1
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Bonanno SL, Sanfilippo P, Eamani A, Sampson MM, Kandagedon B, Li K, Burns GD, Makar ME, Zipursky SL, Krantz DE. Constitutive and Conditional Epitope Tagging of Endogenous G-Protein-Coupled Receptors in Drosophila. J Neurosci 2024; 44:e2377232024. [PMID: 38937100 PMCID: PMC11326870 DOI: 10.1523/jneurosci.2377-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/30/2024] [Accepted: 06/06/2024] [Indexed: 06/29/2024] Open
Abstract
To visualize the cellular and subcellular localization of neuromodulatory G-protein-coupled receptors in Drosophila, we implement a molecular strategy recently used to add epitope tags to ionotropic receptors at their endogenous loci. Leveraging evolutionary conservation to identify sites more likely to permit insertion of a tag, we generated constitutive and conditional tagged alleles for Drosophila 5-HT1A, 5-HT2A, 5-HT2B, Oct β 1R, Oct β 2R, two isoforms of OAMB, and mGluR The conditional alleles allow for the restricted expression of tagged receptor in specific cell types, an option not available for any previous reagents to label these proteins. We show expression patterns for these receptors in female brains and that 5-HT1A and 5-HT2B localize to the mushroom bodies (MBs) and central complex, respectively, as predicted by their roles in sleep. By contrast, the unexpected enrichment of Octβ1R in the central complex and of 5-HT1A and 5-HT2A to nerve terminals in lobular columnar cells in the visual system suggest new hypotheses about their functions at these sites. Using an additional tagged allele of the serotonin transporter, a marker of serotonergic tracts, we demonstrate diverse spatial relationships between postsynaptic 5-HT receptors and presynaptic 5-HT neurons, consistent with the importance of both synaptic and volume transmission. Finally, we use the conditional allele of 5-HT1A to show that it localizes to distinct sites within the MBs as both a postsynaptic receptor in Kenyon cells and a presynaptic autoreceptor.
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Affiliation(s)
- Shivan L Bonanno
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - Piero Sanfilippo
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, California 90095
- Howard Hughes Medical Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90095
| | - Aditya Eamani
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - Maureen M Sampson
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - Binu Kandagedon
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - Kenneth Li
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - Giselle D Burns
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - Marylyn E Makar
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
| | - S Lawrence Zipursky
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, California 90095
- Howard Hughes Medical Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90095
| | - David E Krantz
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, California 90095
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2
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Lee GG, Peterson AJ, Kim MJ, O’Connor MB, Park JH. Multiple isoforms of the Activin-like receptor baboon differentially regulate proliferation and conversion behaviors of neuroblasts and neuroepithelial cells in the Drosophila larval brain. PLoS One 2024; 19:e0305696. [PMID: 38913612 PMCID: PMC11195991 DOI: 10.1371/journal.pone.0305696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 06/04/2024] [Indexed: 06/26/2024] Open
Abstract
In Drosophila coordinated proliferation of two neural stem cells, neuroblasts (NB) and neuroepithelial (NE) cells, is pivotal for proper larval brain growth that ultimately determines the final size and performance of an adult brain. The larval brain growth displays two phases based on behaviors of NB and NEs: the first one in early larval stages, influenced by nutritional status and the second one in the last larval stage, promoted by ecdysone signaling after critical weight checkpoint. Mutations of the baboon (babo) gene that produces three isoforms (BaboA-C), all acting as type-I receptors of Activin-type transforming growth factor β (TGF-β) signaling, cause a small brain phenotype due to severely reduced proliferation of the neural stem cells. In this study we show that loss of babo function severely affects proliferation of NBs and NEs as well as conversion of NEs from both phases. By analyzing babo-null and newly generated isoform-specific mutants by CRISPR mutagenesis as well as isoform-specific RNAi knockdowns in a cell- and stage-specific manner, our data support differential contributions of the isoforms for these cellular events with BaboA playing the major role. Stage-specific expression of EcR-B1 in the brain is also regulated primarily by BaboA along with function of the other isoforms. Blocking EcR function in both neural stem cells results in a small brain phenotype that is more severe than baboA-knockdown alone. In summary, our study proposes that the Babo-mediated signaling promotes proper behaviors of the neural stem cells in both phases and achieves this by acting upstream of EcR-B1 expression in the second phase.
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Affiliation(s)
- Gyunghee G. Lee
- Department of Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Aidan J. Peterson
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Myung-Jun Kim
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Michael B. O’Connor
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Jae H. Park
- Department of Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee, United States of America
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3
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Malin JA, Chen YC, Simon F, Keefer E, Desplan C. Spatial patterning controls neuron numbers in the Drosophila visual system. Dev Cell 2024; 59:1132-1145.e6. [PMID: 38531357 PMCID: PMC11078608 DOI: 10.1016/j.devcel.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 12/18/2023] [Accepted: 03/01/2024] [Indexed: 03/28/2024]
Abstract
Neurons must be made in the correct proportions to communicate with the appropriate synaptic partners and form functional circuits. In the Drosophila visual system, multiple subtypes of distal medulla (Dm) inhibitory interneurons are made in distinct, reproducible numbers-from 5 to 800 per optic lobe. These neurons are born from a crescent-shaped neuroepithelium called the outer proliferation center (OPC), which can be subdivided into specific domains based on transcription factor and growth factor expression. We fate mapped Dm neurons and found that more abundant neural types are born from larger neuroepithelial subdomains, while less abundant subtypes are born from smaller ones. Additionally, morphogenetic Dpp/BMP signaling provides a second layer of patterning that subdivides the neuroepithelium into smaller domains to provide more granular control of cell proportions. Apoptosis appears to play a minor role in regulating Dm neuron abundance. This work describes an underappreciated mechanism for the regulation of neuronal stoichiometry.
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Affiliation(s)
- Jennifer A Malin
- 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
| | - Félix Simon
- Department of Biology, New York University, New York, NY 10003, USA
| | - Evelyn Keefer
- Department of Biology, New York University, New York, NY 10003, USA
| | - Claude Desplan
- Department of Biology, New York University, New York, NY 10003, USA.
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4
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Bonanno SL, Sanfilippo P, Eamani A, Sampson MM, Binu K, Li K, Burns GD, Makar ME, Zipursky SL, Krantz DE. Constitutive and conditional epitope-tagging of endogenous G protein coupled receptors in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.27.573472. [PMID: 38234787 PMCID: PMC10793450 DOI: 10.1101/2023.12.27.573472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
To visualize the cellular and subcellular localization of neuromodulatory G-protein coupled receptors (GPCRs) in Drosophila , we implement a molecular strategy recently used to add epitope tags to ionotropic receptors at their endogenous loci. Leveraging evolutionary conservation to identify sites more likely to permit insertion of a tag, we generated constitutive and conditional tagged alleles for Drosophila 5-HT1A, 5-HT2A, 5-HT2B, Octβ1R, Octβ2R, two isoforms of OAMB, and mGluR. The conditional alleles allow for the restricted expression of tagged receptor in specific cell types, an option not available for any previous reagents to label these proteins. We show that 5-HT1A and 5-HT2B localize to the mushroom bodies and central complex respectively, as predicted by their roles in sleep. By contrast, the unexpected enrichment of Octβ1R in the central complex and of 5-HT1A and 5-HT2A to nerve terminals in lobular columnar cells in the visual system suggest new hypotheses about their function at these sites. Using an additional tagged allele of the serotonin transporter, a marker of serotonergic tracts, we demonstrate diverse spatial relationships between postsynaptic 5-HT receptors and presynaptic 5-HT neurons, consistent with the importance of both synaptic and volume transmission. Finally, we use the conditional allele of 5-HT1A to show that it localizes to distinct sites within the mushroom bodies as both a postsynaptic receptor in Kenyon cells and a presynaptic autoreceptor. Significance Statement In Drosophila , despite remarkable advances in both connectomic and genomic studies, antibodies to many aminergic GPCRs are not available. We have overcome this obstacle using evolutionary conservation to identify loci in GPCRs amenable to epitope-tagging, and CRISPR/Cas9 genome editing to generated eight novel lines. This method also may be applied to other GPCRs and allows cell-specific expression of the tagged locus. We have used the tagged alleles we generated to address several questions that remain poorly understood. These include the relationship between pre- and post-synaptic sites that express the same receptor, and the use of relatively distant targets by pre-synaptic release sites that may employ volume transmission as well as standard synaptic signaling.
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5
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Chua NJ, Makarova AA, Gunn P, Villani S, Cohen B, Thasin M, Wu J, Shefter D, Pang S, Xu CS, Hess HF, Polilov AA, Chklovskii DB. A complete reconstruction of the early visual system of an adult insect. Curr Biol 2023; 33:4611-4623.e4. [PMID: 37774707 DOI: 10.1016/j.cub.2023.09.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 10/01/2023]
Abstract
For most model organisms in neuroscience, research into visual processing in the brain is difficult because of a lack of high-resolution maps that capture complex neuronal circuitry. The microinsect Megaphragma viggianii, because of its small size and non-trivial behavior, provides a unique opportunity for tractable whole-organism connectomics. We image its whole head using serial electron microscopy. We reconstruct its compound eye and analyze the optical properties of the ommatidia as well as the connectome of the first visual neuropil-the lamina. Compared with the fruit fly and the honeybee, Megaphragma visual system is highly simplified: it has 29 ommatidia per eye and 6 lamina neuron types. We report features that are both stereotypical among most ommatidia and specialized to some. By identifying the "barebones" circuits critical for flying insects, our results will facilitate constructing computational models of visual processing in insects.
