151
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Kunst M, Laurell E, Mokayes N, Kramer A, Kubo F, Fernandes AM, Förster D, Dal Maschio M, Baier H. A Cellular-Resolution Atlas of the Larval Zebrafish Brain. Neuron 2019; 103:21-38.e5. [DOI: 10.1016/j.neuron.2019.04.034] [Citation(s) in RCA: 138] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 04/10/2019] [Accepted: 04/23/2019] [Indexed: 02/06/2023]
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152
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Reisenman CE, Scott K. Food-derived volatiles enhance consumption in Drosophila melanogaster. ACTA ACUST UNITED AC 2019; 222:jeb.202762. [PMID: 31085598 DOI: 10.1242/jeb.202762] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 05/02/2019] [Indexed: 11/20/2022]
Abstract
Insects use multiple sensory modalities when searching for and accepting a food source, in particular odor and taste cues. Food-derived odorants are generally involved in mediating long- and short-range attraction. Taste cues, in contrast, act directly by contact with the food source, promoting the ingestion of nutritious food and the avoidance of toxic substances. It is possible, however, that insects integrate information from these sensory modalities during the process of feeding itself. Here, using a simple feeding assay, we investigated whether odors modulate food consumption in the fruit fly Drosophila melanogaster We found that the presence of both single food-derived odorants and complex odor mixtures enhanced consumption of an appetitive food. Feeding enhancement depended on the concentration and the chemical identity of the odorant. Volatile cues alone were sufficient to mediate this effect, as feeding was also increased when animals were prevented from contacting the odor source. Both males and females, including virgin females, increased ingestion in the presence of food-derived volatiles. Moreover, the presence of food-derived odorants significantly increased the consumption of food mixtures containing aversive bitter compounds, suggesting that flies integrate diverse olfactory and gustatory cues to guide feeding decisions, including situations in which animals are confronted with stimuli of opposite valence. Overall, these results show that food-derived olfactory cues directly modulate feeding in D. melanogaster, enhancing ingestion.
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Affiliation(s)
- Carolina E Reisenman
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA .,Essig Museum of Entomology, University of California Berkeley, Berkeley, CA 94720, USA
| | - Kristin Scott
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA.,Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
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153
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Dolan MJ, Frechter S, Bates AS, Dan C, Huoviala P, Roberts RJV, Schlegel P, Dhawan S, Tabano R, Dionne H, Christoforou C, Close K, Sutcliffe B, Giuliani B, Li F, Costa M, Ihrke G, Meissner GW, Bock DD, Aso Y, Rubin GM, Jefferis GSXE. Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body. eLife 2019; 8:e43079. [PMID: 31112130 PMCID: PMC6529221 DOI: 10.7554/elife.43079] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 02/07/2019] [Indexed: 01/26/2023] Open
Abstract
Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.
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Affiliation(s)
- Michael-John Dolan
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | - Shahar Frechter
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | | | - Chuntao Dan
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Paavo Huoviala
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | | | - Philipp Schlegel
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
- Department of ZoologyUniversity of CambridgeCambridgeUnited Kingdom
| | - Serene Dhawan
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
- Department of ZoologyUniversity of CambridgeCambridgeUnited Kingdom
| | - Remy Tabano
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Heather Dionne
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | | | - Kari Close
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Ben Sutcliffe
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | - Bianca Giuliani
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Feng Li
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Marta Costa
- Department of ZoologyUniversity of CambridgeCambridgeUnited Kingdom
| | - Gudrun Ihrke
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | | | - Davi D Bock
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Yoshinori Aso
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Gerald M Rubin
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | - Gregory SXE Jefferis
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
- Division of NeurobiologyMRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
- Department of ZoologyUniversity of CambridgeCambridgeUnited Kingdom
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154
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Frechter S, Bates AS, Tootoonian S, Dolan MJ, Manton J, Jamasb AR, Kohl J, Bock D, Jefferis G. Functional and anatomical specificity in a higher olfactory centre. eLife 2019; 8:44590. [PMID: 31112127 PMCID: PMC6550879 DOI: 10.7554/elife.44590] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/12/2019] [Indexed: 12/16/2022] Open
Abstract
Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli.
