1
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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 DOI: 10.1016/j.cell.2024.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [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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2
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Moreno-Sanchez A, Vasserman AN, Jang H, Hina BW, von Reyn CR, Ausborn J. Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons. bioRxiv 2024:2024.04.24.591016. [PMID: 38712267 PMCID: PMC11071487 DOI: 10.1101/2024.04.24.591016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in Drosophila melanogaster looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.
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3
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Volonté C, Liguori F, Amadio S. A Closer Look at Histamine in Drosophila. Int J Mol Sci 2024; 25:4449. [PMID: 38674034 PMCID: PMC11050612 DOI: 10.3390/ijms25084449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 04/12/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
The present work intends to provide a closer look at histamine in Drosophila. This choice is motivated firstly because Drosophila has proven over the years to be a very simple, but powerful, model organism abundantly assisting scientists in explaining not only normal functions, but also derangements that occur in higher organisms, not excluding humans. Secondly, because histamine has been demonstrated to be a pleiotropic master molecule in pharmacology and immunology, with increasingly recognized roles also in the nervous system. Indeed, it interacts with various neurotransmitters and controls functions such as learning, memory, circadian rhythm, satiety, energy balance, nociception, and motor circuits, not excluding several pathological conditions. In view of this, our review is focused on the knowledge that the use of Drosophila has added to the already vast histaminergic field. In particular, we have described histamine's actions on photoreceptors sustaining the visual system and synchronizing circadian rhythms, but also on temperature preference, courtship behavior, and mechanosensory transmission. In addition, we have highlighted the pathophysiological consequences of mutations on genes involved in histamine metabolism and signaling. By promoting critical discussion and further research, our aim is to emphasize and renew the importance of histaminergic research in biomedicine through the exploitation of Drosophila, hopefully extending the scientific debate to the academic, industry, and general public audiences.
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Affiliation(s)
- Cinzia Volonté
- National Research Council, Institute for Systems Analysis and Computer Science “A. Ruberti”, Via Dei Taurini 19, 00185 Rome, Italy;
- Experimental Neuroscience and Neurological Disease Models, Santa Lucia Foundation IRCCS, Via Del Fosso di Fiorano 65, 00143 Rome, Italy;
| | - Francesco Liguori
- National Research Council, Institute for Systems Analysis and Computer Science “A. Ruberti”, Via Dei Taurini 19, 00185 Rome, Italy;
- Experimental Neuroscience and Neurological Disease Models, Santa Lucia Foundation IRCCS, Via Del Fosso di Fiorano 65, 00143 Rome, Italy;
| | - Susanna Amadio
- Experimental Neuroscience and Neurological Disease Models, Santa Lucia Foundation IRCCS, Via Del Fosso di Fiorano 65, 00143 Rome, Italy;
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Nern A, Lösche F, Takemura SY, Burnett LE, Dreher M, Gruntman E, Hoeller J, Huang GB, Januszewski M, Klapoetke NC, Koskela S, Longden KD, Lu Z, Preibisch S, Qiu W, Rogers EM, Seenivasan P, Zhao A, Bogovic J, Canino BS, Clements J, Cook M, Finley-May S, Flynn MA, Hameed I, Hayworth KJ, Hopkins GP, Hubbard PM, Katz WT, Kovalyak J, Lauchie SA, Leonard M, Lohff A, Maldonado CA, Mooney C, Okeoma N, Olbris DJ, Ordish C, Paterson T, Phillips EM, Pietzsch T, Salinas JR, Rivlin PK, Scott AL, Scuderi LA, Takemura S, Talebi I, Thomson A, Trautman ET, Umayam L, Walsh C, Walsh JJ, Shan Xu C, Yakal EA, Yang T, Zhao T, Funke J, George R, Hess HF, Jefferis GSXE, Knecht C, Korff W, Plaza SM, Romani S, Saalfeld S, Scheffer LK, Berg S, Rubin GM, Reiser MB. Connectome-driven neural inventory of a complete visual system. bioRxiv 2024:2024.04.16.589741. [PMID: 38659887 PMCID: PMC11042306 DOI: 10.1101/2024.04.16.589741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain's volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly's visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the ~53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Gregory SXE Jefferis
- MRC Laboratory of Molecular Biology, Cambridge, UK and Department of Zoology, University of Cambridge, UK
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5
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Clements J, Goina C, Hubbard PM, Kawase T, Olbris DJ, Otsuna H, Svirskas R, Rokicki K. NeuronBridge: an intuitive web application for neuronal morphology search across large data sets. BMC Bioinformatics 2024; 25:114. [PMID: 38491365 PMCID: PMC10943809 DOI: 10.1186/s12859-024-05732-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/06/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome's structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. RESULTS Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine. CONCLUSIONS NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org .
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Affiliation(s)
- Jody Clements
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Cristian Goina
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Philip M Hubbard
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Takashi Kawase
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Donald J Olbris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Hideo Otsuna
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Robert Svirskas
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Konrad Rokicki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA.
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6
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Zhang Y, Li X. Development of the Drosophila Optic Lobe. Cold Spring Harb Protoc 2024; 2024:pdb.top108156. [PMID: 37758285 DOI: 10.1101/pdb.top108156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
The Drosophila visual system has been a great model to study fundamental questions in neurobiology, such as neural fate specification, axon guidance, circuit formation, and information processing. The Drosophila visual system is composed of the compound eye and the optic lobe. The optic lobe is divided into four neuropils-namely, the lamina, medulla, lobula, and lobula plate. There are around 200 types of optic lobe neurons, which wire together to form a complex neural structure to processes visual information. These neurons are derived from two neuroepithelial structures-namely, the outer proliferation center (OPC) and the inner proliferation center (IPC), in the larval brain. Recent work on the Drosophila optic lobe has revealed basic principles underlying the development of this complex neural structure, and immunostaining has been a key tool in these studies. Here, we provide a brief overview of the Drosophila optic lobe structure and development, as revealed by immunostaining. First, we introduce the structure of the adult optic lobe. Then, we summarize recent advances in the study of neural fate specification during development of different parts of the optic lobe. Last, we briefly summarize general aspects of axon guidance and neuropil assembly in the optic lobe. With this review, we aim to familiarize readers with this complex neural structure and highlight the power of this great model to study neural development to facilitate further developmental and functional studies using this system.
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Affiliation(s)
- Yu Zhang
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Xin Li
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
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7
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Osaka J, Ishii A, Wang X, Iwanaga R, Kawamura H, Akino S, Sugie A, Hakeda-Suzuki S, Suzuki T. Complex formation of immunoglobulin superfamily molecules Side-IV and Beat-IIb regulates synaptic specificity. Cell Rep 2024; 43:113798. [PMID: 38381608 DOI: 10.1016/j.celrep.2024.113798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/03/2023] [Accepted: 01/31/2024] [Indexed: 02/23/2024] Open
Abstract
Neurons establish specific synapses based on the adhesive properties of cell-surface proteins while also retaining the ability to form synapses in a relatively non-selective manner. However, comprehensive understanding of the underlying mechanism reconciling these opposing characteristics remains incomplete. Here, we have identified Side-IV/Beat-IIb, members of the Drosophila immunoglobulin superfamily, as a combination of cell-surface recognition molecules inducing synapse formation. The Side-IV/Beat-IIb combination transduces bifurcated signaling with Side-IV's co-receptor, Kirre, and a synaptic scaffold protein, Dsyd-1. Genetic experiments and subcellular protein localization analyses showed the Side-IV/Beat-IIb/Kirre/Dsyd-1 complex to have two essential functions. First, it narrows neuronal binding specificity through Side-IV/Beat-IIb extracellular interactions. Second, it recruits synapse formation factors, Kirre and Dsyd-1, to restrict synaptic loci and inhibit miswiring. This dual function explains how the combinations of cell-surface molecules enable the ranking of preferred interactions among neuronal pairs to achieve synaptic specificity in complex circuits in vivo.
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Affiliation(s)
- Jiro Osaka
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan; Brain Research Institute, Niigata University, Niigata 951-8585, Japan
| | - Arisa Ishii
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan
| | - Xu Wang
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan
| | - Riku Iwanaga
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan
| | - Hinata Kawamura
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan
| | - Shogo Akino
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan
| | - Atsushi Sugie
- Brain Research Institute, Niigata University, Niigata 951-8585, Japan
| | - Satoko Hakeda-Suzuki
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan; Research Initiatives and Promotion Organization, Yokohama National University, Yokohama 240-8501, Japan
| | - Takashi Suzuki
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama 226-8501, Japan.
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8
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Cornean J, Molina-Obando S, Gür B, Bast A, Ramos-Traslosheros G, Chojetzki J, Lörsch L, Ioannidou M, Taneja R, Schnaitmann C, Silies M. Heterogeneity of synaptic connectivity in the fly visual system. Nat Commun 2024; 15:1570. [PMID: 38383614 PMCID: PMC10882054 DOI: 10.1038/s41467-024-45971-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 02/08/2024] [Indexed: 02/23/2024] Open
Abstract
Visual systems are homogeneous structures, where repeating columnar units retinotopically cover the visual field. Each of these columns contain many of the same neuron types that are distinguished by anatomic, genetic and - generally - by functional properties. However, there are exceptions to this rule. In the 800 columns of the Drosophila eye, there is an anatomically and genetically identifiable cell type with variable functional properties, Tm9. Since anatomical connectivity shapes functional neuronal properties, we identified the presynaptic inputs of several hundred Tm9s across both optic lobes using the full adult female fly brain (FAFB) electron microscopic dataset and FlyWire connectome. Our work shows that Tm9 has three major and many sparsely distributed inputs. This differs from the presynaptic connectivity of other Tm neurons, which have only one major, and more stereotypic inputs than Tm9. Genetic synapse labeling showed that the heterogeneous wiring exists across individuals. Together, our data argue that the visual system uses heterogeneous, distributed circuit properties to achieve robust visual processing.