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Affiliation(s)
- Nicholas J Chua
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA; Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | | | - Pat Gunn
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Sonia Villani
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Ben Cohen
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Myisha Thasin
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Jingpeng Wu
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Deena Shefter
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Song Pang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - C Shan Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Harald F Hess
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Alexey A Polilov
- Faculty of Biology, Lomonosov Moscow State University, Moscow 119991, Russia
| | - Dmitri B Chklovskii
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA; Neuroscience Institute, New York University Langone Medical Center, New York, NY 10016, USA.
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6
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Pandey P, Shrestha B, Lee Y. Acid and Alkali Taste Sensation. Metabolites 2023; 13:1131. [PMID: 37999227 PMCID: PMC10673112 DOI: 10.3390/metabo13111131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 11/25/2023] Open
Abstract
Living organisms rely on pH levels for a multitude of crucial biological processes, such as the digestion of food and the facilitation of enzymatic reactions. Among these organisms, animals, including insects, possess specialized taste organs that enable them to discern between acidic and alkaline substances present in their food sources. This ability is vital, as the pH of these compounds directly influences both the nutritional value and the overall health impact of the ingested substances. In response to the various chemical properties of naturally occurring compounds, insects have evolved peripheral taste organs. These sensory structures play a pivotal role in identifying and distinguishing between nourishing and potentially harmful foods. In this concise review, we aim to provide an in-depth examination of the molecular mechanisms governing pH-dependent taste responses, encompassing both acidic and alkaline stimuli, within the peripheral taste organs of the fruit fly, Drosophila melanogaster, drawing insights from a comprehensive analysis of existing research articles.
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Affiliation(s)
| | | | - Youngseok Lee
- Department of Bio and Fermentation Convergence Technology, Kookmin University, Seoul 02707, Republic of Korea; (P.P.); (B.S.)
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7
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Mano O, Choi M, Tanaka R, Creamer MS, Matos NCB, Shomar JW, Badwan BA, Clandinin TR, Clark DA. Long-timescale anti-directional rotation in Drosophila optomotor behavior. eLife 2023; 12:e86076. [PMID: 37751469 PMCID: PMC10522332 DOI: 10.7554/elife.86076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 09/12/2023] [Indexed: 09/28/2023] Open
Abstract
Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.
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Affiliation(s)
- Omer Mano
- Department of Molecular, Cellular, and Developmental Biology, Yale UniversityNew HavenUnited States
| | - Minseung Choi
- Department of Neurobiology, Stanford UniversityStanfordUnited States
| | - Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
| | - Matthew S Creamer
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
| | - Natalia CB Matos
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
| | - Joseph W Shomar
- Department of Physics, Yale UniversityNew HavenUnited States
| | - Bara A Badwan
- Department of Chemical Engineering, Yale UniversityNew HavenUnited States
| | | | - Damon A Clark
- Department of Molecular, Cellular, and Developmental Biology, Yale UniversityNew HavenUnited States
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
- Department of Physics, Yale UniversityNew HavenUnited States
- Department of Neuroscience, Yale UniversityNew HavenUnited States
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8
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Grüter C, Balbuena MS, Valadares L. Mechanisms and adaptations that shape division of labour in stingless bees. CURRENT OPINION IN INSECT SCIENCE 2023; 58:101057. [PMID: 37230412 DOI: 10.1016/j.cois.2023.101057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 04/12/2023] [Accepted: 05/02/2023] [Indexed: 05/27/2023]
Abstract
Stingless bees are a diverse and ecologically important group of pollinators in the tropics. Division of labour allows bee colonies to meet the various demands of their social life, but has been studied in only ∼3% of all described stingless bee species. The available data suggest that division of labour shows both parallels and striking differences compared with other social bees. Worker age is a reliable predictor of worker behaviour in many species, while morphological variation in body size or differences in brain structure are important for specific worker tasks in some species. Stingless bees provide opportunities to confirm general patterns of division of labour, but they also offer prospects to discover and study novel mechanisms underlying the different lifestyles found in eusocial bees.
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Affiliation(s)
- Christoph Grüter
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, BS8 1TQ, UK.
| | - María Sol Balbuena
- Laboratorio de Insectos Sociales, Departamento de Biodiversidad y Biología Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, CABA, Argentina; Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), CONICET, Universidad de Ciencias Naturales y Exactas, Universidad de Buenos Aires, CABA, Argentina
| | - Lohan Valadares
- Evolution, Genomes, Behavior, and Ecology (EGCE), Université Paris-Saclay, CNRS, IRD, Gif-sur-Yvette, France
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9
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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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10
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Mano O, Choi M, Tanaka R, Creamer MS, Matos NC, Shomar J, Badwan BA, Clandinin TR, Clark DA. Long timescale anti-directional rotation in Drosophila optomotor behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.06.523055. [PMID: 36711627 PMCID: PMC9882005 DOI: 10.1101/2023.01.06.523055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied D. melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such "anti-directional turning" is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.
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Affiliation(s)
- Omer Mano
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Minseung Choi
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | - Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Matthew S. Creamer
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Natalia C.B. Matos
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Joseph Shomar
- Department of Physics, Yale University, New Haven, CT 06511, USA
| | - Bara A. Badwan
- Department of Chemical Engineering, Yale University, New Haven, CT 06511, USA
| | | | - Damon A. Clark
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06511, USA
- Interdepartmental Neuroscience Program, 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
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11
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Valadares L, Vieira BG, Santos do Nascimento F, Sandoz JC. Brain size and behavioral specialization in the jataí stingless bee (Tetragonisca angustula). J Comp Neurol 2022; 530:2304-2314. [PMID: 35513351 DOI: 10.1002/cne.25333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 04/11/2022] [Accepted: 04/13/2022] [Indexed: 11/08/2022]
Abstract
Social insects are instructive models for understanding the association between investment in brain size and behavioral variability because they show a relatively simple nervous system associated with a large set of complex behaviors. In the jataí stingless bee (Tetragonisca angustula), division of labor relies both on age and body size differences among workers. When young, both minors and soldiers engage in intranidal tasks and move to extranidal tasks as they age. Minors switch to foraging activities, while soldiers take over defensive roles. Nest defense performed by soldiers includes two different tasks: (1) hovering around the nest entrance for the detection and interception of heterospecific bees (a task relying mostly on vision) and (2) standing at the nest entrance tube for inspection of returning foragers and discrimination against conspecific non-nestmates based on olfactory cues. Here, using different-sized individuals (minors and soldiers) as well as same-sized individuals (hovering and standing soldiers) performing distinct tasks, we investigated the effects of both morphological and behavioral variability on brain size. We found a negative allometric growth between brain size and body size across jataí workers, meaning that minors had relatively larger brains than soldiers. Between soldier types, we found that hovering soldiers had larger brain compartments related to visual processing (the optic lobes) and learning (the mushroom bodies). Brain size differences between jataí soldiers thus correspond to behavioral specialization in defense (i.e., vision for hovering soldiers) and illustrate a functional neuroplasticity underpinning division of labor.
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Affiliation(s)
- Lohan Valadares
- Evolution, Genomes, Behavior, and Ecology (EGCE), Université Paris-Saclay, CNRS, IRD, Gif-sur-Yvette, France
| | - Bruno Gusmão Vieira
- Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Fabio Santos do Nascimento
- Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Jean-Christophe Sandoz
- Evolution, Genomes, Behavior, and Ecology (EGCE), Université Paris-Saclay, CNRS, IRD, Gif-sur-Yvette, France
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12
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Multimodal Information Processing and Associative Learning in the Insect Brain. INSECTS 2022; 13:insects13040332. [PMID: 35447774 PMCID: PMC9033018 DOI: 10.3390/insects13040332] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/23/2022] [Accepted: 03/25/2022] [Indexed: 02/04/2023]
Abstract
Simple Summary Insect behaviors are a great indicator of evolution and provide useful information about the complexity of organisms. The realistic sensory scene of an environment is complex and replete with multisensory inputs, making the study of sensory integration that leads to behavior highly relevant. We summarize the recent findings on multimodal sensory integration and the behaviors that originate from them in our review. Abstract The study of sensory systems in insects has a long-spanning history of almost an entire century. Olfaction, vision, and gustation are thoroughly researched in several robust insect models and new discoveries are made every day on the more elusive thermo- and mechano-sensory systems. Few specialized senses such as hygro- and magneto-reception are also identified in some insects. In light of recent advancements in the scientific investigation of insect behavior, it is not only important to study sensory modalities individually, but also as a combination of multimodal inputs. This is of particular significance, as a combinatorial approach to study sensory behaviors mimics the real-time environment of an insect with a wide spectrum of information available to it. As a fascinating field that is recently gaining new insight, multimodal integration in insects serves as a fundamental basis to understand complex insect behaviors including, but not limited to navigation, foraging, learning, and memory. In this review, we have summarized various studies that investigated sensory integration across modalities, with emphasis on three insect models (honeybees, ants and flies), their behaviors, and the corresponding neuronal underpinnings.