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Affiliation(s)
- Shahar Frechter
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
| | | | - Sina Tootoonian
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.,Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.,Neurophysiology of Behaviour Laboratory, The Francis Crick Institute, London, United Kingdom
| | - Michael-John Dolan
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.,Janelia Research Campus, Howard Hughes Medical Institute, Chevy Chase, United States
| | - James Manton
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
| | | | - Johannes Kohl
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
| | - Davi Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Chevy Chase, United States
| | - Gregory Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.,Department of Zoology, University of Cambridge, Cambridge, United Kingdom
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155
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Shepherd D, Sahota V, Court R, Williams DW, Truman JW. Developmental organization of central neurons in the adult Drosophila ventral nervous system. J Comp Neurol 2019; 527:2573-2598. [PMID: 30919956 DOI: 10.1002/cne.24690] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 03/18/2019] [Accepted: 03/19/2019] [Indexed: 12/15/2022]
Abstract
We have used MARCM to reveal the adult morphology of the post embryonically produced neurons in the thoracic neuromeres of the Drosophila VNS. The work builds on previous studies of the origins of the adult VNS neurons to describe the clonal organization of the adult VNS. We present data for 58 of 66 postembryonic thoracic lineages, excluding the motor neuron producing lineages (15 and 24) which have been described elsewhere. MARCM labels entire lineages but where both A and B hemilineages survive (e.g., lineages 19, 12, 13, 6, 1, 3, 8, and 11), the two hemilineages can be discriminated and we have described each hemilineage separately. Hemilineage morphology is described in relation to the known functional domains of the VNS neuropil and based on the anatomy we are able to assign broad functional roles for each hemilineage. The data show that in a thoracic hemineuromere, 16 hemilineages are primarily involved in controlling leg movements and walking, 9 are involved in the control of wing movements, and 10 interface between both leg and wing control. The data provide a baseline of understanding of the functional organization of the adult Drosophila VNS. By understanding the morphological organization of these neurons, we can begin to define and test the rules by which neuronal circuits are assembled during development and understand the functional logic and evolution of neuronal networks.
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Affiliation(s)
- David Shepherd
- School of Natural Sciences, Bangor University, Bangor, Gwynedd, UK
| | - Virender Sahota
- School of Natural Sciences, Bangor University, Bangor, Gwynedd, UK
| | - Robert Court
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Darren W Williams
- Centre for Developmental Neurobiology, King's College London, London, UK
| | - James W Truman
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, Virginia.,Friday Harbor Laboratories, University of Washington, Friday Harbor, Washington, USA
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156
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Thyme SB, Pieper LM, Li EH, Pandey S, Wang Y, Morris NS, Sha C, Choi JW, Herrera KJ, Soucy ER, Zimmerman S, Randlett O, Greenwood J, McCarroll SA, Schier AF. Phenotypic Landscape of Schizophrenia-Associated Genes Defines Candidates and Their Shared Functions. Cell 2019; 177:478-491.e20. [PMID: 30929901 PMCID: PMC6494450 DOI: 10.1016/j.cell.2019.01.048] [Citation(s) in RCA: 138] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 10/15/2018] [Accepted: 01/27/2019] [Indexed: 01/25/2023]
Abstract
Genomic studies have identified hundreds of candidate genes near loci associated with risk for schizophrenia. To define candidates and their functions, we mutated zebrafish orthologs of 132 human schizophrenia-associated genes. We created a phenotype atlas consisting of whole-brain activity maps, brain structural differences, and profiles of behavioral abnormalities. Phenotypes were diverse but specific, including altered forebrain development and decreased prepulse inhibition. Exploration of these datasets identified promising candidates in more than 10 gene-rich regions, including the magnesium transporter cnnm2 and the translational repressor gigyf2, and revealed shared anatomical sites of activity differences, including the pallium, hypothalamus, and tectum. Single-cell RNA sequencing uncovered an essential role for the understudied transcription factor znf536 in the development of forebrain neurons implicated in social behavior and stress. This phenotypic landscape of schizophrenia-associated genes prioritizes more than 30 candidates for further study and provides hypotheses to bridge the divide between genetic association and biological mechanism.
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Affiliation(s)
- Summer B Thyme
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Lindsey M Pieper
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Eric H Li
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Shristi Pandey
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Yiqun Wang
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Nathan S Morris
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Carrie Sha
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Joo Won Choi
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Kristian J Herrera
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Edward R Soucy
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Steve Zimmerman
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Owen Randlett
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Joel Greenwood
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Steven A McCarroll
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Cambridge, MA 02142, USA
| | - Alexander F Schier
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA; Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Biozentrum, University of Basel, CH-4056 Basel, Switzerland; Harvard Stem Cell Institute, Cambridge, MA 02138, USA; FAS Center for Systems Biology, Harvard University, MA 02138, USA; Allen Discovery Center for Cell Lineage Tracing, Seattle, WA 98104, USA.