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Affiliation(s)
- Jacqueline Cornean
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Sebastian Molina-Obando
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Burak Gür
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Annika Bast
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Giordano Ramos-Traslosheros
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
- Department of Neurobiology, Harvard Medical School, Boston, MA, 02115, USA
| | - Jonas Chojetzki
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Lena Lörsch
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Maria Ioannidou
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Rachita Taneja
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Christopher Schnaitmann
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany
| | - Marion Silies
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University, 55128, Mainz, Germany.
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9
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Simon F, Holguera I, Chen YC, Malin J, Valentino P, Erclik T, Desplan C. High-throughput identification of the spatial origins of Drosophila optic lobe neurons using single-cell mRNA-sequencing. bioRxiv 2024:2024.02.05.578975. [PMID: 38370610 PMCID: PMC10871188 DOI: 10.1101/2024.02.05.578975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The medulla is the largest neuropil of the Drosophila optic lobe. It contains about 100 neuronal types that have been comprehensively characterized morphologically and molecularly. These neuronal types are specified from a larval neuroepithelium called the Outer Proliferation Center (OPC) via the integration of temporal, spatial, and Notch-driven mechanisms. Although we recently characterized the temporal windows of origin of all medulla neurons, as well as their Notch status, their spatial origins remained unknown. Here, we isolated cells from different OPC spatial domains and performed single-cell mRNA-sequencing to identify the neuronal types produced in these domains. This allowed us to characterize in a high-throughput manner the spatial origins of all medulla neurons and to identify two new spatial subdivisions of the OPC. Moreover, our work shows that the most abundant neuronal types are produced from epithelial domains of different sizes despite being present in a similar number of copies. Combined with our previously published scRNA-seq developmental atlas of the optic lobe, our work opens the door for further studies on how specification factor expression in progenitors impacts gene expression in developing and adult neurons.
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Affiliation(s)
- Félix Simon
- Department of Biology, New York University, New York, NY 10003, USA
| | - Isabel Holguera
- Department of Biology, New York University, New York, NY 10003, USA
| | - Yen-Chung Chen
- Department of Biology, New York University, New York, NY 10003, USA
| | - Jennifer Malin
- Department of Biology, New York University, New York, NY 10003, USA
| | - Priscilla Valentino
- Department of Biology, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Ted Erclik
- Department of Biology, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Claude Desplan
- Department of Biology, New York University, New York, NY 10003, USA
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10
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Chen T, Zhang M, Ding Z, Hu J, Yang J, He L, Jia J, Yang J, Yang J, Song X, Chen P, Zhai Z, Huang J, Wang Y, Qin H. The Drosophila NPY-like system protects against chronic stress-induced learning deficit by preventing the disruption of autophagic flux. Proc Natl Acad Sci U S A 2023; 120:e2307632120. [PMID: 38079543 PMCID: PMC10743384 DOI: 10.1073/pnas.2307632120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 11/09/2023] [Indexed: 12/18/2023] Open
Abstract
Chronic stress may induce learning and memory deficits that are associated with a depression-like state in Drosophila melanogaster. The molecular and neural mechanisms underlying the etiology of chronic stress-induced learning deficit (CSLD) remain elusive. Here, we show that the autophagy-lysosomal pathway, a conserved cellular signaling mechanism, is associated with chronic stress in Drosophila, as indicated by time-series transcriptome profiling. Our findings demonstrate that chronic stress induces the disruption of autophagic flux, and chronic disruption of autophagic flux could lead to a learning deficit. Remarkably, preventing the disruption of autophagic flux by up-regulating the basal autophagy level is sufficient to protect against CSLD. Consistent with the essential role of the dopaminergic system in modulating susceptibility to CSLD, dopamine neuronal activity is also indispensable for chronic stress to induce the disruption of autophagic flux. By screening knockout mutants, we found that neuropeptide F, the Drosophila homolog of neuropeptide Y, is necessary for normal autophagic flux and promotes resilience to CSLD. Moreover, neuropeptide F signaling during chronic stress treatment promotes resilience to CSLD by preventing the disruption of autophagic flux. Importantly, neuropeptide F receptor activity in dopamine neurons also promotes resilience to CSLD. Together, our data elucidate a mechanism by which stress-induced excessive dopaminergic activity precipitates the disruption of autophagic flux, and chronic disruption of autophagic flux leads to CSLD, while inhibitory neuropeptide F signaling to dopamine neurons promotes resilience to CSLD by preventing the disruption of autophagic flux.
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Affiliation(s)
- Tianli Chen
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Mengyu Zhang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Zhaowen Ding
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Jiao Hu
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Jie Yang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Lei He
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Jia Jia
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Jingjing Yang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Junfei Yang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Xiaoxu Song
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Peng Chen
- School of Pharmaceutical Science & Yunnan Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming650500, China
| | - Zongzhao Zhai
- Hunan Provincial Key Laboratory of Animal Intestinal Function and Regulation, Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, College of Life Sciences, Hunan Normal University, Changsha410081, Hunan, China
| | - Jing Huang
- Hunan Provincial Key Laboratory of Animal Models and Molecular Medicine, School of Biomedical Sciences, Hunan University, Changsha410082, Hunan, China
| | - Yirong Wang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
| | - Hongtao Qin
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha410082, China
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11
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Abstract
A typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ~180° realignment between the vector encoded in the neuronal population and the fly's internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-α1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.
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Affiliation(s)
- Itzel G. Ishida
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
| | - Sachin Sethi
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
| | - Thomas L. Mohren
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
| | - L.F. Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York NY, USA
| | - Gaby Maimon
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
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12
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Longden KD, Rogers EM, Nern A, Dionne H, Reiser MB. Different spectral sensitivities of ON- and OFF-motion pathways enhance the detection of approaching color objects in Drosophila. Nat Commun 2023; 14:7693. [PMID: 38001097 PMCID: PMC10673857 DOI: 10.1038/s41467-023-43566-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
Color and motion are used by many species to identify salient objects. They are processed largely independently, but color contributes to motion processing in humans, for example, enabling moving colored objects to be detected when their luminance matches the background. Here, we demonstrate an unexpected, additional contribution of color to motion vision in Drosophila. We show that behavioral ON-motion responses are more sensitive to UV than for OFF-motion, and we identify cellular pathways connecting UV-sensitive R7 photoreceptors to ON and OFF-motion-sensitive T4 and T5 cells, using neurogenetics and calcium imaging. Remarkably, this contribution of color circuitry to motion vision enhances the detection of approaching UV discs, but not green discs with the same chromatic contrast, and we show how this could generalize for systems with ON- and OFF-motion pathways. Our results provide a computational and circuit basis for how color enhances motion vision to favor the detection of saliently colored objects.
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Affiliation(s)
- Kit D Longden
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA.
| | - Edward M Rogers
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Aljoscha Nern
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Heather Dionne
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Michael B Reiser
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA.
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13
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Tanaka R, Zhou B, Agrochao M, Badwan BA, Au B, Matos NCB, Clark DA. Neural mechanisms to incorporate visual counterevidence in self-movement estimation. Curr Biol 2023; 33:4960-4979.e7. [PMID: 37918398 PMCID: PMC10848174 DOI: 10.1016/j.cub.2023.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 10/07/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023]
Abstract
In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion created by objects moving in the world. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly Drosophila. In silico experiments show that artificial neural networks (ANNs) that are optimized to distinguish observer movement from external object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion and optic-flow detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.
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Affiliation(s)
- Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Baohua Zhou
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA
| | - Margarida Agrochao
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Bara A Badwan
- School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA
| | - Braedyn Au
- Department of Physics, Yale University, New Haven, CT 06511, USA
| | - Natalia C B Matos
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Damon A Clark
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Department of Physics, Yale University, New Haven, CT 06511, USA; Department of Neuroscience, Yale University, New Haven, CT 06511, USA; Wu Tsai Institute, Yale University, New Haven, CT 06511, USA; Quantitative Biology Institute, Yale University, New Haven, CT 06511, USA.
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14
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Ammer G, Serbe-Kamp E, Mauss AS, Richter FG, Fendl S, Borst A. Multilevel visual motion opponency in Drosophila. Nat Neurosci 2023; 26:1894-1905. [PMID: 37783895 PMCID: PMC10620086 DOI: 10.1038/s41593-023-01443-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 08/30/2023] [Indexed: 10/04/2023]
Abstract
Inhibitory interactions between opponent neuronal pathways constitute a common circuit motif across brain areas and species. However, in most cases, synaptic wiring and biophysical, cellular and network mechanisms generating opponency are unknown. Here, we combine optogenetics, voltage and calcium imaging, connectomics, electrophysiology and modeling to reveal multilevel opponent inhibition in the fly visual system. We uncover a circuit architecture in which a single cell type implements direction-selective, motion-opponent inhibition at all three network levels. This inhibition, mediated by GluClα receptors, is balanced with excitation in strength, despite tenfold fewer synapses. The different opponent network levels constitute a nested, hierarchical structure operating at increasing spatiotemporal scales. Electrophysiology and modeling suggest that distributing this computation over consecutive network levels counteracts a reduction in gain, which would result from integrating large opposing conductances at a single instance. We propose that this neural architecture provides resilience to noise while enabling high selectivity for relevant sensory information.
