Crane
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yulia Akbergenova
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Nicole A Aponte-Santiago
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Karen L Cunningham
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Charles A Whittaker
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - J Troy Littleton
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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3
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Cooney PC, Huang Y, Li W, Perera DM, Hormigo R, Tabachnik T, Godage I, Hillman EMC, Grueber WB, Zarin AA. Neuromuscular Basis of Drosophila larval rolling escape behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.01.526733. [PMID: 36778508 PMCID: PMC9915593 DOI: 10.1101/2023.02.01.526733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally-Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, the muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larval circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression lead to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior, and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.
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4
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Kohsaka H. Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion. Front Neural Circuits 2023; 17:1175899. [PMID: 37711343 PMCID: PMC10499525 DOI: 10.3389/fncir.2023.1175899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/13/2023] [Indexed: 09/16/2023] Open
Abstract
The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.
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Affiliation(s)
- Hiroshi Kohsaka
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo, Japan
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
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5
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Liu Y, Hasegawa E, Nose A, Zwart MF, Kohsaka H. Synchronous multi-segmental activity between metachronal waves controls locomotion speed in Drosophila larvae. eLife 2023; 12:e83328. [PMID: 37551094 PMCID: PMC10409504 DOI: 10.7554/elife.83328] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 06/14/2023] [Indexed: 08/09/2023] Open
Abstract
The ability to adjust the speed of locomotion is essential for survival. In limbed animals, the frequency of locomotion is modulated primarily by changing the duration of the stance phase. The underlying neural mechanisms of this selective modulation remain an open question. Here, we report a neural circuit controlling a similarly selective adjustment of locomotion frequency in Drosophila larvae. Drosophila larvae crawl using peristaltic waves of muscle contractions. We find that larvae adjust the frequency of locomotion mostly by varying the time between consecutive contraction waves, reminiscent of limbed locomotion. A specific set of muscles, the lateral transverse (LT) muscles, co-contract in all segments during this phase, the duration of which sets the duration of the interwave phase. We identify two types of GABAergic interneurons in the LT neural network, premotor neuron A26f and its presynaptic partner A31c, which exhibit segmentally synchronized activity and control locomotor frequency by setting the amplitude and duration of LT muscle contractions. Altogether, our results reveal an inhibitory central circuit that sets the frequency of locomotion by controlling the duration of the period in between peristaltic waves. Further analysis of the descending inputs onto this circuit will help understand the higher control of this selective modulation.
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Affiliation(s)
- Yingtao Liu
- Department of Physics, Graduate School of Science, The University of TokyoTokyoJapan
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of TokyoKashiwaJapan
| | - Eri Hasegawa
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of TokyoKashiwaJapan
| | - Akinao Nose
- Department of Physics, Graduate School of Science, The University of TokyoTokyoJapan
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of TokyoKashiwaJapan
| | - Maarten F Zwart
- School of Psychology and Neuroscience, Centre of Biophotonics, University of St AndrewsSt AndrewsUnited Kingdom
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of TokyoKashiwaJapan
- Graduate School of Informatics and Engineering, The University of Electro-CommunicationsTokyoJapan
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6
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Thane M, Paisios E, Stöter T, Krüger AR, Gläß S, Dahse AK, Scholz N, Gerber B, Lehmann DJ, Schleyer M. High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation. Open Biol 2023; 13:220308. [PMID: 37072034 PMCID: PMC10113034 DOI: 10.1098/rsob.220308] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 03/05/2023] [Indexed: 04/20/2023] Open
Abstract
Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending 'mooncrawler' neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts.
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Affiliation(s)
- Michael Thane
- Department Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Simulation and Graphics, Otto von Guerike University, Magdeburg, Germany
| | - Emmanouil Paisios
- Department Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Torsten Stöter
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Anna-Rosa Krüger
- Department Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Institute of Biology, Free University of Berlin, Berlin, Germany
| | - Sebastian Gläß
- Department Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Anne-Kristin Dahse
- Division of General Biochemistry, Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, Leipzig University, Leipzig, Germany
| | - Nicole Scholz
- Division of General Biochemistry, Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, Leipzig University, Leipzig, Germany
| | - Bertram Gerber
- Department Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Institute of Biology, Otto von Guericke University Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Dirk J. Lehmann
- Department of Simulation and Graphics, Otto von Guerike University, Magdeburg, Germany
- Department for Information Engineering, Faculty of Computer Science, Ostfalia University of Applied Science, Brunswick-Wolfenbuettel, Germany
| | - Michael Schleyer
- Department Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
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7
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Winding M, Pedigo BD, Barnes CL, Patsolic HG, Park Y, Kazimiers T, Fushiki A, Andrade IV, Khandelwal A, Valdes-Aleman J, Li F, Randel N, Barsotti E, Correia A, Fetter RD, Hartenstein V, Priebe CE, Vogelstein JT, Cardona A, Zlatic M. The connectome of an insect brain. Science 2023; 379:eadd9330. [PMID: 36893230 PMCID: PMC7614541 DOI: 10.1126/science.add9330] [Citation(s) in RCA: 76] [Impact Index Per Article: 76.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 02/07/2023] [Indexed: 03/11/2023]
Abstract
Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain's most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.
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Affiliation(s)
- Michael Winding
- University of Cambridge, Department of Zoology, Cambridge, UK
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Benjamin D. Pedigo
- Johns Hopkins University, Department of Biomedical Engineering, Baltimore, MD, USA
| | - Christopher L. Barnes
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
- University of Cambridge, Department of Physiology, Development, and Neuroscience, Cambridge, UK
| | - Heather G. Patsolic
- Johns Hopkins University, Department of Applied Mathematics and Statistics, Baltimore, MD, USA
- Accenture, Arlington, VA, USA
| | - Youngser Park
- Johns Hopkins University, Center for Imaging Science, Baltimore, MD, USA
| | - Tom Kazimiers
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- kazmos GmbH, Dresden, Germany
| | - Akira Fushiki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Ingrid V. Andrade
- University of California Los Angeles, Department of Molecular, Cell and Developmental Biology, Los Angeles, CA, USA
| | - Avinash Khandelwal
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Javier Valdes-Aleman
- University of Cambridge, Department of Zoology, Cambridge, UK
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Feng Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Nadine Randel
- University of Cambridge, Department of Zoology, Cambridge, UK
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
| | - Elizabeth Barsotti
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
- University of Cambridge, Department of Physiology, Development, and Neuroscience, Cambridge, UK
| | - Ana Correia
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
- University of Cambridge, Department of Physiology, Development, and Neuroscience, Cambridge, UK
| | - Richard D. Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Stanford University, Stanford, CA, USA
| | - Volker Hartenstein
- University of California Los Angeles, Department of Molecular, Cell and Developmental Biology, Los Angeles, CA, USA
| | - Carey E. Priebe
- Johns Hopkins University, Department of Applied Mathematics and Statistics, Baltimore, MD, USA
- Johns Hopkins University, Center for Imaging Science, Baltimore, MD, USA
| | - Joshua T. Vogelstein
- Johns Hopkins University, Department of Biomedical Engineering, Baltimore, MD, USA
- Johns Hopkins University, Center for Imaging Science, Baltimore, MD, USA
| | - Albert Cardona
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- University of Cambridge, Department of Physiology, Development, and Neuroscience, Cambridge, UK
| | - Marta Zlatic
- University of Cambridge, Department of Zoology, Cambridge, UK
- MRC Laboratory of Molecular Biology, Neurobiology Division, Cambridge, UK
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
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8
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Jetti SK, Crane AB, Akbergenova Y, Aponte-Santiago NA, Cunningham KL, Whittaker CA, Littleton JT. Molecular Logic of Synaptic Diversity Between Drosophila Tonic and Phasic Motoneurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.17.524447. [PMID: 36711745 PMCID: PMC9882338 DOI: 10.1101/2023.01.17.524447] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Although neuronal subtypes display unique synaptic organization and function, the underlying transcriptional differences that establish these features is poorly understood. To identify molecular pathways that contribute to synaptic diversity, single neuron PatchSeq RNA profiling was performed on Drosophila tonic and phasic glutamatergic motoneurons. Tonic motoneurons form weaker facilitating synapses onto single muscles, while phasic motoneurons form stronger depressing synapses onto multiple muscles. Super-resolution microscopy and in vivo imaging demonstrated synaptic active zones in phasic motoneurons are more compact and display enhanced Ca 2+ influx compared to their tonic counterparts. Genetic analysis identified unique synaptic properties that mapped onto gene expression differences for several cellular pathways, including distinct signaling ligands, post-translational modifications and intracellular Ca 2+ buffers. These findings provide insights into how unique transcriptomes drive functional and morphological differences between neuronal subtypes.
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Affiliation(s)
- Suresh K Jetti
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Andrés B Crane
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Yulia Akbergenova
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Nicole A Aponte-Santiago
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Karen L Cunningham
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Charles A Whittaker
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - J Troy Littleton
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
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9
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Coulson B, Hunter I, Doran S, Parkin J, Landgraf M, Baines RA. Critical periods in Drosophila neural network development: Importance to network tuning and therapeutic potential. Front Physiol 2022; 13:1073307. [PMID: 36531164 PMCID: PMC9757492 DOI: 10.3389/fphys.2022.1073307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 11/23/2022] [Indexed: 02/25/2024] Open
Abstract
Critical periods are phases of heightened plasticity that occur during the development of neural networks. Beginning with pioneering work of Hubel and Wiesel, which identified a critical period for the formation of ocular dominance in mammalian visual network connectivity, critical periods have been identified for many circuits, both sensory and motor, and across phyla, suggesting a universal phenomenon. However, a key unanswered question remains why these forms of plasticity are restricted to specific developmental periods rather than being continuously present. The consequence of this temporal restriction is that activity perturbations during critical periods can have lasting and significant functional consequences for mature neural networks. From a developmental perspective, critical period plasticity might enable reproducibly robust network function to emerge from ensembles of cells, whose properties are necessarily variable and fluctuating. Critical periods also offer significant clinical opportunity. Imposed activity perturbation during these periods has shown remarkable beneficial outcomes in a range of animal models of neurological disease including epilepsy. In this review, we spotlight the recent identification of a locomotor critical period in Drosophila larva and describe how studying this model organism, because of its simplified nervous system and an almost complete wired connectome, offers an attractive prospect of understanding how activity during a critical period impacts a neuronal network.