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157
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Wang SL, Kahaki SMM, Stepanyants A. Artificial neural network filters for enhancing 3D optical microscopy images of neurites. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2019; 10949. [PMID: 30971853 DOI: 10.1117/12.2512989] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
The ability to extract accurate morphology of labeled neurons from microscopy images is crucial for mapping brain connectivity and for understanding changes in connectivity that underlie learning and neurological disorders. There are, however, two problems, specific to optical microscopy imaging of neurons, which make accurate neuron tracing exceedingly challenging: (i) neurites can appear broken due to inhomogeneous labeling and (ii) neurites can appear fused in 3D due to limited resolution. Here, we propose and evaluate several artificial neural network (ANN) architectures and conventional image enhancement filters with the aim of alleviating both problems. We developed four image quality metrics to evaluate the effects of the proposed filters: normalized intensity in the cross-over regions between neurites, effective radius of neurites, coefficient of variation of intensity along neurites, and local background to neurite intensity ratio. Our results show that ANN-based filters, trained on optimized semi-manual traces of neurites, can significantly outperform conventional filters. In particular, U-Net based filtering can virtually eliminate background intensity, while also reducing the effective radius of neurites to nearly 1 voxel. In addition, this filter significantly decreases intensity in the cross-over regions between neurites and reduces fluctuations of intensity on neurites' centerlines. These results suggest that including an ANN-based filtering step, which does not require substantial extra time or computing power, can be beneficial for automated neuron tracing projects.
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Affiliation(s)
- Shih-Luen Wang
- Department of Physics and Center for Interdisciplinary Research on Complex Systems, Northeastern University, Boston, MA 02115, USA
| | - Seyed M M Kahaki
- Department of Physics and Center for Interdisciplinary Research on Complex Systems, Northeastern University, Boston, MA 02115, USA
| | - Armen Stepanyants
- Department of Physics and Center for Interdisciplinary Research on Complex Systems, Northeastern University, Boston, MA 02115, USA
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158
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Neural Evolution of Context-Dependent Fly Song. Curr Biol 2019; 29:1089-1099.e7. [PMID: 30880014 DOI: 10.1016/j.cub.2019.02.019] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 12/21/2018] [Accepted: 02/05/2019] [Indexed: 01/06/2023]
Abstract
It is unclear where in the nervous system evolutionary changes tend to occur. To localize the source of neural evolution that has generated divergent behaviors, we developed a new approach to label and functionally manipulate homologous neurons across Drosophila species. We examined homologous descending neurons that drive courtship song in two species that sing divergent song types and localized relevant evolutionary changes in circuit function downstream of the intrinsic physiology of these descending neurons. This evolutionary change causes different species to produce divergent motor patterns in similar social contexts. Artificial stimulation of these descending neurons drives multiple song types, suggesting that multifunctional properties of song circuits may facilitate rapid evolution of song types.
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159
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Groschner LN, Miesenböck G. Mechanisms of Sensory Discrimination: Insights from Drosophila Olfaction. Annu Rev Biophys 2019; 48:209-229. [PMID: 30786228 DOI: 10.1146/annurev-biophys-052118-115655] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
All an animal can do to infer the state of its environment is to observe the sensory-evoked activity of its own neurons. These inferences about the presence, quality, or similarity of objects are probabilistic and inform behavioral decisions that are often made in close to real time. Neural systems employ several strategies to facilitate sensory discrimination: Biophysical mechanisms separate the neuronal response distributions in coding space, compress their variances, and combine information from sequential observations. We review how these strategies are implemented in the olfactory system of the fruit fly. The emerging principles of odor discrimination likely apply to other neural circuits of similar architecture.