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Affiliation(s)
- Georg Ammer
- Max Planck Institute for Biological Intelligence, Martinsried, Germany.
| | - Etienne Serbe-Kamp
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
- Ludwig Maximilian University of Munich, Munich, Germany
| | - Alex S Mauss
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Florian G Richter
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Sandra Fendl
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Alexander Borst
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
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15
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Xiao N, Xu S, Li ZK, Tang M, Mao R, Yang T, Ma SX, Wang PH, Li MT, Sunilkumar A, Rouyer F, Cao LH, Luo DG. A single photoreceptor splits perception and entrainment by cotransmission. Nature 2023; 623:562-570. [PMID: 37880372 PMCID: PMC10651484 DOI: 10.1038/s41586-023-06681-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 09/26/2023] [Indexed: 10/27/2023]
Abstract
Vision enables both image-forming perception, driven by a contrast-based pathway, and unconscious non-image-forming circadian photoentrainment, driven by an irradiance-based pathway1,2. Although two distinct photoreceptor populations are specialized for each visual task3-6, image-forming photoreceptors can additionally contribute to photoentrainment of the circadian clock in different species7-15. However, it is unknown how the image-forming photoreceptor pathway can functionally implement the segregation of irradiance signals required for circadian photoentrainment from contrast signals required for image perception. Here we report that the Drosophila R8 photoreceptor separates image-forming and irradiance signals by co-transmitting two neurotransmitters, histamine and acetylcholine. This segregation is further established postsynaptically by histamine-receptor-expressing unicolumnar retinotopic neurons and acetylcholine-receptor-expressing multicolumnar integration neurons. The acetylcholine transmission from R8 photoreceptors is sustained by an autocrine negative feedback of the cotransmitted histamine during the light phase of light-dark cycles. At the behavioural level, elimination of histamine and acetylcholine transmission impairs R8-driven motion detection and circadian photoentrainment, respectively. Thus, a single type of photoreceptor can achieve the dichotomy of visual perception and circadian photoentrainment as early as the first visual synapses, revealing a simple yet robust mechanism to segregate and translate distinct sensory features into different animal behaviours.
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Affiliation(s)
- Na Xiao
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Shuang Xu
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Ze-Kai Li
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Min Tang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Renbo Mao
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Tian Yang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Si-Xing Ma
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Peng-Hao Wang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Meng-Tong Li
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | - Ajay Sunilkumar
- Institut des Neurosciences Paris-Saclay, Université Paris-Sud, Université Paris-Saclay, CNRS, Gif-sur-Yvette, France
| | - François Rouyer
- Institut des Neurosciences Paris-Saclay, Université Paris-Sud, Université Paris-Saclay, CNRS, Gif-sur-Yvette, France
| | - Li-Hui Cao
- School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Capital Medical University, Beijing, China
| | - Dong-Gen Luo
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- School of Life Sciences, Peking University, Beijing, China.
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- Chinese Institute for Brain Research, Beijing, China.
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16
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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 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] [What about the content of this article? (0)] [Affiliation(s)] [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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17
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Lago-Baldaia I, Cooper M, Seroka A, Trivedi C, Powell GT, Wilson SW, Ackerman SD, Fernandes VM. A Drosophila glial cell atlas reveals a mismatch between transcriptional and morphological diversity. PLoS Biol 2023; 21:e3002328. [PMID: 37862379 PMCID: PMC10619882 DOI: 10.1371/journal.pbio.3002328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 11/01/2023] [Accepted: 09/08/2023] [Indexed: 10/22/2023] Open
Abstract
Morphology is a defining feature of neuronal identity. Like neurons, glia display diverse morphologies, both across and within glial classes, but are also known to be morphologically plastic. Here, we explored the relationship between glial morphology and transcriptional signature using the Drosophila central nervous system (CNS), where glia are categorised into 5 main classes (outer and inner surface glia, cortex glia, ensheathing glia, and astrocytes), which show within-class morphological diversity. We analysed and validated single-cell RNA sequencing data of Drosophila glia in 2 well-characterised tissues from distinct developmental stages, containing distinct circuit types: the embryonic ventral nerve cord (VNC) (motor) and the adult optic lobes (sensory). Our analysis identified a new morphologically and transcriptionally distinct surface glial population in the VNC. However, many glial morphological categories could not be distinguished transcriptionally, and indeed, embryonic and adult astrocytes were transcriptionally analogous despite differences in developmental stage and circuit type. While we did detect extensive within-class transcriptomic diversity for optic lobe glia, this could be explained entirely by glial residence in the most superficial neuropil (lamina) and an associated enrichment for immune-related gene expression. In summary, we generated a single-cell transcriptomic atlas of glia in Drosophila, and our extensive in vivo validation revealed that glia exhibit more diversity at the morphological level than was detectable at the transcriptional level. This atlas will serve as a resource for the community to probe glial diversity and function.
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Affiliation(s)
- Inês Lago-Baldaia
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | - Maia Cooper
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | - Austin Seroka
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, Oregon, United States of America
| | - Chintan Trivedi
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | - Gareth T. Powell
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | - Stephen W. Wilson
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | - Sarah D. Ackerman
- Department of Pathology and Immunology, Brain Immunology and Glia Center, Washington University School of Medicine, Saint Louis, Missouri, United States of America
- Department of Developmental Biology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Vilaiwan M. Fernandes
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
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18
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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19
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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: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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20
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Krupp S, Hubbard I, Tam O, Hammell GM, Dubnau J. TDP-43 pathology in Drosophila induces glial-cell type specific toxicity that can be ameliorated by knock-down of SF2/SRSF1. PLoS Genet 2023; 19:e1010973. [PMID: 37747929 PMCID: PMC10553832 DOI: 10.1371/journal.pgen.1010973] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 10/05/2023] [Accepted: 09/13/2023] [Indexed: 09/27/2023] Open
Abstract
Accumulation of cytoplasmic inclusions of TAR-DNA binding protein 43 (TDP-43) is seen in both neurons and glia in a range of neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) and Alzheimer's disease (AD). Disease progression involves non-cell autonomous interactions among multiple cell types, including neurons, microglia and astrocytes. We investigated the effects in Drosophila of inducible, glial cell type-specific TDP-43 overexpression, a model that causes TDP-43 protein pathology including loss of nuclear TDP-43 and accumulation of cytoplasmic inclusions. We report that TDP-43 pathology in Drosophila is sufficient to cause progressive loss of each of the 5 glial sub-types. But the effects on organismal survival were most pronounced when TDP-43 pathology was induced in the perineural glia (PNG) or astrocytes. In the case of PNG, this effect is not attributable to loss of the glial population, because ablation of these glia by expression of pro-apoptotic reaper expression has relatively little impact on survival. To uncover underlying mechanisms, we used cell-type-specific nuclear RNA sequencing to characterize the transcriptional changes induced by pathological TDP-43 expression. We identified numerous glial cell-type specific transcriptional changes. Notably, SF2/SRSF1 levels were found to be decreased in both PNG and in astrocytes. We found that further knockdown of SF2/SRSF1 in either PNG or astrocytes lessens the detrimental effects of TDP-43 pathology on lifespan, but extends survival of the glial cells. Thus TDP-43 pathology in astrocytes or PNG causes systemic effects that shorten lifespan and SF2/SRSF1 knockdown rescues the loss of these glia, and also reduces their systemic toxicity to the organism.
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Affiliation(s)
- Sarah Krupp
- Program in Neuroscience, Department of Neurobiology and Behavior, Stony Brook University, New York, United States of America
| | - Isabel Hubbard
- Program in Neuroscience, Department of Neurobiology and Behavior, Stony Brook University, New York, United States of America
| | - Oliver Tam
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Gale M. Hammell
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Josh Dubnau
- Program in Neuroscience, Department of Neurobiology and Behavior, Stony Brook University, New York, United States of America
- Department of Anesthesiology, Stony Brook School of Medicine, New York, United States of America
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21
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Chen YCD, Chen YC, Rajesh R, Shoji N, Jacy M, Lacin H, Erclik T, Desplan C. Using single-cell RNA sequencing to generate predictive cell-type-specific split-GAL4 reagents throughout development. Proc Natl Acad Sci U S A 2023; 120:e2307451120. [PMID: 37523539 PMCID: PMC10410749 DOI: 10.1073/pnas.2307451120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/03/2023] [Indexed: 08/02/2023] Open
Abstract
Cell-type-specific tools facilitate the identification and functional characterization of the distinct cell types that form the complexity of neuronal circuits. A large collection of existing genetic tools in Drosophila relies on enhancer activity to label different subsets of cells and has been extremely useful in analyzing functional circuits in adults. However, these enhancer-based GAL4 lines often do not reflect the expression of nearby gene(s) as they only represent a small portion of the full gene regulatory elements. While genetic intersectional techniques such as the split-GAL4 system further improve cell-type-specificity, it requires significant time and resources to screen through combinations of enhancer expression patterns. Here, we use existing developmental single-cell RNA sequencing (scRNAseq) datasets to select gene pairs for split-GAL4 and provide a highly efficient and predictive pipeline (scMarco) to generate cell-type-specific split-GAL4 lines at any time during development, based on the native gene regulatory elements. These gene-specific split-GAL4 lines can be generated from a large collection of coding intronic MiMIC/CRIMIC lines or by CRISPR knock-in. We use the developing Drosophila visual system as a model to demonstrate the high predictive power of scRNAseq-guided gene-specific split-GAL4 lines in targeting known cell types, annotating clusters in scRNAseq datasets as well as in identifying novel cell types. Lastly, the gene-specific split-GAL4 lines are broadly applicable to any other Drosophila tissue. Our work opens new avenues for generating cell-type-specific tools for the targeted manipulation of distinct cell types throughout development and represents a valuable resource for the Drosophila community.