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Affiliation(s)
- Bramwell Coulson
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Iain Hunter
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Sarah Doran
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Jill Parkin
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Matthias Landgraf
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Richard A. Baines
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
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10
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Giachello CNG, Hunter I, Pettini T, Coulson B, Knüfer A, Cachero S, Winding M, Arzan Zarin A, Kohsaka H, Fan YN, Nose A, Landgraf M, Baines RA. Electrophysiological Validation of Monosynaptic Connectivity between Premotor Interneurons and the aCC Motoneuron in the Drosophila Larval CNS. J Neurosci 2022; 42:6724-6738. [PMID: 35868863 PMCID: PMC9435966 DOI: 10.1523/jneurosci.2463-21.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 04/28/2022] [Accepted: 05/31/2022] [Indexed: 11/21/2022] Open
Abstract
The Drosophila connectome project aims to map the synaptic connectivity of entire larval and adult fly neural networks, which is essential for understanding nervous system development and function. So far, the project has produced an impressive amount of electron microscopy data that has facilitated reconstructions of specific synapses, including many in the larval locomotor circuit. While this breakthrough represents a technical tour de force, the data remain underutilized, partly because of a lack of functional validation of reconstructions. Attempts to validate connectivity posited by the connectome project, have mostly relied on behavioral assays and/or GFP reconstitution across synaptic partners (GRASP) or GCaMP imaging. While these techniques are useful, they have limited spatial or temporal resolution. Electrophysiological assays of synaptic connectivity overcome these limitations. Here, we combine patch-clamp recordings with optogenetic stimulation in male and female larvae, to test synaptic connectivity proposed by connectome reconstructions. Specifically, we use multiple driver lines to confirm that several connections between premotor interneurons and the anterior corner cell motoneuron are, as the connectome project suggests, monosynaptic. In contrast, our results also show that conclusions based on GRASP imaging may provide false-positive results regarding connectivity between cells. We also present a novel imaging tool, based on the same technology as our electrophysiology, as a favorable alternative to GRASP imaging. Finally, of eight Gal4 lines tested, five are reliably expressed in the premotor interneurons they are targeted to. Thus, our work highlights the need to confirm functional synaptic connectivity, driver line specificity, and use of appropriate genetic tools to support connectome projects.SIGNIFICANCE STATEMENT The Drosophila connectome project aims to provide a complete description of connectivity between neurons in an organism that presents experimental advantages over other models. It has reconstructed hundreds of thousands of synaptic connections of the fly larva by manual identification of anatomic landmarks present in serial section transmission electron microscopy (ssTEM) volumes of the larval CNS. We use a highly reliable electrophysiological approach to verify these connections, providing useful insight into the accuracy of work based on ssTEM. We also present a novel imaging tool for validating excitatory monosynaptic connections between cells and show that several genetic driver lines designed to target neurons of the larval connectome exhibit nonspecific and/or unreliable expression.
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Affiliation(s)
- Carlo N G Giachello
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Iain Hunter
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Tom Pettini
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Bramwell Coulson
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Athene Knüfer
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Sebastian Cachero
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, United Kingdom
| | - Michael Winding
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Aref Arzan Zarin
- Department of Biology, Texas A&M University, College Station, Texas 77843-3258
| | - Hiroshi Kohsaka
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo 182-8585, Japan
| | - Yuen Ngan Fan
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Akinao Nose
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Chiba 277-8561, Japan
| | - Matthias Landgraf
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Richard A Baines
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
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11
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Sun X, Liu Y, Liu C, Mayumi K, Ito K, Nose A, Kohsaka H. A neuromechanical model for Drosophila larval crawling based on physical measurements. BMC Biol 2022; 20:130. [PMID: 35701821 PMCID: PMC9199175 DOI: 10.1186/s12915-022-01336-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 05/20/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Animal locomotion requires dynamic interactions between neural circuits, the body (typically muscles), and surrounding environments. While the neural circuitry of movement has been intensively studied, how these outputs are integrated with body mechanics (neuromechanics) is less clear, in part due to the lack of understanding of the biomechanical properties of animal bodies. Here, we propose an integrated neuromechanical model of movement based on physical measurements by taking Drosophila larvae as a model of soft-bodied animals. RESULTS We first characterized the kinematics of forward crawling in Drosophila larvae at a segmental and whole-body level. We then characterized the biomechanical parameters of fly larvae, namely the contraction forces generated by neural activity, and passive elastic and viscosity of the larval body using a stress-relaxation test. We established a mathematical neuromechanical model based on the physical measurements described above, obtaining seven kinematic values characterizing crawling locomotion. By optimizing the parameters in the neural circuit, our neuromechanical model succeeded in quantitatively reproducing the kinematics of larval locomotion that were obtained experimentally. This model could reproduce the observation of optogenetic studies reported previously. The model predicted that peristaltic locomotion could be exhibited in a low-friction condition. Analysis of floating larvae provided results consistent with this prediction. Furthermore, the model predicted a significant contribution of intersegmental connections in the central nervous system, which contrasts with a previous study. This hypothesis allowed us to make a testable prediction for the variability in intersegmental connection in sister species of the genus Drosophila. CONCLUSIONS We generated a neurochemical model based on physical measurement to provide a new foundation to study locomotion in soft-bodied animals and soft robot engineering.
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Affiliation(s)
- Xiyang Sun
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, the University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan
| | - Yingtao Liu
- Department of Physics, Graduate School of Science, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 133-0033, Japan
| | - Chang Liu
- Department of Advanced Materials Science, Graduate School of Frontier Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan
| | - Koichi Mayumi
- Department of Advanced Materials Science, Graduate School of Frontier Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan
| | - Kohzo Ito
- Department of Advanced Materials Science, Graduate School of Frontier Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan
| | - Akinao Nose
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, the University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan.,Department of Physics, Graduate School of Science, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 133-0033, Japan
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, the University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan. .,Division of General Education, Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1, Chofugaoka, Chofu, Tokyo, 182-8585, Japan.
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12
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Agrawal S, Tuthill JC. The two-body problem: Proprioception and motor control across the metamorphic divide. Curr Opin Neurobiol 2022; 74:102546. [PMID: 35512562 DOI: 10.1016/j.conb.2022.102546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/11/2022] [Accepted: 03/27/2022] [Indexed: 11/17/2022]
Abstract
Like a rocket being propelled into space, evolution has engineered flies to launch into adulthood via multiple stages. Flies develop and deploy two distinct bodies, linked by the transformative process of metamorphosis. The fly larva is a soft hydraulic tube that can crawl to find food and avoid predators. The adult fly has a stiff exoskeleton with articulated limbs that enable long-distance navigation and rich social interactions. Because the larval and adult forms are so distinct in structure, they require distinct strategies for sensing and moving the body. The metamorphic divide thus presents an opportunity for comparative analysis of neural circuits. Here, we review recent progress toward understanding the neural mechanisms of proprioception and motor control in larval and adult Drosophila. We highlight commonalities that point toward general principles of sensorimotor control and differences that may reflect unique constraints imposed by biomechanics. Finally, we discuss emerging opportunities for comparative analysis of neural circuit architecture in the fly and other animal species.
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Affiliation(s)
- Sweta Agrawal
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA.
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
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13
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Zeng X, Komanome Y, Kawasaki T, Inada K, Jonaitis J, Pulver SR, Kazama H, Nose A. An electrically coupled pioneer circuit enables motor development via proprioceptive feedback in Drosophila embryos. Curr Biol 2021; 31:5327-5340.e5. [PMID: 34666002 DOI: 10.1016/j.cub.2021.10.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 09/03/2021] [Accepted: 10/04/2021] [Indexed: 02/02/2023]
Abstract
Precocious movements are widely seen in embryos of various animal species. Whether such movements via proprioceptive feedback play instructive roles in motor development or are a mere reflection of activities in immature motor circuits is a long-standing question. Here we image the emerging motor activities in Drosophila embryos that lack proprioceptive feedback and show that proprioceptive experience is essential for the development of locomotor central pattern generators (CPGs). Downstream of proprioceptive inputs, we identify a pioneer premotor circuit composed of two pairs of segmental interneurons, whose gap-junctional transmission requires proprioceptive experience and plays a crucial role in CPG formation. The circuit autonomously generates rhythmic plateau potentials via IP3-mediated Ca2+ release from internal stores, which contribute to muscle contractions and hence produce proprioceptive feedback. Our findings demonstrate the importance of self-generated movements in instructing motor development and identify the cells, circuit, and physiology at the core of this proprioceptive feedback.
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Affiliation(s)
- Xiangsunze Zeng
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
| | - Yuko Komanome
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
| | - Tappei Kawasaki
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
| | - Kengo Inada
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Julius Jonaitis
- School of Psychology and Neuroscience, University of St Andrews, St Mary's Quad, South Street, St Andrews KY16 9JP, UK
| | - Stefan R Pulver
- School of Psychology and Neuroscience, University of St Andrews, St Mary's Quad, South Street, St Andrews KY16 9JP, UK
| | - Hokto Kazama
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan; Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan.
| | - Akinao Nose
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan; Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
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14
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Sharples SA, Miles GB. Maturation of persistent and hyperpolarization-activated inward currents shapes the differential activation of motoneuron subtypes during postnatal development. eLife 2021; 10:e71385. [PMID: 34783651 PMCID: PMC8641952 DOI: 10.7554/elife.71385] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 11/15/2021] [Indexed: 12/15/2022] Open
Abstract
The size principle underlies the orderly recruitment of motor units; however, motoneuron size is a poor predictor of recruitment amongst functionally defined motoneuron subtypes. Whilst intrinsic properties are key regulators of motoneuron recruitment, the underlying currents involved are not well defined. Whole-cell patch-clamp electrophysiology was deployed to study intrinsic properties, and the underlying currents, that contribute to the differential activation of delayed and immediate firing motoneuron subtypes. Motoneurons were studied during the first three postnatal weeks in mice to identify key properties that contribute to rheobase and may be important to establish orderly recruitment. We find that delayed and immediate firing motoneurons are functionally homogeneous during the first postnatal week and are activated based on size, irrespective of subtype. The rheobase of motoneuron subtypes becomes staggered during the second postnatal week, which coincides with the differential maturation of passive and active properties, particularly persistent inward currents. Rheobase of delayed firing motoneurons increases further in the third postnatal week due to the development of a prominent resting hyperpolarization-activated inward current. Our results suggest that motoneuron recruitment is multifactorial, with recruitment order established during postnatal development through the differential maturation of passive properties and sequential integration of persistent and hyperpolarization-activated inward currents.
