1
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Yang HH, Brezovec BE, Serratosa Capdevila L, Vanderbeck QX, Adachi A, Mann RS, Wilson RI. Fine-grained descending control of steering in walking Drosophila. Cell 2024:S0092-8674(24)00962-0. [PMID: 39293446 DOI: 10.1016/j.cell.2024.08.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 06/18/2024] [Accepted: 08/16/2024] [Indexed: 09/20/2024]
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 of 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. Our results suggest that 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 specific, coordinated modulations of low-level patterns.
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Affiliation(s)
- Helen H Yang
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Bella E Brezovec
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | | | - Quinn X Vanderbeck
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, 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.
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2
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Xu C, Li Z, Lyu C, Hu Y, McLaughlin CN, Wong KKL, Xie Q, Luginbuhl DJ, Li H, Udeshi ND, Svinkina T, Mani DR, Han S, Li T, Li Y, Guajardo R, Ting AY, Carr SA, Li J, Luo L. Molecular and cellular mechanisms of teneurin signaling in synaptic partner matching. Cell 2024; 187:5081-5101.e19. [PMID: 38996528 DOI: 10.1016/j.cell.2024.06.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 05/20/2024] [Accepted: 06/18/2024] [Indexed: 07/14/2024]
Abstract
In developing brains, axons exhibit remarkable precision in selecting synaptic partners among many non-partner cells. Evolutionarily conserved teneurins are transmembrane proteins that instruct synaptic partner matching. However, how intracellular signaling pathways execute teneurins' functions is unclear. Here, we use in situ proximity labeling to obtain the intracellular interactome of a teneurin (Ten-m) in the Drosophila brain. Genetic interaction studies using quantitative partner matching assays in both olfactory receptor neurons (ORNs) and projection neurons (PNs) reveal a common pathway: Ten-m binds to and negatively regulates a RhoGAP, thus activating the Rac1 small GTPases to promote synaptic partner matching. Developmental analyses with single-axon resolution identify the cellular mechanism of synaptic partner matching: Ten-m signaling promotes local F-actin levels and stabilizes ORN axon branches that contact partner PN dendrites. Combining spatial proteomics and high-resolution phenotypic analyses, this study advanced our understanding of both cellular and molecular mechanisms of synaptic partner matching.
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Affiliation(s)
- Chuanyun Xu
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Biology Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Zhuoran Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Biology Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Cheng Lyu
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Yixin Hu
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Biology Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Colleen N McLaughlin
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Kenneth Kin Lam Wong
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Qijing Xie
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Neurosciences Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - David J Luginbuhl
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Hongjie Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Namrata D Udeshi
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tanya Svinkina
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - D R Mani
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shuo Han
- Departments of Genetics, Biology, and Chemistry, Chan Zuckerberg Biohub, Stanford University, Stanford, CA 94305, USA
| | - Tongchao Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Yang Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Biology Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Ricardo Guajardo
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Alice Y Ting
- Departments of Genetics, Biology, and Chemistry, Chan Zuckerberg Biohub, Stanford University, Stanford, CA 94305, USA
| | - Steven A Carr
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jiefu Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Biology Graduate Program, Stanford University, Stanford, CA 94305, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
| | - Liqun Luo
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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3
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Lin Y, Ding Y, Chang S, Ge X, Sui X, Jiang Y. RS 2-Net: An end-to-end deep learning framework for rodent skull stripping in multi-center brain MRI. Neuroimage 2024; 298:120769. [PMID: 39122056 DOI: 10.1016/j.neuroimage.2024.120769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 08/01/2024] [Accepted: 08/02/2024] [Indexed: 08/12/2024] Open
Abstract
Skull stripping is a crucial preprocessing step in magnetic resonance imaging (MRI), where experts manually create brain masks. This labor-intensive process heavily relies on the annotator's expertise, as automation faces challenges such as low tissue contrast, significant variations in image resolution, and blurred boundaries between the brain and surrounding tissues, particularly in rodents. In this study, we have developed a lightweight framework based on Swin-UNETR to automate the skull stripping process in MRI scans of mice and rats. The primary objective of this framework is to eliminate the need for preprocessing, reduce the workload, and provide an out-of-the-box solution capable of adapting to various MRI image resolutions. By employing a lightweight neural network, we aim to lower the performance requirements of the framework. To validate the effectiveness of our approach, we trained and evaluated the network using publicly available multi-center data, encompassing 1,037 rodents and 1,142 images from 89 centers, resulting in a preliminary mean Dice coefficient of 0.9914. The framework, data, and pre-trained models can be found on the following link: https://github.com/VitoLin21/Rodent-Skull-Stripping.
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Affiliation(s)
| | | | | | - Xinting Ge
- Shandong Normal University, Jinan, China
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4
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McKim TH, Gera J, Gayban AJ, Reinhard N, Manoli G, Hilpert S, Helfrich-Förster C, Zandawala M. Synaptic connectome of a neurosecretory network in the Drosophila brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.28.609616. [PMID: 39257829 PMCID: PMC11384003 DOI: 10.1101/2024.08.28.609616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2024]
Abstract
Hormones mediate inter-organ signaling which is crucial in orchestrating diverse behaviors and physiological processes including sleep and activity, feeding, growth, metabolism and reproduction. The pars intercerebralis and pars lateralis in insects represent major hubs which contain neurosecretory cells (NSC) that produce various hormones. To obtain insight into how hormonal signaling is regulated, we have characterized the synaptic connectome of NSC in the adult Drosophila brain. Identification of neurons providing inputs to multiple NSC subtypes implicates diuretic hormone 44-expressing NSC as a major coordinator of physiology and behavior. Surprisingly, despite most NSC having dendrites in the subesophageal zone (primary taste processing center), gustatory inputs to NSC are largely indirect. We also deciphered pathways via which diverse olfactory inputs are relayed to NSC. Further, our analyses revealed substantial inputs from descending neurons to NSC, suggesting that descending neurons regulate both endocrine and motor output to synchronize physiological changes with appropriate behaviors. In contrast to NSC inputs, synaptic output from NSC is sparse and mostly mediated by corazonin NSC. Therefore, we additionally determine putative paracrine interconnectivity between NSC subtypes and hormonal pathways from NSC to peripheral tissues by analyzing single-cell transcriptomic datasets. Our comprehensive characterization of the Drosophila neurosecretory network connectome provides a platform to understand complex hormonal networks and how they orchestrate animal behaviors and physiology.
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Affiliation(s)
- Theresa H. McKim
- Integrative Neuroscience Program, University of Nevada Reno, Reno, 89557, NV, USA
- Department of Biology, University of Nevada Reno, Reno, 89557, NV, USA
| | - Jayati Gera
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Ariana J. Gayban
- Integrative Neuroscience Program, University of Nevada Reno, Reno, 89557, NV, USA
- Department of Biochemistry and Molecular Biology, University of Nevada Reno, Reno, 89557, NV, USA
| | - Nils Reinhard
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Giulia Manoli
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Selina Hilpert
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Charlotte Helfrich-Förster
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Meet Zandawala
- Integrative Neuroscience Program, University of Nevada Reno, Reno, 89557, NV, USA
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, 97074 Würzburg, Germany
- Department of Biochemistry and Molecular Biology, University of Nevada Reno, Reno, 89557, NV, USA
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5
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Thornton-Kolbe EM, Ahmed M, Gordon FR, Sieriebriennikov B, Williams DL, Kurmangaliyev YZ, Clowney EJ. Spatial constraints and cell surface molecule depletion structure a randomly connected learning circuit. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.17.603956. [PMID: 39071296 PMCID: PMC11275898 DOI: 10.1101/2024.07.17.603956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
The brain can represent almost limitless objects to "categorize an unlabeled world" (Edelman, 1989). This feat is supported by expansion layer circuit architectures, in which neurons carrying information about discrete sensory channels make combinatorial connections onto much larger postsynaptic populations. Combinatorial connections in expansion layers are modeled as randomized sets. The extent to which randomized wiring exists in vivo is debated, and how combinatorial connectivity patterns are generated during development is not understood. Non-deterministic wiring algorithms could program such connectivity using minimal genomic information. Here, we investigate anatomic and transcriptional patterns and perturb partner availability to ask how Kenyon cells, the expansion layer neurons of the insect mushroom body, obtain combinatorial input from olfactory projection neurons. Olfactory projection neurons form their presynaptic outputs in an orderly, predictable, and biased fashion. We find that Kenyon cells accept spatially co-located but molecularly heterogeneous inputs from this orderly map, and ask how Kenyon cell surface molecule expression impacts partner choice. Cell surface immunoglobulins are broadly depleted in Kenyon cells, and we propose that this allows them to form connections with molecularly heterogeneous partners. This model can explain how developmentally identical neurons acquire diverse wiring identities.
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Affiliation(s)
- Emma M. Thornton-Kolbe
- Neurosciences Graduate Program, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Maria Ahmed
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Finley R. Gordon
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | | | - Donnell L. Williams
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | | | - E. Josephine Clowney
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
- Michigan Neuroscience Institute, Ann Arbor, MI, USA
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6
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Meschi E, Duquenoy L, Otto N, Dempsey G, Waddell S. Compensatory enhancement of input maintains aversive dopaminergic reinforcement in hungry Drosophila. Neuron 2024; 112:2315-2332.e8. [PMID: 38795709 DOI: 10.1016/j.neuron.2024.04.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 03/12/2024] [Accepted: 04/30/2024] [Indexed: 05/28/2024]
Abstract
Hungry animals need compensatory mechanisms to maintain flexible brain function, while modulation reconfigures circuits to prioritize resource seeking. In Drosophila, hunger inhibits aversively reinforcing dopaminergic neurons (DANs) to permit the expression of food-seeking memories. Multitasking the reinforcement system for motivation potentially undermines aversive learning. We find that chronic hunger mildly enhances aversive learning and that satiated-baseline and hunger-enhanced learning require endocrine adipokinetic hormone (AKH) signaling. Circulating AKH influences aversive learning via its receptor in four neurons in the ventral brain, two of which are octopaminergic. Connectomics revealed AKH receptor-expressing neurons to be upstream of several classes of ascending neurons, many of which are presynaptic to aversively reinforcing DANs. Octopaminergic modulation of and output from at least one of these ascending pathways is required for shock- and bitter-taste-reinforced aversive learning. We propose that coordinated enhancement of input compensates for hunger-directed inhibition of aversive DANs to preserve reinforcement when required.
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Affiliation(s)
- Eleonora Meschi
- University of Oxford, Centre for Neural Circuits and Behaviour, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK
| | - Lucille Duquenoy
- University of Oxford, Centre for Neural Circuits and Behaviour, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK
| | - Nils Otto
- University of Oxford, Centre for Neural Circuits and Behaviour, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK
| | - Georgia Dempsey
- University of Oxford, Centre for Neural Circuits and Behaviour, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK
| | - Scott Waddell
- University of Oxford, Centre for Neural Circuits and Behaviour, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK.