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Tanaka 田中涼介 R, Clark DA. Identifying Inputs to Visual Projection Neurons in Drosophila Lobula by Analyzing Connectomic Data. eNeuro 2022; 9:ENEURO.0053-22.2022. [PMID: 35410869 PMCID: PMC9034759 DOI: 10.1523/eneuro.0053-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/26/2022] [Accepted: 03/30/2022] [Indexed: 11/21/2022] Open
Abstract
Electron microscopy (EM)-based connectomes provide important insights into how visual circuitry of fruit fly Drosophila computes various visual features, guiding and complementing behavioral and physiological studies. However, connectomic analyses of the lobula, a neuropil putatively dedicated to detecting object-like features, remains underdeveloped, largely because of incomplete data on the inputs to the brain region. Here, we attempted to map the columnar inputs into the Drosophila lobula neuropil by performing connectivity-based and morphology-based clustering on a densely reconstructed connectome dataset. While the dataset mostly lacked visual neuropils other than lobula, which would normally help identify inputs to lobula, our clustering analysis successfully extracted clusters of cells with homogeneous connectivity and morphology, likely representing genuine cell types. We were able to draw a correspondence between the resulting clusters and previously identified cell types, revealing previously undocumented connectivity between lobula input and output neurons. While future, more complete connectomic reconstructions are necessary to verify the results presented here, they can serve as a useful basis for formulating hypotheses on mechanisms of visual feature detection in lobula.
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Affiliation(s)
- Ryosuke Tanaka 田中涼介
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511
| | - Damon A Clark
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511
- Department of Physics, Yale University, New Haven, CT 06511
- Department of Neuroscience, Yale University, New Haven, CT 06511
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14
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Nagel K. Motion vision: Pinning down motion computation in an ever-changing circuit. Curr Biol 2021; 31:R1523-R1525. [PMID: 34875241 DOI: 10.1016/j.cub.2021.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
A new electrophysiological study of the Drosophila visual system, recording from columnar inputs to motion-detecting neurons, has provided new insights into the computations that underlie motion vision.
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Affiliation(s)
- Katherine Nagel
- Neuroscience Institute, NYU School of Medicine, 435 E. 30(th) Street, Room 1102, New York, NY 10016, USA.
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15
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O'Donnell S, Bulova S, Barrett M. Experience-expectant brain plasticity corresponds to caste-specific abiotic challenges in dampwood termites (Zootermopsis angusticollis and Z. nevadensis). Naturwissenschaften 2021; 108:57. [PMID: 34665344 DOI: 10.1007/s00114-021-01763-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 09/21/2021] [Accepted: 09/22/2021] [Indexed: 02/03/2023]
Abstract
Hypotheses for adaptive brain investment predict associations between the relative sizes of functionally distinct brain regions and the sensory/cognitive demands animals confront. We measured developmental differences in the relative sizes of visual processing brain regions (optic lobes) among dampwood termite castes to test whether optic lobe investment matches caste differences in exposure to visually complex environments. The winged primary reproductives (Kings/Queens) on mating flights are the only caste to leave the dark nest cavities and as predicted, Kings/Queens showed greater relative investment in optic lobe tissue than nestbound (neotenic) reproductives and soldiers in two dampwood termite species (Zootermopsis angusticollis and Z. nevadensis). Relative optic lobe size spanned more than an order of magnitude among the castes we studied, suggesting the growth of the optic lobes incurs substantial tissue costs. Optic lobe growth was experience-expectant: the optic lobes of Z. angusticollis brachypterous nymphs, which typically develop into Kings/Queens, were relatively larger than the optic lobes of apterous nymphs, which precede neotenics and soldiers, and relative optic lobe size of nestbound brachypterous nymphs was statistically similar to that of Kings/Queens. Experience-expectant brain tissue growth is rarely documented in insects, likely because it entails high potential costs of tissue production and maintenance and relatively low immediate sensory/cognitive benefits. We develop hypotheses for the conditions under which experience-expectant growth in brain regions could be favored by natural selection.
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Affiliation(s)
- Sean O'Donnell
- Departments of Biodiversity Earth & Environmental Science and Biology, Drexel University, Philadelphia, PA, 19081, USA.
| | - Susan Bulova
- Departments of Biodiversity Earth & Environmental Science and Biology, Drexel University, Philadelphia, PA, 19081, USA
| | - Meghan Barrett
- Departments of Biodiversity Earth & Environmental Science and Biology, Drexel University, Philadelphia, PA, 19081, USA
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16
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Gruntman E, Reimers P, Romani S, Reiser MB. Non-preferred contrast responses in the Drosophila motion pathways reveal a receptive field structure that explains a common visual illusion. Curr Biol 2021; 31:5286-5298.e7. [PMID: 34672960 DOI: 10.1016/j.cub.2021.09.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 09/14/2021] [Accepted: 09/24/2021] [Indexed: 10/20/2022]
Abstract
Diverse sensory systems, from audition to thermosensation, feature a separation of inputs into ON (increments) and OFF (decrements) signals. In the Drosophila visual system, separate ON and OFF pathways compute the direction of motion, yet anatomical and functional studies have identified some crosstalk between these channels. We used this well-studied circuit to ask whether the motion computation depends on ON-OFF pathway crosstalk. Using whole-cell electrophysiology, we recorded visual responses of T4 (ON) and T5 (OFF) cells, mapped their composite ON-OFF receptive fields, and found that they share a similar spatiotemporal structure. We fit a biophysical model to these receptive fields that accurately predicts directionally selective T4 and T5 responses to both ON and OFF moving stimuli. This model also provides a detailed mechanistic explanation for the directional preference inversion in response to the prominent reverse-phi illusion. Finally, we used the steering responses of tethered flying flies to validate the model's predicted effects of varying stimulus parameters on the behavioral turning inversion.
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Affiliation(s)
- Eyal Gruntman
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, USA.
| | - Pablo Reimers
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, USA
| | - Sandro Romani
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, USA
| | - Michael B Reiser
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA, USA.
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17
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Neural specification, targeting, and circuit formation during visual system assembly. Proc Natl Acad Sci U S A 2021; 118:2101823118. [PMID: 34183440 DOI: 10.1073/pnas.2101823118] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Like other sensory systems, the visual system is topographically organized: Its sensory neurons, the photoreceptors, and their targets maintain point-to-point correspondence in physical space, forming a retinotopic map. The iterative wiring of circuits in the visual system conveniently facilitates the study of its development. Over the past few decades, experiments in Drosophila have shed light on the principles that guide the specification and connectivity of visual system neurons. In this review, we describe the main findings unearthed by the study of the Drosophila visual system and compare them with similar events in mammals. We focus on how temporal and spatial patterning generates diverse cell types, how guidance molecules distribute the axons and dendrites of neurons within the correct target regions, how vertebrates and invertebrates generate their retinotopic map, and the molecules and mechanisms required for neuronal migration. We suggest that basic principles used to wire the fly visual system are broadly applicable to other systems and highlight its importance as a model to study nervous system development.
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18
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Han X, Wang M, Liu C, Trush O, Takayama R, Akiyama T, Naito T, Tomomizu T, Imamura K, Sato M. DWnt4 and DWnt10 Regulate Morphogenesis and Arrangement of Columnar Units via Fz2/PCP Signaling in the Drosophila Brain. Cell Rep 2020; 33:108305. [PMID: 33113378 DOI: 10.1016/j.celrep.2020.108305] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 09/13/2020] [Accepted: 10/02/2020] [Indexed: 01/09/2023] Open
Abstract
Columns are structural and functional units of the brain. However, the mechanism of column formation remains unclear. The medulla of the fly visual center shares features with the mammalian cerebral cortex, such as columnar and layered structures, and provides a good opportunity to study the mechanisms of column formation. Column formation is initiated by three core neurons in the medulla, namely, Mi1, R8, and R7. The proper orientation of neurons is required for the orientation and arrangement of multiple columns. Their orientations may be under the control of planar cell polarity (PCP) signaling, because it is known to regulate the orientation of cells in two-dimensional tissue structures. In this study, we demonstrate that the ligands DWnt4 and DWnt10 expressed specifically in the ventral medulla and dorsal medulla, respectively, globally regulate the columnar arrangement and orientation of Mi1 and R8 terminals through Fz2/PCP signaling in a three-dimensional space.
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Affiliation(s)
- Xujun Han
- Mathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan; Nano Life Science Institute, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Miaoxing Wang
- Mathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Chuyan Liu
- Laboratory of Developmental Neurobiology, Graduate School of Medical Sciences, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Olena Trush
- Laboratory of Developmental Neurobiology, Graduate School of Medical Sciences, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Rie Takayama
- Mathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Takaaki Akiyama
- Division of Electrical Engineering and Computer Science, Graduate School of Natural Science and Technology, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Toshiki Naito
- Graduate School of Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Takeshi Tomomizu
- Graduate School of Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Kousuke Imamura
- Faculty of Electrical, Information and Communication Engineering, Institute of Science and Engineering, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan
| | - Makoto Sato
- Mathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan; Graduate School of Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa, Ishikawa 920-8640, Japan.