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Affiliation(s)
- Simon A Sharples
- School of Psychology and Neuroscience, University of St AndrewsSt AndrewsUnited Kingdom
| | - Gareth B Miles
- School of Psychology and Neuroscience, University of St AndrewsSt AndrewsUnited Kingdom
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15
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Matsuo Y, Nose A, Kohsaka H. Interspecies variation of larval locomotion kinematics in the genus Drosophila and its relation to habitat temperature. BMC Biol 2021; 19:176. [PMID: 34470643 PMCID: PMC8411537 DOI: 10.1186/s12915-021-01110-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 07/29/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Speed and trajectory of locomotion are the characteristic traits of individual species. Locomotion kinematics may have been shaped during evolution towards increased survival in the habitats of each species. Although kinematics of locomotion is thought to be influenced by habitats, the quantitative relation between the kinematics and environmental factors has not been fully revealed. Here, we performed comparative analyses of larval locomotion in 11 Drosophila species. RESULTS We found that larval locomotion kinematics are divergent among the species. The diversity is not correlated to the body length but is correlated instead to the habitat temperature of the species. Phylogenetic analyses using Bayesian inference suggest that the evolutionary rate of the kinematics is diverse among phylogenetic tree branches. CONCLUSIONS The results of this study imply that the kinematics of larval locomotion has diverged in the evolutionary history of the genus Drosophila and evolved under the effects of the ambient temperature of habitats.
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Affiliation(s)
- Yuji Matsuo
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan
| | - Akinao Nose
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan
- Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 133-0033, Japan
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan.
- School of Informatics and Engineering, The University of Electro-Communications, 1-5-1, Chofugaoka, Chofu-shi, Tokyo, 182-8585, Japan.
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16
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Hunter I, Coulson B, Zarin AA, Baines RA. The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function. Front Neural Circuits 2021; 15:684969. [PMID: 34276315 PMCID: PMC8282269 DOI: 10.3389/fncir.2021.684969] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 06/09/2021] [Indexed: 11/13/2022] Open
Abstract
It is difficult to answer important questions in neuroscience, such as: "how do neural circuits generate behaviour?," because research is limited by the complexity and inaccessibility of the mammalian nervous system. Invertebrate model organisms offer simpler networks that are easier to manipulate. As a result, much of what we know about the development of neural circuits is derived from work in crustaceans, nematode worms and arguably most of all, the fruit fly, Drosophila melanogaster. This review aims to demonstrate the utility of the Drosophila larval locomotor network as a model circuit, to those who do not usually use the fly in their work. This utility is explored first by discussion of the relatively complete connectome associated with one identified interneuron of the locomotor circuit, A27h, and relating it to similar circuits in mammals. Next, it is developed by examining its application to study two important areas of neuroscience research: critical periods of development and interindividual variability in neural circuits. In summary, this article highlights the potential to use the larval locomotor network as a "generic" model circuit, to provide insight into mammalian circuit development and function.
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Affiliation(s)
- Iain Hunter
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
| | - Bramwell Coulson
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
| | - Aref Arzan Zarin
- Department of Biology, The Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, United States
| | - Richard A Baines
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
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17
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Hiramoto A, Jonaitis J, Niki S, Kohsaka H, Fetter RD, Cardona A, Pulver SR, Nose A. Regulation of coordinated muscular relaxation in Drosophila larvae by a pattern-regulating intersegmental circuit. Nat Commun 2021; 12:2943. [PMID: 34011945 PMCID: PMC8134441 DOI: 10.1038/s41467-021-23273-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 04/22/2021] [Indexed: 02/03/2023] Open
Abstract
Typical patterned movements in animals are achieved through combinations of contraction and delayed relaxation of groups of muscles. However, how intersegmentally coordinated patterns of muscular relaxation are regulated by the neural circuits remains poorly understood. Here, we identify Canon, a class of higher-order premotor interneurons, that regulates muscular relaxation during backward locomotion of Drosophila larvae. Canon neurons are cholinergic interneurons present in each abdominal neuromere and show wave-like activity during fictive backward locomotion. Optogenetic activation of Canon neurons induces relaxation of body wall muscles, whereas inhibition of these neurons disrupts timely muscle relaxation. Canon neurons provide excitatory outputs to inhibitory premotor interneurons. Canon neurons also connect with each other to form an intersegmental circuit and regulate their own wave-like activities. Thus, our results demonstrate how coordinated muscle relaxation can be realized by an intersegmental circuit that regulates its own patterned activity and sequentially terminates motor activities along the anterior-posterior axis.
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Affiliation(s)
- Atsuki Hiramoto
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Julius Jonaitis
- School of Psychology and Neuroscience, University of St Andrews, St Andrews, UK
| | - Sawako Niki
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | | | - Albert Cardona
- HHMI Janelia Research Campus, Ashburn, VA, USA
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Stefan R Pulver
- School of Psychology and Neuroscience, University of St Andrews, St Andrews, UK
| | - Akinao Nose
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
- Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan.
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18
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Phelps JS, Hildebrand DGC, Graham BJ, Kuan AT, Thomas LA, Nguyen TM, Buhmann J, Azevedo AW, Sustar A, Agrawal S, Liu M, Shanny BL, Funke J, Tuthill JC, Lee WCA. Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy. Cell 2021; 184:759-774.e18. [PMID: 33400916 PMCID: PMC8312698 DOI: 10.1016/j.cell.2020.12.013] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 09/17/2020] [Accepted: 12/09/2020] [Indexed: 02/08/2023]
Abstract
To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to acquire a synapse-resolution dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we studied neuronal networks that control leg and wing movements by reconstructing all 507 motor neurons that control the limbs. We show that a specific class of leg sensory neurons synapses directly onto motor neurons with the largest-caliber axons on both sides of the body, representing a unique pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM more accessible and affordable to the scientific community.
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Affiliation(s)
- Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA; Program in Neuroscience, Division of Medical Sciences, Graduate School of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA
| | - David Grant Colburn Hildebrand
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA; Program in Neuroscience, Division of Medical Sciences, Graduate School of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Brett J Graham
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Aaron T Kuan
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Logan A Thomas
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Tri M Nguyen
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Julia Buhmann
- HHMI Janelia Research Campus, Ashburn, VA 20147, USA
| | - Anthony W Azevedo
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Anne Sustar
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Sweta Agrawal
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Mingguan Liu
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Brendan L Shanny
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Jan Funke
- HHMI Janelia Research Campus, Ashburn, VA 20147, USA
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Wei-Chung Allen Lee
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.
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19
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Aponte-Santiago NA, Littleton JT. Synaptic Properties and Plasticity Mechanisms of Invertebrate Tonic and Phasic Neurons. Front Physiol 2020; 11:611982. [PMID: 33391026 PMCID: PMC7772194 DOI: 10.3389/fphys.2020.611982] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 11/24/2020] [Indexed: 12/15/2022] Open
Abstract
Defining neuronal cell types and their associated biophysical and synaptic diversity has become an important goal in neuroscience as a mechanism to create comprehensive brain cell atlases in the post-genomic age. Beyond broad classification such as neurotransmitter expression, interneuron vs. pyramidal, sensory or motor, the field is still in the early stages of understanding closely related cell types. In both vertebrate and invertebrate nervous systems, one well-described distinction related to firing characteristics and synaptic release properties are tonic and phasic neuronal subtypes. In vertebrates, these classes were defined based on sustained firing responses during stimulation (tonic) vs. transient responses that rapidly adapt (phasic). In crustaceans, the distinction expanded to include synaptic release properties, with tonic motoneurons displaying sustained firing and weaker synapses that undergo short-term facilitation to maintain muscle contraction and posture. In contrast, phasic motoneurons with stronger synapses showed rapid depression and were recruited for short bursts during fast locomotion. Tonic and phasic motoneurons with similarities to those in crustaceans have been characterized in Drosophila, allowing the genetic toolkit associated with this model to be used for dissecting the unique properties and plasticity mechanisms for these neuronal subtypes. This review outlines general properties of invertebrate tonic and phasic motoneurons and highlights recent advances that characterize distinct synaptic and plasticity pathways associated with two closely related glutamatergic neuronal cell types that drive invertebrate locomotion.
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Affiliation(s)
- Nicole A. Aponte-Santiago
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - J. Troy Littleton
- The Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
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20
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Eschbach C, Zlatic M. Useful road maps: studying Drosophila larva's central nervous system with the help of connectomics. Curr Opin Neurobiol 2020; 65:129-137. [PMID: 33242722 PMCID: PMC7773133 DOI: 10.1016/j.conb.2020.09.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/21/2020] [Accepted: 09/24/2020] [Indexed: 12/16/2022]
Abstract
The larva of Drosophila melanogaster is emerging as a powerful model system for comprehensive brain-wide understanding of the circuit implementation of neural computations. With an unprecedented amount of tools in hand, including synaptic-resolution connectomics, whole-brain imaging, and genetic tools for selective targeting of single neuron types, it is possible to dissect which circuits and computations are at work behind behaviors that have an interesting level of complexity. Here we present some of the recent advances regarding multisensory integration, learning, and action selection in Drosophila larva.
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Affiliation(s)
- Claire Eschbach
- Department of Zoology, University of Cambridge, United Kingdom.
| | - Marta Zlatic
- Department of Zoology, University of Cambridge, United Kingdom; MRC Laboratory of Molecular Biology, United Kingdom.