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7
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Ganguly I, Heckman EL, Litwin-Kumar A, Clowney EJ, Behnia R. Diversity of visual inputs to Kenyon cells of the Drosophila mushroom body. Nat Commun 2024; 15:5698. [PMID: 38972924 PMCID: PMC11228034 DOI: 10.1038/s41467-024-49616-z] [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: 01/24/2024] [Accepted: 06/11/2024] [Indexed: 07/09/2024] Open
Abstract
The arthropod mushroom body is well-studied as an expansion layer representing olfactory stimuli and linking them to contingent events. However, 8% of mushroom body Kenyon cells in Drosophila melanogaster receive predominantly visual input, and their function remains unclear. Here, we identify inputs to visual Kenyon cells using the FlyWire adult whole-brain connectome. Input repertoires are similar across hemispheres and connectomes with certain inputs highly overrepresented. Many visual neurons presynaptic to Kenyon cells have large receptive fields, while interneuron inputs receive spatially restricted signals that may be tuned to specific visual features. Individual visual Kenyon cells randomly sample sparse inputs from combinations of visual channels, including multiple optic lobe neuropils. These connectivity patterns suggest that visual coding in the mushroom body, like olfactory coding, is sparse, distributed, and combinatorial. However, the specific input repertoire to the smaller population of visual Kenyon cells suggests a constrained encoding of visual stimuli.
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Affiliation(s)
- Ishani Ganguly
- Department of Neuroscience, Columbia University, New York, NY, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
| | - Emily L Heckman
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Ashok Litwin-Kumar
- Department of Neuroscience, Columbia University, New York, NY, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
| | - E Josephine Clowney
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA.
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA.
| | - Rudy Behnia
- Department of Neuroscience, Columbia University, New York, NY, USA.
- Zuckerman Institute, Columbia University, New York, NY, USA.
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
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8
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Gou L, Wang Y, Gao L, Zhong Y, Xie L, Wang H, Zha X, Shao Y, Xu H, Xu X, Yan J. Gapr for large-scale collaborative single-neuron reconstruction. Nat Methods 2024:10.1038/s41592-024-02345-z. [PMID: 38961277 DOI: 10.1038/s41592-024-02345-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 06/06/2024] [Indexed: 07/05/2024]
Abstract
Whole-brain analysis of single-neuron morphology is crucial for unraveling the complex structure of the brain. However, large-scale neuron reconstruction from terabyte and even petabyte data of mammalian brains generated by state-of-the-art light microscopy is a daunting task. Here, we developed 'Gapr' (Gapr accelerates projectome reconstruction) that streamlines deep learning-based automatic reconstruction, 'automatic proofreading' that reduces human workloads at high-confidence sites, and high-throughput collaborative proofreading by crowd users through the Internet. Furthermore, Gapr offers a seamless user interface that ensures high proofreading speed per annotator, on-demand conversion for handling large datasets, flexible workflows tailored to diverse datasets and rigorous error tracking for quality control. Finally, we demonstrated Gapr's efficacy by reconstructing over 4,000 neurons in mouse brains, revealing the morphological diversity in cortical interneurons and hypothalamic neurons. Here, we present Gapr as a solution for large-scale single-neuron reconstruction projects.
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Affiliation(s)
- Lingfeng Gou
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Yanzhi Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Shanghai, China
| | - Le Gao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Yiting Zhong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Shanghai, China
| | - Lucheng Xie
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Haifang Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Xi Zha
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Yinqi Shao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Huatai Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Xiaohong Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Jun Yan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China.
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9
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Leite J, Nhoatto F, Jacob A, Santana R, Lobato F. Computational Tools for Neuronal Morphometric Analysis: A Systematic Search and Review. Neuroinformatics 2024; 22:353-377. [PMID: 38922389 DOI: 10.1007/s12021-024-09674-6] [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] [Accepted: 06/08/2024] [Indexed: 06/27/2024]
Abstract
Morphometry is fundamental for studying and correlating neuronal morphology with brain functions. With increasing computational power, it is possible to extract morphometric characteristics automatically, including features such as length, volume, and number of neuron branches. However, to the best of our knowledge, there is no mapping of morphometric tools yet. In this context, we conducted a systematic search and review to identify and analyze tools within the scope of neuron analysis. Thus, the work followed a well-defined protocol and sought to answer the following research questions: What open-source tools are available for neuronal morphometric analysis? What morphometric characteristics are extracted by these tools? For this, aiming for greater robustness and coverage, the study was based on the paper analysis as well as the study of documentation and tests with the tools available in repositories. We analyzed 1,586 papers and mapped 23 tools, where NeuroM, L-Measure, and NeuroMorphoVis extract the most features. Furthermore, we contribute to the body of knowledge with the unprecedented presentation of 150 unique morphometric features whose terminologies were categorized and standardized. Overall, the study contributes to advancing the understanding of the complex mechanisms underlying the brain.
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Affiliation(s)
- Jéssica Leite
- Institute of Engineering and Geosciences, Federal University of Western Pará, Santarém, Pará, Brazil
| | - Fabiano Nhoatto
- Institute of Engineering and Geosciences, Federal University of Western Pará, Santarém, Pará, Brazil
| | - Antonio Jacob
- Department of Computer Engineering, State University of Maranhão, São Luís, Maranhão, Brazil
| | - Roberto Santana
- Department of Computer Science and Artificial Intelligence, University of the Basque Country, Donostia/San Sebastián, Guipúzcoa, Spain
| | - Fábio Lobato
- Institute of Engineering and Geosciences, Federal University of Western Pará, Santarém, Pará, Brazil.
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10
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Stürner T, Brooks P, Capdevila LS, Morris BJ, Javier A, Fang S, Gkantia M, Cachero S, Beckett IR, Champion AS, Moitra I, Richards A, Klemm F, Kugel L, Namiki S, Cheong HS, Kovalyak J, Tenshaw E, Parekh R, Schlegel P, Phelps JS, Mark B, Dorkenwald S, Bates AS, Matsliah A, Yu SC, McKellar CE, Sterling A, Seung S, Murthy M, Tuthill J, Lee WCA, Card GM, Costa M, Jefferis GS, Eichler K. Comparative connectomics of the descending and ascending neurons of the Drosophila nervous system: stereotypy and sexual dimorphism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.596633. [PMID: 38895426 PMCID: PMC11185702 DOI: 10.1101/2024.06.04.596633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and information bottleneck connecting the brain and the ventral nerve cord (VNC, spinal cord analogue) and comprises diverse populations of descending (DN), ascending (AN) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Integrating three separate EM datasets, we now provide a complete connectomic description of the ascending and descending neurons of the female nervous system of Drosophila and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions have been matched across hemispheres, datasets and sexes. Crucially, we have also matched 51% of DN cell types to light level data defining specific driver lines as well as classifying all ascending populations. We use these results to reveal the general architecture, tracts, neuropil innervation and connectivity of neck connective neurons. We observe connected chains of descending and ascending neurons spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analysis of circuits implicated in sex-related behaviours, including female ovipositor extrusion (DNp13), male courtship (DNa12/aSP22) and song production (AN hemilineage 08B). Our work represents the first EM-level circuit analyses spanning the entire central nervous system of an adult animal.
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Affiliation(s)
- Tomke Stürner
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Paul Brooks
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Billy J. Morris
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Alexandre Javier
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Siqi Fang
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Marina Gkantia
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Sebastian Cachero
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Andrew S. Champion
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Ilina Moitra
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Alana Richards
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Finja Klemm
- Genetics Department, Leipzig University, Leipzig, Germany
| | - Leonie Kugel
- Genetics Department, Leipzig University, Leipzig, Germany
| | - Shigehiro Namiki
- Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan
| | - Han S.J. Cheong
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
- Zuckerman Institute, Columbia University, New York, United States
| | - Julie Kovalyak
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Emily Tenshaw
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Ruchi Parekh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Jasper S. Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
- Brain Mind Institute & Institute of Bioengineering, EPFL, 1015 Lausanne, Switzerland
| | - Brandon Mark
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, USA
| | - Alexander S. Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
- Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Szi-chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Amy Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, USA
| | - Mala Murthy
- Computer Science Department, Princeton University, USA
| | - John Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Wei-Chung A. Lee
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
- FM Kirby Neurobiology Center, Boston Children’s Hospital, Boston, MA, USA
| | - Gwyneth M. Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
- Zuckerman Institute, Columbia University, New York, United States
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Gregory S.X.E. Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Genetics Department, Leipzig University, Leipzig, Germany
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11
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Eckstein N, Bates AS, Champion A, Du M, Yin Y, Schlegel P, Lu AKY, Rymer T, Finley-May S, Paterson T, Parekh R, Dorkenwald S, Matsliah A, Yu SC, McKellar C, Sterling A, Eichler K, Costa M, Seung S, Murthy M, Hartenstein V, Jefferis GSXE, Funke J. Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster. Cell 2024; 187:2574-2594.e23. [PMID: 38729112 PMCID: PMC11106717 DOI: 10.1016/j.cell.2024.03.016] [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: 04/02/2023] [Revised: 10/04/2023] [Accepted: 03/13/2024] [Indexed: 05/12/2024]
Abstract
High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.
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Affiliation(s)
- Nils Eckstein
- HHMI Janelia Research Campus, Ashburn, VA, USA; Institute of Neuroinformatics UZH/ETHZ, Zurich, Switzerland
| | - Alexander Shakeel Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK; Department of Neurobiology and Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Andrew Champion
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Michelle Du
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | - Yijie Yin
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | | | | | | | | | | | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Szi-Chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Claire McKellar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Amy Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Volker Hartenstein
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Gregory S X E Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK.
| | - Jan Funke
- HHMI Janelia Research Campus, Ashburn, VA, USA.
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12
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Hofbauer B, Zandawala M, Reinhard N, Rieger D, Werner C, Evers JF, Wegener C. The neuropeptide pigment-dispersing factor signals independently of Bruchpilot-labelled active zones in daily remodelled terminals of Drosophila clock neurons. Eur J Neurosci 2024; 59:2665-2685. [PMID: 38414155 DOI: 10.1111/ejn.16294] [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: 06/21/2023] [Revised: 02/06/2024] [Accepted: 02/08/2024] [Indexed: 02/29/2024]
Abstract
The small ventrolateral neurons (sLNvs) are key components of the central clock in the Drosophila brain. They signal via the neuropeptide pigment-dispersing factor (PDF) to align the molecular clockwork of different central clock neurons and to modulate downstream circuits. The dorsal terminals of the sLNvs undergo daily morphological changes that affect presynaptic sites organised by the active zone protein Bruchpilot (BRP), a homolog of mammalian ELKS proteins. However, the role of these presynaptic sites for PDF release is ill-defined. Here, we combined expansion microscopy with labelling of active zones by endogenously tagged BRP to examine the spatial correlation between PDF-containing dense-core vesicles and BRP-labelled active zones. We found that the number of BRP-labelled puncta in the sLNv terminals was similar while their density differed between Zeitgeber time (ZT) 2 and 14. The relative distance between BRP- and PDF-labelled puncta was increased in the morning, around the reported time of PDF release. Spontaneous dense-core vesicle release profiles of sLNvs in a publicly available ssTEM dataset (FAFB) consistently lacked spatial correlation to BRP-organised active zones. RNAi-mediated downregulation of brp and other active zone proteins expressed by the sLNvs did not affect PDF-dependent locomotor rhythmicity. In contrast, down-regulation of genes encoding proteins of the canonical vesicle release machinery, the dense-core vesicle-related protein CADPS, as well as PDF impaired locomotor rhythmicity. Taken together, our study suggests that PDF release from the sLNvs is independent of BRP-organised active zones, while BRP may be redistributed to active zones in a time-dependent manner.