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Affiliation(s)
| | - Yen-Chung Chen
- Department of Biology, New York University, New York,NY10003
| | - Raghuvanshi Rajesh
- Department of Biology, New York University, New York,NY10003
- Center for Genomics and Systems Biology, New York University, Abu Dhabi51133, United Arab Emirates
| | - Nathalie Shoji
- Department of Biology, New York University, New York,NY10003
| | - Maisha Jacy
- Department of Biology, New York University, New York,NY10003
| | - Haluk Lacin
- Division of Biological and Biomedical Systems, University of Missouri - Kansas City, Kansas City, MO64110
| | - Ted Erclik
- Department of Biology and Cell, University of Toronto - Mississauga, Mississauga, ONL5L 1C6, Canada
- Department of Systems Biology, University of Toronto - Mississauga, Mississauga, ONL5L 1C6, Canada
| | - Claude Desplan
- Department of Biology, New York University, New York,NY10003
- Center for Genomics and Systems Biology, New York University, Abu Dhabi51133, United Arab Emirates
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22
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Ferreira AAG, Desplan C. An Atlas of the Developing Drosophila Visual System Glia and Subcellular mRNA Localization of Transcripts in Single Cells. bioRxiv 2023:2023.08.06.552169. [PMID: 37609218 PMCID: PMC10441313 DOI: 10.1101/2023.08.06.552169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Glial cells are essential for proper nervous system development and function. To understand glial development and function, we comprehensively annotated glial cells in a single-cell mRNA-sequencing (scRNAseq) atlas of the developing Drosophila visual system. This allowed us to study their developmental trajectories, from larval to adult stages, and to understand how specific types of glia diversify during development. For example, neuropil glia that are initially transcriptionally similar in larvae, split into ensheathing and astrocyte-like glia during pupal stages. Other glial types, such as chiasm glia change gradually during development without splitting into two cell types. The analysis of scRNA-seq allowed us to discover that the transcriptome of glial cell bodies can be distinguished from that of their broken processes. The processes contain distinct enriched mRNAs that were validated in vivo. Therefore, we have identified most glial types in the developing optic lobe and devised a computational approach to identify mRNA species that are localized to cell bodies or cellular processes.
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Affiliation(s)
| | - Claude Desplan
- Department of Biology, New York University, New York, NY, USA
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23
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Christenson MP, Díez ÁS, Heath SL, Saavedra-Weisenhaus M, Adachi A, Abbott LF, Behnia R. Hue selectivity from recurrent circuitry in Drosophila. bioRxiv 2023:2023.07.12.548573. [PMID: 37502934 PMCID: PMC10369983 DOI: 10.1101/2023.07.12.548573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
A universal principle of sensory perception is the progressive transformation of sensory information from broad non-specific signals to stimulus-selective signals that form the basis of perception. To perceive color, our brains must transform the wavelengths of light reflected off objects into the derived quantities of brightness, saturation and hue. Neurons responding selectively to hue have been reported in primate cortex, but it is unknown how their narrow tuning in color space is produced by upstream circuit mechanisms. To enable circuit level analysis of color perception, we here report the discovery of neurons in the Drosophila optic lobe with hue selective properties. Using the connectivity graph of the fly brain, we construct a connectomics-constrained circuit model that accounts for this hue selectivity. Unexpectedly, our model predicts that recurrent connections in the circuit are critical for hue selectivity. Experiments using genetic manipulations to perturb recurrence in adult flies confirms this prediction. Our findings reveal the circuit basis for hue selectivity in color vision.
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24
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Tanaka R, Zhou B, Agrochao M, Badwan BA, Au B, Matos NCB, Clark DA. Neural mechanisms to incorporate visual counterevidence in self motion estimation. bioRxiv 2023:2023.01.04.522814. [PMID: 36711843 PMCID: PMC9881891 DOI: 10.1101/2023.01.04.522814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can confuse the movement of external objects with genuine self motion. Here, we show that stationary patterns on the retina, which constitute negative evidence against self rotation, are used by the fruit fly Drosophila to suppress inappropriate stabilizing rotational behavior. In silico experiments show that artificial neural networks optimized to distinguish self and world motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's motion- and optic flow-detectors. Our results exemplify how the compact brain of the fly incorporates negative evidence to improve heading stability, exploiting geometrical constraints of the visual world.
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Affiliation(s)
- Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
- Present Address: Institute of Neuroscience, Technical University of Munich, Munich 80802, Germany
| | - Baohua Zhou
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA
| | - Margarida Agrochao
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Bara A. Badwan
- School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA
| | - Braedyn Au
- Department of Physics, Yale University, New Haven, CT 06511, USA
| | - Natalia C. B. Matos
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Damon A. Clark
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
- Department of Physics, Yale University, New Haven, CT 06511, USA
- Department of Neuroscience, Yale University, New Haven, CT 06511, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
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25
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Dorkenwald S, Matsliah A, Sterling AR, Schlegel P, Yu SC, McKellar CE, Lin A, Costa M, Eichler K, Yin Y, Silversmith W, Schneider-Mizell C, Jordan CS, Brittain D, Halageri A, Kuehner K, Ogedengbe O, Morey R, Gager J, Kruk K, Perlman E, Yang R, Deutsch D, Bland D, Sorek M, Lu R, Macrina T, Lee K, Bae JA, Mu S, Nehoran B, Mitchell E, Popovych S, Wu J, Jia Z, Castro M, Kemnitz N, Ih D, Bates AS, Eckstein N, Funke J, Collman F, Bock DD, Jefferis GS, Seung HS, Murthy M. Neuronal wiring diagram of an adult brain. bioRxiv 2023:2023.06.27.546656. [PMID: 37425937 PMCID: PMC10327113 DOI: 10.1101/2023.06.27.546656] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×107 chemical synapses between ~130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.
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Affiliation(s)
- Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Amy R Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Eyewire, Boston, USA
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Szi-chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Albert Lin
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Center for the Physics of Biological Function, Princeton University, Princeton, USA
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Yijie Yin
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Will Silversmith
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Chris S. Jordan
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Akhilesh Halageri
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Kai Kuehner
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Ryan Morey
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Jay Gager
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | | | - Runzhe Yang
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - David Deutsch
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Department of Neurobiology, University of Haifa, Haifa, Israel
| | - Doug Bland
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Marissa Sorek
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Eyewire, Boston, 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
| | - Kisuk Lee
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Brain & Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, USA
| | - J. Alexander Bae
- 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
| | - Eric Mitchell
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Sergiy Popovych
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Jingpeng Wu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Zhen Jia
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Manuel Castro
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Dodam Ih
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Alexander Shakeel Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Harvard Medical School, Boston, USA
- Centre for Neural Circuits and Behaviour, The University of Oxford, Oxford, UK
| | - Nils Eckstein
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Jan Funke
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | | | - Davi D. Bock
- Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, 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
| | - H. Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
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26
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Abstract
How neurons detect the direction of motion is a prime example of neural computation: Motion vision is found in the visual systems of virtually all sighted animals, it is important for survival, and it requires interesting computations with well-defined linear and nonlinear processing steps-yet the whole process is of moderate complexity. The genetic methods available in the fruit fly Drosophila and the charting of a connectome of its visual system have led to rapid progress and unprecedented detail in our understanding of how neurons compute the direction of motion in this organism. The picture that emerged incorporates not only the identity, morphology, and synaptic connectivity of each neuron involved but also its neurotransmitters, its receptors, and their subcellular localization. Together with the neurons' membrane potential responses to visual stimulation, this information provides the basis for a biophysically realistic model of the circuit that computes the direction of visual motion.
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Affiliation(s)
- Alexander Borst
- Max Planck Institute for Biological Intelligence, Martinsried, Germany; ,
| | - Lukas N Groschner
- Max Planck Institute for Biological Intelligence, Martinsried, Germany; ,
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27
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Pirogova N, Borst A. Contrast normalization affects response time-course of visual interneurons. PLoS One 2023; 18:e0285686. [PMID: 37294743 PMCID: PMC10256145 DOI: 10.1371/journal.pone.0285686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 04/28/2023] [Indexed: 06/11/2023] Open
Abstract
In natural environments, light intensities and visual contrasts vary widely, yet neurons have a limited response range for encoding them. Neurons accomplish that by flexibly adjusting their dynamic range to the statistics of the environment via contrast normalization. The effect of contrast normalization is usually measured as a reduction of neural signal amplitudes, but whether it influences response dynamics is unknown. Here, we show that contrast normalization in visual interneurons of Drosophila melanogaster not only suppresses the amplitude but also alters the dynamics of responses when a dynamic surround is present. We present a simple model that qualitatively reproduces the simultaneous effect of the visual surround on the response amplitude and temporal dynamics by altering the cells' input resistance and, thus, their membrane time constant. In conclusion, single-cell filtering properties as derived from artificial stimulus protocols like white-noise stimulation cannot be transferred one-to-one to predict responses under natural conditions.
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Affiliation(s)
- Nadezhda Pirogova
- Department Circuits-Computation-Models, Max Planck Institute for Biological Intelligence, Planegg, Martinsried, Germany
- Graduate School of Systemic Neurosciences, LMU Munich, Planegg, Martinsried, Germany
| | - Alexander Borst
- Department Circuits-Computation-Models, Max Planck Institute for Biological Intelligence, Planegg, Martinsried, Germany
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28
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Abstract
Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.