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21
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Mantziaris C, Bockemühl T, Büschges A. Central pattern generating networks in insect locomotion. Dev Neurobiol 2020; 80:16-30. [PMID: 32128970 DOI: 10.1002/dneu.22738] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 02/26/2020] [Accepted: 02/26/2020] [Indexed: 11/08/2022]
Abstract
Central pattern generators (CPGs) are neural circuits that based on their connectivity can generate rhythmic and patterned output in the absence of rhythmic external inputs. This property makes CPGs crucial elements in the generation of many kinds of rhythmic motor behaviors in insects, such as flying, walking, swimming, or crawling. Arguably representing the most diverse group of animals, insects utilize at least one of these types of locomotion during one stage of their ontogenesis. Insects have been extensively used to study the neural basis of rhythmic motor behaviors, and particularly the structure and operation of CPGs involved in locomotion. Here, we review insect locomotion with regard to flying, walking, and crawling, and we discuss the contribution of central pattern generation to these three forms of locomotion. In each case, we compare and contrast the topology and structure of the CPGs, and we point out how these factors are involved in the generation of the respective motor pattern. We focus on the importance of sensory information for establishing a functional motor output and we indicate behavior-specific adaptations. Furthermore, we report on the mechanisms underlying coordination between different body parts. Last but not least, by reviewing the state-of-the-art knowledge concerning the role of CPGs in insect locomotion, we endeavor to create a common ground, upon which future research in the field of motor control in insects can build.
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Affiliation(s)
- Charalampos Mantziaris
- Department of Animal Physiology, Institute of Zoology, University of Cologne, Cologne, Germany
| | - Till Bockemühl
- Department of Animal Physiology, Institute of Zoology, University of Cologne, Cologne, Germany
| | - Ansgar Büschges
- Department of Animal Physiology, Institute of Zoology, University of Cologne, Cologne, Germany
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22
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Jovanic T. Studying neural circuits of decision-making in Drosophila larva. J Neurogenet 2020; 34:162-170. [PMID: 32054384 DOI: 10.1080/01677063.2020.1719407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
To study neural circuits underlying decisions, the model organism used for that purpose has to be simple enough to be able to dissect the circuitry neuron by neuron across the nervous system and in the same time complex enough to be able to perform different types of decisions. Here, I lay out the case: (1) that Drosophila larva is an advantageous model system that balances well these two requirements and (2) the insights gained from this model, assuming that circuit principles may be shared across species, can be used to advance our knowledge of neural circuit implementation of decision-making in general, including in more complex brains.
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Affiliation(s)
- Tihana Jovanic
- Université Paris-Saclay, CNRS, Institut des Neurosciences Paris Saclay, Gif-sur-Yvette, France.,Decision and Bayesian Computation, UMR 3571 Neuroscience Department & USR 3756 (C3BI/DBC), Institut Pasteur & CNRS, Paris, France
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23
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Masson JB, Laurent F, Cardona A, Barré C, Skatchkovsky N, Zlatic M, Jovanic T. Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila. PLoS Genet 2020; 16:e1008589. [PMID: 32059010 PMCID: PMC7173939 DOI: 10.1371/journal.pgen.1008589] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 04/21/2020] [Accepted: 12/30/2019] [Indexed: 11/21/2022] Open
Abstract
Nervous systems have the ability to select appropriate actions and action sequences in response to sensory cues. The circuit mechanisms by which nervous systems achieve choice, stability and transitions between behaviors are still incompletely understood. To identify neurons and brain areas involved in controlling these processes, we combined a large-scale neuronal inactivation screen with automated action detection in response to a mechanosensory cue in Drosophila larva. We analyzed behaviors from 2.9x105 larvae and identified 66 candidate lines for mechanosensory responses out of which 25 for competitive interactions between actions. We further characterize in detail the neurons in these lines and analyzed their connectivity using electron microscopy. We found the neurons in the mechanosensory network are located in different regions of the nervous system consistent with a distributed model of sensorimotor decision-making. These findings provide the basis for understanding how selection and transition between behaviors are controlled by the nervous system.
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Affiliation(s)
- Jean-Baptiste Masson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department, Institut Pasteur & CNRS, Paris, France
| | - François Laurent
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department, Institut Pasteur & CNRS, Paris, France
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
- Department of Physiology, Development, and Neuroscience, Cambridge University, Cambridge, United Kingdom
- MRC Laboratory of Molecular Biology, Trumpington, Cambridge, United Kingdom
| | - Chloé Barré
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department, Institut Pasteur & CNRS, Paris, France
| | - Nicolas Skatchkovsky
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department, Institut Pasteur & CNRS, Paris, France
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
- MRC Laboratory of Molecular Biology, Trumpington, Cambridge, United Kingdom
- Department of Zoology, Cambridge University, Cambridge, United Kingdom
| | - Tihana Jovanic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department, Institut Pasteur & CNRS, Paris, France
- Université Paris-Saclay, CNRS, Institut des Neurosciences Paris Saclay, Gif-sur-Yvette, France
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24
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Abstract
The full functionality of the brain is determined by its molecular, cellular and circuit structure. Modern neuroscience now prioritizes the mapping of whole brain connectomes by detecting all direct neuron to neuron synaptic connections, a feat first accomplished for C. elegans, a full reconstruction of a 302-neuron nervous system. Efforts at Janelia Research Campus will soon reconstruct the whole brain connectomes of a larval and an adult Drosophila. These connectomes will provide a framework for incorporating detailed neural circuit information that Drosophila neuroscientists have gathered over decades. But when viewed in the context of a whole brain, it becomes difficult to isolate the contributions of distinct circuits, whether sensory systems or higher brain regions. The complete wiring diagram tells us that sensory information is not only processed in separate channels, but that even the earliest sensory layers are strongly synaptically interconnected. In the higher brain, long-range projections densely interconnect major brain regions and convergence centers that integrate input from different sensory systems. Furthermore, we also need to understand the impact of neuronal communication beyond direct synaptic modulation. Nevertheless, all of this can be pursued with Drosophila, combining connectomics with a diverse array of genetic tools and behavioral paradigms that provide effective approaches to entire brain function.
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Affiliation(s)
- Katrin Vogt
- Department of Physics, Harvard University, Cambridge, MA, USA.,Center for Brain Science, Harvard University, Cambridge, MA, USA
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25
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Zarin AA, Mark B, Cardona A, Litwin-Kumar A, Doe CQ. A multilayer circuit architecture for the generation of distinct locomotor behaviors in Drosophila. eLife 2019; 8:e51781. [PMID: 31868582 PMCID: PMC6994239 DOI: 10.7554/elife.51781] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Accepted: 12/22/2019] [Indexed: 12/22/2022] Open
Abstract
Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. Here, we characterize Drosophila larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. We show that all body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. We used TEM to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN 'labeled line' connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. We generated a recurrent network model that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors.
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Affiliation(s)
- Aref Arzan Zarin
- Institute of NeuroscienceHoward Hughes Medical Institute, University of OregonEugeneUnited States
| | - Brandon Mark
- Institute of NeuroscienceHoward Hughes Medical Institute, University of OregonEugeneUnited States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Ashok Litwin-Kumar
- Mortimer B Zuckerman Mind Brain Behavior Institute, Department of NeuroscienceColumbia UniversityNew YorkUnited States
| | - Chris Q Doe
- Institute of NeuroscienceHoward Hughes Medical Institute, University of OregonEugeneUnited States
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26
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A GABAergic Maf-expressing interneuron subset regulates the speed of locomotion in Drosophila. Nat Commun 2019; 10:4796. [PMID: 31641138 PMCID: PMC6805931 DOI: 10.1038/s41467-019-12693-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 09/23/2019] [Indexed: 12/19/2022] Open
Abstract
Interneurons (INs) coordinate motoneuron activity to generate appropriate patterns of muscle contractions, providing animals with the ability to adjust their body posture and to move over a range of speeds. In Drosophila larvae several IN subtypes have been morphologically described and their function well documented. However, the general lack of molecular characterization of those INs prevents the identification of evolutionary counterparts in other animals, limiting our understanding of the principles underlying neuronal circuit organization and function. Here we characterize a restricted subset of neurons in the nerve cord expressing the Maf transcription factor Traffic Jam (TJ). We found that TJ+ neurons are highly diverse and selective activation of these different subtypes disrupts larval body posture and induces specific locomotor behaviors. Finally, we show that a small subset of TJ+ GABAergic INs, singled out by the expression of a unique transcription factors code, controls larval crawling speed. Spinal interneurons (IN) coordinate motoneuron activity to modulate locomotion behavior. Here, the authors characterize a subset of IN subtypes expressing the Maf transcription factor Traffic Jam (TJ) and report the distinct effects of their activation on body posture and locomotion in Drosophila larvae.
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27
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Loveless J, Lagogiannis K, Webb B. Modelling the mechanics of exploration in larval Drosophila. PLoS Comput Biol 2019; 15:e1006635. [PMID: 31276489 PMCID: PMC6636753 DOI: 10.1371/journal.pcbi.1006635] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 07/17/2019] [Accepted: 11/08/2018] [Indexed: 12/03/2022] Open
Abstract
The Drosophila larva executes a stereotypical exploratory routine that appears to consist of stochastic alternation between straight peristaltic crawling and reorientation events through lateral bending. We present a model of larval mechanics for axial and transverse motion over a planar substrate, and use it to develop a simple, reflexive neuromuscular model from physical principles. The mechanical model represents the midline of the larva as a set of point masses which interact with each other via damped translational and torsional springs, and with the environment via sliding friction forces. The neuromuscular model consists of: 1. segmentally localised reflexes that amplify axial compression in order to counteract frictive energy losses, and 2. long-range mutual inhibition between reflexes in distant segments, enabling overall motion of the model larva relative to its substrate. In the absence of damping and driving, the mechanical model produces axial travelling waves, lateral oscillations, and unpredictable, chaotic deformations. The neuromuscular model counteracts friction to recover these motion patterns, giving rise to forward and backward peristalsis in addition to turning. Our model produces spontaneous exploration, even though the nervous system has no intrinsic pattern generating or decision making ability, and neither senses nor drives bending motions. Ultimately, our model suggests a novel view of larval exploration as a deterministic superdiffusion process which is mechanistically grounded in the chaotic mechanics of the body. We discuss how this may provide new interpretations for existing observations at the level of tissue-scale activity patterns and neural circuitry, and provide some experimental predictions that would test the extent to which the mechanisms we present translate to the real larva. We investigate the relationship between brain, body and environment in the exploratory behaviour of fruitfly larva. A larva crawls forward by propagating a wave of compression through its segmented body, and changes its crawling direction by bending to one side or the other. We show first that a purely mechanical model of the larva’s body can produce travelling compression waves, sideways bending, and unpredictable, chaotic motions. For this body to locomote through its environment, it is necessary to add a neuromuscular system to counteract the loss of energy due to friction, and to limit the simultaneous compression of segments. These simple additions allow our model larva to generate life-like forward and backward crawling as well as spontaneous turns, which occur without any direct sensing or control of reorientation. The unpredictability inherent in the larva’s physics causes the model to explore its environment, despite the lack of any neural mechanism for rhythm generation or for deciding when to switch from crawling to turning. Our model thus demonstrates how understanding body mechanics can generate and simplify neurobiological hypotheses as to how behaviour arises.
