1
|
Lesser E, Azevedo AW, Phelps JS, Elabbady L, Cook A, Syed DS, Mark B, Kuroda S, Sustar A, Moussa A, Dallmann CJ, Agrawal S, Lee SYJ, Pratt B, 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, Macrina T, Dickinson M, Lee WCA, Tuthill JC. Synaptic architecture of leg and wing premotor control networks in Drosophila. Nature 2024; 631:369-377. [PMID: 38926579 DOI: 10.1038/s41586-024-07600-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 05/23/2024] [Indexed: 06/28/2024]
Abstract
Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles1. MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours2-6. Here we use connectomics7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.
Collapse
Affiliation(s)
- Ellen Lesser
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Anthony W Azevedo
- 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
| | - Leila Elabbady
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Andrew Cook
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | | | - Brandon Mark
- 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
| | - 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
| | | | - Stephan Gerhard
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- UniDesign Solutions LLC, Zurich, Switzerland
| | - Ran Lu
- Zetta AI, LLC, Sherrill, NY, USA
| | | | - Kisuk Lee
- Zetta AI, LLC, Sherrill, NY, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | | | - Dodam Ih
- Zetta AI, LLC, Sherrill, NY, 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.
| |
Collapse
|
2
|
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 DOI: 10.1038/s41586-024-07389-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [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.
Collapse
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.
| |
Collapse
|
3
|
Syed DS, Ravbar P, Simpson JH. Inhibitory circuits coordinate leg movements during Drosophila grooming. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.05.597468. [PMID: 38895414 PMCID: PMC11185647 DOI: 10.1101/2024.06.05.597468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Limbs execute diverse actions coordinated by the nervous system through multiple motor programs. The basic architecture of motor neurons that activate muscles which articulate joints for antagonistic flexion and extension movements is conserved from flies to vertebrates. While excitatory premotor circuits are expected to establish sets of leg motor neurons that work together, our study uncovered an instructive role for inhibitory circuits. Using electron microscopy data for the Drosophila nerve cord, we categorized ~120 GABAergic inhibitory neurons from the 13A and 13B hemi-lineages into classes based on similarities in morphology and connectivity. By mapping their synaptic partners, we uncovered redundant pathways for inhibiting specific groups of motor neurons, disinhibiting antagonistic counterparts, or inducing alternation between flexion and extension. We tested the function of specific inhibitory neurons through optogenetic activation and silencing, using quantitative leg movement assays for coordination during grooming. Behavior experiments and modeling demonstrate that inhibition can induce rhythmic motion, highlighting the importance of inhibitory circuits in motor control.
Collapse
Affiliation(s)
- Durafshan Sakeena Syed
- UC Santa Barbara, Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, Santa Barbara, CA, USA
| | - Primoz Ravbar
- UC Santa Barbara, Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, Santa Barbara, CA, USA
| | - Julie H. Simpson
- UC Santa Barbara, Neuroscience Research Institute and Department of Molecular, Cellular and Developmental Biology, Santa Barbara, CA, USA
| |
Collapse
|
4
|
Yoshikawa S, Tang P, Simpson JH. Mechanosensory and command contributions to the Drosophila grooming sequence. Curr Biol 2024; 34:2066-2076.e3. [PMID: 38657610 PMCID: PMC11179149 DOI: 10.1016/j.cub.2024.04.003] [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: 11/13/2023] [Revised: 02/14/2024] [Accepted: 04/02/2024] [Indexed: 04/26/2024]
Abstract
Flies groom in response to competing mechanosensory cues in an anterior-to-posterior order using specific legs. From behavior screens, we identified a pair of cholinergic command-like neurons, Mago-no-Te (MGT), whose optogenetic activation elicits thoracic grooming by the back legs. Thoracic grooming is typically composed of body sweeps and leg rubs in alternation, but clonal analysis coupled with amputation experiments revealed that MGT activation only commands the body sweeps: initiation of leg rubbing requires contact between the leg and thorax. With new electron microscopy (EM) connectome data for the ventral nerve cord (VNC), we uncovered a circuit-based explanation for why stimulation of posterior thoracic mechanosensory bristles initiates cleaning by the back legs. Our previous work showed that flies weigh mechanosensory inputs across the body to select which part to groom, but we did not know why the thorax was always cleaned last. Here, the connectome for the VNC enabled us to identify a pair of GABAergic inhibitory neurons, UMGT1, that receives diverse sensory inputs and synapses onto both MGT and components of its downstream circuits. Optogenetic activation of UMGT1 suppresses thoracic cleaning, representing a mechanism by which mechanosensory stimuli on other body parts could take precedence in the grooming hierarchy. We also anatomically mapped the pre-motor circuit downstream of MGT, including inhibitory feedback connections that may enable rhythmicity and coordination of limb movement during thoracic grooming. The combination of behavioral screens and connectome analysis allowed us to identify a neural circuit connecting sensory-to-motor neurons that contributes to thoracic grooming.
Collapse
Affiliation(s)
- Shingo Yoshikawa
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Paul Tang
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Julie H Simpson
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA.
| |
Collapse
|
5
|
Gowda SBM, Banu A, Hussain S, Mohammad F. Neuronal mechanisms regulating locomotion in adult Drosophila. J Neurosci Res 2024; 102:e25332. [PMID: 38646942 DOI: 10.1002/jnr.25332] [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: 02/26/2024] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024]
Abstract
The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.