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Affiliation(s)
- Benedikt Hofbauer
- Biocenter, Theodor-Boveri-Institute, Neurobiology and Genetics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Meet Zandawala
- Biocenter, Theodor-Boveri-Institute, Neurobiology and Genetics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
- Department of Biochemistry and Molecular Biology, University of Nevada Reno, Reno, NV, USA
| | - Nils Reinhard
- Biocenter, Theodor-Boveri-Institute, Neurobiology and Genetics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Dirk Rieger
- Biocenter, Theodor-Boveri-Institute, Neurobiology and Genetics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Christian Werner
- Biocenter, Theodor-Boveri-Institute, Department of Biotechnology and Biophysics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Jan Felix Evers
- Centre for organismal studies COS, Universität Heidelberg, Heidelberg, Germany
- Cairn GmbH, Heidelberg, Germany
| | - Christian Wegener
- Biocenter, Theodor-Boveri-Institute, Neurobiology and Genetics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
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13
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Eichler K, Hampel S, Alejandro-García A, Calle-Schuler SA, Santana-Cruz A, Kmecova L, Blagburn JM, Hoopfer ED, Seeds AM. Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila. eLife 2024; 12:RP87602. [PMID: 38634460 PMCID: PMC11026096 DOI: 10.7554/elife.87602] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024] Open
Abstract
Mechanosensory neurons located across the body surface respond to tactile stimuli and elicit diverse behavioral responses, from relatively simple stimulus location-aimed movements to complex movement sequences. How mechanosensory neurons and their postsynaptic circuits influence such diverse behaviors remains unclear. We previously discovered that Drosophila perform a body location-prioritized grooming sequence when mechanosensory neurons at different locations on the head and body are simultaneously stimulated by dust (Hampel et al., 2017; Seeds et al., 2014). Here, we identify nearly all mechanosensory neurons on the Drosophila head that individually elicit aimed grooming of specific head locations, while collectively eliciting a whole head grooming sequence. Different tracing methods were used to reconstruct the projections of these neurons from different locations on the head to their distinct arborizations in the brain. This provides the first synaptic resolution somatotopic map of a head, and defines the parallel-projecting mechanosensory pathways that elicit head grooming.
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Affiliation(s)
- Katharina Eichler
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Stefanie Hampel
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Adrián Alejandro-García
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Steven A Calle-Schuler
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Alexis Santana-Cruz
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Lucia Kmecova
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Jonathan M Blagburn
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
| | - Eric D Hoopfer
- Neuroscience Program, Carleton CollegeNorthfieldUnited States
| | - Andrew M Seeds
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences CampusSan JuanPuerto Rico
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14
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Sanfilippo P, Kim AJ, Bhukel A, Yoo J, Mirshahidi PS, Pandey V, Bevir H, Yuen A, Mirshahidi PS, Guo P, Li HS, Wohlschlegel JA, Aso Y, Zipursky SL. Mapping of multiple neurotransmitter receptor subtypes and distinct protein complexes to the connectome. Neuron 2024; 112:942-958.e13. [PMID: 38262414 PMCID: PMC10957333 DOI: 10.1016/j.neuron.2023.12.014] [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: 08/28/2023] [Revised: 12/03/2023] [Accepted: 12/20/2023] [Indexed: 01/25/2024]
Abstract
Neurons express various combinations of neurotransmitter receptor (NR) subunits and receive inputs from multiple neuron types expressing different neurotransmitters. Localizing NR subunits to specific synaptic inputs has been challenging. Here, we use epitope-tagged endogenous NR subunits, expansion light-sheet microscopy, and electron microscopy (EM) connectomics to molecularly characterize synapses in Drosophila. We show that in directionally selective motion-sensitive neurons, different multiple NRs elaborated a highly stereotyped molecular topography with NR localized to specific domains receiving cell-type-specific inputs. Developmental studies suggested that NRs or complexes of them with other membrane proteins determine patterns of synaptic inputs. In support of this model, we identify a transmembrane protein selectively associated with a subset of spatially restricted synapses and demonstrate its requirement for synapse formation through genetic analysis. We propose that mechanisms that regulate the precise spatial distribution of NRs provide a molecular cartography specifying the patterns of synaptic connections onto dendrites.
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Affiliation(s)
- Piero Sanfilippo
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Alexander J Kim
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Anuradha Bhukel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Juyoun Yoo
- Neuroscience Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Pegah S Mirshahidi
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Vijaya Pandey
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Harry Bevir
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Ashley Yuen
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Parmis S Mirshahidi
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Peiyi Guo
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Hong-Sheng Li
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - James A Wohlschlegel
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yoshinori Aso
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - S Lawrence Zipursky
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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15
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Cheong HSJ, Boone KN, Bennett MM, Salman F, Ralston JD, Hatch K, Allen RF, Phelps AM, Cook AP, Phelps JS, Erginkaya M, Lee WCA, Card GM, Daly KC, Dacks AM. Organization of an ascending circuit that conveys flight motor state in Drosophila. Curr Biol 2024; 34:1059-1075.e5. [PMID: 38402616 PMCID: PMC10939832 DOI: 10.1016/j.cub.2024.01.071] [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: 06/08/2023] [Revised: 12/08/2023] [Accepted: 01/29/2024] [Indexed: 02/27/2024]
Abstract
Natural behaviors are a coordinated symphony of motor acts that drive reafferent (self-induced) sensory activation. Individual sensors cannot disambiguate exafferent (externally induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to carry out adaptive behaviors through corollary discharge circuits (CDCs), which provide predictive motor signals from motor pathways to sensory processing and other motor pathways. Yet, how CDCs comprehensively integrate into the nervous system remains unexplored. Here, we use connectomics, neuroanatomical, physiological, and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs) in Drosophila, which function as a predictive CDC in other insects. Both AHN pairs receive input primarily from a partially overlapping population of descending neurons, especially from DNg02, which controls wing motor output. Using Ca2+ imaging and behavioral recordings, we show that AHN activation is correlated to flight behavior and precedes wing motion. Optogenetic activation of DNg02 is sufficient to activate AHNs, indicating that AHNs are activated by descending commands in advance of behavior and not as a consequence of sensory input. Downstream, each AHN pair targets predominantly non-overlapping networks, including those that process visual, auditory, and mechanosensory information, as well as networks controlling wing, haltere, and leg sensorimotor control. These results support the conclusion that the AHNs provide a predictive motor signal about wing motor state to mostly non-overlapping sensory and motor networks. Future work will determine how AHN signaling is driven by other descending neurons and interpreted by AHN downstream targets to maintain adaptive sensorimotor performance.
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Affiliation(s)
- Han S J Cheong
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Zuckerman Institute, Columbia University, New York, NY 10027, USA
| | - Kaitlyn N Boone
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Marryn M Bennett
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Farzaan Salman
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Jacob D Ralston
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Kaleb Hatch
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Raven F Allen
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Alec M Phelps
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Andrew P Cook
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA; Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Mert Erginkaya
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon 1400-038, Portugal
| | - Wei-Chung A Lee
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Zuckerman Institute, Columbia University, New York, NY 10027, USA
| | - Kevin C Daly
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Department of Neuroscience, West Virginia University, Morgantown, WV 26505, USA
| | - Andrew M Dacks
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Department of Neuroscience, West Virginia University, Morgantown, WV 26505, USA.
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16
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Tao L, Ayembem D, Barranca VJ, Bhandawat V. Neurons underlying aggressive actions that are shared by both males and females in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582148. [PMID: 38464020 PMCID: PMC10925114 DOI: 10.1101/2024.02.26.582148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Aggression involves both sexually monomorphic and dimorphic actions. How the brain implements these two types of actions is poorly understood. We found that a set of neurons, which we call CL062, previously shown to mediate male aggression also mediate female aggression. These neurons elicit aggression acutely and without the presence of a target. Although the same set of actions is elicited in males and females, the overall behavior is sexually dimorphic. The CL062 neurons do not express fruitless , a gene required for sexual dimorphism in flies, and expressed by most other neurons important for controlling fly aggression. Connectomic analysis suggests that these neurons have limited connections with fruitless expressing neurons that have been shown to be important for aggression, and signal to different descending neurons. Thus, CL062 is part of a monomorphic circuit for aggression that functions parallel to the known dimorphic circuits.
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17
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Brezovec BE, Berger AB, Hao YA, Chen F, Druckmann S, Clandinin TR. Mapping the neural dynamics of locomotion across the Drosophila brain. Curr Biol 2024; 34:710-726.e4. [PMID: 38242122 DOI: 10.1016/j.cub.2023.12.063] [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: 08/16/2023] [Revised: 11/13/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024]
Abstract
Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.
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Affiliation(s)
- Bella E Brezovec
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Andrew B Berger
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Yukun A Hao
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Feng Chen
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA.
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18
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Jagannathan SR, Jeans T, Van De Poll MN, van Swinderen B. Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies. SCIENCE ADVANCES 2024; 10:eadj4399. [PMID: 38381836 PMCID: PMC10881036 DOI: 10.1126/sciadv.adj4399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 01/18/2024] [Indexed: 02/23/2024]
Abstract
Identifying different sleep stages in humans and other mammals has traditionally relied on electroencephalograms. Such an approach is not feasible in certain animals such as invertebrates, although these animals could also be sleeping in stages. Here, we perform long-term multichannel local field potential recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We acquired consistent spatial recordings of local field potentials across multiple flies, allowing us to compare brain activity across awake and sleep periods. Using machine learning, we uncover distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of microbehaviors associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.
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Affiliation(s)
- Sridhar R. Jagannathan
- Department of Psychology, University of Cambridge, Cambridge, UK
- Institute of Neurophysiology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Travis Jeans
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD Australia
| | | | - Bruno van Swinderen
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD Australia
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19
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Westeinde EA, Kellogg E, Dawson PM, Lu J, Hamburg L, Midler B, Druckmann S, Wilson RI. Transforming a head direction signal into a goal-oriented steering command. Nature 2024; 626:819-826. [PMID: 38326621 PMCID: PMC10881397 DOI: 10.1038/s41586-024-07039-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/05/2024] [Indexed: 02/09/2024]
Abstract
To navigate, we must continuously estimate the direction we are headed in, and we must correct deviations from our goal1. Direction estimation is accomplished by ring attractor networks in the head direction system2,3. However, we do not fully understand how the sense of direction is used to guide action. Drosophila connectome analyses4,5 reveal three cell populations (PFL3R, PFL3L and PFL2) that connect the head direction system to the locomotor system. Here we use imaging, electrophysiology and chemogenetic stimulation during navigation to show how these populations function. Each population receives a shifted copy of the head direction vector, such that their three reference frames are shifted approximately 120° relative to each other. Each cell type then compares its own head direction vector with a common goal vector; specifically, it evaluates the congruence of these vectors via a nonlinear transformation. The output of all three cell populations is then combined to generate locomotor commands. PFL3R cells are recruited when the fly is oriented to the left of its goal, and their activity drives rightward turning; the reverse is true for PFL3L. Meanwhile, PFL2 cells increase steering speed, and are recruited when the fly is oriented far from its goal. PFL2 cells adaptively increase the strength of steering as directional error increases, effectively managing the tradeoff between speed and accuracy. Together, our results show how a map of space in the brain can be combined with an internal goal to generate action commands, via a transformation from world-centric coordinates to body-centric coordinates.