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Affiliation(s)
- Jane Loveless
- Institute for Perception, Action, and Behaviour, School of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Konstantinos Lagogiannis
- Institute for Perception, Action, and Behaviour, School of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- MRC Centre for Developmental Neurobiology, New Hunt’s House, King’s College London, London, United Kingdom
| | - Barbara Webb
- Institute for Perception, Action, and Behaviour, School of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- * E-mail:
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28
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Yoon Y, Park J, Taniguchi A, Kohsaka H, Nakae K, Nonaka S, Ishii S, Nose A. System level analysis of motor-related neural activities in larval Drosophila. J Neurogenet 2019; 33:179-189. [PMID: 31172848 DOI: 10.1080/01677063.2019.1605365] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
The way in which the central nervous system (CNS) governs animal movement is complex and difficult to solve solely by the analyses of muscle movement patterns. We tackle this problem by observing the activity of a large population of neurons in the CNS of larval Drosophila. We focused on two major behaviors of the larvae - forward and backward locomotion - and analyzed the neuronal activity related to these behaviors during the fictive locomotion that occurs spontaneously in the isolated CNS. We expressed a genetically-encoded calcium indicator, GCaMP and a nuclear marker in all neurons and then used digitally scanned light-sheet microscopy to record (at a fast frame rate) neural activities in the entire ventral nerve cord (VNC). We developed image processing tools that automatically detected the cell position based on the nuclear staining and allocate the activity signals to each detected cell. We also applied a machine learning-based method that we recently developed to assign motor status in each time frame. Our experimental procedures and computational pipeline enabled systematic identification of neurons that showed characteristic motor activities in larval Drosophila. We found cells whose activity was biased toward forward locomotion and others biased toward backward locomotion. In particular, we identified neurons near the boundary of the subesophageal zone (SEZ) and thoracic neuromeres, which were strongly active during an early phase of backward but not forward fictive locomotion.
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Affiliation(s)
- Youngteak Yoon
- a Department of Physics, Graduate School of Science , University of Tokyo , Tokyo , Japan
| | - Jeonghyuk Park
- a Department of Physics, Graduate School of Science , University of Tokyo , Tokyo , Japan
| | - Atsushi Taniguchi
- b Laboratory for Spatiotemporal Regulations , National Institute for Basic Biology , Aichi , Japan
| | - Hiroshi Kohsaka
- c Department of Complexity Science and Engineering , University of Tokyo , Chiba , Japan
| | - Ken Nakae
- d Graduate School of Informatics , Kyoto University , Kyoto , Japan
| | - Shigenori Nonaka
- b Laboratory for Spatiotemporal Regulations , National Institute for Basic Biology , Aichi , Japan
| | - Shin Ishii
- d Graduate School of Informatics , Kyoto University , Kyoto , Japan.,e ATR Cognitive Mechanisms Laboratories , Kyoto , Japan
| | - Akinao Nose
- a Department of Physics, Graduate School of Science , University of Tokyo , Tokyo , Japan.,c Department of Complexity Science and Engineering , University of Tokyo , Chiba , Japan
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29
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Jovanic T, Winding M, Cardona A, Truman JW, Gershow M, Zlatic M. Neural Substrates of Drosophila Larval Anemotaxis. Curr Biol 2019; 29:554-566.e4. [PMID: 30744969 PMCID: PMC6380933 DOI: 10.1016/j.cub.2019.01.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 11/29/2018] [Accepted: 01/04/2019] [Indexed: 01/08/2023]
Abstract
Animals use sensory information to move toward more favorable conditions. Drosophila larvae can move up or down gradients of odors (chemotax), light (phototax), and temperature (thermotax) by modulating the probability, direction, and size of turns based on sensory input. Whether larvae can anemotax in gradients of mechanosensory cues is unknown. Further, although many of the sensory neurons that mediate taxis have been described, the central circuits are not well understood. Here, we used high-throughput, quantitative behavioral assays to demonstrate Drosophila larvae anemotax in gradients of wind speeds and to characterize the behavioral strategies involved. We found that larvae modulate the probability, direction, and size of turns to move away from higher wind speeds. This suggests that similar central decision-making mechanisms underlie taxis in somatosensory and other sensory modalities. By silencing the activity of single or very few neuron types in a behavioral screen, we found two sensory (chordotonal and multidendritic class III) and six nerve cord neuron types involved in anemotaxis. We reconstructed the identified neurons in an electron microscopy volume that spans the entire larval nervous system and found they received direct input from the mechanosensory neurons or from each other. In this way, we identified local interneurons and first- and second-order subesophageal zone (SEZ) and brain projection neurons. Finally, silencing a dopaminergic brain neuron type impairs anemotaxis. These findings suggest that anemotaxis involves both nerve cord and brain circuits. The candidate neurons and circuitry identified in our study provide a basis for future detailed mechanistic understanding of the circuit principles of anemotaxis.
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Affiliation(s)
- Tihana Jovanic
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
| | - Michael Winding
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Department of Physiology, Development, and Neuroscience, Cambridge University, Cambridge, UK
| | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Friday Harbor Laboratories, University of Washington, Friday Harbor, WA 98250, USA
| | - Marc Gershow
- Department of Physics, New York University, New York, NY, USA; Center for Neural Science, New York University, New York, NY, USA; Neuroscience Institute, New York University, New York, NY, USA.
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Department of Zoology, Cambridge University, Cambridge, UK.
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30
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Connectomics and function of a memory network: the mushroom body of larval Drosophila. Curr Opin Neurobiol 2018; 54:146-154. [PMID: 30368037 DOI: 10.1016/j.conb.2018.10.007] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 10/04/2018] [Indexed: 11/20/2022]
Abstract
The Drosophila larva is a relatively simple, 10 000-neuron study case for learning and memory with enticing analytical power, combining genetic tractability, the availability of robust behavioral assays, the opportunity for single-cell transgenic manipulation, and an emerging synaptic connectome of its complete central nervous system. Indeed, although the insect mushroom body is a much-studied memory network, the connectome revealed that more than half of the classes of connection within the mushroom body had escaped attention. The connectome also revealed circuitry that integrates, both within and across brain hemispheres, higher-order sensory input, intersecting valence signals, and output neurons that instruct behavior. Further, it was found that activating individual dopaminergic mushroom body input neurons can have a rewarding or a punishing effect on olfactory stimuli associated with it, depending on the relative timing of this activation, and that larvae form molecularly dissociable short-term, long-term, and amnesia-resistant memories. Together, the larval mushroom body is a suitable study case to achieve a nuanced account of molecular function in a behaviorally meaningful memory network.
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31
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Abstract
Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light.
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32
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The sulfite oxidase Shopper controls neuronal activity by regulating glutamate homeostasis in Drosophila ensheathing glia. Nat Commun 2018; 9:3514. [PMID: 30158546 PMCID: PMC6115356 DOI: 10.1038/s41467-018-05645-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 07/13/2018] [Indexed: 01/01/2023] Open
Abstract
Specialized glial subtypes provide support to developing and functioning neural networks. Astrocytes modulate information processing by neurotransmitter recycling and release of neuromodulatory substances, whereas ensheathing glial cells have not been associated with neuromodulatory functions yet. To decipher a possible role of ensheathing glia in neuronal information processing, we screened for glial genes required in the Drosophila central nervous system for normal locomotor behavior. Shopper encodes a mitochondrial sulfite oxidase that is specifically required in ensheathing glia to regulate head bending and peristalsis. shopper mutants show elevated sulfite levels affecting the glutamate homeostasis which then act on neuronal network function. Interestingly, human patients lacking the Shopper homolog SUOX develop neurological symptoms, including seizures. Given an enhanced expression of SUOX by oligodendrocytes, our findings might indicate that in both invertebrates and vertebrates more than one glial cell type may be involved in modulating neuronal activity.
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33
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Goldammer J, Mantziaris C, Büschges A, Schmidt J. Calcium imaging of CPG-evoked activity in efferent neurons of the stick insect. PLoS One 2018; 13:e0202822. [PMID: 30142206 PMCID: PMC6108493 DOI: 10.1371/journal.pone.0202822] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Accepted: 08/09/2018] [Indexed: 12/11/2022] Open
Abstract
The stick insect is a well-established experimental animal to study the neural basis of walking. Here, we introduce a preparation that allows combining calcium imaging in efferent neurons with electrophysiological recordings of motor neuron activity in the stick insect thoracic nerve cord. The intracellular free calcium concentration in middle leg retractor coxae motor neurons and modulatory octopaminergic DUM neurons was monitored after backfilling lateral nerve nl5 that contains the axons of these neurons with the calcium indicator Oregon Green BAPTA-1. Rhythmic spike activity in retractor and protractor motor neurons was evoked by pharmacological activation of central pattern generating neuronal networks and recorded extracellularly from lateral nerves. A primary goal of this study was to investigate whether changes in the intracellular free calcium concentration observed in motor neurons during oscillatory activity depend on action potentials. We show that rhythmic spike activity in leg motor neurons induced either pharmacologically or by tactile stimulation of the animal is accompanied by a synchronous modulation in the intracellular free calcium concentration. Calcium oscillations in motor neurons do not appear to depend on calcium influx through voltage-sensitive calcium channels that are gated by action potentials because Calcium oscillations persist after pharmacologically blocking action potentials in the motor neurons. Calcium oscillations were also apparent in the modulatory DUM neurons innervating the same leg muscle. However, the timing of calcium oscillations varied not only between DUM neurons and motor neurons, but also among different DUM neurons. Therefore, we conclude that the motor neurons and the different DUM neurons receive independent central drive.