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Affiliation(s)
- Timothy A Currier
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michelle M Pang
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
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29
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Patop IL, Anduaga AM, Bussi IL, Ceriani MF, Kadener S. Organismal landscape of clock cells and circadian gene expression in Drosophila. bioRxiv 2023:2023.05.23.542009. [PMID: 37292867 PMCID: PMC10245886 DOI: 10.1101/2023.05.23.542009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Background Circadian rhythms time physiological and behavioral processes to 24-hour cycles. It is generally assumed that most cells contain self-sustained circadian clocks that drive circadian rhythms in gene expression that ultimately generating circadian rhythms in physiology. While those clocks supposedly act cell autonomously, current work suggests that in Drosophila some of them can be adjusted by the brain circadian pacemaker through neuropeptides, like the Pigment Dispersing Factor (PDF). Despite these findings and the ample knowledge of the molecular clockwork, it is still unknown how circadian gene expression in Drosophila is achieved across the body. Results Here, we used single-cell and bulk RNAseq data to identify cells within the fly that express core-clock components. Surprisingly, we found that less than a third of the cell types in the fly express core-clock genes. Moreover, we identified Lamina wild field (Lawf) and Ponx-neuro positive (Poxn) neurons as putative new circadian neurons. In addition, we found several cell types that do not express core clock components but are highly enriched for cyclically expressed mRNAs. Strikingly, these cell types express the PDF receptor (Pdfr), suggesting that PDF drives rhythmic gene expression in many cell types in flies. Other cell types express both core circadian clock components and Pdfr, suggesting that in these cells, PDF regulates the phase of rhythmic gene expression. Conclusions Together, our data suggest three different mechanisms generate cyclic daily gene expression in cells and tissues: canonical endogenous canonical molecular clock, PDF signaling-driven expression, or a combination of both.
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Affiliation(s)
- Ines L. Patop
- Biology Department, Brandeis University, Waltham, MA, 02454, USA
| | | | - Ivana L. Bussi
- Laboratorio de Genética del Comportamiento, Fundación Instituto Leloir – Instituto de Investigaciones Bioquímicas de Buenos Aires (IIBBA CONICET), Buenos Aires, Argentina
| | - M. Fernanda Ceriani
- Laboratorio de Genética del Comportamiento, Fundación Instituto Leloir – Instituto de Investigaciones Bioquímicas de Buenos Aires (IIBBA CONICET), Buenos Aires, Argentina
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30
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Shekhar S, Moehlman AT, Park B, Ewnetu M, Tracy C, Titos I, Pawłowski K, Tagliabracci VS, Krämer H. Allnighter pseudokinase-mediated feedback links proteostasis and sleep in Drosophila. Nat Commun 2023; 14:2932. [PMID: 37217484 DOI: 10.1038/s41467-023-38485-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 05/04/2023] [Indexed: 05/24/2023] Open
Abstract
In nervous systems, retrograde signals are key for organizing circuit activity and maintaining neuronal homeostasis. We identify the conserved Allnighter (Aln) pseudokinase as a cell non-autonomous regulator of proteostasis responses necessary for normal sleep and structural plasticity of Drosophila photoreceptors. In aln mutants exposed to extended ambient light, proteostasis is dysregulated and photoreceptors develop striking, but reversible, dysmorphology. The aln gene is widely expressed in different neurons, but not photoreceptors. However, secreted Aln protein is retrogradely endocytosed by photoreceptors. Inhibition of photoreceptor synaptic release reduces Aln levels in lamina neurons, consistent with secreted Aln acting in a feedback loop. In addition, aln mutants exhibit reduced night time sleep, providing a molecular link between dysregulated proteostasis and sleep, two characteristics of ageing and neurodegenerative diseases.
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Affiliation(s)
- Shashank Shekhar
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX; O'Donnell Brain Institute, Dallas, USA.
| | - Andrew T Moehlman
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX; O'Donnell Brain Institute, Dallas, USA
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Brenden Park
- Department of Molecular Biology UT Southwestern Medical Center, Dallas, TX, USA
| | - Michael Ewnetu
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX; O'Donnell Brain Institute, Dallas, USA
| | - Charles Tracy
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX; O'Donnell Brain Institute, Dallas, USA
| | - Iris Titos
- Molecular Medicine Program, University of Utah, School of Medicine, Salt Lake City, UT, USA
| | - Krzysztof Pawłowski
- Department of Molecular Biology UT Southwestern Medical Center, Dallas, TX, USA
- Department of Biochemistry and Microbiology, Institute of Biology, Warsaw University of Life Sciences, Warsaw, 02-776, Poland
| | - Vincent S Tagliabracci
- Department of Molecular Biology UT Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Maryland, USA
| | - Helmut Krämer
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX; O'Donnell Brain Institute, Dallas, USA.
- Department of Cell Biology, UT Southwestern Medical Center, Dallas, TX, USA.
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31
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Krupp S, Tam O, Hammell MG, Dubnau J. TDP-43 pathology in Drosophila induces glial-cell type specific toxicity that can be ameliorated by knock-down of SF2/SRSF1. bioRxiv 2023:2023.05.04.539439. [PMID: 37205372 PMCID: PMC10187300 DOI: 10.1101/2023.05.04.539439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Accumulation of cytoplasmic inclusions of TAR-DNA binding protein 43 (TDP-43) is seen in both neurons and glia in a range of neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) and Alzheimer's disease (AD). Disease progression involves non-cell autonomous interactions among multiple cell types, including neurons, microglia and astrocytes. We investigated the effects in Drosophila of inducible, glial cell type-specific TDP-43 overexpression, a model that causes TDP-43 protein pathology including loss of nuclear TDP-43 and accumulation of cytoplasmic inclusions. We report that TDP-43 pathology in Drosophila is sufficient to cause progressive loss of each of the 5 glial sub-types. But the effects on organismal survival were most pronounced when TDP-43 pathology was induced in the perineural glia (PNG) or astrocytes. In the case of PNG, this effect is not attributable to loss of the glial population, because ablation of these glia by expression of pro-apoptotic reaper expression has relatively little impact on survival. To uncover underlying mechanisms, we used cell-type-specific nuclear RNA sequencing to characterize the transcriptional changes induced by pathological TDP-43 expression. We identified numerous glial cell-type specific transcriptional changes. Notably, SF2/SRSF1 levels were found to be decreased in both PNG and in astrocytes. We found that further knockdown of SF2/SRSF1 in either PNG or astrocytes lessens the detrimental effects of TDP-43 pathology on lifespan, but extends survival of the glial cells. Thus TDP-43 pathology in astrocytes or PNG causes systemic effects that shorten lifespan and SF2/SRSF1 knockdown rescues the loss of these glia, and also reduces their systemic toxicity to the organism.
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Affiliation(s)
- S. Krupp
- Program in Neuroscience, Department of Neurobiology and Behavior, Stony Brook University, NY 11794, USA
| | - O Tam
- Cold Spring Harbor Laboratory, 1 Bungtown road, Cold Spring Harbor, NY.,11794
| | - M Gale Hammell
- Cold Spring Harbor Laboratory, 1 Bungtown road, Cold Spring Harbor, NY.,11794
| | - J Dubnau
- Program in Neuroscience, Department of Neurobiology and Behavior, Stony Brook University, NY 11794, USA
- Department of Anesthesiology, Stony Brook School of Medicine, NY 11794, USA
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Mishra A, Serbe-Kamp E, Borst A, Haag J. Voltage to Calcium Transformation Enhances Direction Selectivity in Drosophila T4 Neurons. J Neurosci 2023; 43:2497-2514. [PMID: 36849417 PMCID: PMC10082464 DOI: 10.1523/jneurosci.2297-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/03/2023] [Accepted: 02/08/2023] [Indexed: 03/01/2023] Open
Abstract
An important step in neural information processing is the transformation of membrane voltage into calcium signals leading to transmitter release. However, the effect of voltage to calcium transformation on neural responses to different sensory stimuli is not well understood. Here, we use in vivo two-photon imaging of genetically encoded voltage and calcium indicators, ArcLight and GCaMP6f, respectively, to measure responses in direction-selective T4 neurons of female Drosophila Comparison between ArcLight and GCaMP6f signals reveals calcium signals to have a significantly higher direction selectivity compared with voltage signals. Using these recordings, we build a model which transforms T4 voltage responses into calcium responses. Using a cascade of thresholding, temporal filtering and a stationary nonlinearity, the model reproduces experimentally measured calcium responses across different visual stimuli. These findings provide a mechanistic underpinning of the voltage to calcium transformation and show how this processing step, in addition to synaptic mechanisms on the dendrites of T4 cells, enhances direction selectivity in the output signal of T4 neurons. Measuring the directional tuning of postsynaptic vertical system (VS)-cells with inputs from other cells blocked, we found that, indeed, it matches the one of the calcium signal in presynaptic T4 cells.SIGNIFICANCE STATEMENT The transformation of voltage to calcium influx is an important step in the signaling cascade within a nerve cell. While this process has been intensely studied in the context of transmitter release mechanism, its consequences for information transmission and neural computation are unclear. Here, we measured both membrane voltage and cytosolic calcium levels in direction-selective cells of Drosophila in response to a large set of visual stimuli. We found direction selectivity in the calcium signal to be significantly enhanced compared with membrane voltage through a nonlinear transformation of voltage to calcium. Our findings highlight the importance of an additional step in the signaling cascade for information processing within single nerve cells.