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Affiliation(s)
| | - Emily Kellogg
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Paul M Dawson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jenny Lu
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Lydia Hamburg
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Benjamin Midler
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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20
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Eichler K, Hampel S, Alejandro-García A, Calle-Schuler SA, Santana-Cruz A, Kmecova L, Blagburn JM, Hoopfer ED, Seeds AM. Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.11.528119. [PMID: 36798384 PMCID: PMC9934617 DOI: 10.1101/2023.02.11.528119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Mechanosensory neurons located across the body surface respond to tactile stimuli and elicit diverse behavioral responses, from relatively simple stimulus location-aimed movements to complex movement sequences. How mechanosensory neurons and their postsynaptic circuits influence such diverse behaviors remains unclear. We previously discovered that Drosophila perform a body location-prioritized grooming sequence when mechanosensory neurons at different locations on the head and body are simultaneously stimulated by dust (Hampel et al., 2017; Seeds et al., 2014). Here, we identify nearly all mechanosensory neurons on the Drosophila head that individually elicit aimed grooming of specific head locations, while collectively eliciting a whole head grooming sequence. Different tracing methods were used to reconstruct the projections of these neurons from different locations on the head to their distinct arborizations in the brain. This provides the first synaptic resolution somatotopic map of a head, and defines the parallel-projecting mechanosensory pathways that elicit head grooming.
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Affiliation(s)
- Katharina Eichler
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
- Contributed equally
| | - Stefanie Hampel
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
- Contributed equally
| | - Adrián Alejandro-García
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
- Contributed equally
| | - Steven A Calle-Schuler
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
| | - Alexis Santana-Cruz
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
| | - Lucia Kmecova
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
- Neuroscience Program, Carleton College, Northfield, Minnesota
- Contributed equally
| | - Jonathan M Blagburn
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
| | - Eric D Hoopfer
- Neuroscience Program, Carleton College, Northfield, Minnesota
| | - Andrew M Seeds
- Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico
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21
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Mehta K, Ljungquist B, Ogden J, Nanda S, Ascoli RG, Ng L, Ascoli GA. Online conversion of reconstructed neural morphologies into standardized SWC format. Nat Commun 2023; 14:7429. [PMID: 37973857 PMCID: PMC10654402 DOI: 10.1038/s41467-023-42931-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023] Open
Abstract
Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. In addition, we introduce xyz2swc, a free online service that converts all 26 reconstruction formats (and 72 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface ( https://neuromorpho.org/xyz2swc/ui/ ) and an Application Programming Interface (API).
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Affiliation(s)
- Ketan Mehta
- Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA
| | - Bengt Ljungquist
- Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA
| | - James Ogden
- Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA
| | - Sumit Nanda
- Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA
| | - Ruben G Ascoli
- Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Giorgio A Ascoli
- Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA.
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22
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Mancini N, Thoener J, Tafani E, Pauls D, Mayseless O, Strauch M, Eichler K, Champion A, Kobler O, Weber D, Sen E, Weiglein A, Hartenstein V, Chytoudis-Peroudis CC, Jovanic T, Thum AS, Rohwedder A, Schleyer M, Gerber B. Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval Drosophila. J Neurosci 2023; 43:7393-7428. [PMID: 37734947 PMCID: PMC10621887 DOI: 10.1523/jneurosci.2310-22.2023] [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: 12/17/2022] [Revised: 07/19/2023] [Accepted: 08/26/2023] [Indexed: 09/23/2023] Open
Abstract
Larvae of the fruit fly Drosophila melanogaster are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL). Using behavioral and connectomic analyses, optogenetics, Ca2+ imaging, and pharmacology, we study how APL affects associative olfactory memory. We first provide a detailed account of the structure, regional polarity, connectivity, and metamorphic development of APL, and further confirm that optogenetic activation of APL has an inhibiting effect on its main targets, the mushroom body Kenyon cells. All these findings are consistent with the previously identified function of APL in the sparsening of sensory representations. To our surprise, however, we found that optogenetically activating APL can also have a strong rewarding effect. Specifically, APL activation together with odor presentation establishes an odor-specific, appetitive, associative short-term memory, whereas naive olfactory behavior remains unaffected. An acute, systemic inhibition of dopamine synthesis as well as an ablation of the dopaminergic pPAM neurons impair reward learning through APL activation. Our findings provide a study case of complex circuit function in a numerically simple brain, and suggest a previously unrecognized capacity of central-brain GABAergic neurons to engage in dopaminergic reinforcement.SIGNIFICANCE STATEMENT The single, identified giant anterior paired lateral (APL) neuron is one of the most complex neurons in the insect brain. It is GABAergic and contributes to the sparsening of neuronal activity in the mushroom body, the memory center of insects. We provide the most detailed account yet of the structure of APL in larval Drosophila as a neurogenetically accessible study case. We further reveal that, contrary to expectations, the experimental activation of APL can exert a rewarding effect, likely via dopaminergic reward pathways. The present study both provides an example of unexpected circuit complexity in a numerically simple brain, and reports an unexpected effect of activity in central-brain GABAergic circuits.
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Affiliation(s)
- Nino Mancini
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Juliane Thoener
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Esmeralda Tafani
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Dennis Pauls
- Department of Animal Physiology, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Oded Mayseless
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Martin Strauch
- Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, 52074, Germany
| | - Katharina Eichler
- Institute of Neurobiology, University of Puerto Rico Medical Science Campus, Old San Juan, Puerto Rico, 00901
| | - Andrew Champion
- Department of Physiology, Development and Neuroscience, Cambridge University, Cambridge, CB2 3EL, United Kingdom
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, 20147, Virginia
| | - Oliver Kobler
- Leibniz Institute for Neurobiology, Combinatorial Neuroimaging Core Facility, Magdeburg, 39118, Germany
| | - Denise Weber
- Department of Genetics, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Edanur Sen
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Aliće Weiglein
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Volker Hartenstein
- University of California, Department of Molecular, Cell and Developmental Biology, Los Angeles, California 90095-1606
| | | | - Tihana Jovanic
- Université Paris-Saclay, Centre National de la Recherche Scientifique, Institut des neurosciences Paris-Saclay, Saclay, 91400, France
| | - Andreas S Thum
- Department of Genetics, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Astrid Rohwedder
- Department of Genetics, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Michael Schleyer
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Bertram Gerber
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
- Center for Behavioral Brain Sciences, Magdeburg, 39106, Germany
- Institute for Biology, Otto von Guericke University, Magdeburg, 39120, Germany
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23
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Jovanoski KD, Duquenoy L, Mitchell J, Kapoor I, Treiber CD, Croset V, Dempsey G, Parepalli S, Cognigni P, Otto N, Felsenberg J, Waddell S. Dopaminergic systems create reward seeking despite adverse consequences. Nature 2023; 623:356-365. [PMID: 37880370 PMCID: PMC10632144 DOI: 10.1038/s41586-023-06671-8] [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: 07/04/2022] [Accepted: 09/22/2023] [Indexed: 10/27/2023]
Abstract
Resource-seeking behaviours are ordinarily constrained by physiological needs and threats of danger, and the loss of these controls is associated with pathological reward seeking1. Although dysfunction of the dopaminergic valuation system of the brain is known to contribute towards unconstrained reward seeking2,3, the underlying reasons for this behaviour are unclear. Here we describe dopaminergic neural mechanisms that produce reward seeking despite adverse consequences in Drosophila melanogaster. Odours paired with optogenetic activation of a defined subset of reward-encoding dopaminergic neurons become cues that starved flies seek while neglecting food and enduring electric shock punishment. Unconstrained seeking of reward is not observed after learning with sugar or synthetic engagement of other dopaminergic neuron populations. Antagonism between reward-encoding and punishment-encoding dopaminergic neurons accounts for the perseverance of reward seeking despite punishment, whereas synthetic engagement of the reward-encoding dopaminergic neurons also impairs the ordinary need-dependent dopaminergic valuation of available food. Connectome analyses reveal that the population of reward-encoding dopaminergic neurons receives highly heterogeneous input, consistent with parallel representation of diverse rewards, and recordings demonstrate state-specific gating and satiety-related signals. We propose that a similar dopaminergic valuation system dysfunction is likely to contribute to maladaptive seeking of rewards by mammals.
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Affiliation(s)
| | - Lucille Duquenoy
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
| | - Jessica Mitchell
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Ishaan Kapoor
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
| | | | - Vincent Croset
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
- Department of Biosciences, Durham University, Durham, UK
| | - Georgia Dempsey
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
| | - Sai Parepalli
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
| | - Paola Cognigni
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
- Northern Medical Physics and Clinical Engineering, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Nils Otto
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
- Institute of Anatomy and Molecular Neurobiology, Westfälische Wilhelms-University, Münster, Germany
| | - Johannes Felsenberg
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Scott Waddell
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK.
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24
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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.
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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
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25
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Zhao A, Nern A, Koskela S, Dreher M, Erginkaya M, Laughland CW, Ludwigh H, Thomson A, Hoeller J, Parekh R, Romani S, Bock DD, Chiappe E, Reiser MB. A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.16.562634. [PMID: 37904921 PMCID: PMC10614863 DOI: 10.1101/2023.10.16.562634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.
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Affiliation(s)
- Arthur Zhao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Sanna Koskela
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Marisa Dreher
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Mert Erginkaya
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Connor W Laughland
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Henrique Ludwigh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Alex Thomson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Judith Hoeller
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Ruchi Parekh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Sandro Romani
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Davi D Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
- Department of Neurological Sciences, Larner College of Medicine, University of Vermont, USA
| | - Eugenia Chiappe
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Michael B Reiser
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
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26
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Ganguly I, Heckman EL, Litwin-Kumar A, Clowney EJ, Behnia R. Diversity of visual inputs to Kenyon cells of the Drosophila mushroom body. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.12.561793. [PMID: 37873086 PMCID: PMC10592809 DOI: 10.1101/2023.10.12.561793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The arthropod mushroom body is well-studied as an expansion layer that represents olfactory stimuli and links them to contingent events. However, 8% of mushroom body Kenyon cells in Drosophila melanogaster receive predominantly visual input, and their tuning and function are poorly understood. Here, we use the FlyWire adult whole-brain connectome to identify inputs to visual Kenyon cells. The types of visual neurons we identify are similar across hemispheres and connectomes with certain inputs highly overrepresented. Many visual projection neurons presynaptic to Kenyon cells receive input from large swathes of visual space, while local visual interneurons, providing smaller fractions of input, receive more spatially restricted signals that may be tuned to specific features of the visual scene. Like olfactory Kenyon cells, visual Kenyon cells receive sparse inputs from different combinations of visual channels, including inputs from multiple optic lobe neuropils. The sets of inputs to individual visual Kenyon cells are consistent with random sampling of available inputs. These connectivity patterns suggest that visual coding in the mushroom body, like olfactory coding, is sparse, distributed, and combinatorial. However, the expansion coding properties appear different, with a specific repertoire of visual inputs projecting onto a relatively small number of visual Kenyon cells.