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Affiliation(s)
- Jens Goldammer
- Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
| | - Charalampos Mantziaris
- Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
| | - Ansgar Büschges
- Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
| | - Joachim Schmidt
- Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
- * E-mail:
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34
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Carreira-Rosario A, Zarin AA, Clark MQ, Manning L, Fetter RD, Cardona A, Doe CQ. MDN brain descending neurons coordinately activate backward and inhibit forward locomotion. eLife 2018; 7:38554. [PMID: 30070205 PMCID: PMC6097840 DOI: 10.7554/elife.38554] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 07/28/2018] [Indexed: 01/04/2023] Open
Abstract
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 Drosophila 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. When we choose to make one kind of movement, it often prevents us making another. We cannot move forward and backward at the same time, for example, and a horse cannot simultaneously gallop and walk. These ‘antagonistic’ behaviors often use the same group of muscles, but the muscles contract in a different order. This requires exquisite control over muscle contractions. Neurons located in the central nervous system form circuits to produce distinct patterns of muscle contractions and to switch between these patterns. Smooth, rapid switching between behaviors is important for animal escape and survival, as well as for performing fine movements. However, we know little about how the activity of the neuronal circuits enables this. Carreira-Rosario, Zarin, Clark et al. set out to identify the underlying neuronal circuitry that allows larval fruit flies to transition between crawling forward and backward. Results from a combination of genetics and microscopy techniques revealed that a neuron called the Mooncrawler Descending Neuron (MDN) induces a switch from forward to backward travel. MDN activates a neuron that stops the larvae crawling forward, and at the same time activates a different neuron that is only active when the larvae crawl backward. Carreira-Rosario et al. also found that MDN triggers backward crawling in the six-limbed adult fly. Understanding how a single neuron – in this case MDN – can trigger a smooth switch between opposing behaviors could be beneficial for the medical and robotics fields. In the medical field, understanding how movement is generated could help to improve therapies that fix damage to the relevant neuronal circuits. Understanding how behavioral transitions occur may also help to design autonomous robots that can navigate complex terrain.
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Affiliation(s)
- Arnaldo Carreira-Rosario
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Aref Arzan Zarin
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Matthew Q Clark
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Laurina Manning
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Richard D Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Chris Q Doe
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
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35
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Park J, Kondo S, Tanimoto H, Kohsaka H, Nose A. Data-driven analysis of motor activity implicates 5-HT2A neurons in backward locomotion of larval Drosophila. Sci Rep 2018; 8:10307. [PMID: 29985473 PMCID: PMC6037780 DOI: 10.1038/s41598-018-28680-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 06/27/2018] [Indexed: 01/16/2023] Open
Abstract
Rhythmic animal behaviors are regulated in part by neural circuits called the central pattern generators (CPGs). Classifying neural population activities correlated with body movements and identifying the associated component neurons are critical steps in understanding CPGs. Previous methods that classify neural dynamics obtained by dimension reduction algorithms often require manual optimization which could be laborious and preparation-specific. Here, we present a simpler and more flexible method that is based on the pre-trained convolutional neural network model VGG-16 and unsupervised learning, and successfully classifies the fictive motor patterns in Drosophila larvae under various imaging conditions. We also used voxel-wise correlation mapping to identify neurons associated with motor patterns. By applying these methods to neurons targeted by 5-HT2A-GAL4, which we generated by the CRISPR/Cas9-system, we identified two classes of interneurons, termed Seta and Leta, which are specifically active during backward but not forward fictive locomotion. Optogenetic activation of Seta and Leta neurons increased backward locomotion. Conversely, thermogenetic inhibition of 5-HT2A-GAL4 neurons or application of a 5-HT2 antagonist decreased backward locomotion induced by noxious light stimuli. This study establishes an accelerated pipeline for activity profiling and cell identification in larval Drosophila and implicates the serotonergic system in the modulation of backward locomotion.
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Affiliation(s)
- Jeonghyuk Park
- Department of Physics, Graduate School of Science, University of Tokyo, Tokyo, 113-0033, Japan
| | - Shu Kondo
- Invertebrate Genetics Laboratory, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
| | - Hiromu Tanimoto
- Graduate School of Life Sciences, Tohoku University, Sendai, 980-8577, Japan
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, University of Tokyo, Chiba, 277-8561, Japan
| | - Akinao Nose
- Department of Physics, Graduate School of Science, University of Tokyo, Tokyo, 113-0033, Japan.
- Department of Complexity Science and Engineering, University of Tokyo, Chiba, 277-8561, Japan.
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36
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Clark MQ, Zarin AA, Carreira-Rosario A, Doe CQ. Neural circuits driving larval locomotion in Drosophila. Neural Dev 2018; 13:6. [PMID: 29673388 PMCID: PMC5907184 DOI: 10.1186/s13064-018-0103-z] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Accepted: 04/05/2018] [Indexed: 11/10/2022] Open
Abstract
More than 30 years of studies into Drosophila melanogaster neurogenesis have revealed fundamental insights into our understanding of axon guidance mechanisms, neural differentiation, and early cell fate decisions. What is less understood is how a group of neurons from disparate anterior-posterior axial positions, lineages and developmental periods of neurogenesis coalesce to form a functional circuit. Using neurogenetic techniques developed in Drosophila it is now possible to study the neural substrates of behavior at single cell resolution. New mapping tools described in this review, allow researchers to chart neural connectivity to better understand how an anatomically simple organism performs complex behaviors.
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Affiliation(s)
- Matthew Q Clark
- Institute of Neuroscience, Institute of Molecular Biology, Howard Hughes Medical Institute, University of Oregon, Eugene, OR, 97403, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasedena, CA, 91125, USA
| | - Aref Arzan Zarin
- Institute of Neuroscience, Institute of Molecular Biology, Howard Hughes Medical Institute, University of Oregon, Eugene, OR, 97403, USA
| | | | - Chris Q Doe
- Institute of Neuroscience, Institute of Molecular Biology, Howard Hughes Medical Institute, University of Oregon, Eugene, OR, 97403, USA.
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37
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Widmann A, Eichler K, Selcho M, Thum AS, Pauls D. Odor-taste learning in Drosophila larvae. JOURNAL OF INSECT PHYSIOLOGY 2018; 106:47-54. [PMID: 28823531 DOI: 10.1016/j.jinsphys.2017.08.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 08/07/2017] [Accepted: 08/16/2017] [Indexed: 06/07/2023]
Abstract
The Drosophila larva is an attractive model system to study fundamental questions in the field of neuroscience. Like the adult fly, the larva offers a seemingly unlimited genetic toolbox, which allows one to visualize, silence or activate neurons down to the single cell level. This, combined with its simplicity in terms of cell numbers, offers a useful system to study the neuronal correlates of complex processes including associative odor-taste learning and memory formation. Here, we summarize the current knowledge about odor-taste learning and memory at the behavioral level and integrate the recent progress on the larval connectome to shed light on the sub-circuits that allow Drosophila larvae to integrate present sensory input in the context of past experience and to elicit an appropriate behavioral response.
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Affiliation(s)
| | - Katharina Eichler
- Department of Biology, University of Konstanz, D-78464 Konstanz, Germany; HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Mareike Selcho
- Department of Neurobiology and Genetics, Theodor-Boveri-Institute, Biocenter, University of Würzburg, D-97074 Würzburg, Germany
| | - Andreas S Thum
- Department of Biology, University of Konstanz, D-78464 Konstanz, Germany; Department of Genetics, University of Leipzig, D-04103 Leipzig, Germany.
| | - Dennis Pauls
- Department of Neurobiology and Genetics, Theodor-Boveri-Institute, Biocenter, University of Würzburg, D-97074 Würzburg, Germany.
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38
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Schlegel P, Costa M, Jefferis GS. Learning from connectomics on the fly. CURRENT OPINION IN INSECT SCIENCE 2017; 24:96-105. [PMID: 29208230 DOI: 10.1016/j.cois.2017.09.011] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 09/18/2017] [Accepted: 09/19/2017] [Indexed: 06/07/2023]
Abstract
Parallels between invertebrates and vertebrates in nervous system development, organisation and circuits are powerful reasons to use insects to study the mechanistic basis of behaviour. The last few years have seen the generation in Drosophila melanogaster of very large light microscopy data sets, genetic driver lines and tools to report or manipulate neural activity. These resources in conjunction with computational tools are enabling large scale characterisation of neuronal types and their functional properties. These are complemented by 3D electron microscopy, providing synaptic resolution data. A whole brain connectome of the fly larva is approaching completion based on manual reconstruction of electron-microscopy data. An adult whole brain dataset is already publicly available and focussed reconstruction is under way, but its 40× greater volume would require ∼500-5000 person-years of manual labour. Nevertheless rapid technical improvements in imaging and especially automated segmentation will likely deliver a complete adult connectome in the next 5 years. To enhance our understanding of the circuit basis of behaviour, light and electron microscopy outputs must be integrated with functional and physiological information into comprehensive databases. We review presently available data, tools and opportunities in Drosophila. We then consider the limits and potential of future progress and how this may impact neuroscience in rich model systems provided by larger insects and vertebrates.
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Affiliation(s)
- Philipp Schlegel
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
| | - Gregory Sxe Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
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39
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Takagi S, Cocanougher BT, Niki S, Miyamoto D, Kohsaka H, Kazama H, Fetter RD, Truman JW, Zlatic M, Cardona A, Nose A. Divergent Connectivity of Homologous Command-like Neurons Mediates Segment-Specific Touch Responses in Drosophila. Neuron 2017; 96:1373-1387.e6. [PMID: 29198754 DOI: 10.1016/j.neuron.2017.10.030] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 09/23/2017] [Accepted: 10/24/2017] [Indexed: 10/18/2022]
Abstract
Animals adaptively respond to a tactile stimulus by choosing an ethologically relevant behavior depending on the location of the stimuli. Here, we investigate how somatosensory inputs on different body segments are linked to distinct motor outputs in Drosophila larvae. Larvae escape by backward locomotion when touched on the head, while they crawl forward when touched on the tail. We identify a class of segmentally repeated second-order somatosensory interneurons, that we named Wave, whose activation in anterior and posterior segments elicit backward and forward locomotion, respectively. Anterior and posterior Wave neurons extend their dendrites in opposite directions to receive somatosensory inputs from the head and tail, respectively. Downstream of anterior Wave neurons, we identify premotor circuits including the neuron A03a5, which together with Wave, is necessary for the backward locomotion touch response. Thus, Wave neurons match their receptive field to appropriate motor programs by participating in different circuits in different segments.