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19
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20
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Hörmann N, Schilling T, Ali AH, Serbe E, Mayer C, Borst A, Pujol-Martí J. A combinatorial code of transcription factors specifies subtypes of visual motion-sensing neurons in Drosophila. Development 2020; 147:223179. [PMID: 32238425 PMCID: PMC7240302 DOI: 10.1242/dev.186296] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 03/20/2020] [Indexed: 12/21/2022]
Abstract
Direction-selective T4/T5 neurons exist in four subtypes, each tuned to visual motion along one of the four cardinal directions. Along with their directional tuning, neurons of each T4/T5 subtype orient their dendrites and project their axons in a subtype-specific manner. Directional tuning, thus, appears strictly linked to morphology in T4/T5 neurons. How the four T4/T5 subtypes acquire their distinct morphologies during development remains largely unknown. Here, we investigated when and how the dendrites of the four T4/T5 subtypes acquire their specific orientations, and profiled the transcriptomes of all T4/T5 neurons during this process. This revealed a simple and stable combinatorial code of transcription factors defining the four T4/T5 subtypes during their development. Changing the combination of transcription factors of specific T4/T5 subtypes resulted in predictable and complete conversions of subtype-specific properties, i.e. dendrite orientation and matching axon projection pattern. Therefore, a combinatorial code of transcription factors coordinates the development of dendrite and axon morphologies to generate anatomical specializations that differentiate subtypes of T4/T5 motion-sensing neurons. Summary: Morphological and transcriptomic analyses allowed the identification of a combinatorial code of transcription factors that controls the development of subtype-specific morphologies in motion-detecting neurons of the Drosophila visual system.
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Affiliation(s)
- Nikolai Hörmann
- Department of Circuits - Computation - Models, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Tabea Schilling
- Department of Circuits - Computation - Models, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Aicha Haji Ali
- Department of Circuits - Computation - Models, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Etienne Serbe
- Department of Circuits - Computation - Models, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Christian Mayer
- Laboratory of Neurogenomics, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Alexander Borst
- Department of Circuits - Computation - Models, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Jesús Pujol-Martí
- Department of Circuits - Computation - Models, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
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21
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Cortese A, Zhu Y, Rebelo AP, Negri S, Courel S, Abreu L, Bacon CJ, Bai Y, Bis-Brewer DM, Bugiardini E, Buglo E, Danzi MC, Feely SME, Athanasiou-Fragkouli A, Haridy NA, Isasi R, Khan A, Laurà M, Magri S, Pipis M, Pisciotta C, Powell E, Rossor AM, Saveri P, Sowden JE, Tozza S, Vandrovcova J, Dallman J, Grignani E, Marchioni E, Scherer SS, Tang B, Lin Z, Al-Ajmi A, Schüle R, Synofzik M, Maisonobe T, Stojkovic T, Auer-Grumbach M, Abdelhamed MA, Hamed SA, Zhang R, Manganelli F, Santoro L, Taroni F, Pareyson D, Houlden H, Herrmann DN, Reilly MM, Shy ME, Zhai RG, Zuchner S. Biallelic mutations in SORD cause a common and potentially treatable hereditary neuropathy with implications for diabetes. Nat Genet 2020; 52:473-481. [PMID: 32367058 DOI: 10.1038/s41588-020-0615-4] [Citation(s) in RCA: 95] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 03/20/2020] [Indexed: 01/08/2023]
Abstract
Here we report biallelic mutations in the sorbitol dehydrogenase gene (SORD) as the most frequent recessive form of hereditary neuropathy. We identified 45 individuals from 38 families across multiple ancestries carrying the nonsense c.757delG (p.Ala253GlnfsTer27) variant in SORD, in either a homozygous or compound heterozygous state. SORD is an enzyme that converts sorbitol into fructose in the two-step polyol pathway previously implicated in diabetic neuropathy. In patient-derived fibroblasts, we found a complete loss of SORD protein and increased intracellular sorbitol. Furthermore, the serum fasting sorbitol levels in patients were dramatically increased. In Drosophila, loss of SORD orthologs caused synaptic degeneration and progressive motor impairment. Reducing the polyol influx by treatment with aldose reductase inhibitors normalized intracellular sorbitol levels in patient-derived fibroblasts and in Drosophila, and also dramatically ameliorated motor and eye phenotypes. Together, these findings establish a novel and potentially treatable cause of neuropathy and may contribute to a better understanding of the pathophysiology of diabetes.
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Affiliation(s)
- Andrea Cortese
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA. .,Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK. .,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
| | - Yi Zhu
- Department of Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL, USA.,Program in Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Adriana P Rebelo
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sara Negri
- Istituiti Clinici Scientifici Maugeri IRCCS, Environmental Research Center, Pavia, Italy
| | - Steve Courel
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Lisa Abreu
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Chelsea J Bacon
- Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Yunhong Bai
- Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Dana M Bis-Brewer
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Enrico Bugiardini
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Elena Buglo
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Matt C Danzi
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Shawna M E Feely
- Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Alkyoni Athanasiou-Fragkouli
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Nourelhoda A Haridy
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK.,Department of Neurology and Psychiatry, Faculty of Medicine, Assiut University Hospital, Assiut, Egypt
| | | | - Rosario Isasi
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alaa Khan
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK.,Molecular Diagnostic Unit, Clinical Laboratory Department, King Abdullah Medical City in Makkah, Mecca, Saudi Arabia
| | - Matilde Laurà
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Stefania Magri
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Menelaos Pipis
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Chiara Pisciotta
- Unit of Rare Neurodegenerative and Neurometabolic Diseases, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Eric Powell
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alexander M Rossor
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Paola Saveri
- Unit of Rare Neurodegenerative and Neurometabolic Diseases, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Janet E Sowden
- Department of Neurology, University of Rochester, Rochester, NY, USA
| | - Stefano Tozza
- Department of Neuroscience, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Jana Vandrovcova
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Julia Dallman
- Department of Biology, University of Miami, Coral Gables, FL, USA
| | - Elena Grignani
- Istituiti Clinici Scientifici Maugeri IRCCS, Environmental Research Center, Pavia, Italy
| | | | - Steven S Scherer
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhiqiang Lin
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Abdullah Al-Ajmi
- Division of Neurology, Department of Medicine, Al-Jahra Hospital, Al-Jahra, Kuwait
| | - Rebecca Schüle
- Department of Neurodegenerative Disease, Hertie-Institute for Clinical Brain Research, and Center for Neurology, University of Tübingen, Tübingen, Germany.,German Center of Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Disease, Hertie-Institute for Clinical Brain Research, and Center for Neurology, University of Tübingen, Tübingen, Germany.,German Center of Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Thierry Maisonobe
- Department of Neurophysiology, AP-HP, Sorbonne Université, Hôpital Pitié Salpêtrière, Paris, France
| | - Tanya Stojkovic
- Centre de Référence des Maladies Neuromusculaires Nord/Est/Ile de France, AP-HP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Michaela Auer-Grumbach
- Department of Orthopaedics and Traumatology, Medical University of Vienna, Vienna, Austria
| | - Mohamed A Abdelhamed
- Department of Neurology and Psychiatry, Faculty of Medicine, Assiut University Hospital, Assiut, Egypt
| | - Sherifa A Hamed
- Department of Neurology and Psychiatry, Faculty of Medicine, Assiut University Hospital, Assiut, Egypt
| | - Ruxu Zhang
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Fiore Manganelli
- Department of Neuroscience, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Lucio Santoro
- Department of Neuroscience, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Franco Taroni
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Davide Pareyson
- Unit of Rare Neurodegenerative and Neurometabolic Diseases, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Henry Houlden
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - David N Herrmann
- Department of Neurology, University of Rochester, Rochester, NY, USA
| | - Mary M Reilly
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology and The National Hospital for Neurology, London, UK
| | - Michael E Shy
- Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - R Grace Zhai
- Department of Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL, USA. .,Program in Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL, USA.
| | - Stephan Zuchner
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA.
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22
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de Andres-Bragado L, Sprecher SG. Mechanisms of vision in the fruit fly. CURRENT OPINION IN INSECT SCIENCE 2019; 36:25-32. [PMID: 31325739 DOI: 10.1016/j.cois.2019.06.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 06/17/2019] [Accepted: 06/21/2019] [Indexed: 06/10/2023]
Abstract
Vision is essential to maximize the efficiency of daily tasks such as feeding, avoiding predators or finding mating partners. An advantageous model is Drosophila melanogaster, since it offers tools that allow genetic and neuronal manipulation with high spatial and temporal resolution, which can be combined with behavioral, anatomical and physiological assays. Recent advances have expanded our knowledge on the neural circuitry underlying such important behaviors as color vision (role of reciprocal inhibition to enhance color signal at the level of the ommatidia); motion vision (motion-detection neurones receive both excitatory and inhibitory input), and sensory processing (role of the central complex in spatial navigation, and in orchestrating the information from other senses and the inner state). Research on synergies between pathways is shaping the field.
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Affiliation(s)
| | - Simon G Sprecher
- Department of Biology, University of Fribourg, Fribourg, Switzerland.