Collapse
Affiliation(s)
- Swetha B M Gowda
- Division of Biological and Biomedical Sciences (BBS), College of Health and Life Sciences (CHLS), Hamad Bin Khalifa University (HBKU), Doha, Qatar
| | - Ayesha Banu
- Division of Biological and Biomedical Sciences (BBS), College of Health and Life Sciences (CHLS), Hamad Bin Khalifa University (HBKU), Doha, Qatar
| | - Sadam Hussain
- Division of Biological and Biomedical Sciences (BBS), College of Health and Life Sciences (CHLS), Hamad Bin Khalifa University (HBKU), Doha, Qatar
| | - Farhan Mohammad
- Division of Biological and Biomedical Sciences (BBS), College of Health and Life Sciences (CHLS), Hamad Bin Khalifa University (HBKU), Doha, Qatar
| |
Collapse
|
6
|
Gorko B, Siwanowicz I, Close K, Christoforou C, Hibbard KL, Kabra M, Lee A, Park JY, Li SY, Chen AB, Namiki S, Chen C, Tuthill JC, Bock DD, Rouault H, Branson K, Ihrke G, Huston SJ. Motor neurons generate pose-targeted movements via proprioceptive sculpting. Nature 2024; 628:596-603. [PMID: 38509371 DOI: 10.1038/s41586-024-07222-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 02/22/2024] [Indexed: 03/22/2024]
Abstract
Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.
Collapse
Affiliation(s)
- Benjamin Gorko
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Igor Siwanowicz
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kari Close
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Karen L Hibbard
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Mayank Kabra
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Allen Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jin-Yong Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Si Ying Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | - Alex B Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Program in Neuroscience, Harvard Medical School, Boston, MA, USA
| | - Shigehiro Namiki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan
| | - Chenghao Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- 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
| | - Davi D Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Neurological Sciences, University of Vermont, Burlington, VT, USA
| | - Hervé Rouault
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Turing Centre for Living systems, Aix-Marseille University, Université de Toulon, CNRS, CPT (UMR 7332), Marseille, France
| | - Kristin Branson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Gudrun Ihrke
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Stephen J Huston
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
| |
Collapse
|
7
|
Simpson JH. Descending control of motor sequences in Drosophila. Curr Opin Neurobiol 2024; 84:102822. [PMID: 38096757 PMCID: PMC11215313 DOI: 10.1016/j.conb.2023.102822] [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: 08/01/2023] [Revised: 11/22/2023] [Accepted: 11/22/2023] [Indexed: 02/18/2024]
Abstract
The descending neurons connecting the fly's brain to its ventral nerve cord respond to sensory stimuli and evoke motor programs of varying complexity. Anatomical characterization of the descending neurons and their synaptic connections suggests how these circuits organize movements, while optogenetic manipulation of their activity reveals what behaviors they can induce. Monitoring their responses to sensory stimuli or during behavior performance indicates what information they may encode. Recent advances in all three approaches make the descending neurons an excellent place to better understand the sensorimotor integration and transformation required for nervous systems to govern the motor sequences that constitute animal behavior.
Collapse
Affiliation(s)
- Julie H Simpson
- Dept. Molecular Cellular and Developmental Biology and Neuroscience Research Institute, University of California Santa Barbara, USA.
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
Yoshikawa S, Tang P, Simpson JH. Mechanosensory and command contributions to the Drosophila grooming sequence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.19.567707. [PMID: 38045358 PMCID: PMC10690200 DOI: 10.1101/2023.11.19.567707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Flies groom in response to competing mechanosensory cues in an anterior to posterior order using specific legs. From behavior screens, we identified a pair of cholinergic command-like neurons, Mago-no-Te (MGT), whose optogenetic activation elicits thoracic grooming by hind legs. Thoracic grooming is typically composed of body sweeps and leg rubs in alternation, but clonal analysis coupled with amputation experiments revealed that MGT activation only commands the body sweeps: initiation of leg rubbing requires contact between leg and thorax. With new electron microscopy (EM) connectome data for the ventral nerve cord (VNC), we uncovered a circuit-based explanation for why stimulation of posterior thoracic mechanosensory bristles initiates cleaning by the hind legs. Our previous work showed that flies weigh mechanosensory inputs across the body to select which part to groom, but we did not know why the thorax was always cleaned last. Here, the connectome for the VNC enabled us to identify a pair of GABAergic inhibitory neurons, UMGT1, that receive diverse sensory inputs and synapse onto both MGT and components of its downstream pre-motor circuits. Optogenetic activation of UMGT1 suppresses thoracic cleaning, representing a mechanism by which mechanosensory stimuli on other body parts could take precedence in the grooming hierarchy. We also mapped the pre-motor circuit downstream of MGT, including inhibitory feedback connections that may enable rhythmicity and coordination of limb movement during thoracic grooming.
Collapse
Affiliation(s)
- Shingo Yoshikawa
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Paul Tang
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Julie H. Simpson
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| |
Collapse
|
10
|
Yang HH, Brezovec LE, Capdevila LS, Vanderbeck QX, Adachi A, Mann RS, Wilson RI. Fine-grained descending control of steering in walking Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.15.562426. [PMID: 37904997 PMCID: PMC10614758 DOI: 10.1101/2023.10.15.562426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream from distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Notably, a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from brain cells that drive specific, coordinated modulations of low-level patterns.
Collapse
Affiliation(s)
- Helen H. Yang
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115 USA
| | - Luke E. Brezovec
- Department of Neurobiology, Stanford University, Stanford, CA 94305 USA
| | | | | | - Atsuko Adachi
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Richard S. Mann
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Rachel I. Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115 USA
- Lead contact
| |
Collapse
|
11
|
Mamiya A, Sustar A, Siwanowicz I, Qi Y, Lu TC, Gurung P, Chen C, Phelps JS, Kuan AT, Pacureanu A, Lee WCA, Li H, Mhatre N, Tuthill JC. Biomechanical origins of proprioceptor feature selectivity and topographic maps in the Drosophila leg. Neuron 2023; 111:3230-3243.e14. [PMID: 37562405 PMCID: PMC10644877 DOI: 10.1016/j.neuron.2023.07.009] [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: 09/07/2022] [Revised: 04/28/2023] [Accepted: 07/12/2023] [Indexed: 08/12/2023]
Abstract
Our ability to sense and move our bodies relies on proprioceptors, sensory neurons that detect mechanical forces within the body. Different subtypes of proprioceptors detect different kinematic features, such as joint position, movement, and vibration, but the mechanisms that underlie proprioceptor feature selectivity remain poorly understood. Using single-nucleus RNA sequencing (RNA-seq), we found that proprioceptor subtypes in the Drosophila leg lack differential expression of mechanosensitive ion channels. However, anatomical reconstruction of the proprioceptors and connected tendons revealed major biomechanical differences between subtypes. We built a model of the proprioceptors and tendons that identified a biomechanical mechanism for joint angle selectivity and predicted the existence of a topographic map of joint angle, which we confirmed using calcium imaging. Our findings suggest that biomechanical specialization is a key determinant of proprioceptor feature selectivity in Drosophila. More broadly, the discovery of proprioceptive maps reveals common organizational principles between proprioception and other topographically organized sensory systems.