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Affiliation(s)
- Suguru Takagi
- Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
| | | | - Sawako Niki
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan
| | - Dohjin Miyamoto
- Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan
| | - Hokto Kazama
- RIKEN Brain Science Institute, Saitama 351-0198, Japan
| | - Richard Doty Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - James William Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Akinao Nose
- Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan.
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40
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Gerhard S, Andrade I, Fetter RD, Cardona A, Schneider-Mizell CM. Conserved neural circuit structure across Drosophila larval development revealed by comparative connectomics. eLife 2017; 6:e29089. [PMID: 29058674 PMCID: PMC5662290 DOI: 10.7554/elife.29089] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Accepted: 10/22/2017] [Indexed: 11/14/2022] Open
Abstract
During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. Previously , we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila (Schneider-Mizell et al., 2016). Here, we examined how neuronal morphology and connectivity change between first instar and third instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell type-specific connectivity changes that preserved the fraction of total synaptic input associated with each pre-synaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.
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Affiliation(s)
- Stephan Gerhard
- Janelia Research CampusHoward Hughes Medical InstituteAshburnUnited States
| | - Ingrid Andrade
- Janelia Research CampusHoward Hughes Medical InstituteAshburnUnited States
| | - Richard D Fetter
- Janelia Research CampusHoward Hughes Medical InstituteAshburnUnited States
| | - Albert Cardona
- Janelia Research CampusHoward Hughes Medical InstituteAshburnUnited States
- Department of Physiology, Development and NeuroscienceUniversity of CambridgeCambridgeUnited Kingdom
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41
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Eichler K, Li F, Litwin-Kumar A, Park Y, Andrade I, Schneider-Mizell CM, Saumweber T, Huser A, Eschbach C, Gerber B, Fetter RD, Truman JW, Priebe CE, Abbott LF, Thum AS, Zlatic M, Cardona A. The complete connectome of a learning and memory centre in an insect brain. Nature 2017; 548:175-182. [PMID: 28796202 PMCID: PMC5806122 DOI: 10.1038/nature23455] [Citation(s) in RCA: 275] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 07/04/2017] [Indexed: 12/19/2022]
Abstract
Associating stimuli with positive or negative reinforcement is essential for survival, but a complete wiring diagram of a higher-order circuit supporting associative memory has not been previously available. Here we reconstruct one such circuit at synaptic resolution, the Drosophila larval mushroom body. We find that most Kenyon cells integrate random combinations of inputs but that a subset receives stereotyped inputs from single projection neurons. This organization maximizes performance of a model output neuron on a stimulus discrimination task. We also report a novel canonical circuit in each mushroom body compartment with previously unidentified connections: reciprocal Kenyon cell to modulatory neuron connections, modulatory neuron to output neuron connections, and a surprisingly high number of recurrent connections between Kenyon cells. Stereotyped connections found between output neurons could enhance the selection of learned behaviours. The complete circuit map of the mushroom body should guide future functional studies of this learning and memory centre.
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Affiliation(s)
- Katharina Eichler
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
- Department of Biology, University of Konstanz, Universitätsstrasse 10, 78464 Konstanz, Germany
| | - Feng Li
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Ashok Litwin-Kumar
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, New York 10027, USA
| | - Youngser Park
- Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, 100 Whitehead Hall, 3400 North Charles Street, Baltimore, Maryland 21218, USA
| | - Ingrid Andrade
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Casey M Schneider-Mizell
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Timo Saumweber
- Abteilung Genetik von Lernen und Gedächtnis, Leibniz Institut für Neurobiologie, 39118 Magdeburg, Germany
| | - Annina Huser
- Department of Biology, University of Konstanz, Universitätsstrasse 10, 78464 Konstanz, Germany
| | - Claire Eschbach
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Bertram Gerber
- Abteilung Genetik von Lernen und Gedächtnis, Leibniz Institut für Neurobiologie, 39118 Magdeburg, Germany
- Otto von Guericke Universität Magdeburg, Institut für Biologie, Verhaltensgenetik, Universitätsplatz 2, D-39106 Magdeburg, Germany
- Otto-von-Guericke University Magdeburg, Center for Behavioral Brain Sciences, Universitätsplatz 2, D-39106 Magdeburg, Germany
| | - Richard D Fetter
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - James W Truman
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Carey E Priebe
- Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, 100 Whitehead Hall, 3400 North Charles Street, Baltimore, Maryland 21218, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, New York 10027, USA
- Department of Physiology and Cellular Biophysics, Columbia University, Russ Berrie Pavilion, 1150 St Nicholas Avenue, New York, New York 10032, USA
| | - Andreas S Thum
- Department of Biology, University of Konstanz, Universitätsstrasse 10, 78464 Konstanz, Germany
| | - Marta Zlatic
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Albert Cardona
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
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42
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Almeida-Carvalho MJ, Berh D, Braun A, Chen YC, Eichler K, Eschbach C, Fritsch PMJ, Gerber B, Hoyer N, Jiang X, Kleber J, Klämbt C, König C, Louis M, Michels B, Miroschnikow A, Mirth C, Miura D, Niewalda T, Otto N, Paisios E, Pankratz MJ, Petersen M, Ramsperger N, Randel N, Risse B, Saumweber T, Schlegel P, Schleyer M, Soba P, Sprecher SG, Tanimura T, Thum AS, Toshima N, Truman JW, Yarali A, Zlatic M. The Ol1mpiad: concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae. J Exp Biol 2017; 220:2452-2475. [DOI: 10.1242/jeb.156646] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 05/03/2017] [Indexed: 12/25/2022]
Abstract
ABSTRACT
Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva – because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol1mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour–taste associative learning, as well as light/dark–electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages.
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Affiliation(s)
| | - Dimitri Berh
- Institute of Neurobiology and Behavioural Biology, University of Münster, 48149 Münster, Germany
- Department of Mathematics and Computer Science, University of Münster, 48149 Münster, Germany
| | - Andreas Braun
- EMBL/CRG Systems Biology Unit, Centre for Genomic Regulation, 08003 Barcelona, Spain
- Universitat Pompeu Fabra, 08002 Barcelona, Spain
| | - Yi-chun Chen
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | - Katharina Eichler
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Claire Eschbach
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | | | - Bertram Gerber
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
- Institute of Biology, Otto von Guericke University Magdeburg, 39118 Magdeburg, Germany
- Center for Behavioral Brain Sciences, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany
| | - Nina Hoyer
- Center for Molecular Neurobiology, University of Hamburg, 20251 Hamburg, Germany
| | - Xiaoyi Jiang
- Department of Mathematics and Computer Science, University of Münster, 48149 Münster, Germany
| | - Jörg Kleber
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | - Christian Klämbt
- Institute of Neurobiology and Behavioural Biology, University of Münster, 48149 Münster, Germany
| | - Christian König
- Leibniz Institute for Neurobiology (Molecular Systems Biology), 39118 Magdeburg, Germany
- Institute of Pharmacology and Toxicology, Otto von Guericke University Magdeburg, 39118 Magdeburg, Germany
| | - Matthieu Louis
- EMBL/CRG Systems Biology Unit, Centre for Genomic Regulation, 08003 Barcelona, Spain
- Universitat Pompeu Fabra, 08002 Barcelona, Spain
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA 93117, USA
| | - Birgit Michels
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | | | - Christen Mirth
- Gulbenkian Institute of Science, 2780-156 Oeiras, Portugal
- School of Biological Sciences, Monash University, Melbourne, VIC 3800, Australia
| | - Daisuke Miura
- Department of Biology, Kyushu University, 819-0395 Fukuoka, Japan
| | - Thomas Niewalda
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | - Nils Otto
- Institute of Neurobiology and Behavioural Biology, University of Münster, 48149 Münster, Germany
| | - Emmanouil Paisios
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | | | - Meike Petersen
- Center for Molecular Neurobiology, University of Hamburg, 20251 Hamburg, Germany
| | - Noel Ramsperger
- Department of Biology, University of Konstanz, 78464 Konstanz, Germany
| | - Nadine Randel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Benjamin Risse
- Institute of Neurobiology and Behavioural Biology, University of Münster, 48149 Münster, Germany
- Department of Mathematics and Computer Science, University of Münster, 48149 Münster, Germany
| | - Timo Saumweber
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | | | - Michael Schleyer
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
| | - Peter Soba
- Center for Molecular Neurobiology, University of Hamburg, 20251 Hamburg, Germany
| | - Simon G. Sprecher
- Department of Biology, University of Fribourg, 1700 Fribourg, Switzerland
| | - Teiichi Tanimura
- Department of Biology, Kyushu University, 819-0395 Fukuoka, Japan
| | - Andreas S. Thum
- Department of Biology, University of Konstanz, 78464 Konstanz, Germany
| | - Naoko Toshima
- Leibniz Institute for Neurobiology (Genetics), 39118 Magdeburg, Germany
- Department of Biology, Kyushu University, 819-0395 Fukuoka, Japan
| | - Jim W. Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
- Friday Harbor Laboratories, University of Washington, Friday Harbor, WA 98250, USA
| | - Ayse Yarali
- Center for Behavioral Brain Sciences, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany
- Leibniz Institute for Neurobiology (Molecular Systems Biology), 39118 Magdeburg, Germany
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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43
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Michels B, Saumweber T, Biernacki R, Thum J, Glasgow RDV, Schleyer M, Chen YC, Eschbach C, Stocker RF, Toshima N, Tanimura T, Louis M, Arias-Gil G, Marescotti M, Benfenati F, Gerber B. Pavlovian Conditioning of Larval Drosophila: An Illustrated, Multilingual, Hands-On Manual for Odor-Taste Associative Learning in Maggots. Front Behav Neurosci 2017; 11:45. [PMID: 28469564 PMCID: PMC5395560 DOI: 10.3389/fnbeh.2017.00045] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Accepted: 02/27/2017] [Indexed: 01/25/2023] Open
Abstract
Larval Drosophila offer a study case for behavioral neurogenetics that is simple enough to be experimentally tractable, yet complex enough to be worth the effort. We provide a detailed, hands-on manual for Pavlovian odor-reward learning in these animals. Given the versatility of Drosophila for genetic analyses, combined with the evolutionarily shared genetic heritage with humans, the paradigm has utility not only in behavioral neurogenetics and experimental psychology, but for translational biomedicine as well. Together with the upcoming total synaptic connectome of the Drosophila nervous system and the possibilities of single-cell-specific transgene expression, it offers enticing opportunities for research. Indeed, the paradigm has already been adopted by a number of labs and is robust enough to be used for teaching in classroom settings. This has given rise to a demand for a detailed, hands-on manual directed at newcomers and/or at laboratory novices, and this is what we here provide. The paradigm and the present manual have a unique set of features: The present manual can thus foster science education at an earlier age and enable research by a broader community than has been the case to date.