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Affiliation(s)
- Ishani Ganguly
- The Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - Emily L Heckman
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Ashok Litwin-Kumar
- The Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - E Josephine Clowney
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
- Michigan Neuroscience Institute Affiliate
| | - Rudy Behnia
- The Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA
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27
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Sanfilippo P, Kim AJ, Bhukel A, Yoo J, Mirshahidi PS, Pandey V, Bevir H, Yuen A, Mirshahidi PS, Guo P, Li HS, Wohlschlegel JA, Aso Y, Zipursky SL. Mapping of multiple neurotransmitter receptor subtypes and distinct protein complexes to the connectome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.02.560011. [PMID: 37873314 PMCID: PMC10592863 DOI: 10.1101/2023.10.02.560011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Neurons express different combinations of neurotransmitter receptor (NR) subunits and receive inputs from multiple neuron types expressing different neurotransmitters. Localizing NR subunits to specific synaptic inputs has been challenging. Here we use epitope tagged endogenous NR subunits, expansion light-sheet microscopy, and EM connectomics to molecularly characterize synapses in Drosophila. We show that in directionally selective motion sensitive neurons, different multiple NRs elaborated a highly stereotyped molecular topography with NR localized to specific domains receiving cell-type specific inputs. Developmental studies suggested that NRs or complexes of them with other membrane proteins determines patterns of synaptic inputs. In support of this model, we identify a transmembrane protein associated selectively with a subset of spatially restricted synapses and demonstrate through genetic analysis its requirement for synapse formation. We propose that mechanisms which regulate the precise spatial distribution of NRs provide a molecular cartography specifying the patterns of synaptic connections onto dendrites.
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Affiliation(s)
- Piero Sanfilippo
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexander J Kim
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Anuradha Bhukel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Juyoun Yoo
- Neuroscience Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Pegah S Mirshahidi
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Vijaya Pandey
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Harry Bevir
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Ashley Yuen
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Parmis S Mirshahidi
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Peiyi Guo
- Department of Neurobiology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Hong-Sheng Li
- Department of Neurobiology, University of Massachusetts Medical School, Worcester, MA, USA
| | - James A Wohlschlegel
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Yoshinori Aso
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - S Lawrence Zipursky
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Lead Contact
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28
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Mabuchi Y, Cui X, Xie L, Kim H, Jiang T, Yapici N. Visual feedback neurons fine-tune Drosophila male courtship via GABA-mediated inhibition. Curr Biol 2023; 33:3896-3910.e7. [PMID: 37673068 PMCID: PMC10529139 DOI: 10.1016/j.cub.2023.08.034] [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: 02/09/2023] [Revised: 06/27/2023] [Accepted: 08/11/2023] [Indexed: 09/08/2023]
Abstract
Many species of animals use vision to regulate their social behaviors. However, the molecular and circuit mechanisms underlying visually guided social interactions remain largely unknown. Here, we show that the Drosophila ortholog of the human GABAA-receptor-associated protein (GABARAP) is required in a class of visual feedback neurons, lamina tangential (Lat) cells, to fine-tune male courtship. GABARAP is a ubiquitin-like protein that maintains cell-surface levels of GABAA receptors. We demonstrate that knocking down GABARAP or GABAAreceptors in Lat neurons or hyperactivating them induces male courtship toward other males. Inhibiting Lat neurons, on the other hand, delays copulation by impairing the ability of males to follow females. Remarkably, the fly GABARAP protein and its human ortholog share a strong sequence identity, and the fly GABARAP function in Lat neurons can be rescued by its human ortholog. Using in vivo two-photon imaging and optogenetics, we reveal that Lat neurons are functionally connected to neural circuits that mediate visually guided courtship pursuits in males. Our work identifies a novel physiological function for GABARAP in regulating visually guided courtship pursuits in Drosophila males. Reduced GABAA signaling has been linked to social deficits observed in the autism spectrum and bipolar disorders. The functional similarity between the human and the fly GABARAP raises the possibility of a conserved role for this gene in regulating social behaviors across insects and mammals.
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Affiliation(s)
- Yuta Mabuchi
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Xinyue Cui
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Lily Xie
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Haein Kim
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Tianxing Jiang
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Nilay Yapici
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA.
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29
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Yoo J, Dombrovski M, Mirshahidi P, Nern A, LoCascio SA, Zipursky SL, Kurmangaliyev YZ. Brain wiring determinants uncovered by integrating connectomes and transcriptomes. Curr Biol 2023; 33:3998-4005.e6. [PMID: 37647901 DOI: 10.1016/j.cub.2023.08.020] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/12/2023] [Accepted: 08/04/2023] [Indexed: 09/01/2023]
Abstract
Advances in brain connectomics have demonstrated the extraordinary complexity of neural circuits.1,2,3,4,5 Developing neurons encounter the axons and dendrites of many different neuron types and form synapses with only a subset of them. During circuit assembly, neurons express cell-type-specific repertoires comprising many cell adhesion molecules (CAMs) that can mediate interactions between developing neurites.6,7,8 Many CAM families have been shown to contribute to brain wiring in different ways.9,10 It has been challenging, however, to identify receptor-ligand pairs directly matching neurons with their synaptic targets. Here, we integrated the synapse-level connectome of the neural circuit11,12 with the developmental expression patterns7 and binding specificities of CAMs6,13 on pre- and postsynaptic neurons in the Drosophila visual system. To overcome the complexity of neural circuits, we focus on pairs of genetically related neurons that make differential wiring choices. In the motion detection circuit,14 closely related subtypes of T4/T5 neurons choose between alternative synaptic targets in adjacent layers of neuropil.12 This choice correlates with the matching expression in synaptic partners of different receptor-ligand pairs of the Beat and Side families of CAMs. Genetic analysis demonstrated that presynaptic Side-II and postsynaptic Beat-VI restrict synaptic partners to the same layer. Removal of this receptor-ligand pair disrupts layers and leads to inappropriate targeting of presynaptic sites and postsynaptic dendrites. We propose that different Side/Beat receptor-ligand pairs collaborate with other recognition molecules to determine wiring specificities in the fly brain. Combining transcriptomes, connectomes, and protein interactome maps allow unbiased identification of determinants of brain wiring.
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Affiliation(s)
- Juyoun Yoo
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Neuroscience Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mark Dombrovski
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Parmis Mirshahidi
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Samuel A LoCascio
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - S Lawrence Zipursky
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Yerbol Z Kurmangaliyev
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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30
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González Segarra AJ, Pontes G, Jourjine N, Del Toro A, Scott K. Hunger- and thirst-sensing neurons modulate a neuroendocrine network to coordinate sugar and water ingestion. eLife 2023; 12:RP88143. [PMID: 37732734 PMCID: PMC10513480 DOI: 10.7554/elife.88143] [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] [Indexed: 09/22/2023] Open
Abstract
Consumption of food and water is tightly regulated by the nervous system to maintain internal nutrient homeostasis. Although generally considered independently, interactions between hunger and thirst drives are important to coordinate competing needs. In Drosophila, four neurons called the interoceptive subesophageal zone neurons (ISNs) respond to intrinsic hunger and thirst signals to oppositely regulate sucrose and water ingestion. Here, we investigate the neural circuit downstream of the ISNs to examine how ingestion is regulated based on internal needs. Utilizing the recently available fly brain connectome, we find that the ISNs synapse with a novel cell-type bilateral T-shaped neuron (BiT) that projects to neuroendocrine centers. In vivo neural manipulations revealed that BiT oppositely regulates sugar and water ingestion. Neuroendocrine cells downstream of ISNs include several peptide-releasing and peptide-sensing neurons, including insulin producing cells (IPCs), crustacean cardioactive peptide (CCAP) neurons, and CCHamide-2 receptor isoform RA (CCHa2R-RA) neurons. These neurons contribute differentially to ingestion of sugar and water, with IPCs and CCAP neurons oppositely regulating sugar and water ingestion, and CCHa2R-RA neurons modulating only water ingestion. Thus, the decision to consume sugar or water occurs via regulation of a broad peptidergic network that integrates internal signals of nutritional state to generate nutrient-specific ingestion.
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Affiliation(s)
| | - Gina Pontes
- University of California, BerkeleyBerkeleyUnited States
| | | | | | - Kristin Scott
- University of California, BerkeleyBerkeleyUnited States
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31
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Sizemore TR, Jonaitis J, Dacks AM. Heterogeneous receptor expression underlies non-uniform peptidergic modulation of olfaction in Drosophila. Nat Commun 2023; 14:5280. [PMID: 37644052 PMCID: PMC10465596 DOI: 10.1038/s41467-023-41012-3] [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: 02/02/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023] Open
Abstract
Sensory systems are dynamically adjusted according to the animal's ongoing needs by neuromodulators, such as neuropeptides. Neuropeptides are often widely-distributed throughout sensory networks, but it is unclear whether such neuropeptides uniformly modulate network activity. Here, we leverage the Drosophila antennal lobe (AL) to resolve whether myoinhibitory peptide (MIP) uniformly modulates AL processing. Despite being uniformly distributed across the AL, MIP decreases olfactory input to some glomeruli, while increasing olfactory input to other glomeruli. We reveal that a heterogeneous ensemble of local interneurons (LNs) are the sole source of AL MIP, and show that differential expression of the inhibitory MIP receptor across glomeruli allows MIP to act on distinct intraglomerular substrates. Our findings demonstrate how even a seemingly simple case of modulation can have complex consequences on network processing by acting non-uniformly within different components of the overall network.
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Affiliation(s)
- Tyler R Sizemore
- Department of Biology, Life Sciences Building, West Virginia University, Morgantown, WV, 26506, USA.
- Department of Molecular, Cellular, and Developmental Biology, Yale Science Building, Yale University, New Haven, CT, 06520-8103, USA.
| | - Julius Jonaitis
- Department of Biology, Life Sciences Building, West Virginia University, Morgantown, WV, 26506, USA
| | - Andrew M Dacks
- Department of Biology, Life Sciences Building, West Virginia University, Morgantown, WV, 26506, USA.
- Department of Neuroscience, West Virginia University, Morgantown, WV, 26506, USA.