Collapse
Affiliation(s)
- Akira Mamiya
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Anne Sustar
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Igor Siwanowicz
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yanyan Qi
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Tzu-Chiao Lu
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Pralaksha Gurung
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Chenghao Chen
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Aaron T Kuan
- Department of Neurobiology, Harvard Medical School, Boston, MA, 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
| | - Hongjie Li
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Natasha Mhatre
- Department of Biology, University of Western Ontario, London, ON, Canada
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA.
| |
Collapse
|
12
|
Cruz TL, Chiappe ME. Multilevel visuomotor control of locomotion in Drosophila. Curr Opin Neurobiol 2023; 82:102774. [PMID: 37651855 DOI: 10.1016/j.conb.2023.102774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/26/2023] [Accepted: 08/01/2023] [Indexed: 09/02/2023]
Abstract
Vision is critical for the control of locomotion, but the underlying neural mechanisms by which visuomotor circuits contribute to the movement of the body through space are yet not well understood. Locomotion engages multiple control systems, forming distinct interacting "control levels" driven by the activity of distributed and overlapping circuits. Therefore, a comprehensive understanding of the mechanisms underlying locomotion control requires the consideration of all control levels and their necessary coordination. Due to their small size and the wide availability of experimental tools, Drosophila has become an important model system to study this coordination. Traditionally, insect locomotion has been divided into studying either the biomechanics and local control of limbs, or navigation and course control. However, recent developments in tracking techniques, and physiological and genetic tools in Drosophila have prompted researchers to examine multilevel control coordination in flight and walking.
Collapse
Affiliation(s)
- Tomás L Cruz
- Champalimaud Research, Champalimaud Centre for the Unknown, 1400-038 Lisbon, Portugal
| | - M Eugenia Chiappe
- Champalimaud Research, Champalimaud Centre for the Unknown, 1400-038 Lisbon, Portugal.
| |
Collapse
|
13
|
Yoshida S, Takaki K, Yamawaki Y. Roles of muscle activities in foreleg movements during predatory strike of the mantis. JOURNAL OF INSECT PHYSIOLOGY 2023; 145:104474. [PMID: 36596320 DOI: 10.1016/j.jinsphys.2022.104474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/28/2022] [Accepted: 12/30/2022] [Indexed: 06/17/2023]
Abstract
Foreleg trajectory in the mantis strike varies depending on prey distance. To examine how muscle activities affect foreleg trajectory, we recorded strike behaviours of the Chinese mantis with a high-speed camera and electromyograms of the foreleg trochanteral extensor and flexor. At the approach phase of the mantis strike, the prothorax-coxa (P-C) joint elevated and the femur-tibia (F-T) joint extended. At the sweep phase, the coxa-trochanter (C-T) joint rapidly extended, then, the F-T joint rapidly flexed to capture the prey. At capture initiation, the C-T joint extended more with greater prey distance. After cutting the tendon of the trochanteral flexor, the C-T joint extended similarly to that of the intact foreleg but did not flex after it reached its peak angle. After cutting the tendon of the trochanteral extensor, the C-T joint did not extend as much as that of the intact foreleg. During rapid extension of the C-T joint, a burst of spikes from the coxal trochanteral extensor was observed in electromyograms. Among several parameters, burst duration was the best predictor of C-T joint angular change during strike. Unexpectedly, trochanteral flexor activity was also observed during rapid extension of the C-T joint. These results indicated that the coxal trochanteral extensor mainly contributed to the rapid C-T extension during strike, but other muscles also contributed at the beginning of extension. The trochanteral flexor appeared to contribute to C-T flexion by countering the rapid extension.
Collapse
Affiliation(s)
- Shigeki Yoshida
- Department of Biology, Faculty of Science, Kyushu University, Fukuoka 819-0395, Japan
| | - Keigo Takaki
- Department of Biology, Faculty of Science, Kyushu University, Fukuoka 819-0395, Japan
| | - Yoshifumi Yamawaki
- Department of Biology, Faculty of Science, Kyushu University, Fukuoka 819-0395, Japan.
| |
Collapse
|
14
|
Hug F, Avrillon S, Ibáñez J, Farina D. Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation. J Physiol 2023; 601:11-20. [PMID: 36353890 PMCID: PMC10098498 DOI: 10.1113/jp283698] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 11/07/2022] [Indexed: 11/11/2022] Open
Abstract
Understanding how movement is controlled by the CNS remains a major challenge, with ongoing debate about basic features underlying this control. In current established views, the concepts of motor neuron recruitment order, common synaptic input to motor neurons and muscle synergies are usually addressed separately and therefore seen as independent features of motor control. In this review, we analyse the body of literature in a broader perspective and we identify a unified approach to explain apparently divergent observations at different scales of motor control. Specifically, we propose a new conceptual framework of the neural control of movement, which merges the concept of common input to motor neurons and modular control, together with the constraints imposed by recruitment order. This framework is based on the following assumptions: (1) motor neurons are grouped into functional groups (clusters) based on the common inputs they receive; (2) clusters may significantly differ from the classical definition of motor neuron pools, such that they may span across muscles and/or involve only a portion of a muscle; (3) clusters represent functional modules used by the CNS to reduce the dimensionality of the control; and (4) selective volitional control of single motor neurons within a cluster receiving common inputs cannot be achieved. Here, we discuss this framework and its underlying theoretical and experimental evidence.