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Affiliation(s)
- Birgit Michels
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany
| | - Timo Saumweber
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany
| | - Roland Biernacki
- Department Neurobiology and Genetics, Julius Maximilians UniversityWürzburg, Germany
| | - Jeanette Thum
- Department Neurobiology and Genetics, Julius Maximilians UniversityWürzburg, Germany
| | - Rupert D V Glasgow
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany
| | - Michael Schleyer
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany
| | - Yi-Chun Chen
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany
| | | | | | - Naoko Toshima
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany
| | | | - Matthieu Louis
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa BarbaraSanta Barbara, CA, USA
| | - Gonzalo Arias-Gil
- Department Systems Physiology, Leibniz Institute for Neurobiology MagdeburgMagdeburg, Germany
| | | | - Fabio Benfenati
- Italian Institute of Technology, Center for Synaptic Neuroscience and TechnologyGenova, Italy
| | - Bertram Gerber
- Department of Genetics, Leibniz Institute for NeurobiologyMagdeburg, Germany.,Institute of Biology, Otto von Guericke UniversityMagdeburg, Germany.,Center for Behavioral Brain SciencesMagdeburg, Germany
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44
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Newman ZL, Hoagland A, Aghi K, Worden K, Levy SL, Son JH, Lee LP, Isacoff EY. Input-Specific Plasticity and Homeostasis at the Drosophila Larval Neuromuscular Junction. Neuron 2017; 93:1388-1404.e10. [PMID: 28285823 DOI: 10.1016/j.neuron.2017.02.028] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 12/18/2016] [Accepted: 02/15/2017] [Indexed: 11/28/2022]
Abstract
Synaptic connections undergo activity-dependent plasticity during development and learning, as well as homeostatic re-adjustment to ensure stability. Little is known about the relationship between these processes, particularly in vivo. We addressed this with novel quantal resolution imaging of transmission during locomotive behavior at glutamatergic synapses of the Drosophila larval neuromuscular junction. We find that two motor input types, Ib and Is, provide distinct forms of excitatory drive during crawling and differ in key transmission properties. Although both inputs vary in transmission probability, active Is synapses are more reliable. High-frequency firing "wakes up" silent Ib synapses and depresses Is synapses. Strikingly, homeostatic compensation in presynaptic strength only occurs at Ib synapses. This specialization is associated with distinct regulation of postsynaptic CaMKII. Thus, basal synaptic strength, short-term plasticity, and homeostasis are determined input-specifically, generating a functional diversity that sculpts excitatory transmission and behavioral function.
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Affiliation(s)
- Zachary L Newman
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Adam Hoagland
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Krishan Aghi
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Kurtresha Worden
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Sabrina L Levy
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Jun Ho Son
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Berkeley Sensor and Actuator Center, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Luke P Lee
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Berkeley Sensor and Actuator Center, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA; Biomedical Institute for Global Health Research and Technology, National University of Singapore, 119077 Singapore, Singapore
| | - Ehud Y Isacoff
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Bioscience Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
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45
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Schwarz O, Bohra AA, Liu X, Reichert H, VijayRaghavan K, Pielage J. Motor control of Drosophila feeding behavior. eLife 2017; 6:e19892. [PMID: 28211791 PMCID: PMC5315463 DOI: 10.7554/elife.19892] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 02/02/2017] [Indexed: 12/01/2022] Open
Abstract
The precise coordination of body parts is essential for survival and behavior of higher organisms. While progress has been made towards the identification of central mechanisms coordinating limb movement, only limited knowledge exists regarding the generation and execution of sequential motor action patterns at the level of individual motoneurons. Here we use Drosophila proboscis extension as a model system for a reaching-like behavior. We first provide a neuroanatomical description of the motoneurons and muscles contributing to proboscis motion. Using genetic targeting in combination with artificial activation and silencing assays we identify the individual motoneurons controlling the five major sequential steps of proboscis extension and retraction. Activity-manipulations during naturally evoked proboscis extension show that orchestration of serial motoneuron activation does not rely on feed-forward mechanisms. Our data support a model in which central command circuits recruit individual motoneurons to generate task-specific proboscis extension sequences.
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Affiliation(s)
- Olivia Schwarz
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- Biozentrum University of Basel, Basel, Switzerland
- Division of Zoology and Neurobiology, Technical University Kaiserslautern, Kaiserslautern, Germany
| | - Ali Asgar Bohra
- National Centre for Biological Sciences, Tata Institute for Fundamental Research, Bangalore, India
| | - Xinyu Liu
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- Biozentrum University of Basel, Basel, Switzerland
| | | | | | - Jan Pielage
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- Biozentrum University of Basel, Basel, Switzerland
- Division of Zoology and Neurobiology, Technical University Kaiserslautern, Kaiserslautern, Germany
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Kohsaka H, Guertin PA, Nose A. Neural Circuits Underlying Fly Larval Locomotion. Curr Pharm Des 2017; 23:1722-1733. [PMID: 27928962 PMCID: PMC5470056 DOI: 10.2174/1381612822666161208120835] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 12/01/2016] [Indexed: 12/17/2022]
Abstract
Locomotion is a complex motor behavior that may be expressed in different ways using a variety of strategies depending upon species and pathological or environmental conditions. Quadrupedal or bipedal walking, running, swimming, flying and gliding constitute some of the locomotor modes enabling the body, in all cases, to move from one place to another. Despite these apparent differences in modes of locomotion, both vertebrate and invertebrate species share, at least in part, comparable neural control mechanisms for locomotor rhythm and pattern generation and modulation. Significant advances have been made in recent years in studies of the genetic aspects of these control systems. Findings made specifically using Drosophila (fruit fly) models and preparations have contributed to further understanding of the key role of genes in locomotion. This review focuses on some of the main findings made in larval fruit flies while briefly summarizing the basic advantages of using this powerful animal model for studying the neural locomotor system.
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Affiliation(s)
- Hiroshi Kohsaka
- Department of Complexity Science and Engineering, University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
| | - Pierre A. Guertin
- Department of Psychiatry & Neurosciences, Laval University, Québec City, QC, Canada
| | - Akinao Nose
- Department of Complexity Science and Engineering, University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
- Department of Physics, Graduate School of Science, University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
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Wanner AA, Genoud C, Friedrich RW. 3-dimensional electron microscopic imaging of the zebrafish olfactory bulb and dense reconstruction of neurons. Sci Data 2016; 3:160100. [PMID: 27824337 PMCID: PMC5100684 DOI: 10.1038/sdata.2016.100] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 09/22/2016] [Indexed: 01/27/2023] Open
Abstract
Large-scale reconstructions of neuronal populations are critical for structural analyses of neuronal cell types and circuits. Dense reconstructions of neurons from image data require ultrastructural resolution throughout large volumes, which can be achieved by automated volumetric electron microscopy (EM) techniques. We used serial block face scanning EM (SBEM) and conductive sample embedding to acquire an image stack from an olfactory bulb (OB) of a zebrafish larva at a voxel resolution of 9.25×9.25×25 nm3. Skeletons of 1,022 neurons, 98% of all neurons in the OB, were reconstructed by manual tracing and efficient error correction procedures. An ergonomic software package, PyKNOSSOS, was created in Python for data browsing, neuron tracing, synapse annotation, and visualization. The reconstructions allow for detailed analyses of morphology, projections and subcellular features of different neuron types. The high density of reconstructions enables geometrical and topological analyses of the OB circuitry. Image data can be accessed and viewed through the neurodata web services (http://www.neurodata.io). Raw data and reconstructions can be visualized in PyKNOSSOS.
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Affiliation(s)
- Adrian A. Wanner
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
- University of Basel, 4003 Basel, Switzerland
| | - Christel Genoud
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - Rainer W. Friedrich
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
- University of Basel, 4003 Basel, Switzerland
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48
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Liu B, Bossing T. Single neuron transcriptomics identify SRSF/SR protein B52 as a regulator of axon growth and Choline acetyltransferase splicing. Sci Rep 2016; 6:34952. [PMID: 27725692 PMCID: PMC5057162 DOI: 10.1038/srep34952] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Accepted: 09/21/2016] [Indexed: 01/14/2023] Open
Abstract
We removed single identified neurons from living Drosophila embryos to gain insight into the transcriptional control of developing neuronal networks. The microarray analysis of the transcriptome of two sibling neurons revealed seven differentially expressed transcripts between both neurons (threshold: log21.4). One transcript encodes the RNA splicing factor B52. Loss of B52 increases growth of axon branches. B52 function is also required for Choline acetyltransferase (ChAT ) splicing. At the end of embryogenesis, loss of B52 function impedes splicing of ChAT, reduces acetylcholine synthesis, and extends the period of uncoordinated muscle twitches during larval hatching. ChAT regulation by SRSF proteins may be a conserved feature since changes in SRSF5 expression and increased acetylcholine levels in brains of bipolar disease patients have been reported recently.
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Affiliation(s)
- Boyin Liu
- School of Biological Sciences, Bangor University, Deiniol Road, Bangor LL57 2UW, U.K
| | - Torsten Bossing
- School of Biomedical and Healthcare Sciences, Plymouth University, John Bull Building, Plymouth, PL6 8BU, U.K
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