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32
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Cole AA, Reese TS. Transsynaptic Assemblies Link Domains of Presynaptic and Postsynaptic Intracellular Structures across the Synaptic Cleft. J Neurosci 2023; 43:5883-5892. [PMID: 37369583 PMCID: PMC10436760 DOI: 10.1523/jneurosci.2195-22.2023] [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: 11/28/2022] [Revised: 06/06/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
The chemical synapse is a complex machine separated into three parts: presynaptic, postsynaptic, and cleft. Super-resolution light microscopy has revealed alignment of presynaptic vesicle release machinery and postsynaptic neurotransmitter-receptors and scaffolding components in synapse spanning nanocolumns. Cryo-electron tomography confirmed that postsynaptic glutamate receptor-like structures align with presynaptic structures in proximity to synaptic vesicles into transsynaptic assemblies. In our electron tomographic renderings, nearly all transcleft structures visibly connect to intracellular structures through transmembrane structures to form transsynaptic assemblies, potentially providing a structural basis for transsynaptic alignment. Here, we describe the patterns of composition, distribution, and interactions of all assemblies spanning the synapse by producing three-dimensional renderings of all visibly connected structures in excitatory and inhibitory synapses in dissociated rat hippocampal neuronal cultures of both sexes prepared by high-pressure freezing and freeze-substitution. The majority of transcleft structures connect to material in both presynaptic and postsynaptic compartments. We found several instances of assemblies connecting to both synaptic vesicles and postsynaptic density scaffolding. Each excitatory synaptic vesicle within 30 nm of the active zone contacts one or more assembly. Further, intracellular structures were often shared between assemblies, entangling them to form larger complexes or association domains, often in small clusters of vesicles. Our findings suggest that transsynaptic assemblies physically connect the three compartments, allow for coordinated molecular organization, and may combine to form specialized functional association domains, resembling the light-level nanocolumns.SIGNIFICANCE STATEMENT A recent tomographic study uncovered that receptor-like cleft structures align across the synapse. These aligned structures were designated as transsynaptic assemblies and demonstrate the coordinated organization of synaptic transmission molecules between compartments. Our present tomographic study expands on the definition of transsynaptic assemblies by analyzing the three-dimensional distribution and connectivity of all cleft-spanning structures and their connected intracellular structures. While one-to-one component alignment occurs across the synapse, we find that many assemblies share components, leading to a complex entanglement of assemblies, typically around clusters of synaptic vesicles. Transsynaptic assemblies appear to form domains which may be the structural basis for alignment of molecular nanodomains into synapse spanning nanocolumns described by super-resolution light microscopy.
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Affiliation(s)
- Andy A Cole
- Laboratory of Neurobiology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892
| | - Thomas S Reese
- Laboratory of Neurobiology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892
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Dorkenwald S, Schneider-Mizell CM, Brittain D, Halageri A, Jordan C, Kemnitz N, Castro MA, Silversmith W, Maitin-Shephard J, Troidl J, Pfister H, Gillet V, Xenes D, Bae JA, Bodor AL, Buchanan J, Bumbarger DJ, Elabbady L, Jia Z, Kapner D, Kinn S, Lee K, Li K, Lu R, Macrina T, Mahalingam G, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Takeno M, Torres R, Turner NL, Wong W, Wu J, Yin W, Yu SC, Reid RC, da Costa NM, Seung HS, Collman F. CAVE: Connectome Annotation Versioning Engine. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.26.550598. [PMID: 37546753 PMCID: PMC10402030 DOI: 10.1101/2023.07.26.550598] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets (~1mm3) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVE's data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date.
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Affiliation(s)
- Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | | | | | - Akhilesh Halageri
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Chris Jordan
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Manual A. Castro
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | | | - Jakob Troidl
- School of Engineering and Applied Sciences, Harvard University, Boston, USA
| | - Hanspeter Pfister
- School of Engineering and Applied Sciences, Harvard University, Boston, USA
| | - Valentin Gillet
- Lund University, Department of Biology, Lund Vision Group, Lund, Sweden
| | - Daniel Xenes
- Research & Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, United States
| | - J. Alexander Bae
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Electrical and Computer Engineering Department, Princeton University, Princeton, USA
| | | | | | | | | | - Zhen Jia
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | | | - Sam Kinn
- Allen Institute for Brain Science, Seattle, USA
| | - Kisuk Lee
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Brain & Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, USA
| | - Kai Li
- Computer Science Department, Princeton University, Princeton, USA
| | - Ran Lu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Thomas Macrina
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | | | - Eric Mitchell
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Shanka Subhra Mondal
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Electrical and Computer Engineering Department, Princeton University, Princeton, USA
| | - Shang Mu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Barak Nehoran
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Sergiy Popovych
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Marc Takeno
- Allen Institute for Brain Science, Seattle, USA
| | | | - Nicholas L. Turner
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - William Wong
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Jingpeng Wu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Wenjing Yin
- Allen Institute for Brain Science, Seattle, USA
| | - Szi-chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | | | - H. Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
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34
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Schlegel P, Yin Y, Bates AS, Dorkenwald S, Eichler K, Brooks P, Han DS, Gkantia M, Dos Santos M, Munnelly EJ, Badalamente G, Capdevila LS, Sane VA, Pleijzier MW, Tamimi IFM, Dunne CR, Salgarella I, Javier A, Fang S, Perlman E, Kazimiers T, Jagannathan SR, Matsliah A, Sterling AR, Yu SC, McKellar CE, Costa M, Seung HS, Murthy M, Hartenstein V, Bock DD, Jefferis GSXE. Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.27.546055. [PMID: 37425808 PMCID: PMC10327018 DOI: 10.1101/2023.06.27.546055] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.
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Keto L, Manninen T. CellRemorph: A Toolkit for Transforming, Selecting, and Slicing 3D Cell Structures on the Road to Morphologically Detailed Astrocyte Simulations. Neuroinformatics 2023; 21:483-500. [PMID: 37133688 PMCID: PMC10406679 DOI: 10.1007/s12021-023-09627-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 05/04/2023]
Abstract
Understanding functions of astrocytes can be greatly enhanced by building and simulating computational models that capture their morphological details. Novel computational tools enable utilization of existing morphological data of astrocytes and building models that have appropriate level of details for specific simulation purposes. In addition to analyzing existing computational tools for constructing, transforming, and assessing astrocyte morphologies, we present here the CellRemorph toolkit implemented as an add-on for Blender, a 3D modeling platform increasingly recognized for its utility for manipulating 3D biological data. To our knowledge, CellRemorph is the first toolkit for transforming astrocyte morphologies from polygonal surface meshes into adjustable surface point clouds and vice versa, precisely selecting nanoprocesses, and slicing morphologies into segments with equal surface areas or volumes. CellRemorph is an open-source toolkit under the GNU General Public License and easily accessible via an intuitive graphical user interface. CellRemorph will be a valuable addition to other Blender add-ons, providing novel functionality that facilitates the creation of realistic astrocyte morphologies for different types of morphologically detailed simulations elucidating the role of astrocytes both in health and disease.
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Affiliation(s)
- Laura Keto
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
| | - Tiina Manninen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
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36
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González-Segarra AJ, Pontes G, Jourjine N, Del Toro A, Scott K. Hunger- and thirst-sensing neurons modulate a neuroendocrine network to coordinate sugar and water ingestion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.06.535891. [PMID: 37066363 PMCID: PMC10104137 DOI: 10.1101/2023.04.06.535891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Consumption of food and water is tightly regulated by the nervous system to maintain internal nutrient homeostasis. Although generally considered independently, interactions between hunger and thirst drives are important to coordinate competing needs. In Drosophila , four neurons called the Interoceptive Subesophageal zone Neurons (ISNs) respond to intrinsic hunger and thirst signals to oppositely regulate sucrose and water ingestion. Here, we investigate the neural circuit downstream of the ISNs to examine how ingestion is regulated based on internal needs. Utilizing the recently available fly brain connectome, we find that the ISNs synapse with a novel cell type Bilateral T-shaped neuron (BiT) that projects to neuroendocrine centers. In vivo neural manipulations revealed that BiT oppositely regulates sugar and water ingestion. Neuroendocrine cells downstream of ISNs include several peptide-releasing and peptide-sensing neurons, including insulin producing cells (IPC), crustacean cardioactive peptide (CCAP) neurons, and CCHamide-2 receptor isoform RA (CCHa2R-RA) neurons. These neurons contribute differentially to ingestion of sugar and water, with IPCs and CCAP neurons oppositely regulating sugar and water ingestion, and CCHa2R-RA neurons modulating only water ingestion. Thus, the decision to consume sugar or water occurs via regulation of a broad peptidergic network that integrates internal signals of nutritional state to generate nutrient-specific ingestion.
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Affiliation(s)
| | - Gina Pontes
- University of California, Berkeley, United States
- present address: IBBEA, CONICET-UBA, Buenos Aires, Argentina
| | - Nicholas Jourjine
- University of California, Berkeley, United States
- present address: Harvard University, Cambridge, United States
| | - Alexander Del Toro
- University of California, Berkeley, United States
- present address: Brown University, Rhode Island, United States
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37
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Cheong HSJ, Boone KN, Bennett MM, Salman F, Ralston JD, Hatch K, Allen RF, Phelps AM, Cook AP, Phelps JS, Erginkaya M, Lee WCA, Card GM, Daly KC, Dacks AM. Organization of an Ascending Circuit that Conveys Flight Motor State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.544074. [PMID: 37333334 PMCID: PMC10274802 DOI: 10.1101/2023.06.07.544074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.
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Affiliation(s)
- Han S. J. Cheong
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, United States of America
| | - Kaitlyn N. Boone
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Marryn M. Bennett
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Farzaan Salman
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Jacob D. Ralston
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Kaleb Hatch
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Raven F. Allen
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Alec M. Phelps
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Andrew P. Cook
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Jasper S. Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, United States of America
| | - Mert Erginkaya
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, 1400-038, Portugal
| | - Wei-Chung A. Lee
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, United States of America
| | - Gwyneth M. Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, United States of America
- Zuckerman Institute, Columbia University, New York, NY 10027, United States of America
| | - Kevin C. Daly
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
- Department of Neuroscience, West Virginia University, Morgantown, WV 26505, United States of America
| | - Andrew M. Dacks
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
- Department of Neuroscience, West Virginia University, Morgantown, WV 26505, United States of America
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38
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Taisz I, Donà E, Münch D, Bailey SN, Morris BJ, Meechan KI, Stevens KM, Varela-Martínez I, Gkantia M, Schlegel P, Ribeiro C, Jefferis GSXE, Galili DS. Generating parallel representations of position and identity in the olfactory system. Cell 2023; 186:2556-2573.e22. [PMID: 37236194 PMCID: PMC10403364 DOI: 10.1016/j.cell.2023.04.038] [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: 05/27/2022] [Revised: 12/07/2022] [Accepted: 04/28/2023] [Indexed: 05/28/2023]
Abstract
In Drosophila, a dedicated olfactory channel senses a male pheromone, cis-vaccenyl acetate (cVA), promoting female courtship while repelling males. Here, we show that separate cVA-processing streams extract qualitative and positional information. cVA sensory neurons respond to concentration differences in a 5-mm range around a male. Second-order projection neurons encode the angular position of a male by detecting inter-antennal differences in cVA concentration, which are amplified through contralateral inhibition. At the third circuit layer, we identify 47 cell types with diverse input-output connectivity. One population responds tonically to male flies, a second is tuned to olfactory looming, while a third integrates cVA and taste to coincidentally promote female mating. The separation of olfactory features resembles the mammalian what and where visual streams; together with multisensory integration, this enables behavioral responses appropriate to specific ethological contexts.