Collapse
Affiliation(s)
- François Hug
- Université Côte d'Azur, LAMHESS, Nice, France.,School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, Australia
| | - Simon Avrillon
- Department of Bioengineering, Imperial College London, London, UK
| | - Jaime Ibáñez
- Department of Bioengineering, Imperial College London, London, UK.,BSICoS, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain.,Department for Clinical and movement neurosciences, Institute of Neurology, University College London, London, UK
| | - Dario Farina
- Department of Bioengineering, Imperial College London, London, UK
| |
Collapse
|
15
|
Katti P, Ajayi PT, Aponte A, Bleck CKE, Glancy B. Identification of evolutionarily conserved regulators of muscle mitochondrial network organization. Nat Commun 2022; 13:6622. [PMID: 36333356 PMCID: PMC9636386 DOI: 10.1038/s41467-022-34445-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 10/25/2022] [Indexed: 11/06/2022] Open
Abstract
Mitochondrial networks provide coordinated energy distribution throughout muscle cells. However, pathways specifying mitochondrial networks are incompletely understood and it is unclear how they might affect contractile fiber-type. Here, we show that natural energetic demands placed on Drosophila melanogaster muscles yield native cell-types among which contractile and mitochondrial network-types are regulated differentially. Proteomic analyses of indirect flight, jump, and leg muscles, together with muscles misexpressing known fiber-type specification factor salm, identified transcription factors H15 and cut as potential mitochondrial network regulators. We demonstrate H15 operates downstream of salm regulating flight muscle contractile and mitochondrial network-type. Conversely, H15 regulates mitochondrial network configuration but not contractile type in jump and leg muscles. Further, we find that cut regulates salm expression in flight muscles and mitochondrial network configuration in leg muscles. These data indicate cell type-specific regulation of muscle mitochondrial network organization through evolutionarily conserved transcription factors cut, salm, and H15.
Collapse
Affiliation(s)
- Prasanna Katti
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Peter T Ajayi
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Angel Aponte
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Christopher K E Bleck
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Brian Glancy
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
- National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.
| |
Collapse
|
16
|
Menelaou E, Kishore S, McLean DL. Mixed synapses reconcile violations of the size principle in zebrafish spinal cord. eLife 2022; 11:64063. [PMID: 36166290 PMCID: PMC9514842 DOI: 10.7554/elife.64063] [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: 10/15/2020] [Accepted: 09/12/2022] [Indexed: 11/24/2022] Open
Abstract
Mixed electrical-chemical synapses potentially complicate electrophysiological interpretations of neuronal excitability and connectivity. Here, we disentangle the impact of mixed synapses within the spinal locomotor circuitry of larval zebrafish. We demonstrate that soma size is not linked to input resistance for interneurons, contrary to the biophysical predictions of the ‘size principle’ for motor neurons. Next, we show that time constants are faster, excitatory currents stronger, and mixed potentials larger in lower resistance neurons, linking mixed synapse density to resting excitability. Using a computational model, we verify the impact of weighted electrical synapses on membrane properties, synaptic integration and the low-pass filtering and distribution of coupling potentials. We conclude differences in mixed synapse density can contribute to excitability underestimations and connectivity overestimations. The contribution of mixed synaptic inputs to resting excitability helps explain ‘violations’ of the size principle, where neuron size, resistance and recruitment order are unrelated.
Collapse
Affiliation(s)
- Evdokia Menelaou
- Department of Neurobiology, Northwestern University, Evanston, United States
| | - Sandeep Kishore
- Department of Neurobiology, Northwestern University, Evanston, United States
| | - David L McLean
- Department of Neurobiology, Northwestern University, Evanston, United States
| |
Collapse
|
17
|
Cabrita A, Medeiros AM, Pereira T, Rodrigues AS, Kranendonk M, Mendes CS. Motor dysfunction in Drosophila melanogaster as a biomarker for developmental neurotoxicity. iScience 2022; 25:104541. [PMID: 35769875 PMCID: PMC9234254 DOI: 10.1016/j.isci.2022.104541] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/30/2021] [Accepted: 06/02/2022] [Indexed: 11/18/2022] Open
Abstract
Adequate alternatives to conventional animal testing are needed to study developmental neurotoxicity (DNT). Here, we used kinematic analysis to assess DNT of known (toluene (TOL) and chlorpyrifos (CPS)) and putative (β-N-methylamino-L-alanine (BMAA)) neurotoxic compounds. Drosophila melanogaster was exposed to these compounds during development and evaluated for survival and adult kinematic parameters using the FlyWalker system, a kinematics evaluation method. At concentrations that do not induce general toxicity, the solvent DMSO had a significant effect on kinematic parameters. Moreover, while TOL did not significantly induce lethality or kinematic dysfunction, CPS not only induced developmental lethality but also significantly impaired coordination in comparison to DMSO. Interestingly, BMAA, which was not lethal during development, induced motor decay in young adult animals, phenotypically resembling aged flies, an effect later attenuated upon aging. Furthermore, BMAA induced abnormal development of leg motor neuron projections. Our results suggest that our kinematic approach can assess potential DNT of chemical compounds. Alternatives to mammalian testing are needed to detect developmental neurotoxicity The pesticide chlorpyrifos causes partial lethality and motor dysfunction Non-lethal levels of BMAA induce motor dysfunction in a dose-dependent manner Kinematic profiling of adult Drosophila can identify developmental neurotoxicity
Collapse
Affiliation(s)
- Ana Cabrita
- iNOVA4Health, NOVA Medical School|Faculdade de Ciências Médicas, NMS|FCM, Universidade Nova de Lisboa, Lisboa, Portugal
| | - Alexandra M. Medeiros
- iNOVA4Health, NOVA Medical School|Faculdade de Ciências Médicas, NMS|FCM, Universidade Nova de Lisboa, Lisboa, Portugal
| | - Telmo Pereira