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23
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How fly neurons compute the direction of visual motion. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2019; 206:109-124. [PMID: 31691093 PMCID: PMC7069908 DOI: 10.1007/s00359-019-01375-9] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 10/16/2019] [Accepted: 10/23/2019] [Indexed: 10/25/2022]
Abstract
Detecting the direction of image motion is a fundamental component of visual computation, essential for survival of the animal. However, at the level of individual photoreceptors, the direction in which the image is shifting is not explicitly represented. Rather, directional motion information needs to be extracted from the photoreceptor array by comparing the signals of neighboring units over time. The exact nature of this process as implemented in the visual system of the fruit fly Drosophila melanogaster has been studied in great detail, and much progress has recently been made in determining the neural circuits giving rise to directional motion information. The results reveal the following: (1) motion information is computed in parallel ON and OFF pathways. (2) Within each pathway, T4 (ON) and T5 (OFF) cells are the first neurons to represent the direction of motion. Four subtypes of T4 and T5 cells exist, each sensitive to one of the four cardinal directions. (3) The core process of direction selectivity as implemented on the dendrites of T4 and T5 cells comprises both an enhancement of signals for motion along their preferred direction as well as a suppression of signals for motion along the opposite direction. This combined strategy ensures a high degree of direction selectivity right at the first stage where the direction of motion is computed. (4) At the subsequent processing stage, tangential cells spatially integrate direct excitation from ON and OFF-selective T4 and T5 cells and indirect inhibition from bi-stratified LPi cells activated by neighboring T4/T5 terminals, thus generating flow-field-selective responses.
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24
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Fabian JM, Dunbier JR, O'Carroll DC, Wiederman SD. Properties of predictive gain modulation in a dragonfly visual neuron. ACTA ACUST UNITED AC 2019; 222:jeb.207316. [PMID: 31395677 DOI: 10.1242/jeb.207316] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 08/02/2019] [Indexed: 11/20/2022]
Abstract
Dragonflies pursue and capture tiny prey and conspecifics with extremely high success rates. These moving targets represent a small visual signal on the retina and successful chases require accurate detection and amplification by downstream neuronal circuits. This amplification has been observed in a population of neurons called small target motion detectors (STMDs), through a mechanism we term predictive gain modulation. As targets drift through the neuron's receptive field, spike frequency builds slowly over time. This increased likelihood of spiking or gain is modulated across the receptive field, enhancing sensitivity just ahead of the target's path, with suppression of activity in the remaining surround. Whilst some properties of this mechanism have been described, it is not yet known which stimulus parameters modulate the amount of response gain. Previous work suggested that the strength of gain enhancement was predominantly determined by the duration of the target's prior path. Here, we show that predictive gain modulation is more than a slow build-up of responses over time. Rather, the strength of gain is dependent on the velocity of a prior stimulus combined with the current stimulus attributes (e.g. angular size). We also describe response variability as a major challenge of target-detecting neurons and propose that the role of predictive gain modulation is to drive neurons towards response saturation, thus minimising neuronal variability despite noisy visual input signals.
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Affiliation(s)
- Joseph M Fabian
- Adelaide Medical School, The University of Adelaide, Adelaide, SA 5000, Australia .,Department of Bioengineering, Imperial College London, London SW7 2AZ, UK
| | - James R Dunbier
- Adelaide Medical School, The University of Adelaide, Adelaide, SA 5000, Australia
| | | | - Steven D Wiederman
- Adelaide Medical School, The University of Adelaide, Adelaide, SA 5000, Australia
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Richter FG, Fendl S, Haag J, Drews MS, Borst A. Glutamate Signaling in the Fly Visual System. iScience 2018; 7:85-95. [PMID: 30267688 PMCID: PMC6135900 DOI: 10.1016/j.isci.2018.08.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 08/13/2018] [Accepted: 08/23/2018] [Indexed: 10/28/2022] Open
Abstract
For a proper understanding of neural circuit function, it is important to know which signals neurons relay to their downstream partners. Calcium imaging with genetically encoded calcium sensors like GCaMP has become the default approach for mapping these responses. How well such measurements represent the true neurotransmitter output of any given cell, however, remains unclear. Here, we demonstrate the viability of the glutamate sensor iGluSnFR for 2-photon in vivo imaging in Drosophila melanogaster and prove its usefulness for estimating spatiotemporal receptive fields in the visual system. We compare the results obtained with iGluSnFR with the ones obtained with GCaMP6f and find that the spatial aspects of the receptive fields are preserved between indicators. In the temporal domain, however, measurements obtained with iGluSnFR reveal the underlying response properties to be much faster than those acquired with GCaMP6f. Our approach thus offers a more accurate description of glutamatergic neurons in the fruit fly.
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Affiliation(s)
| | - Sandra Fendl
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Jürgen Haag
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Michael S Drews
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Alexander Borst
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany.
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26
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Development of Concurrent Retinotopic Maps in the Fly Motion Detection Circuit. Cell 2018; 173:485-498.e11. [PMID: 29576455 DOI: 10.1016/j.cell.2018.02.053] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 12/24/2017] [Accepted: 02/21/2018] [Indexed: 11/22/2022]
Abstract
Understanding how complex brain wiring is produced during development is a daunting challenge. In Drosophila, information from 800 retinal ommatidia is processed in distinct brain neuropiles, each subdivided into 800 matching retinotopic columns. The lobula plate comprises four T4 and four T5 neuronal subtypes. T4 neurons respond to bright edge motion, whereas T5 neurons respond to dark edge motion. Each is tuned to motion in one of the four cardinal directions, effectively establishing eight concurrent retinotopic maps to support wide-field motion. We discovered a mode of neurogenesis where two sequential Notch-dependent divisions of either a horizontal or a vertical progenitor produce matching sets of two T4 and two T5 neurons retinotopically coincident with pairwise opposite direction selectivity. We show that retinotopy is an emergent characteristic of this neurogenic program and derives directly from neuronal birth order. Our work illustrates how simple developmental rules can implement complex neural organization.
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27
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Haag J, Mishra A, Borst A. A common directional tuning mechanism of Drosophila motion-sensing neurons in the ON and in the OFF pathway. eLife 2017; 6:29044. [PMID: 28829040 PMCID: PMC5582866 DOI: 10.7554/elife.29044] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 08/21/2017] [Indexed: 01/19/2023] Open
Abstract
In the fruit fly optic lobe, T4 and T5 cells represent the first direction-selective neurons, with T4 cells responding selectively to moving brightness increments (ON) and T5 cells to brightness decrements (OFF). Both T4 and T5 cells comprise four subtypes with directional tuning to one of the four cardinal directions. We had previously found that upward-sensitive T4 cells implement both preferred direction enhancement and null direction suppression (Haag et al., 2016). Here, we asked whether this mechanism generalizes to OFF-selective T5 cells and to all four subtypes of both cell classes. We found that all four subtypes of both T4 and T5 cells implement both mechanisms, that is preferred direction enhancement and null direction inhibition, on opposing sides of their receptive fields. This gives rise to the high degree of direction selectivity observed in both T4 and T5 cells within each subpopulation.
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Affiliation(s)
- Juergen Haag
- Max-Planck-Institute of Neurobiology, Martinsried, Germany
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28
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Ngo KT, Andrade I, Hartenstein V. Spatio-temporal pattern of neuronal differentiation in the Drosophila visual system: A user's guide to the dynamic morphology of the developing optic lobe. Dev Biol 2017; 428:1-24. [PMID: 28533086 PMCID: PMC5825191 DOI: 10.1016/j.ydbio.2017.05.008] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2017] [Revised: 05/08/2017] [Accepted: 05/09/2017] [Indexed: 11/20/2022]
Abstract
Visual information processing in animals with large image forming eyes is carried out in highly structured retinotopically ordered neuropils. Visual neuropils in Drosophila form the optic lobe, which consists of four serially arranged major subdivisions; the lamina, medulla, lobula and lobula plate; the latter three of these are further subdivided into multiple layers. The visual neuropils are formed by more than 100 different cell types, distributed and interconnected in an invariant highly regular pattern. This pattern relies on a protracted sequence of developmental steps, whereby different cell types are born at specific time points and nerve connections are formed in a tightly controlled sequence that has to be coordinated among the different visual neuropils. The developing fly visual system has become a highly regarded and widely studied paradigm to investigate the genetic mechanisms that control the formation of neural circuits. However, these studies are often made difficult by the complex and shifting patterns in which different types of neurons and their connections are distributed throughout development. In the present paper we have reconstructed the three-dimensional architecture of the Drosophila optic lobe from the early larva to the adult. Based on specific markers, we were able to distinguish the populations of progenitors of the four optic neuropils and map the neurons and their connections. Our paper presents sets of annotated confocal z-projections and animated 3D digital models of these structures for representative stages. The data reveal the temporally coordinated growth of the optic neuropils, and clarify how the position and orientation of the neuropils and interconnecting tracts (inner and outer optic chiasm) changes over time. Finally, we have analyzed the emergence of the discrete layers of the medulla and lobula complex using the same markers (DN-cadherin, Brp) employed to systematically explore the structure and development of the central brain neuropil. Our work will facilitate experimental studies of the molecular mechanisms regulating neuronal fate and connectivity in the fly visual system, which bears many fundamental similarities with the retina of vertebrates.