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Affiliation(s)
- Abhishek Mishra
- Max Planck Institute for Biological Intelligence, 82152 Martinsried, Germany
- Graduate School of Systemic Neurosciences, Ludwig Maximilian University of Munich, 82152 Martinsried, Germany
| | - Etienne Serbe-Kamp
- Max Planck Institute for Biological Intelligence, 82152 Martinsried, Germany
| | - Alexander Borst
- Max Planck Institute for Biological Intelligence, 82152 Martinsried, Germany
- Graduate School of Systemic Neurosciences, Ludwig Maximilian University of Munich, 82152 Martinsried, Germany
| | - Juergen Haag
- Max Planck Institute for Biological Intelligence, 82152 Martinsried, Germany
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Praschberger R, Kuenen S, Schoovaerts N, Kaempf N, Singh J, Janssens J, Swerts J, Nachman E, Calatayud C, Aerts S, Poovathingal S, Verstreken P. Neuronal identity defines α-synuclein and tau toxicity. Neuron 2023; 111:1577-1590.e11. [PMID: 36948206 DOI: 10.1016/j.neuron.2023.02.033] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/22/2022] [Accepted: 02/23/2023] [Indexed: 03/24/2023]
Abstract
Pathogenic α-synuclein and tau are critical drivers of neurodegeneration, and their mutations cause neuronal loss in patients. Whether the underlying preferential neuronal vulnerability is a cell-type-intrinsic property or a consequence of increased expression levels remains elusive. Here, we explore cell-type-specific α-synuclein and tau expression in human brain datasets and use deep phenotyping as well as brain-wide single-cell RNA sequencing of >200 live neuron types in fruit flies to determine which cellular environments react most to α-synuclein or tau toxicity. We detect phenotypic and transcriptomic evidence of differential neuronal vulnerability independent of α-synuclein or tau expression levels. Comparing vulnerable with resilient neurons in Drosophila enabled us to predict numerous human neuron subtypes with increased intrinsic susceptibility to pathogenic α-synuclein or tau. By uncovering synapse- and Ca2+ homeostasis-related genes as tau toxicity modifiers, our work paves the way to leverage neuronal identity to uncover modifiers of neurodegeneration-associated toxic proteins.
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Affiliation(s)
- Roman Praschberger
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium.
| | - Sabine Kuenen
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Nils Schoovaerts
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Natalie Kaempf
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Jeevanjot Singh
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Jasper Janssens
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Human Genetics, 3000 Leuven, Belgium
| | - Jef Swerts
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Eliana Nachman
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Carles Calatayud
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Stein Aerts
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Human Genetics, 3000 Leuven, Belgium
| | | | - Patrik Verstreken
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium.
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Osaka J, Yasuda H, Watanuki Y, Kato Y, Nitta Y, Sugie A, Sato M, Suzuki T. Identification of genes regulating stimulus-dependent synaptic assembly in Drosophila using an automated synapse quantification system. Genes Genet Syst 2023; 97:297-309. [PMID: 36878557 DOI: 10.1266/ggs.22-00114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
Abstract
Neural activity-dependent synaptic plasticity is an important physiological phenomenon underlying environmental adaptation, memory and learning. However, its molecular basis, especially in presynaptic neurons, is not well understood. Previous studies have shown that the number of presynaptic active zones in the Drosophila melanogaster photoreceptor R8 is reversibly changed in an activity-dependent manner. During reversible synaptic changes, both synaptic disassembly and assembly processes were observed. Although we have established a paradigm for screening molecules involved in synaptic stability and several genes have been identified, genes involved in stimulus-dependent synaptic assembly are still elusive. Therefore, the aim of this study was to identify genes regulating stimulus-dependent synaptic assembly in Drosophila using an automated synapse quantification system. To this end, we performed RNAi screening against 300 memory-defective, synapse-related or transmembrane molecules in photoreceptor R8 neurons. Candidate genes were narrowed down to 27 genes in the first screen using presynaptic protein aggregation as a sign of synaptic disassembly. In the second screen, we directly quantified the decreasing synapse number using a GFP-tagged presynaptic protein marker. We utilized custom-made image analysis software, which automatically locates synapses and counts their number along individual R8 axons, and identified cirl as a candidate gene responsible for synaptic assembly. Finally, we present a new model of stimulus-dependent synaptic assembly through the interaction of cirl and its possible ligand, ten-a. This study demonstrates the feasibility of using the automated synapse quantification system to explore activity-dependent synaptic plasticity in Drosophila R8 photoreceptors in order to identify molecules involved in stimulus-dependent synaptic assembly.
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Affiliation(s)
- Jiro Osaka
- School of Life Science and Technology, Tokyo Institute of Technology
| | - Haruka Yasuda
- School of Life Science and Technology, Tokyo Institute of Technology
| | - Yusuke Watanuki
- School of Life Science and Technology, Tokyo Institute of Technology
| | - Yuya Kato
- School of Life Science and Technology, Tokyo Institute of Technology
| | - Yohei Nitta
- Brain Research Institute, Niigata University
| | | | - Makoto Sato
- Mathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University.,Graduate School of Frontier Science Initiative, Kanazawa University
| | - Takashi Suzuki
- School of Life Science and Technology, Tokyo Institute of Technology
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Meissner GW, Nern A, Dorman Z, DePasquale GM, Forster K, Gibney T, Hausenfluck JH, He Y, Iyer NA, Jeter J, Johnson L, Johnston RM, Lee K, Melton B, Yarbrough B, Zugates CT, Clements J, Goina C, Otsuna H, Rokicki K, Svirskas RR, Aso Y, Card GM, Dickson BJ, Ehrhardt E, Goldammer J, Ito M, Kainmueller D, Korff W, Mais L, Minegishi R, Namiki S, Rubin GM, Sterne GR, Wolff T, Malkesman O. A searchable image resource of Drosophila GAL4 driver expression patterns with single neuron resolution. eLife 2023; 12:e80660. [PMID: 36820523 PMCID: PMC10030108 DOI: 10.7554/elife.80660] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 02/21/2023] [Indexed: 02/24/2023] Open
Abstract
Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here, we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end, we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.
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Affiliation(s)
- Geoffrey W Meissner
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Zachary Dorman
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gina M DePasquale
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Kaitlyn Forster
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Theresa Gibney
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | | | - Yisheng He
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Nirmala A Iyer
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Jennifer Jeter
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Lauren Johnson
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Rebecca M Johnston
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Kelley Lee
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Brian Melton
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Brianna Yarbrough
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | | | - Jody Clements
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Cristian Goina
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Hideo Otsuna
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Konrad Rokicki
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Robert R Svirskas
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Yoshinori Aso
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Erica Ehrhardt
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Jens Goldammer
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Masayoshi Ito
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Dagmar Kainmueller
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC)BerlinGermany
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Lisa Mais
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC)BerlinGermany
| | - Ryo Minegishi
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Shigehiro Namiki
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gabriella R Sterne
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Tanya Wolff
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Oz Malkesman
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
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36
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Zhang Y, Lowe S, Ding AZ, Li X. Notch-dependent binary fate choice regulates the Netrin pathway to control axon guidance of Drosophila visual projection neurons. Cell Rep 2023; 42:112143. [PMID: 36821442 PMCID: PMC10124989 DOI: 10.1016/j.celrep.2023.112143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 10/22/2022] [Accepted: 02/07/2023] [Indexed: 02/24/2023] Open
Abstract
Notch-dependent binary fate choice between sister neurons is one of the mechanisms to generate neural diversity. How these upstream neural fate specification programs regulate downstream effector genes to control axon targeting and neuropil assembly remains less well understood. Here, we report that Notch-dependent binary fate choice in Drosophila medulla neurons is required to regulate the Netrin axon guidance pathway, which controls targeting of transmedullary (Tm) neurons to lobula. In medulla neurons of Notch-on hemilineage composed of mostly lobula-targeting neurons, Notch signaling is required to activate the expression of Netrin-B and repress the expression of its repulsive receptor Unc-5. Turning off Unc-5 is necessary for Tm neurons to target lobula. Furthermore, Netrin-B provided by Notch-on medulla neurons is required for correct targeting of Tm axons from later-generated medulla columns. Thus, the coordinate regulation of Netrin pathway components by Notch signaling ensures correct targeting of Tm axons and contributes to the neuropil assembly.
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Affiliation(s)
- Yu Zhang
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Scott Lowe
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Andrew Z Ding
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Xin Li
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
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37
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Bengochea M, Hassan B. Numerosity as a visual property: Evidence from two highly evolutionary distant species. Front Physiol 2023; 14:1086213. [PMID: 36846325 PMCID: PMC9949967 DOI: 10.3389/fphys.2023.1086213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/31/2023] [Indexed: 02/11/2023] Open
Abstract
Most animals, from humans to invertebrates, possess an ability to estimate numbers. This evolutionary advantage facilitates animals' choice of environments with more food sources, more conspecifics to increase mating success, and/or reduced predation risk among others. However, how the brain processes numerical information remains largely unknown. There are currently two lines of research interested in how numerosity of visual objects is perceived and analyzed in the brain. The first argues that numerosity is an advanced cognitive ability processed in high-order brain areas, while the second proposes that "numbers" are attributes of the visual scene and thus numerosity is processed in the visual sensory system. Recent evidence points to a sensory involvement in estimating magnitudes. In this Perspective, we highlight this evidence in two highly evolutionary distant species: humans and flies. We also discuss the advantages of studying numerical processing in fruit flies in order to dissect the neural circuits involved in and required for numerical processing. Based on experimental manipulation and the fly connectome, we propose a plausible neural network for number sense in invertebrates.