- NOVA Medical School|Faculdade de Ciências Médicas, NMS|FCM, Universidade Nova de Lisboa, Lisboa, Portugal
| | - António Sebastião Rodrigues
- ToxOmics, NOVA Medical School|Faculdade de Ciências Médicas, NMS|FCM, Universidade Nova de Lisboa, Lisboa, Portugal
| | - Michel Kranendonk
- ToxOmics, NOVA Medical School|Faculdade de Ciências Médicas, NMS|FCM, Universidade Nova de Lisboa, Lisboa, Portugal
- Corresponding author
| | - César S. Mendes
- iNOVA4Health, NOVA Medical School|Faculdade de Ciências Médicas, NMS|FCM, Universidade Nova de Lisboa, Lisboa, Portugal
- Corresponding author
| |
Collapse
|
18
|
NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster. Nat Methods 2022; 19:620-627. [PMID: 35545713 DOI: 10.1038/s41592-022-01466-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 03/23/2022] [Indexed: 11/08/2022]
Abstract
Animal behavior emerges from an interaction between neural network dynamics, musculoskeletal properties and the physical environment. Accessing and understanding the interplay between these elements requires the development of integrative and morphologically realistic neuromechanical simulations. Here we present NeuroMechFly, a data-driven model of the widely studied organism, Drosophila melanogaster. NeuroMechFly combines four independent computational modules: a physics-based simulation environment, a biomechanical exoskeleton, muscle models and neural network controllers. To enable use cases, we first define the minimum degrees of freedom of the leg from real three-dimensional kinematic measurements during walking and grooming. Then, we show how, by replaying these behaviors in the simulator, one can predict otherwise unmeasured torques and contact forces. Finally, we leverage NeuroMechFly's full neuromechanical capacity to discover neural networks and muscle parameters that drive locomotor gaits optimized for speed and stability. Thus, NeuroMechFly can increase our understanding of how behaviors emerge from interactions between complex neuromechanical systems and their physical surroundings.
Collapse
|
19
|
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.
Collapse
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
| |
Collapse
|
20
|
Aymanns F, Chen CL, Ramdya P. Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors. eLife 2022; 11:81527. [PMID: 36286408 PMCID: PMC9605690 DOI: 10.7554/elife.81527] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/13/2022] [Indexed: 11/21/2022] Open
Abstract
Deciphering how the brain regulates motor circuits to control complex behaviors is an important, long-standing challenge in neuroscience. In the fly, Drosophila melanogaster, this is coordinated by a population of ~ 1100 descending neurons (DNs). Activating only a few DNs is known to be sufficient to drive complex behaviors like walking and grooming. However, what additional role the larger population of DNs plays during natural behaviors remains largely unknown. For example, they may modulate core behavioral commands or comprise parallel pathways that are engaged depending on sensory context. We evaluated these possibilities by recording populations of nearly 100 DNs in individual tethered flies while they generated limb-dependent behaviors, including walking and grooming. We found that the largest fraction of recorded DNs encode walking while fewer are active during head grooming and resting. A large fraction of walk-encoding DNs encode turning and far fewer weakly encode speed. Although odor context does not determine which behavior-encoding DNs are recruited, a few DNs encode odors rather than behaviors. Lastly, we illustrate how one can identify individual neurons from DN population recordings by using their spatial, functional, and morphological properties. These results set the stage for a comprehensive, population-level understanding of how the brain’s descending signals regulate complex motor actions.
Collapse
Affiliation(s)
- Florian Aymanns
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFLLausanneSwitzerland
| | - Chin-Lin Chen
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFLLausanneSwitzerland
| | - Pavan Ramdya
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFLLausanneSwitzerland
| |
Collapse
|
21
|
Pethick J, Piasecki M. Alterations in Muscle Force Control With Aging: Is There a Modulatory Effect of Lifelong Physical Activity? Front Sports Act Living 2022; 4:817770. [PMID: 35392594 PMCID: PMC8980913 DOI: 10.3389/fspor.2022.817770] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/28/2022] [Indexed: 11/16/2022] Open
Abstract
Recent technological developments have enabled significant advances in our understanding of the ability to voluntarily control muscle force output. The fluctuations inherent to muscle force output can be quantified according to both their magnitude and temporal structure (or "complexity"), with such quantification facilitating comparison of force control between distinct populations. In comparison to young adults, older adults exhibit an increase in the magnitude (i.e., decreased steadiness) and a decrease in the complexity (i.e., decreased adaptability) of force fluctuations, both of which are indicative of a loss of force control. There remain, however, key gaps in knowledge that limit our interpretation of this age-related loss of force control. One such gap relates to the effect of lifelong physical activity on force control. To date, research on aging and force control has largely been conducted on inactive or moderately active older adults. However, high levels of lifelong physical activity, such as that exhibited by Masters athletes, have been shown to have protective effects on the function and morphology of the neuromuscular system. Some of these effects (e.g., on impaired inhibitory transmission in the motor cortex and on motor unit discharge rates) have the potential to attenuate the age-related loss of force control, while others (e.g., greater motor unit remodeling capacity) have the potential to worsen it. We therefore propose that, in order to progress our knowledge of the effects of aging on force control, future studies must consider the potential modulatory effect of lifelong physical activity.
Collapse
Affiliation(s)
- Jamie Pethick
- School of Sport, Rehabilitation and Exercise Sciences, University of Essex, Colchester, United Kingdom
- *Correspondence: Jamie Pethick
| | - Mathew Piasecki
- Centre of Metabolism, Ageing and Physiology (COMAP), MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| |
Collapse
|
22
|
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.