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Affiliation(s)
- Kathy T Ngo
- Department of Molecular, Cell, and Developmental Biology, United States
| | - Ingrid Andrade
- Department of Molecular, Cell, and Developmental Biology, United States
| | - Volker Hartenstein
- Department of Molecular, Cell, and Developmental Biology, United States; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, United States.
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29
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Characterization of the first-order visual interneurons in the visual system of the bumblebee (Bombus terrestris). J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2017; 203:903-913. [DOI: 10.1007/s00359-017-1201-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 07/11/2017] [Accepted: 07/12/2017] [Indexed: 11/26/2022]
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30
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Abstract
Images projected onto the retina of an animal eye are rarely still. Instead, they usually contain motion signals originating either from moving objects or from retinal slip caused by self-motion. Accordingly, motion signals tell the animal in which direction a predator, prey, or the animal itself is moving. At the neural level, visual motion detection has been proposed to extract directional information by a delay-and-compare mechanism, representing a classic example of neural computation. Neurons responding selectively to motion in one but not in the other direction have been identified in many systems, most prominently in the mammalian retina and the fly optic lobe. Technological advances have now allowed researchers to characterize these neurons' upstream circuits in exquisite detail. Focusing on these upstream circuits, we review and compare recent progress in understanding the mechanisms that generate direction selectivity in the early visual system of mammals and flies.
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Affiliation(s)
- Alex S Mauss
- Max Planck Institute of Neurobiology, 82152 Martinsried, Germany; ,
| | - Anna Vlasits
- Department of Molecular and Cell Biology & Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720; ,
| | - Alexander Borst
- Max Planck Institute of Neurobiology, 82152 Martinsried, Germany; ,
| | - Marla Feller
- Department of Molecular and Cell Biology & Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720; ,
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31
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The Temporal Tuning of the Drosophila Motion Detectors Is Determined by the Dynamics of Their Input Elements. Curr Biol 2017; 27:929-944. [PMID: 28343964 DOI: 10.1016/j.cub.2017.01.051] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Revised: 12/19/2016] [Accepted: 01/25/2017] [Indexed: 11/22/2022]
Abstract
Detecting the direction of motion contained in the visual scene is crucial for many behaviors. However, because single photoreceptors only signal local luminance changes, motion detection requires a comparison of signals from neighboring photoreceptors across time in downstream neuronal circuits. For signals to coincide on readout neurons that thus become motion and direction selective, different input lines need to be delayed with respect to each other. Classical models of motion detection rely on non-linear interactions between two inputs after different temporal filtering. However, recent studies have suggested the requirement for at least three, not only two, input signals. Here, we comprehensively characterize the spatiotemporal response properties of all columnar input elements to the elementary motion detectors in the fruit fly, T4 and T5 cells, via two-photon calcium imaging. Between these input neurons, we find large differences in temporal dynamics. Based on this, computer simulations show that only a small subset of possible arrangements of these input elements maps onto a recently proposed algorithmic three-input model in a way that generates a highly direction-selective motion detector, suggesting plausible network architectures. Moreover, modulating the motion detection system by octopamine-receptor activation, we find the temporal tuning of T4 and T5 cells to be shifted toward higher frequencies, and this shift can be fully explained by the concomitant speeding of the input elements.
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32
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Integration of temporal and spatial patterning generates neural diversity. Nature 2017; 541:365-370. [PMID: 28077877 DOI: 10.1038/nature20794] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2015] [Accepted: 11/16/2016] [Indexed: 12/27/2022]
Abstract
In the Drosophila optic lobes, 800 retinotopically organized columns in the medulla act as functional units for processing visual information. The medulla contains over 80 types of neuron, which belong to two classes: uni-columnar neurons have a stoichiometry of one per column, while multi-columnar neurons contact multiple columns. Here we show that combinatorial inputs from temporal and spatial axes generate this neuronal diversity: all neuroblasts switch fates over time to produce different neurons; the neuroepithelium that generates neuroblasts is also subdivided into six compartments by the expression of specific factors. Uni-columnar neurons are produced in all spatial compartments independently of spatial input; they innervate the neuropil where they are generated. Multi-columnar neurons are generated in smaller numbers in restricted compartments and require spatial input; the majority of their cell bodies subsequently move to cover the entire medulla. The selective integration of spatial inputs by a fixed temporal neuroblast cascade thus acts as a powerful mechanism for generating neural diversity, regulating stoichiometry and the formation of retinotopy.
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33
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Abstract
The most striking structure in the nervous system is the complex yet stereotyped morphology of the neuronal dendritic tree. Dendritic morphologies and the connections they make govern information flow and integration in the brain. The fundamental mechanisms that regulate dendritic outgrowth and branching are subjects of extensive study. In this review, we summarize recent advances in the molecular and cellular mechanisms for routing dendrites in layers and columns, prevalent organizational structures in the brain. We highlight how dendritic patterning influences the formation of synaptic circuits.
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Affiliation(s)
- Jiangnan Luo
- a Section on Neuronal Connectivity, Cell Biology and Neurobiology Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development , Bethesda , MD , USA
| | - Philip G McQueen
- b Mathematical and Statistical Computing Laboratory, Office of Intramural Research, Center for Information Technology , National Institutes of Health , Bethesda , MD , USA
| | - Bo Shi
- a Section on Neuronal Connectivity, Cell Biology and Neurobiology Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development , Bethesda , MD , USA ;,c Biological Sciences Graduate Program, College of Computer, Mathematical, and Natural Sciences , University of Maryland , College Park , MD , USA
| | - Chi-Hon Lee
- a Section on Neuronal Connectivity, Cell Biology and Neurobiology Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development , Bethesda , MD , USA
| | - Chun-Yuan Ting
- a Section on Neuronal Connectivity, Cell Biology and Neurobiology Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development , Bethesda , MD , USA
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34
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Abstract
How stem cells produce the huge diversity of neurons that form the visual system, and how these cells are assembled in neural circuits are a critical question in developmental neurobiology. Investigations in Drosophila have led to the discovery of several basic principles of neural patterning. In this chapter, we provide an overview of the field by describing the development of the Drosophila visual system, from the embryo to the adult and from the gross anatomy to the cellular level. We then explore the general molecular mechanisms identified that might apply to other neural structures in flies or in vertebrates. Finally, we discuss the major challenges that remain to be addressed in the field.
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Affiliation(s)
- Nathalie Nériec
- Center for Genomics & Systems Biology, New York University, Abu Dhabi, UAE; Department of Biology, New York University, New York, USA
| | - Claude Desplan
- Center for Genomics & Systems Biology, New York University, Abu Dhabi, UAE; Department of Biology, New York University, New York, USA.
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35
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Neural Mechanisms for Drosophila Contrast Vision. Neuron 2015; 88:1240-1252. [DOI: 10.1016/j.neuron.2015.11.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Revised: 09/24/2015] [Accepted: 10/28/2015] [Indexed: 01/01/2023]
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36
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Mauss AS, Pankova K, Arenz A, Nern A, Rubin GM, Borst A. Neural Circuit to Integrate Opposing Motions in the Visual Field. Cell 2015; 162:351-362. [PMID: 26186189 DOI: 10.1016/j.cell.2015.06.035] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Revised: 04/01/2015] [Accepted: 05/18/2015] [Indexed: 10/23/2022]
Abstract
When navigating in their environment, animals use visual motion cues as feedback signals that are elicited by their own motion. Such signals are provided by wide-field neurons sampling motion directions at multiple image points as the animal maneuvers. Each one of these neurons responds selectively to a specific optic flow-field representing the spatial distribution of motion vectors on the retina. Here, we describe the discovery of a group of local, inhibitory interneurons in the fruit fly Drosophila key for filtering these cues. Using anatomy, molecular characterization, activity manipulation, and physiological recordings, we demonstrate that these interneurons convey direction-selective inhibition to wide-field neurons with opposite preferred direction and provide evidence for how their connectivity enables the computation required for integrating opposing motions. Our results indicate that, rather than sharpening directional selectivity per se, these circuit elements reduce noise by eliminating non-specific responses to complex visual information.