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Affiliation(s)
| | - Bassem Hassan
- *Correspondence: Mercedes Bengochea, ; Bassem Hassan,
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38
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Chen YCD, Chen YC, Rajesh R, Shoji N, Jacy M, Lacin H, Erclik T, Desplan C. Using single-cell RNA sequencing to generate cell-type-specific split-GAL4 reagents throughout development. bioRxiv 2023:2023.02.03.527019. [PMID: 36778312 PMCID: PMC9915743 DOI: 10.1101/2023.02.03.527019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Cell-type-specific tools facilitate the identification and functional characterization of distinct cell types, which underly the complexity of neuronal circuits. A large collection of existing genetic tools in Drosophila relies on enhancer activity to label different subsets of cells. These enhancer-based GAL4 lines often fail to show a predicable expression pattern to reflect the expression of nearby gene(s), partly due to an incomplete capture of the full gene regulatory elements. While genetic intersectional technique such as the split-GAL4 system further improve cell-type-specificity, it requires significant time and resource to generate and screen through combinations of enhancer expression patterns. In addition, since existing enhancer-based split-GAL4 lines that show cell-type-specific labeling in adult are not necessarily active nor specific in early development, there is a relative lack of tools for the study of neural development. Here, we use an existing single-cell RNA sequencing (scRNAseq) dataset to select gene pairs and provide an efficient pipeline to generate cell-type-specific split-GAL4 lines based on the native genetic regulatory elements. These gene-specific split-GAL4 lines can be generated from a large collection of coding intronic MiMIC/CRIMIC lines either by embryo injection or in vivo cassette swapping crosses and/or CRISPR knock-in at the N or C terminal of the gene. We use the developing Drosophila visual system as a model to demonstrate the high prediction power of scRNAseq-guided gene specific split-GAL4 lines in targeting known cell types. The toolkit allows efficient cluster annotation in scRNAseq datasets but also the identification of novel cell types. Lastly, the gene-specific split-GAL4 lines are broadly applicable to Drosophila tissues. Our work opens new avenues for generating cell-type-specific tools for the targeted manipulation of distinct cell types throughout development and represents a valuable resource to the fly research community. Significance Statement Understanding the functional role of individual cell types in the nervous systems has remained a major challenge for neuroscience researchers, partly due to incomplete identification and characterization of underlying cell types. To study the development of individual cell types and their functional roles in health and disease, experimental access to a specific cell type is often a prerequisite. Here, we establish an experimental pipeline to generate gene-specific split-GAL4 guided by single-cell RNA sequencing datasets. These lines show high accuracy for labeling targeted cell types from early developmental stages to adulthood and can be applied to any tissues in Drosophila. The collection of gene-speicifc-split-GAL4 will provide a valuable resource to the entire fly research community.
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Affiliation(s)
| | - Yen-Chung Chen
- Department of Biology, New York University, New York, NY 10003, USA
| | - Raghuvanshi Rajesh
- Department of Biology, New York University, New York, NY 10003, USA
- Center for Genomics and Systems Biology, New York University, Abu Dhabi 51133, United Arab Emirates
| | - Nathalie Shoji
- Department of Biology, New York University, New York, NY 10003, USA
| | - Maisha Jacy
- Department of Biology, New York University, New York, NY 10003, USA
| | - Haluk Lacin
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ted Erclik
- Department of Cell and Systems Biology, University of Toronto, Toronto, M5S 1A1, Canada
| | - Claude Desplan
- Department of Biology, New York University, New York, NY 10003, USA
- Center for Genomics and Systems Biology, New York University, Abu Dhabi 51133, United Arab Emirates
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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40
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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 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] [What about the content of this article? (0)] [Affiliation(s)] [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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41
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Schenk JE, Gaudry Q. Nonspiking Interneurons in the Drosophila Antennal Lobe Exhibit Spatially Restricted Activity. eNeuro 2023; 10:ENEURO. [PMID: 36650069 DOI: 10.1523/ENEURO.0109-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 09/17/2022] [Accepted: 10/21/2022] [Indexed: 01/19/2023] Open
Abstract
Inhibitory interneurons are important for neuronal circuit function. They regulate sensory inputs and enhance output discriminability (Olsen and Wilson, 2008; Root et al., 2008; Olsen et al., 2010). Often, the identities of interneurons can be determined by location and morphology, which can have implications for their functions (Wachowiak and Shipley, 2006). While most interneurons fire traditional action potentials, many are nonspiking. These can be seen in insect olfaction (Laurent and Davidowitz, 1994; Husch et al., 2009; Tabuchi et al., 2015) and the vertebrate retina (Gleason et al., 1993). Here, we present the novel observation of nonspiking inhibitory interneurons in the antennal lobe (AL) of the adult fruit fly, Drosophila melanogaster These neurons have a morphology where they innervate a patchwork of glomeruli. We used electrophysiology to determine whether their nonspiking characteristic is because of a lack of sodium current. We then used immunohistochemsitry and in situ hybridization to show this is likely achieved through translational regulation of the voltage-gated sodium channel gene, para Using in vivo calcium imaging, we explored how these cells respond to odors, finding regional isolation in their responses' spatial patterns. Further, their response patterns were dependent on both odor identity and concentration. Thus, we surmise these neurons are electrotonically compartmentalized such that activation of the neurites in one region does not propagate across the whole antennal lobe. We propose these neurons may be the source of intraglomerular inhibition in the AL and may contribute to regulation of spontaneous activity within glomeruli.
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42
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Özel MN, Gibbs CS, Holguera I, Soliman M, Bonneau R, Desplan C. Coordinated control of neuronal differentiation and wiring by sustained transcription factors. Science 2022; 378:eadd1884. [PMID: 36480601 DOI: 10.1126/science.add1884] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The large diversity of cell types in nervous systems presents a challenge in identifying the genetic mechanisms that encode it. Here, we report that nearly 200 distinct neurons in the Drosophila visual system can each be defined by unique combinations of on average 10 continuously expressed transcription factors. We show that targeted modifications of this terminal selector code induce predictable conversions of neuronal fates that appear morphologically and transcriptionally complete. Cis-regulatory analysis of open chromatin links one of these genes to an upstream patterning factor that specifies neuronal fates in stem cells. Experimentally validated network models describe the synergistic regulation of downstream effectors by terminal selectors and ecdysone signaling during brain wiring. Our results provide a generalizable framework of how specific fates are implemented in postmitotic neurons.
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Affiliation(s)
| | - Claudia Skok Gibbs
- Flatiron Institute, Center for Computational Biology, Simons Foundation, New York, NY 10010, USA.,Center for Data Science, New York University, New York, NY 10003, USA
| | - Isabel Holguera
- Department of Biology, New York University, New York, NY 10003, USA
| | - Mennah Soliman
- Department of Biology, New York University, New York, NY 10003, USA
| | - Richard Bonneau
- Department of Biology, New York University, New York, NY 10003, USA.,Flatiron Institute, Center for Computational Biology, Simons Foundation, New York, NY 10010, USA.,Center for Data Science, New York University, New York, NY 10003, USA
| | - Claude Desplan
- Department of Biology, New York University, New York, NY 10003, USA.,New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
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43
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Sato M, Suzuki T. Cutting edge technologies expose the temporal regulation of neurogenesis in the Drosophila nervous system. Fly (Austin) 2022; 16:222-232. [PMID: 35549651 PMCID: PMC9116403 DOI: 10.1080/19336934.2022.2073158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/28/2022] [Accepted: 04/28/2022] [Indexed: 11/23/2022] Open
Abstract
During the development of the central nervous system (CNS), extremely large numbers of neurons are produced in a regular fashion to form precise neural circuits. During this process, neural progenitor cells produce different neurons over time due to their intrinsic gene regulatory mechanisms as well as extrinsic mechanisms. The Drosophila CNS has played an important role in elucidating the temporal mechanisms that control neurogenesis over time. It has been shown that a series of temporal transcription factors are sequentially expressed in neural progenitor cells and regulate the temporal specification of neurons in the embryonic CNS. Additionally, similar mechanisms are found in the developing optic lobe and central brain in the larval CNS. However, it is difficult to elucidate the function of numerous molecules in many different cell types solely by molecular genetic approaches. Recently, omics analysis using single-cell RNA-seq and other methods has been used to study the Drosophila nervous system on a large scale and is making a significant contribution to the understanding of the temporal mechanisms of neurogenesis. In this article, recent findings on the temporal patterning of neurogenesis and the contributions of cutting-edge technologies will be reviewed.
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Affiliation(s)
- Makoto Sato
- Mathematical Neuroscience Unit, Institute for Frontier Science Initiative,Laboratory of Developmental Neurobiology, Graduate School of Medical Sciences, Kanazawa University, Ishikawa, Japan
| | - Takumi Suzuki
- College of Science, Department of Science, Ibaraki University, Ibaraki, Japan
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44
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Gonzalez-Suarez AD, Zavatone-Veth JA, Chen J, Matulis CA, Badwan BA, Clark DA. Excitatory and inhibitory neural dynamics jointly tune motion detection. Curr Biol 2022; 32:3659-3675.e8. [PMID: 35868321 PMCID: PMC9474608 DOI: 10.1016/j.cub.2022.06.075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 05/03/2022] [Accepted: 06/24/2022] [Indexed: 11/26/2022]
Abstract
Neurons integrate excitatory and inhibitory signals to produce their outputs, but the role of input timing in this integration remains poorly understood. Motion detection is a paradigmatic example of this integration, since theories of motion detection rely on different delays in visual signals. These delays allow circuits to compare scenes at different times to calculate the direction and speed of motion. Different motion detection circuits have different velocity sensitivity, but it remains untested how the response dynamics of individual cell types drive this tuning. Here, we sped up or slowed down specific neuron types in Drosophila's motion detection circuit by manipulating ion channel expression. Altering the dynamics of individual neuron types upstream of motion detectors increased their sensitivity to fast or slow visual motion, exposing distinct roles for excitatory and inhibitory dynamics in tuning directional signals, including a role for the amacrine cell CT1. A circuit model constrained by functional data and anatomy qualitatively reproduced the observed tuning changes. Overall, these results reveal how excitatory and inhibitory dynamics together tune a canonical circuit computation.