Collapse
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
| |
Collapse
|
23
|
Chen C, Agrawal S, Mark B, Mamiya A, Sustar A, Phelps JS, Lee WCA, Dickson BJ, Card GM, Tuthill JC. Functional architecture of neural circuits for leg proprioception in Drosophila. Curr Biol 2021; 31:5163-5175.e7. [PMID: 34637749 PMCID: PMC8665017 DOI: 10.1016/j.cub.2021.09.035] [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: 04/26/2021] [Revised: 08/30/2021] [Accepted: 09/15/2021] [Indexed: 11/30/2022]
Abstract
To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception. To understand how diverse proprioceptive signals from the Drosophila leg are integrated by downstream circuits, Chen et al. use optogenetics and calcium imaging to map functional connectivity between sensory and central neurons. This work identifies parallel neural pathways for processing leg vibration vs. joint position and movement.
Collapse
Affiliation(s)
- Chenghao Chen
- Department of Physiology and Biophysics, University of Washington, 1705 N.E. Pacific Street, Seattle, WA 98195, USA; Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Sweta Agrawal
- Department of Physiology and Biophysics, University of Washington, 1705 N.E. Pacific Street, Seattle, WA 98195, USA
| | - Brandon Mark
- Department of Physiology and Biophysics, University of Washington, 1705 N.E. Pacific Street, Seattle, WA 98195, USA
| | - Akira Mamiya
- Department of Physiology and Biophysics, University of Washington, 1705 N.E. Pacific Street, Seattle, WA 98195, USA
| | - Anne Sustar
- Department of Physiology and Biophysics, University of Washington, 1705 N.E. Pacific Street, Seattle, WA 98195, USA
| | - Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Wei-Chung Allen Lee
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, 1705 N.E. Pacific Street, Seattle, WA 98195, USA.
| |
Collapse
|
24
|
Karashchuk P, Rupp KL, Dickinson ES, Walling-Bell S, Sanders E, Azim E, Brunton BW, Tuthill JC. Anipose: A toolkit for robust markerless 3D pose estimation. Cell Rep 2021; 36:109730. [PMID: 34592148 PMCID: PMC8498918 DOI: 10.1016/j.celrep.2021.109730] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 06/15/2021] [Accepted: 08/27/2021] [Indexed: 01/12/2023] Open
Abstract
Quantifying movement is critical for understanding animal behavior. Advances in computer vision now enable markerless tracking from 2D video, but most animals move in 3D. Here, we introduce Anipose, an open-source toolkit for robust markerless 3D pose estimation. Anipose is built on the 2D tracking method DeepLabCut, so users can expand their existing experimental setups to obtain accurate 3D tracking. It consists of four components: (1) a 3D calibration module, (2) filters to resolve 2D tracking errors, (3) a triangulation module that integrates temporal and spatial regularization, and (4) a pipeline to structure processing of large numbers of videos. We evaluate Anipose on a calibration board as well as mice, flies, and humans. By analyzing 3D leg kinematics tracked with Anipose, we identify a key role for joint rotation in motor control of fly walking. To help users get started with 3D tracking, we provide tutorials and documentation at http://anipose.org/.
Collapse
Affiliation(s)
- Pierre Karashchuk
- Neuroscience Graduate Program, University of Washington, Seattle, WA, USA
| | - Katie L. Rupp
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Evyn S. Dickinson
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Sarah Walling-Bell
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Elischa Sanders
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Eiman Azim
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bingni W. Brunton
- Department of Biology, University of Washington, Seattle, WA, USA,Senior author,Correspondence: (B.W.B.), (J.C.T.)
| | - John C. Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA,Senior author,Lead contact,Correspondence: (B.W.B.), (J.C.T.)
| |
Collapse
|
25
|
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.
Collapse
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.
| |
Collapse
|
26
|
Agrawal S, Dickinson ES, Sustar A, Gurung P, Shepherd D, Truman JW, Tuthill JC. Central processing of leg proprioception in Drosophila. eLife 2020; 9:e60299. [PMID: 33263281 PMCID: PMC7752136 DOI: 10.7554/elife.60299] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 12/01/2020] [Indexed: 12/28/2022] Open
Abstract
Proprioception, the sense of self-movement and position, is mediated by mechanosensory neurons that detect diverse features of body kinematics. Although proprioceptive feedback is crucial for accurate motor control, little is known about how downstream circuits transform limb sensory information to guide motor output. Here we investigate neural circuits in Drosophila that process proprioceptive information from the fly leg. We identify three cell types from distinct developmental lineages that are positioned to receive input from proprioceptor subtypes encoding tibia position, movement, and vibration. 13Bα neurons encode femur-tibia joint angle and mediate postural changes in tibia position. 9Aα neurons also drive changes in leg posture, but encode a combination of directional movement, high frequency vibration, and joint angle. Activating 10Bα neurons, which encode tibia vibration at specific joint angles, elicits pausing in walking flies. Altogether, our results reveal that central circuits integrate information across proprioceptor subtypes to construct complex sensorimotor representations that mediate diverse behaviors, including reflexive control of limb posture and detection of leg vibration.
