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Azevedo A, Lesser E, Phelps JS, Mark B, Elabbady L, Kuroda S, Sustar A, Moussa A, Khandelwal A, Dallmann CJ, Agrawal S, Lee SYJ, Pratt B, Cook A, Skutt-Kakaria K, Gerhard S, Lu R, Kemnitz N, Lee K, Halageri A, Castro M, Ih D, Gager J, Tammam M, Dorkenwald S, Collman F, Schneider-Mizell C, Brittain D, Jordan CS, Dickinson M, Pacureanu A, Seung HS, Macrina T, Lee WCA, Tuthill JC. Connectomic reconstruction of a female Drosophila ventral nerve cord. Nature 2024; 631:360-368. [PMID: 38926570 PMCID: PMC11348827 DOI: 10.1038/s41586-024-07389-x] [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: 06/02/2023] [Accepted: 04/04/2024] [Indexed: 06/28/2024]
Abstract
A deep understanding of how the brain controls behaviour requires mapping neural circuits down to the muscles that they control. Here, we apply automated tools to segment neurons and identify synapses in an electron microscopy dataset of an adult female Drosophila melanogaster ventral nerve cord (VNC)1, which functions like the vertebrate spinal cord to sense and control the body. We find that the fly VNC contains roughly 45 million synapses and 14,600 neuronal cell bodies. To interpret the output of the connectome, we mapped the muscle targets of leg and wing motor neurons using genetic driver lines2 and X-ray holographic nanotomography3. With this motor neuron atlas, we identified neural circuits that coordinate leg and wing movements during take-off. We provide the reconstruction of VNC circuits, the motor neuron atlas and tools for programmatic and interactive access as resources to support experimental and theoretical studies of how the nervous system controls behaviour.
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Affiliation(s)
- Anthony Azevedo
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Ellen Lesser
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Neuroengineering Laboratory, Brain Mind Institute and Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Brandon Mark
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Leila Elabbady
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Sumiya Kuroda
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Anne Sustar
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Anthony Moussa
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Avinash Khandelwal
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Chris J Dallmann
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Sweta Agrawal
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Su-Yee J Lee
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Brandon Pratt
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Andrew Cook
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | | | - Stephan Gerhard
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- UniDesign Solutions, Zurich, Switzerland
| | - Ran Lu
- Zetta AI, Sherrill, NJ, USA
| | | | - Kisuk Lee
- Zetta AI, Sherrill, NJ, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | | | | | | | | | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | | | | | | | - Chris S Jordan
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | | | | | | | - Wei-Chung Allen Lee
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
- F. M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA.
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Ehrhardt E, Whitehead SC, Namiki S, Minegishi R, Siwanowicz I, Feng K, Otsuna H, Meissner GW, Stern D, Truman J, Shepherd D, Dickinson MH, Ito K, Dickson BJ, Cohen I, Card GM, Korff W. Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.31.542897. [PMID: 37398009 PMCID: PMC10312520 DOI: 10.1101/2023.05.31.542897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their function. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse driver lines targeting 198 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neural circuits and connectivity of premotor circuits while linking them to behavioral outputs.
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Affiliation(s)
- Erica Ehrhardt
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Institute of Zoology, University of Cologne, Zülpicher Str 47b, 50674 Cologne, Germany
| | - Samuel C Whitehead
- Physics Department, Cornell University, 271 Clark Hall, Ithaca, New York 14853, USA
| | - Shigehiro Namiki
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Ryo Minegishi
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Igor Siwanowicz
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Kai Feng
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Queensland Brain Institute, University of Queensland, 79 Upland Rd, Brisbane, QLD, 4072, Australia
| | - Hideo Otsuna
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - FlyLight Project Team
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Geoffrey W Meissner
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - David Stern
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Jim Truman
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Department of Biology, University of Washington, Seattle, Washington 98195, USA
| | - David Shepherd
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Life Sciences Building, Southampton SO17 1BJ
| | - Michael H. Dickinson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- California Institute of Technology, 1200 E California Blvd, Pasadena, California 91125, USA
| | - Kei Ito
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Institute of Zoology, University of Cologne, Zülpicher Str 47b, 50674 Cologne, Germany
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Itai Cohen
- Physics Department, Cornell University, 271 Clark Hall, Ithaca, New York 14853, USA