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Affiliation(s)
- István Taisz
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Erika Donà
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | | | - Billy J Morris
- Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Katie M Stevens
- Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Marina Gkantia
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Gregory S X E Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Department of Zoology, University of Cambridge, Cambridge, UK.
| | - Dana S Galili
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK.
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39
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Zhang J, Lentz L, Goldammer J, Iliescu J, Tanimura J, Riemensperger TD. Asymmetric Presynaptic Depletion of Dopamine Neurons in a Drosophila Model of Parkinson's Disease. Int J Mol Sci 2023; 24:ijms24108585. [PMID: 37239942 DOI: 10.3390/ijms24108585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/27/2023] [Accepted: 05/06/2023] [Indexed: 05/28/2023] Open
Abstract
Parkinson's disease (PD) often displays a strong unilateral predominance in arising symptoms. PD is correlated with dopamine neuron (DAN) degeneration in the substantia nigra pars compacta (SNPC), and in many patients, DANs appear to be affected more severely on one hemisphere than the other. The reason for this asymmetric onset is far from being understood. Drosophila melanogaster has proven its merit to model molecular and cellular aspects of the development of PD. However, the cellular hallmark of the asymmetric degeneration of DANs in PD has not yet been described in Drosophila. We ectopically express human α-synuclein (hα-syn) together with presynaptically targeted syt::HA in single DANs that innervate the Antler (ATL), a symmetric neuropil located in the dorsomedial protocerebrum. We find that expression of hα-syn in DANs innervating the ATL yields asymmetric depletion of synaptic connectivity. Our study represents the first example of unilateral predominance in an invertebrate model of PD and will pave the way to the investigation of unilateral predominance in the development of neurodegenerative diseases in the genetically versatile invertebrate model Drosophila.
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Affiliation(s)
- Jiajun Zhang
- Institute of Zoology, Experimental Morphology and Neuroanatomy, University of Cologne, Zuelpicher Str. 47b, 50674 Cologne, Germany
| | - Lucie Lentz
- Institute of Zoology, Experimental Morphology and Neuroanatomy, University of Cologne, Zuelpicher Str. 47b, 50674 Cologne, Germany
| | - Jens Goldammer
- Institute of Zoology, Experimental Morphology and Neuroanatomy, University of Cologne, Zuelpicher Str. 47b, 50674 Cologne, Germany
| | - Jessica Iliescu
- Institute of Zoology, Experimental Morphology and Neuroanatomy, University of Cologne, Zuelpicher Str. 47b, 50674 Cologne, Germany
| | - Jun Tanimura
- Neuronal Circuit Division, Institute of Molecular and Cellular Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
| | - Thomas Dieter Riemensperger
- Institute of Zoology, Experimental Morphology and Neuroanatomy, University of Cologne, Zuelpicher Str. 47b, 50674 Cologne, Germany
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40
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Sorkaç A, Moșneanu RA, Crown AM, Savaş D, Okoro AM, Memiş E, Talay M, Barnea G. retro-Tango enables versatile retrograde circuit tracing in Drosophila. eLife 2023; 12:e85041. [PMID: 37166114 PMCID: PMC10208638 DOI: 10.7554/elife.85041] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 05/11/2023] [Indexed: 05/12/2023] Open
Abstract
Transsynaptic tracing methods are crucial tools in studying neural circuits. Although a couple of anterograde tracing methods and a targeted retrograde tool have been developed in Drosophila melanogaster, there is still need for an unbiased, user-friendly, and flexible retrograde tracing system. Here, we describe retro-Tango, a method for transsynaptic, retrograde circuit tracing and manipulation in Drosophila. In this genetically encoded system, a ligand-receptor interaction at the synapse triggers an intracellular signaling cascade that results in reporter gene expression in presynaptic neurons. Importantly, panneuronal expression of the elements of the cascade renders this method versatile, enabling its use not only to test hypotheses but also to generate them. We validate retro-Tango in various circuits and benchmark it by comparing our findings with the electron microscopy reconstruction of the Drosophila hemibrain. Our experiments establish retro-Tango as a key method for circuit tracing in neuroscience research.
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Affiliation(s)
- Altar Sorkaç
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Rareș A Moșneanu
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Anthony M Crown
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Doruk Savaş
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Angel M Okoro
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Ezgi Memiş
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Mustafa Talay
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - Gilad Barnea
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
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41
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Okray Z, Jacob PF, Stern C, Desmond K, Otto N, Talbot CB, Vargas-Gutierrez P, Waddell S. Multisensory learning binds neurons into a cross-modal memory engram. Nature 2023; 617:777-784. [PMID: 37100911 PMCID: PMC10208976 DOI: 10.1038/s41586-023-06013-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 03/24/2023] [Indexed: 04/28/2023]
Abstract
Associating multiple sensory cues with objects and experience is a fundamental brain process that improves object recognition and memory performance. However, neural mechanisms that bind sensory features during learning and augment memory expression are unknown. Here we demonstrate multisensory appetitive and aversive memory in Drosophila. Combining colours and odours improved memory performance, even when each sensory modality was tested alone. Temporal control of neuronal function revealed visually selective mushroom body Kenyon cells (KCs) to be required for enhancement of both visual and olfactory memory after multisensory training. Voltage imaging in head-fixed flies showed that multisensory learning binds activity between streams of modality-specific KCs so that unimodal sensory input generates a multimodal neuronal response. Binding occurs between regions of the olfactory and visual KC axons, which receive valence-relevant dopaminergic reinforcement, and is propagated downstream. Dopamine locally releases GABAergic inhibition to permit specific microcircuits within KC-spanning serotonergic neurons to function as an excitatory bridge between the previously 'modality-selective' KC streams. Cross-modal binding thereby expands the KCs representing the memory engram for each modality into those representing the other. This broadening of the engram improves memory performance after multisensory learning and permits a single sensory feature to retrieve the memory of the multimodal experience.
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Affiliation(s)
- Zeynep Okray
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK.
| | - Pedro F Jacob
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK
| | - Ciara Stern
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK
| | - Kieran Desmond
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK
| | - Nils Otto
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK
- Institute of Anatomy and Molecular Neurobiology, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Clifford B Talbot
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK
| | | | - Scott Waddell
- Centre for Neural Circuits & Behaviour, University of Oxford, Oxford, UK.
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42
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Yu Z, Han X, Zhang S, Feng J, Peng T, Zhang XY. MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:1197-1209. [PMID: 36449589 DOI: 10.1109/tmi.2022.3225528] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding their relationships. Compared to a single MRI modality, multimodal MRI data provide complementary tissue features that can be exploited by deep learning models, resulting in better segmentation results. However, multimodal mouse brain MRI data is often lacking, making automatic segmentation of mouse brain fine structure a very challenging task. To address this issue, it is necessary to fuse multimodal MRI data to produce distinguished contrasts in different brain structures. Hence, we propose a novel disentangled and contrastive GAN-based framework, named MouseGAN++, to synthesize multiple MR modalities from single ones in a structure-preserving manner, thus improving the segmentation performance by imputing missing modalities and multi-modality fusion. Our results demonstrate that the translation performance of our method outperforms the state-of-the-art methods. Using the subsequently learned modality-invariant information as well as the modality-translated images, MouseGAN++ can segment fine brain structures with averaged dice coefficients of 90.0% (T2w) and 87.9% (T1w), respectively, achieving around +10% performance improvement compared to the state-of-the-art algorithms. Our results demonstrate that MouseGAN++, as a simultaneous image synthesis and segmentation method, can be used to fuse cross-modality information in an unpaired manner and yield more robust performance in the absence of multimodal data. We release our method as a mouse brain structural segmentation tool for free academic usage at https://github.com/yu02019.
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43
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Shainer I, Kuehn E, Laurell E, Al Kassar M, Mokayes N, Sherman S, Larsch J, Kunst M, Baier H. A single-cell resolution gene expression atlas of the larval zebrafish brain. SCIENCE ADVANCES 2023; 9:eade9909. [PMID: 36812331 PMCID: PMC9946346 DOI: 10.1126/sciadv.ade9909] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/22/2022] [Indexed: 06/18/2023]
Abstract
The advent of multimodal brain atlases promises to accelerate progress in neuroscience by allowing in silico queries of neuron morphology, connectivity, and gene expression. We used multiplexed fluorescent in situ RNA hybridization chain reaction (HCR) technology to generate expression maps across the larval zebrafish brain for a growing set of marker genes. The data were registered to the Max Planck Zebrafish Brain (mapzebrain) atlas, thus allowing covisualization of gene expression, single-neuron tracings, and expertly curated anatomical segmentations. Using post hoc HCR labeling of the immediate early gene cfos, we mapped responses to prey stimuli and food ingestion across the brain of freely swimming larvae. This unbiased approach revealed, in addition to previously described visual and motor areas, a cluster of neurons in the secondary gustatory nucleus, which express the marker calb2a, as well as a specific neuropeptide Y receptor, and project to the hypothalamus. This discovery exemplifies the power of this new atlas resource for zebrafish neurobiology.
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Court R, Costa M, Pilgrim C, Millburn G, Holmes A, McLachlan A, Larkin A, Matentzoglu N, Kir H, Parkinson H, Brown NH, O’Kane CJ, Armstrong JD, Jefferis GSXE, Osumi-Sutherland D. Virtual Fly Brain-An interactive atlas of the Drosophila nervous system. Front Physiol 2023; 14:1076533. [PMID: 36776967 PMCID: PMC9908962 DOI: 10.3389/fphys.2023.1076533] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 01/02/2023] [Indexed: 01/27/2023] Open
Abstract
As a model organism, Drosophila is uniquely placed to contribute to our understanding of how brains control complex behavior. Not only does it have complex adaptive behaviors, but also a uniquely powerful genetic toolkit, increasingly complete dense connectomic maps of the central nervous system and a rapidly growing set of transcriptomic profiles of cell types. But this also poses a challenge: Given the massive amounts of available data, how are researchers to Find, Access, Integrate and Reuse (FAIR) relevant data in order to develop an integrated anatomical and molecular picture of circuits, inform hypothesis generation, and find reagents for experiments to test these hypotheses? The Virtual Fly Brain (virtualflybrain.org) web application & API provide a solution to this problem, using FAIR principles to integrate 3D images of neurons and brain regions, connectomics, transcriptomics and reagent expression data covering the whole CNS in both larva and adult. Users can search for neurons, neuroanatomy and reagents by name, location, or connectivity, via text search, clicking on 3D images, search-by-image, and queries by type (e.g., dopaminergic neuron) or properties (e.g., synaptic input in the antennal lobe). Returned results include cross-registered 3D images that can be explored in linked 2D and 3D browsers or downloaded under open licenses, and extensive descriptions of cell types and regions curated from the literature. These solutions are potentially extensible to cover similar atlasing and data integration challenges in vertebrates.