Collapse
Affiliation(s)
- Sweta Agrawal
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Evyn S Dickinson
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Anne Sustar
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Pralaksha Gurung
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - David Shepherd
- School of Natural Sciences, Bangor UniversityBangorUnited Kingdom
| | - James W Truman
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
- Friday Harbor Laboratories, University of WashingtonFriday HarborUnited States
| | - John C Tuthill
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| |
Collapse
|
27
|
Feng K, Sen R, Minegishi R, Dübbert M, Bockemühl T, Büschges A, Dickson BJ. Distributed control of motor circuits for backward walking in Drosophila. Nat Commun 2020; 11:6166. [PMID: 33268800 PMCID: PMC7710706 DOI: 10.1038/s41467-020-19936-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 11/05/2020] [Indexed: 12/13/2022] Open
Abstract
How do descending inputs from the brain control leg motor circuits to change how an animal walks? Conceptually, descending neurons are thought to function either as command-type neurons, in which a single type of descending neuron exerts a high-level control to elicit a coordinated change in motor output, or through a population coding mechanism, whereby a group of neurons, each with local effects, act in combination to elicit a global motor response. The Drosophila Moonwalker Descending Neurons (MDNs), which alter leg motor circuit dynamics so that the fly walks backwards, exemplify the command-type mechanism. Here, we identify several dozen MDN target neurons within the leg motor circuits, and show that two of them mediate distinct and highly-specific changes in leg muscle activity during backward walking: LBL40 neurons provide the hindleg power stroke during stance phase; LUL130 neurons lift the legs at the end of stance to initiate swing. Through these two effector neurons, MDN directly controls both the stance and swing phases of the backward stepping cycle. These findings suggest that command-type descending neurons can also operate through the distributed control of local motor circuits.
Collapse
Affiliation(s)
- Kai Feng
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, 4072, Australia.
| | - Rajyashree Sen
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, 20147, USA
- The Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Ryo Minegishi
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Michael Dübbert
- Institute for Zoology, Biocenter Cologne, University of Cologne, D-50674, Cologne, Germany
| | - Till Bockemühl
- Institute for Zoology, Biocenter Cologne, University of Cologne, D-50674, Cologne, Germany
| | - Ansgar Büschges
- Institute for Zoology, Biocenter Cologne, University of Cologne, D-50674, Cologne, Germany
| | - Barry J Dickson
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, 4072, Australia.
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, 20147, USA.
| |
Collapse
|
28
|
Kuan AT, Phelps JS, Thomas LA, Nguyen TM, Han J, Chen CL, Azevedo AW, Tuthill JC, Funke J, Cloetens P, Pacureanu A, Lee WCA. Dense neuronal reconstruction through X-ray holographic nano-tomography. Nat Neurosci 2020; 23:1637-1643. [PMID: 32929244 PMCID: PMC8354006 DOI: 10.1038/s41593-020-0704-9] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 08/05/2020] [Indexed: 12/21/2022]
Abstract
Imaging neuronal networks provides a foundation for understanding the nervous system, but resolving dense nanometer-scale structures over large volumes remains challenging for light microscopy (LM) and electron microscopy (EM). Here we show that X-ray holographic nano-tomography (XNH) can image millimeter-scale volumes with sub-100-nm resolution, enabling reconstruction of dense wiring in Drosophila melanogaster and mouse nervous tissue. We performed correlative XNH and EM to reconstruct hundreds of cortical pyramidal cells and show that more superficial cells receive stronger synaptic inhibition on their apical dendrites. By combining multiple XNH scans, we imaged an adult Drosophila leg with sufficient resolution to comprehensively catalog mechanosensory neurons and trace individual motor axons from muscles to the central nervous system. To accelerate neuronal reconstructions, we trained a convolutional neural network to automatically segment neurons from XNH volumes. Thus, XNH bridges a key gap between LM and EM, providing a new avenue for neural circuit discovery.
Collapse
Affiliation(s)
- Aaron T Kuan
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Program in Neuroscience, Harvard University, Boston, MA, USA
| | - Logan A Thomas
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Tri M Nguyen
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Julie Han
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Chiao-Lin Chen
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Anthony W Azevedo
- 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
| | - Jan Funke
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | | | - Alexandra Pacureanu
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
- ESRF, The European Synchrotron, Grenoble, France.
| | - Wei-Chung Allen Lee
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
29
|
Agudelo A, St Amand V, Grissom L, Lafond D, Achilli T, Sahin A, Reenan R, Stilwell G. Age-dependent degeneration of an identified adult leg motor neuron in a Drosophila SOD1 model of ALS. Biol Open 2020; 9:bio049692. [PMID: 32994185 PMCID: PMC7595701 DOI: 10.1242/bio.049692] [Citation(s) in RCA: 4] [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: 11/26/2019] [Accepted: 09/21/2020] [Indexed: 12/31/2022] Open
Abstract
Mutations in superoxide dismutase 1 (SOD1) cause familial amyotrophic lateral sclerosis (ALS) in humans. ALS is a neurodegenerative disease characterized by progressive motor neuron loss leading to paralysis and inevitable death in affected individuals. Using a gene replacement strategy to introduce disease mutations into the orthologous Drosophila sod1 (dsod1) gene, here, we characterize changes at the neuromuscular junction using longer-lived dsod1 mutant adults. Homozygous dsod1H71Y/H71Y or dsod1null/null flies display progressive walking defects with paralysis of the third metathoracic leg. In dissected legs, we assessed age-dependent changes in a single identified motor neuron (MN-I2) innervating the tibia levitator muscle. At adult eclosion, MN-I2 of dsod1H71Y/H71Y or sod1null/null flies is patterned similar to wild-type flies indicating no readily apparent developmental defects. Over the course of 10 days post-eclosion, MN-I2 shows an overall reduction in arborization with bouton swelling and loss of the post-synaptic marker discs-large (dlg) in mutant dsod1 adults. In addition, increases in polyubiquitinated proteins correlate with the timing and extent of MN-I2 changes. Because similar phenotypes are observed between flies homozygous for either dsod1H71Y or dsod1null alleles, we conclude these NMJ changes are mainly associated with sod loss-of-function. Together these studies characterize age-related morphological and molecular changes associated with axonal retraction in a Drosophila model of ALS that recapitulate an important aspect of the human disease.This article has an associated First Person interview with the first author of the paper.