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Affiliation(s)
| | - Jacob A Zavatone-Veth
- Department of Physics, Harvard University, Cambridge, MA 02138, USA; Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Juyue Chen
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | | | - Bara A Badwan
- School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA
| | - Damon A Clark
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA; Department of Physics, Yale University, New Haven, CT 06511, USA; Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06511, USA; Department of Neuroscience, Yale University, New Haven, CT 06511, USA.
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45
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Hayashi M, Kazawa T, Tsunoda H, Kanzaki R. The Understanding of ON-Edge Motion Detection Through the Simulation Based on the Connectome of Drosophila’s Optic Lobe. JRM 2022. [DOI: 10.20965/jrm.2022.p0795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The optic lobe of the fly is one of the prominent model systems for the neural mechanism of the motion detection. How a fly who lives under various visual situations of the nature processes the information from at most a few thousands of ommatidia in their neural circuit for the detection of moving objects is not exactly clear though many computational models of the fly optic lobe as a moving objects detector were suggested. Here we attempted to elucidate the mechanisms of ON-edge motion detection by a simulation approach based on the TEM connectome of Drosophila. Our simulation model of the optic lobe with the NEURON simulator that covers the full scale of ommatidia, reproduced the characteristics of the receptor neurons, lamina monopolar neurons, and T4 cells in the lobula. The contribution of each neuron can be estimated by changing synaptic connection strengths in the simulation and measuring the response to the motion stimulus. Those show the paradelle pathway provide motion detection in the fly optic lobe has more robustness and is more sophisticated than a simple combination of HR and BL systems.
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46
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Chen PJ, Li Y, Lee CH. Calcium Imaging of Neural Activity in Fly Photoreceptors. Cold Spring Harb Protoc 2022; 2022:Pdb.top107800. [PMID: 35641092 DOI: 10.1101/pdb.top107800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Functional imaging methodologies allow researchers to simultaneously monitor the neural activities of all single neurons in a population, and this ability has led to great advances in neuroscience research. Taking advantage of a genetically tractable model organism, functional imaging in Drosophila provides opportunities to probe scientific questions that were previously unanswerable by electrophysiological recordings. Here, we introduce comprehensive protocols for two-photon calcium imaging in fly visual neurons. We also discuss some challenges in applying optical imaging techniques to study visual systems and consider the best practices for making comparisons between different neuron groups.
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Affiliation(s)
- Pei-Ju Chen
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei 11529, Taiwan, Republic of China
| | - Yan Li
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei 11529, Taiwan, Republic of China
| | - Chi-Hon Lee
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei 11529, Taiwan, Republic of China
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47
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Shinomiya K, Nern A, Meinertzhagen IA, Plaza SM, Reiser MB. Neuronal circuits integrating visual motion information in Drosophila melanogaster. Curr Biol 2022; 32:3529-3544.e2. [PMID: 35839763 DOI: 10.1016/j.cub.2022.06.061] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/17/2022] [Accepted: 06/20/2022] [Indexed: 11/25/2022]
Abstract
The detection of visual motion enables sophisticated animal navigation, and studies on flies have provided profound insights into the cellular and circuit bases of this neural computation. The fly's directionally selective T4 and T5 neurons encode ON and OFF motion, respectively. Their axons terminate in one of the four retinotopic layers in the lobula plate, where each layer encodes one of the four directions of motion. Although the input circuitry of the directionally selective neurons has been studied in detail, the synaptic connectivity of circuits integrating T4/T5 motion signals is largely unknown. Here, we report a 3D electron microscopy reconstruction, wherein we comprehensively identified T4/T5's synaptic partners in the lobula plate, revealing a diverse set of new cell types and attributing new connectivity patterns to the known cell types. Our reconstruction explains how the ON- and OFF-motion pathways converge. T4 and T5 cells that project to the same layer connect to common synaptic partners and comprise a core motif together with bilayer interneurons, detailing the circuit basis for computing motion opponency. We discovered pathways that likely encode new directions of motion by integrating vertical and horizontal motion signals from upstream T4/T5 neurons. Finally, we identify substantial projections into the lobula, extending the known motion pathways and suggesting that directionally selective signals shape feature detection there. The circuits we describe enrich the anatomical basis for experimental and computations analyses of motion vision and bring us closer to understanding complete sensory-motor pathways.
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Affiliation(s)
- Kazunori Shinomiya
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Ian A Meinertzhagen
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Department of Psychology and Neuroscience, Dalhousie University, 1355 Oxford Street, Halifax, NS B3H 4R2, Canada
| | - Stephen M Plaza
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Michael B Reiser
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
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48
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Li Q, Wang M, Zhang P, Liu Y, Guo Q, Zhu Y, Wen T, Dai X, Zhang X, Nagel M, Dethlefsen BH, Xie N, Zhao J, Jiang W, Han L, Wu L, Zhong W, Wang Z, Wei X, Dai W, Liu L, Xu X, Lu H, Yang H, Wang J, Boomsma JJ, Liu C, Zhang G, Liu W. A single-cell transcriptomic atlas tracking the neural basis of division of labour in an ant superorganism. Nat Ecol Evol 2022; 6:1191-1204. [PMID: 35711063 PMCID: PMC9349048 DOI: 10.1038/s41559-022-01784-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 05/03/2022] [Indexed: 01/21/2023]
Abstract
Ant colonies with permanent division of labour between castes and highly distinct roles of the sexes have been conceptualized to be superorganisms, but the cellular and molecular mechanisms that mediate caste/sex-specific behavioural specialization have remained obscure. Here we characterized the brain cell repertoire of queens, gynes (virgin queens), workers and males of Monomorium pharaonis by obtaining 206,367 single-nucleus transcriptomes. In contrast to Drosophila, the mushroom body Kenyon cells are abundant in ants and display a high diversity with most subtypes being enriched in worker brains, the evolutionarily derived caste. Male brains are as specialized as worker brains but with opposite trends in cell composition with higher abundances of all optic lobe neuronal subtypes, while the composition of gyne and queen brains remained generalized, reminiscent of solitary ancestors. Role differentiation from virgin gynes to inseminated queens induces abundance changes in roughly 35% of cell types, indicating active neurogenesis and/or programmed cell death during this transition. We also identified insemination-induced cell changes probably associated with the longevity and fecundity of the reproductive caste, including increases of ensheathing glia and a population of dopamine-regulated Dh31-expressing neurons. We conclude that permanent caste differentiation and extreme sex-differentiation induced major changes in the neural circuitry of ants. Using single-cell transcriptomics, the authors generate a brain cell atlas for the pharaoh ant including individuals of different sexes and castes and show changes in cell composition underlying division of labour and reproductive specialization.
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Affiliation(s)
- Qiye Li
- BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | | | | | - Qunfei Guo
- BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | | | - Xueqin Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Xiafang Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Manuel Nagel
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Bjarke Hamberg Dethlefsen
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Nianxia Xie
- BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jie Zhao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | | | - Lei Han
- BGI-Shenzhen, Shenzhen, China
| | - Liang Wu
- BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Wenjiang Zhong
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | | | | | - Wei Dai
- BGI-Shenzhen, Shenzhen, China
| | - Longqi Liu
- BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.,Shenzhen Bay Laboratory, Shenzhen, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.,Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, China
| | - Haorong Lu
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, China.,James D. Watson Institute of Genome Science, Hangzhou, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen, China.,James D. Watson Institute of Genome Science, Hangzhou, China
| | - Jacobus J Boomsma
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | - Guojie Zhang
- BGI-Shenzhen, Shenzhen, China. .,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. .,Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China. .,Evolutionary and Organismal Biology Research Center, School of Medicine, Zhejiang University, Hangzhou, China.
| | - Weiwei Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
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49
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Duhart JC, Mosca TJ. Genetic regulation of central synapse formation and organization in Drosophila melanogaster. Genetics 2022; 221:6597078. [PMID: 35652253 DOI: 10.1093/genetics/iyac078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/29/2022] [Indexed: 01/04/2023] Open
Abstract
A goal of modern neuroscience involves understanding how connections in the brain form and function. Such a knowledge is essential to inform how defects in the exquisite complexity of nervous system growth influence neurological disease. Studies of the nervous system in the fruit fly Drosophila melanogaster enabled the discovery of a wealth of molecular and genetic mechanisms underlying development of synapses-the specialized cell-to-cell connections that comprise the essential substrate for information flow and processing in the nervous system. For years, the major driver of knowledge was the neuromuscular junction due to its ease of examination. Analogous studies in the central nervous system lagged due to a lack of genetic accessibility of specific neuron classes, synaptic labels compatible with cell-type-specific access, and high resolution, quantitative imaging strategies. However, understanding how central synapses form remains a prerequisite to understanding brain development. In the last decade, a host of new tools and techniques extended genetic studies of synapse organization into central circuits to enhance our understanding of synapse formation, organization, and maturation. In this review, we consider the current state-of-the-field. We first discuss the tools, technologies, and strategies developed to visualize and quantify synapses in vivo in genetically identifiable neurons of the Drosophila central nervous system. Second, we explore how these tools enabled a clearer understanding of synaptic development and organization in the fly brain and the underlying molecular mechanisms of synapse formation. These studies establish the fly as a powerful in vivo genetic model that offers novel insights into neural development.
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Affiliation(s)
- Juan Carlos Duhart
- Department of Neuroscience, Vickie and Jack Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Timothy J Mosca
- Department of Neuroscience, Vickie and Jack Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA
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50
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Ryu L, Kim SY, Kim AJ. From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila. Front Neurosci 2022; 16:883640. [PMID: 35600623 PMCID: PMC9115102 DOI: 10.3389/fnins.2022.883640] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 03/28/2022] [Indexed: 11/17/2022] Open
Abstract
Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.
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Affiliation(s)
- Leesun Ryu
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Sung Yong Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Anmo J. Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
- *Correspondence: Anmo J. Kim,
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