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Affiliation(s)
- Robert Court
- School of Informatics, University of Edinburgh, Edinburgh, United Kingtom
| | - Marta Costa
- Department of Zoology, University of Cambridge, Cambridge, United Kingtom
- Department of Genetics, University of Cambridge, Cambridge, United Kingtom
| | - Clare Pilgrim
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingtom
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingtom
| | - Alex Holmes
- Department of Genetics, University of Cambridge, Cambridge, United Kingtom
| | - Alex McLachlan
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingtom
| | - Aoife Larkin
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingtom
| | | | - Huseyin Kir
- European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingtom
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingtom
| | - Nicolas H. Brown
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingtom
| | - Cahir J. O’Kane
- Department of Genetics, University of Cambridge, Cambridge, United Kingtom
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45
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Mabuchi Y, Cui X, Xie L, Kim H, Jiang T, Yapici N. GABA-mediated inhibition in visual feedback neurons fine-tunes Drosophila male courtship. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525544. [PMID: 36747836 PMCID: PMC9900824 DOI: 10.1101/2023.01.25.525544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Vision is critical for the regulation of mating behaviors in many species. Here, we discovered that the Drosophila ortholog of human GABA A -receptor-associated protein (GABARAP) is required to fine-tune male courtship by modulating the activity of visual feedback neurons, lamina tangential cells (Lat). GABARAP is a ubiquitin-like protein that regulates cell-surface levels of GABA A receptors. Knocking down GABARAP or GABA A receptors in Lat neurons or hyperactivating them induces male courtship toward other males. Inhibiting Lat neurons, on the other hand, delays copulation by impairing the ability of males to follow females. Remarkably, the human ortholog of Drosophila GABARAP restores function in Lat neurons. Using in vivo two-photon imaging and optogenetics, we show that Lat neurons are functionally connected to neural circuits that mediate visually-guided courtship pursuits in males. Our work reveals a novel physiological role for GABARAP in fine-tuning the activity of a visual circuit that tracks a mating partner during courtship.
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Affiliation(s)
- Yuta Mabuchi
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA
| | - Xinyue Cui
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA
| | - Lily Xie
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA
| | - Haein Kim
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA
| | - Tianxing Jiang
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA
| | - Nilay Yapici
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA
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46
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Dombrovski M, Peek MY, Park JY, Vaccari A, Sumathipala M, Morrow C, Breads P, Zhao A, Kurmangaliyev YZ, Sanfilippo P, Rehan A, Polsky J, Alghailani S, Tenshaw E, Namiki S, Zipursky SL, Card GM. Synaptic gradients transform object location to action. Nature 2023; 613:534-542. [PMID: 36599984 PMCID: PMC9849133 DOI: 10.1038/s41586-022-05562-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 11/11/2022] [Indexed: 01/06/2023]
Abstract
To survive, animals must convert sensory information into appropriate behaviours1,2. Vision is a common sense for locating ethologically relevant stimuli and guiding motor responses3-5. How circuitry converts object location in retinal coordinates to movement direction in body coordinates remains largely unknown. Here we show through behaviour, physiology, anatomy and connectomics in Drosophila that visuomotor transformation occurs by conversion of topographic maps formed by the dendrites of feature-detecting visual projection neurons (VPNs)6,7 into synaptic weight gradients of VPN outputs onto central brain neurons. We demonstrate how this gradient motif transforms the anteroposterior location of a visual looming stimulus into the fly's directional escape. Specifically, we discover that two neurons postsynaptic to a looming-responsive VPN type promote opposite takeoff directions. Opposite synaptic weight gradients onto these neurons from looming VPNs in different visual field regions convert localized looming threats into correctly oriented escapes. For a second looming-responsive VPN type, we demonstrate graded responses along the dorsoventral axis. We show that this synaptic gradient motif generalizes across all 20 primary VPN cell types and most often arises without VPN axon topography. Synaptic gradients may thus be a general mechanism for conveying spatial features of sensory information into directed motor outputs.
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Affiliation(s)
- Mark Dombrovski
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Martin Y Peek
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jin-Yong Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Andrea Vaccari
- Department of Computer Science, Middlebury College, Middlebury, VT, USA
| | | | - Carmen Morrow
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Patrick Breads
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Arthur Zhao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yerbol Z Kurmangaliyev
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Piero Sanfilippo
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Aadil Rehan
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jason Polsky
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Shada Alghailani
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Emily Tenshaw
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 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
| | - S Lawrence Zipursky
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA. .,Department of Neuroscience, Howard Hughes Medical Institute, The Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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47
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Marquis M, Wilson RI. Locomotor and olfactory responses in dopamine neurons of the Drosophila superior-lateral brain. Curr Biol 2022; 32:5406-5414.e5. [PMID: 36450284 DOI: 10.1016/j.cub.2022.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/17/2022] [Accepted: 11/03/2022] [Indexed: 12/03/2022]
Abstract
The Drosophila brain contains about 50 distinct morphological types of dopamine neurons.1,2,3,4 Physiological studies of Drosophila dopamine neurons have been largely limited to one brain region, the mushroom body,5,6,7,8,9,10,11,12,13 where they are implicated in learning.14,15,16,17,18 By comparison, we know little about the physiology of other Drosophila dopamine neurons. Interestingly, a recent whole-brain imaging study found that dopamine neuron activity in several fly brain regions is correlated with locomotion.19 This is notable because many dopamine neurons in the rodent brain are also correlated with locomotion or other movements20,21,22,23,24,25,26,27,28,29,30; however, most rodent studies have focused on learned and rewarded behaviors, and few have investigated dopamine neuron activity during spontaneous (self-timed) movements. In this study, we monitored dopamine neurons in the Drosophila brain during self-timed locomotor movements, focusing on several previously uncharacterized cell types that arborize in the superior-lateral brain, specifically the lateral horn and superior-lateral protocerebrum. We found that activity of all of these dopamine neurons correlated with spontaneous fluctuations in walking speed, with different cell types showing different speed correlations. Some dopamine neurons also responded to odors, but these responses were suppressed by repeated odor encounters. Finally, we found that the same identifiable dopamine neuron can encode different combinations of locomotion and odor in different individuals. If these dopamine neurons promote synaptic plasticity-like the dopamine neurons of the mushroom body-then, their tuning profiles would imply that plasticity depends on a flexible integration of sensory signals, motor signals, and recent experience.
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Affiliation(s)
- Michael Marquis
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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Fisher YE, Marquis M, D'Alessandro I, Wilson RI. Dopamine promotes head direction plasticity during orienting movements. Nature 2022; 612:316-322. [PMID: 36450986 PMCID: PMC9729112 DOI: 10.1038/s41586-022-05485-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 10/25/2022] [Indexed: 12/05/2022]
Abstract
In neural networks that store information in their connection weights, there is a tradeoff between sensitivity and stability1,2. Connections must be plastic to incorporate new information, but if they are too plastic, stored information can be corrupted. A potential solution is to allow plasticity only during epochs when task-specific information is rich, on the basis of a 'when-to-learn' signal3. We reasoned that dopamine provides a when-to-learn signal that allows the brain's spatial maps to update when new spatial information is available-that is, when an animal is moving. Here we show that the dopamine neurons innervating the Drosophila head direction network are specifically active when the fly turns to change its head direction. Moreover, their activity scales with moment-to-moment fluctuations in rotational speed. Pairing dopamine release with a visual cue persistently strengthens the cue's influence on head direction cells. Conversely, inhibiting these dopamine neurons decreases the influence of the cue. This mechanism should accelerate learning during moments when orienting movements are providing a rich stream of head direction information, allowing learning rates to be low at other times to protect stored information. Our results show how spatial learning in the brain can be compressed into discrete epochs in which high learning rates are matched to high rates of information intake.
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Affiliation(s)
- Yvette E Fisher
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Department of Molecular and Cellular Biology, University of California Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Michael Marquis
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | | | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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49
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Galili DS, Jefferis GS, Costa M. Connectomics and the neural basis of behaviour. CURRENT OPINION IN INSECT SCIENCE 2022; 54:100968. [PMID: 36113710 PMCID: PMC7614087 DOI: 10.1016/j.cois.2022.100968] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/30/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
Methods to acquire and process synaptic-resolution electron-microscopy datasets have progressed very rapidly, allowing production and annotation of larger, more complete connectomes. More accurate neuronal matching techniques are enriching cell type data with gene expression, neuron activity, behaviour and developmental information, providing ways to test hypotheses of circuit function. In a variety of behaviours such as learned and innate olfaction, navigation and sexual behaviour, connectomics has already revealed interconnected modules with a hierarchical structure, recurrence and integration of sensory streams. Comparing individual connectomes to determine which circuit features are robust and which are variable is one key research area; new work in comparative connectomics across development, experience, sex and species will establish strong links between neuronal connectivity and brain function.
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Affiliation(s)
- Dana S Galili
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
| | - Gregory Sxe Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
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50
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Bruckner JJ, Stednitz SJ, Grice MZ, Zaidan D, Massaquoi MS, Larsch J, Tallafuss A, Guillemin K, Washbourne P, Eisen JS. The microbiota promotes social behavior by modulating microglial remodeling of forebrain neurons. PLoS Biol 2022; 20:e3001838. [PMID: 36318534 PMCID: PMC9624426 DOI: 10.1371/journal.pbio.3001838] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 09/19/2022] [Indexed: 11/06/2022] Open
Abstract
Host-associated microbiotas guide the trajectory of developmental programs, and altered microbiota composition is linked to neurodevelopmental conditions such as autism spectrum disorder. Recent work suggests that microbiotas modulate behavioral phenotypes associated with these disorders. We discovered that the zebrafish microbiota is required for normal social behavior and reveal a molecular pathway linking the microbiota, microglial remodeling of neural circuits, and social behavior in this experimentally tractable model vertebrate. Examining neuronal correlates of behavior, we found that the microbiota restrains neurite complexity and targeting of forebrain neurons required for normal social behavior and is necessary for localization of forebrain microglia, brain-resident phagocytes that remodel neuronal arbors. The microbiota also influences microglial molecular functions, including promoting expression of the complement signaling pathway and the synaptic remodeling factor c1q. Several distinct bacterial taxa are individually sufficient for normal microglial and neuronal phenotypes, suggesting that host neuroimmune development is sensitive to a feature common among many bacteria. Our results demonstrate that the microbiota influences zebrafish social behavior by stimulating microglial remodeling of forebrain circuits during early neurodevelopment and suggest pathways for new interventions in multiple neurodevelopmental disorders.
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Affiliation(s)
- Joseph J. Bruckner
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Sarah J. Stednitz
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Max Z. Grice
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Dana Zaidan
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Michelle S. Massaquoi
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Johannes Larsch
- Department Genes-Circuits-Behavior, Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Alexandra Tallafuss
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Karen Guillemin
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
- Humans and the Microbiome Program, CIFAR, Toronto, Ontario, Canada
| | - Philip Washbourne
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
| | - Judith S. Eisen
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, Oregon, United States of America
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