Collapse
Affiliation(s)
- Anthony Agudelo
- Department of Biology, Rhode Island College, 600 Mt. Pleasant Ave., Providence, RI, 02908 USA
| | - Victoria St Amand
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI, 02912 USA
| | - Lindsey Grissom
- Department of Biology, Rhode Island College, 600 Mt. Pleasant Ave., Providence, RI, 02908 USA
| | - Danielle Lafond
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI, 02912 USA
| | - Toni Achilli
- Department of Biology, Rhode Island College, 600 Mt. Pleasant Ave., Providence, RI, 02908 USA
| | - Asli Sahin
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI, 02912 USA
| | - Robert Reenan
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI, 02912 USA
| | - Geoff Stilwell
- Department of Biology, Rhode Island College, 600 Mt. Pleasant Ave., Providence, RI, 02908 USA
| |
Collapse
|
30
|
Harris CM, Dinges GF, Haberkorn A, Gebehart C, Büschges A, Zill SN. Gradients in mechanotransduction of force and body weight in insects. ARTHROPOD STRUCTURE & DEVELOPMENT 2020; 58:100970. [PMID: 32702647 DOI: 10.1016/j.asd.2020.100970] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 06/23/2020] [Accepted: 06/24/2020] [Indexed: 06/11/2023]
Abstract
Posture and walking require support of the body weight, which is thought to be detected by sensory receptors in the legs. Specificity in sensory encoding occurs through the numerical distribution, size and response range of sense organs. We have studied campaniform sensilla, receptors that detect forces as strains in the insect exoskeleton. The sites of mechanotransduction (cuticular caps) were imaged by light and confocal microscopy in four species (stick insects, cockroaches, blow flies and Drosophila). The numbers of receptors and cap diameters were determined in projection images. Similar groups of receptors are present in the legs of each species (flies lack Group 2 on the anterior trochanter). The number of receptors is generally related to the body weight but similar numbers are found in blow flies and Drosophila, despite a 30 fold difference in their weight. Imaging data indicate that the gradient (range) of cap sizes may more closely correlate with the body weight: the range of cap sizes is larger in blow flies than in Drosophila but similar to that found in juvenile cockroaches. These studies support the idea that morphological properties of force-detecting sensory receptors in the legs may be tuned to reflect the body weight.
Collapse
Affiliation(s)
- Christian M Harris
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV 25704, USA
| | - Gesa F Dinges
- Department of Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, 50923 Cologne, Germany
| | - Anna Haberkorn
- Department of Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, 50923 Cologne, Germany
| | - Corinna Gebehart
- Department of Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, 50923 Cologne, Germany
| | - Ansgar Büschges
- Department of Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, 50923 Cologne, Germany
| | - Sasha N Zill
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV 25704, USA.
| |
Collapse
|
31
|
Bidaye SS, Laturney M, Chang AK, Liu Y, Bockemühl T, Büschges A, Scott K. Two Brain Pathways Initiate Distinct Forward Walking Programs in Drosophila. Neuron 2020; 108:469-485.e8. [PMID: 32822613 DOI: 10.1016/j.neuron.2020.07.032] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 06/08/2020] [Accepted: 07/24/2020] [Indexed: 12/12/2022]
Abstract
An animal at rest or engaged in stationary behaviors can instantaneously initiate goal-directed walking. How descending brain inputs trigger rapid transitions from a non-walking state to an appropriate walking state is unclear. Here, we identify two neuronal types, P9 and BPN, in the Drosophila brain that, upon activation, initiate and maintain two distinct coordinated walking patterns. P9 drives forward walking with ipsilateral turning, receives inputs from central courtship-promoting neurons and visual projection neurons, and is necessary for a male to pursue a female during courtship. In contrast, BPN drives straight, forward walking and is not required during courtship. BPN is instead recruited during and required for fast, straight, forward walking bouts. Thus, this study reveals separate brain pathways for object-directed walking and fast, straight, forward walking, providing insight into how the brain initiates context-appropriate walking programs.
Collapse
Affiliation(s)
- Salil S Bidaye
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
| | - Meghan Laturney
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Amy K Chang
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Yuejiang Liu
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Till Bockemühl
- Department of Animal Physiology, Institute of Zoology, University of Cologne, 50674 Cologne, Germany
| | - Ansgar Büschges
- Department of Animal Physiology, Institute of Zoology, University of Cologne, 50674 Cologne, Germany
| | - Kristin Scott
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
| |
Collapse
|
32
|
Azevedo AW, Dickinson ES, Gurung P, Venkatasubramanian L, Mann RS, Tuthill JC. A size principle for recruitment of Drosophila leg motor neurons. eLife 2020; 9:e56754. [PMID: 32490810 PMCID: PMC7347388 DOI: 10.7554/elife.56754] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 06/01/2020] [Indexed: 11/28/2022] Open
Abstract
To move the body, the brain must precisely coordinate patterns of activity among diverse populations of motor neurons. Here, we use in vivo calcium imaging, electrophysiology, and behavior to understand how genetically-identified motor neurons control flexion of the fruit fly tibia. We find that leg motor neurons exhibit a coordinated gradient of anatomical, physiological, and functional properties. Large, fast motor neurons control high force, ballistic movements while small, slow motor neurons control low force, postural movements. Intermediate neurons fall between these two extremes. This hierarchical organization resembles the size principle, first proposed as a mechanism for establishing recruitment order among vertebrate motor neurons. Recordings in behaving flies confirmed that motor neurons are typically recruited in order from slow to fast. However, we also find that fast, intermediate, and slow motor neurons receive distinct proprioceptive feedback signals, suggesting that the size principle is not the only mechanism that dictates motor neuron recruitment. Overall, this work reveals the functional organization of the fly leg motor system and establishes Drosophila as a tractable system for investigating neural mechanisms of limb motor control.
Collapse
Affiliation(s)
- Anthony W Azevedo
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Evyn S Dickinson
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Pralaksha Gurung
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Lalanti Venkatasubramanian
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkUnited States
| | - Richard S Mann
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkUnited States
| | - John C Tuthill
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| |
Collapse
|