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Affiliation(s)
- Alex S Mauss
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany.
| | - Katarina Pankova
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Alexander Arenz
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Alexander Borst
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
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37
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Strutz A, Soelter J, Baschwitz A, Farhan A, Grabe V, Rybak J, Knaden M, Schmuker M, Hansson BS, Sachse S. Decoding odor quality and intensity in the Drosophila brain. eLife 2014; 3:e04147. [PMID: 25512254 PMCID: PMC4270039 DOI: 10.7554/elife.04147] [Citation(s) in RCA: 109] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Accepted: 11/09/2014] [Indexed: 12/12/2022] Open
Abstract
To internally reflect the sensory environment, animals create neural maps encoding the external stimulus space. From that primary neural code relevant information has to be extracted for accurate navigation. We analyzed how different odor features such as hedonic valence and intensity are functionally integrated in the lateral horn (LH) of the vinegar fly, Drosophila melanogaster. We characterized an olfactory-processing pathway, comprised of inhibitory projection neurons (iPNs) that target the LH exclusively, at morphological, functional and behavioral levels. We demonstrate that iPNs are subdivided into two morphological groups encoding positive hedonic valence or intensity information and conveying these features into separate domains in the LH. Silencing iPNs severely diminished flies' attraction behavior. Moreover, functional imaging disclosed a LH region tuned to repulsive odors comprised exclusively of third-order neurons. We provide evidence for a feature-based map in the LH, and elucidate its role as the center for integrating behaviorally relevant olfactory information. DOI:http://dx.doi.org/10.7554/eLife.04147.001 Organisms need to sense and adapt to their environment in order to survive. Senses such as vision and smell allow an organism to absorb information about the external environment and translate it into a meaningful internal image. This internal image helps the organism to remember incidents and act accordingly when they encounter similar situations again. A typical example is when organisms are repeatedly attracted to odors that are essential for survival, such as food and pheromones, and are repulsed by odors that threaten survival. Strutz et al. addressed how attractiveness or repulsiveness of a smell, and also the strength of a smell, are processed by a part of the olfactory system called the lateral horn in fruit flies. This involved mapping the neuronal patterns that were generated in the lateral horn when a fly was exposed to particular odors. Strutz et al. found that a subset of neurons called inhibitory projection neurons processes information about whether the odor is attractive or repulsive, and that a second subset of these neurons process information about the intensity of the odor. Other insects, such as honey bees and hawk moths, have olfactory systems with a similar architecture and might also employ a similar spatial approach to encode information regarding the intensity and identity of odors. Locusts, on the other hand, employ a temporal approach to encoding information about odors. The work of Strutz et al. shows that certain qualities of odors are contained in a spatial map in a specific brain region of the fly. This opens up the question of how the information in this spatial map influences decisions made by the fly. DOI:http://dx.doi.org/10.7554/eLife.04147.002
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Affiliation(s)
- Antonia Strutz
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Jan Soelter
- Department for Biology, Pharmacy and Chemistry, Free University Berlin, Neuroinformatics and Theoretical Neuroscience, Berlin, Germany
| | - Amelie Baschwitz
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Abu Farhan
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Veit Grabe
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Jürgen Rybak
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Markus Knaden
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Michael Schmuker
- Department for Biology, Pharmacy and Chemistry, Free University Berlin, Neuroinformatics and Theoretical Neuroscience, Berlin, Germany
| | - Bill S Hansson
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Silke Sachse
- Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
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38
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Wernet MF, Huberman AD, Desplan C. So many pieces, one puzzle: cell type specification and visual circuitry in flies and mice. Genes Dev 2014; 28:2565-84. [PMID: 25452270 PMCID: PMC4248288 DOI: 10.1101/gad.248245.114] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
The visual system is a powerful model for probing the development, connectivity, and function of neural circuits. Two genetically tractable species, mice and flies, are together providing a great deal of understanding of these processes. Current efforts focus on integrating knowledge gained from three cross-fostering fields of research: (1) understanding how the fates of different cell types are specified during development, (2) revealing the synaptic connections between identified cell types ("connectomics") by high-resolution three-dimensional circuit anatomy, and (3) causal testing of how identified circuit elements contribute to visual perception and behavior. Here we discuss representative examples from fly and mouse models to illustrate the ongoing success of this tripartite strategy, focusing on the ways it is enhancing our understanding of visual processing and other sensory systems.
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Affiliation(s)
- Mathias F Wernet
- Department of Neurobiology, Stanford University, Stanford, California 94305, USA; New York University Abu Dhabi, Saadiyat Island, Abu Dhabi 129188, United Arab Emirates; Department of Biology, New York University, New York, New York 10003, USA
| | - Andrew D Huberman
- Department of Neurosciences, Neurobiology Section, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093, USA
| | - Claude Desplan
- New York University Abu Dhabi, Saadiyat Island, Abu Dhabi 129188, United Arab Emirates; Department of Biology, New York University, New York, New York 10003, USA
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39
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Borst A. In search of the Holy Grail of fly motion vision. Eur J Neurosci 2014; 40:3285-93. [PMID: 25251169 DOI: 10.1111/ejn.12731] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2014] [Revised: 08/19/2014] [Accepted: 08/20/2014] [Indexed: 01/27/2023]
Abstract
Detecting the direction of image motion is important for visual navigation as well as predator, prey and mate detection and, thus, essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits, involving a comparison of the signals from neighbouring photoreceptors over time. The exact nature of this process as implemented at the neuronal level has been a long-standing question in the field. Only recently, much progress has been made in Drosophila by genetically targeting individual neuron types to block, activate or record from them. The results obtained this way indicate that: (i) luminance information from fly photoreceptors R1-6 is split into two parallel motion circuits, specialized to detect the motion of luminance increments (ON-Channel) and decrements (OFF-Channel) separately; (ii) lamina neurons L1 and L2 are the primary input neurons to these circuits (L1 → ON-channel, L2 → OFF-channel); and (iii) T4 and T5 cells carry their output signals (ON → T4, OFF → T5).
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Affiliation(s)
- Alexander Borst
- Department of Circuits, Computation, Models, Max-Planck-Institute of Neurobiology, Am Klopferspitz 18, 82152, Martinsried, Germany
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40
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Abstract
Understanding how the brain controls behaviour is undisputedly one of the grand goals of neuroscience research, and the pursuit of this goal has a long tradition in insect neuroscience. However, appropriate techniques were lacking for a long time. Recent advances in genetic and recording techniques now allow the participation of identified neurons in the execution of specific behaviours to be interrogated. By focusing on fly visual course control, I highlight what has been learned about the neuronal circuit modules that control visual guidance in Drosophila melanogaster through the use of these techniques.
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Affiliation(s)
- Alexander Borst
- Max Planck Institute of Neurobiology Systems and Computational Neuroscience, Am Klopferspitz 18, 82152 Martinsried, Germany
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41
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Processing properties of ON and OFF pathways for Drosophila motion detection. Nature 2014; 512:427-30. [PMID: 25043016 DOI: 10.1038/nature13427] [Citation(s) in RCA: 153] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2013] [Accepted: 05/01/2014] [Indexed: 12/18/2022]
Abstract
The algorithms and neural circuits that process spatio-temporal changes in luminance to extract visual motion cues have been the focus of intense research. An influential model, the Hassenstein-Reichardt correlator, relies on differential temporal filtering of two spatially separated input channels, delaying one input signal with respect to the other. Motion in a particular direction causes these delayed and non-delayed luminance signals to arrive simultaneously at a subsequent processing step in the brain; these signals are then nonlinearly amplified to produce a direction-selective response. Recent work in Drosophila has identified two parallel pathways that selectively respond to either moving light or dark edges. Each of these pathways requires two critical processing steps to be applied to incoming signals: differential delay between the spatial input channels, and distinct processing of brightness increment and decrement signals. Here we demonstrate, using in vivo patch-clamp recordings, that four medulla neurons implement these two processing steps. The neurons Mi1 and Tm3 respond selectively to brightness increments, with the response of Mi1 delayed relative to Tm3. Conversely, Tm1 and Tm2 respond selectively to brightness decrements, with the response of Tm1 delayed compared with Tm2. Remarkably, constraining Hassenstein-Reichardt correlator models using these measurements produces outputs consistent with previously measured properties of motion detectors, including temporal frequency tuning and specificity for light versus dark edges. We propose that Mi1 and Tm3 perform critical processing of the delayed and non-delayed input channels of the correlator responsible for the detection of light edges, while Tm1 and Tm2 play analogous roles in the detection of moving dark edges. Our data show that specific medulla neurons possess response properties that allow them to implement the algorithmic steps that precede the correlative operation in the Hassenstein-Reichardt correlator, revealing elements of the long-sought neural substrates of motion detection in the fly.
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42
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Chin AL, Lin CY, Fu TF, Dickson BJ, Chiang AS. Diversity and wiring variability of visual local neurons in the Drosophila medulla M6 stratum. J Comp Neurol 2014; 522:3795-816. [PMID: 24782245 PMCID: PMC4265792 DOI: 10.1002/cne.23622] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2012] [Revised: 04/21/2014] [Accepted: 04/22/2014] [Indexed: 11/09/2022]
Abstract
Local neurons in the vertebrate retina are instrumental in transforming visual inputs to extract contrast, motion, and color information and in shaping bipolar-to-ganglion cell transmission to the brain. In Drosophila, UV vision is represented by R7 inner photoreceptor neurons that project to the medulla M6 stratum, with relatively little known of this downstream substrate. Here, using R7 terminals as references, we generated a 3D volume model of the M6 stratum, which revealed a retinotopic map for UV representations. Using this volume model as a common 3D framework, we compiled and analyzed the spatial distributions of more than 200 single M6-specific local neurons (M6-LNs). Based on the segregation of putative dendrites and axons, these local neurons were classified into two families, directional and nondirectional. Neurotransmitter immunostaining suggested a signal routing model in which some visual information is relayed by directional M6-LNs from the anterior to the posterior M6 and all visual information is inhibited by a diverse population of nondirectional M6-LNs covering the entire M6 stratum. Our findings suggest that the Drosophila medulla M6 stratum contains diverse LNs that form repeating functional modules similar to those found in the vertebrate inner plexiform layer.