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
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Hürkey S, Niemeyer N, Schleimer JH, Ryglewski S, Schreiber S, Duch C. Gap junctions desynchronize a neural circuit to stabilize insect flight. Nature 2023:10.1038/s41586-023-06099-0. [PMID: 37225999 DOI: 10.1038/s41586-023-06099-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/18/2023] [Indexed: 05/26/2023]
Abstract
Insect asynchronous flight is one of the most prevalent forms of animal locomotion used by more than 600,000 species. Despite profound insights into the motor patterns1, biomechanics2,3 and aerodynamics underlying asynchronous flight4,5, the architecture and function of the central-pattern-generating (CPG) neural network remain unclear. Here, on the basis of an experiment-theory approach including electrophysiology, optophysiology, Drosophila genetics and mathematical modelling, we identify a miniaturized circuit solution with unexpected properties. The CPG network consists of motoneurons interconnected by electrical synapses that, in contrast to doctrine, produce network activity splayed out in time instead of synchronized across neurons. Experimental and mathematical evidence support a generic mechanism for network desynchronization that relies on weak electrical synapses and specific excitability dynamics of the coupled neurons. In small networks, electrical synapses can synchronize or desynchronize network activity, depending on the neuron-intrinsic dynamics and ion channel composition. In the asynchronous flight CPG, this mechanism translates unpatterned premotor input into stereotyped neuronal firing with fixed sequences of cell activation that ensure stable wingbeat power and, as we show, is conserved across multiple species. Our findings prove a wider functional versatility of electrical synapses in the dynamic control of neural circuits and highlight the relevance of detecting electrical synapses in connectomics.
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Affiliation(s)
- Silvan Hürkey
- Institute of Developmental Biology and Neurobiology (iDN), Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Nelson Niemeyer
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | - Stefanie Ryglewski
- Institute of Developmental Biology and Neurobiology (iDN), Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Susanne Schreiber
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.
| | - Carsten Duch
- Institute of Developmental Biology and Neurobiology (iDN), Johannes Gutenberg-University Mainz, Mainz, Germany.
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Polarization-sensitive descending neurons in the locust: connecting the brain to thoracic ganglia. J Neurosci 2011; 31:2238-47. [PMID: 21307260 DOI: 10.1523/jneurosci.3624-10.2011] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Many animal species, in particular insects, exploit the E-vector pattern of the blue sky for sun compass navigation. Like other insects, locusts detect dorsal polarized light via photoreceptors in a specialized dorsal rim area of the compound eye. Polarized light information is transmitted through several processing stages to the central complex, a brain area involved in the control of goal-directed orientation behavior. To investigate how polarized light information is transmitted to thoracic motor circuits, we studied the responses of locust descending neurons to polarized light. Three sets of polarization-sensitive descending neurons were characterized through intracellular recordings from axonal fibers in the neck connectives combined with single-cell dye injections. Two descending neurons from the brain, one with ipsilaterally and the second with contralaterally descending axon, are likely to bridge the gap between polarization-sensitive neurons in the brain and thoracic motor centers. In both neurons, E-vector tuning changed linearly with daytime, suggesting that they signal time-compensated spatial directions, an important prerequisite for navigation using celestial signals. The third type connects the suboesophageal ganglion with the prothoracic ganglion. It showed no evidence for time compensation in E-vector tuning and might play a role in flight stabilization and control of head movements.
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Szpila K, Pape T, Rusinek A. Morphology of the first instar of Calliphora vicina, Phormia regina and Lucilia illustris (Diptera, Calliphoridae). MEDICAL AND VETERINARY ENTOMOLOGY 2008; 22:16-25. [PMID: 18380650 DOI: 10.1111/j.1365-2915.2008.00715.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Scanning electron microscopy documentation of first instar Calliphora vicina Robineau-Desvoidy, Phormia regina (Meigen) and Lucilia illustris (Meigen) (Diptera: Calliphoridae) is presented for the first time, and the following morphological structures are documented: pseudocephalon; antenna; maxillary palpus; facial mask; labial lobe; thoracic and abdominal spinulation; spiracular field; posterior spiracles, and anal pad. Light microscopy documentation and illustrations are provided for the cephaloskeleton in lateral and ventral views. New diagnostic features are revealed in the configuration of the facial mask, cephaloskeleton and posterior spiracles. The first instar morphology of C. vicina, Ph. regina and L. illustris is discussed in the light of existing knowledge about early instars of blowflies.
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Affiliation(s)
- K Szpila
- Department of Animal Ecology, Institute of Ecology and Environmental Protection, Nicolaus Copernicus University, Toruń, Poland.
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