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Affiliation(s)
- An-Lun Chin
- Institute of Biotechnology and Department of Life Science, National Tsing Hua University, Hsinchu, 30013, Taiwan
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Silies M, Clandinin T. Vision: EM-erging Motion-Detecting Circuits. Curr Biol 2014; 24:R390-2. [DOI: 10.1016/j.cub.2014.03.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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44
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Direct Observation of ON and OFF Pathways in the Drosophila Visual System. Curr Biol 2014; 24:976-83. [DOI: 10.1016/j.cub.2014.03.017] [Citation(s) in RCA: 95] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Revised: 02/28/2014] [Accepted: 03/06/2014] [Indexed: 01/14/2023]
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Sztarker J, Tomsic D. Neural organization of the second optic neuropil, the medulla, in the highly visual semiterrestrial crabNeohelice granulata. J Comp Neurol 2014; 522:3177-93. [DOI: 10.1002/cne.23589] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2013] [Revised: 02/28/2014] [Accepted: 03/18/2014] [Indexed: 01/16/2023]
Affiliation(s)
- Julieta Sztarker
- Laboratorio de Neurobiología de la Memoria; Dpto. Fisiología; Biología Molecular y Celular; Facultad de Ciencias Exactas y Naturales; Universidad de Buenos Aires (IFIBYNE- CONICET); Buenos Aires 1428 Argentina
| | - Daniel Tomsic
- Laboratorio de Neurobiología de la Memoria; Dpto. Fisiología; Biología Molecular y Celular; Facultad de Ciencias Exactas y Naturales; Universidad de Buenos Aires (IFIBYNE- CONICET); Buenos Aires 1428 Argentina
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Abstract
Detecting the direction of image motion is a fundamental component of visual computation and is essential for survival of the animal. However, at the level of the photoreceptors, the direction in which the image is shifting locally is not explicitly represented. Rather, directional motion information needs to be extracted from the photoreceptor array by comparing the signals of neighboring photoreceptors over time. The exact nature of this process as implemented in the Drosophila visual system is currently being studied in great detail, and much progress has recently been made in determining the neural circuits giving rise to directional motion information in this species.
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Affiliation(s)
- Alexander Borst
- Max Planck Institute of Neurobiology, Systems and Computational Neuroscience , Martinsried , Germany
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Otsuna H, Shinomiya K, Ito K. Parallel neural pathways in higher visual centers of the Drosophila brain that mediate wavelength-specific behavior. Front Neural Circuits 2014; 8:8. [PMID: 24574974 PMCID: PMC3918591 DOI: 10.3389/fncir.2014.00008] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2013] [Accepted: 01/21/2014] [Indexed: 12/20/2022] Open
Abstract
Compared with connections between the retinae and primary visual centers, relatively less is known in both mammals and insects about the functional segregation of neural pathways connecting primary and higher centers of the visual processing cascade. Here, using the Drosophila visual system as a model, we demonstrate two levels of parallel computation in the pathways that connect primary visual centers of the optic lobe to computational circuits embedded within deeper centers in the central brain. We show that a seemingly simple achromatic behavior, namely phototaxis, is under the control of several independent pathways, each of which is responsible for navigation towards unique wavelengths. Silencing just one pathway is enough to disturb phototaxis towards one characteristic monochromatic source, whereas phototactic behavior towards white light is not affected. The response spectrum of each demonstrable pathway is different from that of individual photoreceptors, suggesting subtractive computations. A choice assay between two colors showed that these pathways are responsible for navigation towards, but not for the detection itself of, the monochromatic light. The present study provides novel insights about how visual information is separated and processed in parallel to achieve robust control of an innate behavior.
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Affiliation(s)
- Hideo Otsuna
- Institute of Molecular and Cellular Biosciences (IMCB), University of TokyoTokyo, Japan
- Department of Neurobiology and Anatomy, University of UtahSalt Lake City, UT, USA
| | - Kazunori Shinomiya
- Institute of Molecular and Cellular Biosciences (IMCB), University of TokyoTokyo, Japan
- Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie UniversityHalifax, NS, Canada
| | - Kei Ito
- Institute of Molecular and Cellular Biosciences (IMCB), University of TokyoTokyo, Japan
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Meier M, Serbe E, Maisak MS, Haag J, Dickson BJ, Borst A. Neural circuit components of the Drosophila OFF motion vision pathway. Curr Biol 2014; 24:385-92. [PMID: 24508173 DOI: 10.1016/j.cub.2014.01.006] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2013] [Revised: 11/29/2013] [Accepted: 01/03/2014] [Indexed: 01/16/2023]
Abstract
BACKGROUND Detecting the direction of visual motion is an essential task of the early visual system. The Reichardt detector has been proven to be a faithful description of the underlying computation in insects. A series of recent studies addressed the neural implementation of the Reichardt detector in Drosophila revealing the overall layout in parallel ON and OFF channels, its input neurons from the lamina (L1→ON, and L2→OFF), and the respective output neurons to the lobula plate (ON→T4, and OFF→T5). While anatomical studies showed that T4 cells receive input from L1 via Mi1 and Tm3 cells, the neurons connecting L2 to T5 cells have not been identified so far. It is, however, known that L2 contacts, among others, two neurons, called Tm2 and L4, which show a pronounced directionality in their wiring. RESULTS We characterized the visual response properties of both Tm2 and L4 neurons via Ca(2+) imaging. We found that Tm2 and L4 cells respond with an increase in activity to moving OFF edges in a direction-unselective manner. To investigate their participation in motion vision, we blocked their output while recording from downstream tangential cells in the lobula plate. Silencing of Tm2 and L4 completely abolishes the response to moving OFF edges. CONCLUSIONS Our results demonstrate that both cell types are essential components of the Drosophila OFF motion vision pathway, prior to the computation of directionality in the dendrites of T5 cells.
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Affiliation(s)
- Matthias Meier
- Department of Circuits-Computation-Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Etienne Serbe
- Department of Circuits-Computation-Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Matthew S Maisak
- Department of Circuits-Computation-Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Jürgen Haag
- Department of Circuits-Computation-Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Barry J Dickson
- Research Institute of Molecular Pathology, Dr. Bohr-Gasse 7, 1030 Vienna, Austria
| | - Alexander Borst
- Department of Circuits-Computation-Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany.
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Abstract
Visual motion cues provide animals with critical information about their environment and guide a diverse array of behaviors. The neural circuits that carry out motion estimation provide a well-constrained model system for studying the logic of neural computation. Through a confluence of behavioral, physiological, and anatomical experiments, taking advantage of the powerful genetic tools available in the fruit fly Drosophila melanogaster, an outline of the neural pathways that compute visual motion has emerged. Here we describe these pathways, the evidence supporting them, and the challenges that remain in understanding the circuits and computations that link sensory inputs to behavior. Studies in flies and vertebrates have revealed a number of functional similarities between motion-processing pathways in different animals, despite profound differences in circuit anatomy and structure. The fact that different circuit mechanisms are used to achieve convergent computational outcomes sheds light on the evolution of the nervous system.
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Affiliation(s)
- Marion Silies
- Department of Neurobiology, Stanford University, Stanford, California 94305; , ,
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Wong DC, Lovick JK, Ngo KT, Borisuthirattana W, Omoto JJ, Hartenstein V. Postembryonic lineages of the Drosophila brain: II. Identification of lineage projection patterns based on MARCM clones. Dev Biol 2013; 384:258-89. [PMID: 23872236 PMCID: PMC3928077 DOI: 10.1016/j.ydbio.2013.07.009] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2013] [Revised: 07/11/2013] [Accepted: 07/11/2013] [Indexed: 01/13/2023]
Abstract
The Drosophila central brain is largely composed of lineages, units of sibling neurons derived from a single progenitor cell or neuroblast. During the early embryonic period, neuroblasts generate the primary neurons that constitute the larval brain. Neuroblasts reactivate in the larva, adding to their lineages a large number of secondary neurons which, according to previous studies in which selected lineages were labeled by stably expressed markers, differentiate during metamorphosis, sending terminal axonal and dendritic branches into defined volumes of the brain neuropil. We call the overall projection pattern of neurons forming a given lineage the "projection envelope" of that lineage. By inducing MARCM clones at the early larval stage, we labeled the secondary progeny of each neuroblast. For the supraesophageal ganglion excluding mushroom body (the part of the brain investigated in the present work) we obtained 81 different types of clones. Based on the trajectory of their secondary axon tracts (described in the accompanying paper, Lovick et al., 2013), we assigned these clones to specific lineages defined in the larva. Since a labeled clone reveals all aspects (cell bodies, axon tracts, terminal arborization) of a lineage, we were able to describe projection envelopes for all secondary lineages of the supraesophageal ganglion. This work provides a framework by which the secondary neurons (forming the vast majority of adult brain neurons) can be assigned to genetically and developmentally defined groups. It also represents a step towards the goal to establish, for each lineage, the link between its mature anatomical and functional phenotype, and the genetic make-up of the neuroblast it descends from.
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Affiliation(s)
- Darren C. Wong
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jennifer K. Lovick
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kathy T. Ngo
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Wichanee Borisuthirattana
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jaison J. Omoto
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Volker Hartenstein
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
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