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Affiliation(s)
- Lukas N Groschner
- Centre for Neural Circuits and Behavior, University of Oxford, Oxford OX1 3SR, United Kingdom;
| | - Gero Miesenböck
- Centre for Neural Circuits and Behavior, University of Oxford, Oxford OX1 3SR, United Kingdom;
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160
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Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila. iScience 2019; 13:113-124. [PMID: 30826726 PMCID: PMC6402261 DOI: 10.1016/j.isci.2019.02.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 01/09/2019] [Accepted: 02/12/2019] [Indexed: 01/31/2023] Open
Abstract
Odorants of behaviorally relevant objects (e.g., food sources) intermingle with those from other sources. Therefore to determine whether an odor source is good or bad—without actually visiting it—animals first need to segregate the odorants from different sources. To do so, animals could use temporal stimulus cues, because odorants from one source exhibit correlated fluctuations, whereas odorants from different sources are less correlated. However, the behaviorally relevant timescales of temporal stimulus cues for odor source segregation remain unclear. Using behavioral experiments with free-flying flies, we show that (1) odorant onset asynchrony increases flies' attraction to a mixture of two odorants with opposing innate or learned valence and (2) attraction does not increase when the attractive odorant arrives first. These data suggest that flies can use stimulus onset asynchrony for odor source segregation and imply temporally precise neural mechanisms for encoding odors and for segregating them into distinct objects. Flies can detect whether two mixed odorants arrive synchronously or asynchronously This temporal sensitivity occurs for odorants with innate and learned valences Flies' behavior suggests use of odor onset asynchrony for odor source segregation
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161
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Chai PC, Cruchet S, Wigger L, Benton R. Sensory neuron lineage mapping and manipulation in the Drosophila olfactory system. Nat Commun 2019; 10:643. [PMID: 30733440 PMCID: PMC6367400 DOI: 10.1038/s41467-019-08345-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 12/28/2018] [Indexed: 11/20/2022] Open
Abstract
Nervous systems exhibit myriad cell types, but understanding how this diversity arises is hampered by the difficulty to visualize and genetically-probe specific lineages, especially at early developmental stages prior to expression of unique molecular markers. Here, we use a genetic immortalization method to analyze the development of sensory neuron lineages in the Drosophila olfactory system, from their origin to terminal differentiation. We apply this approach to define a fate map of nearly all olfactory lineages and refine the model of temporal patterns of lineage divisions. Taking advantage of a selective marker for the lineage that gives rise to Or67d pheromone-sensing neurons and a genome-wide transcription factor RNAi screen, we identify the spatial and temporal requirements for Pointed, an ETS family member, in this developmental pathway. Transcriptomic analysis of wild-type and Pointed-depleted olfactory tissue reveals a universal requirement for this factor as a switch-like determinant of fates in these sensory lineages. Few tools exist to study molecular diversity during neurodevelopment. Here the authors apply a genetic immortalization method in Drosophila to generate a fate map of olfactory sensory lineages, examine the relationships of this map and the neuroanatomical, molecular and evolutionary properties of the mature circuits, and identify a novel factor controlling lineage development.
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Affiliation(s)
- Phing Chian Chai
- Center for Integrative Genomics, Génopode Building, Faculty of Biology and Medicine, University of Lausanne, 1015, Lausanne, Switzerland
| | - Steeve Cruchet
- Center for Integrative Genomics, Génopode Building, Faculty of Biology and Medicine, University of Lausanne, 1015, Lausanne, Switzerland
| | - Leonore Wigger
- Lausanne Genomic Technologies Facility, Génopode Building, Faculty of Biology and Medicine, University of Lausanne, 1015, Lausanne, Switzerland.,Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Richard Benton
- Center for Integrative Genomics, Génopode Building, Faculty of Biology and Medicine, University of Lausanne, 1015, Lausanne, Switzerland.
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162
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Bates AS, Janssens J, Jefferis GS, Aerts S. Neuronal cell types in the fly: single-cell anatomy meets single-cell genomics. Curr Opin Neurobiol 2019; 56:125-134. [PMID: 30703584 DOI: 10.1016/j.conb.2018.12.012] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 12/21/2018] [Accepted: 12/23/2018] [Indexed: 12/21/2022]
Abstract
At around 150 000 neurons, the adult Drosophila melanogaster central nervous system is one of the largest species, for which a complete cellular catalogue is imminent. While numerically much simpler than mammalian brains, its complexity is still difficult to parse without grouping neurons into consistent types, which can number 1-1000 cells per hemisphere. We review how neuroanatomical and gene expression data are being used to discover neuronal types at scale. The correlation among multiple co-varying neuronal properties, including lineage, gene expression, morphology, connectivity, response properties and shared behavioral significance is essential to the definition of neuronal cell type. Initial studies comparing morphological and transcriptomic definitions of neuronal type suggest that these are highly consistent, but there is much to do to match these approaches brain-wide. Matched single-cell transcriptomic and morphological data provide an effective reference point to integrate other data types, including connectomics data. This will significantly enhance our ability to make functional predictions from brain wiring diagrams as well facilitating molecular genetic manipulation of neuronal types.
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Affiliation(s)
| | - Jasper Janssens
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Gregory Sxe Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
| | - Stein Aerts
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium.
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163
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McKellar CE, Lillvis JL, Bath DE, Fitzgerald JE, Cannon JG, Simpson JH, Dickson BJ. Threshold-Based Ordering of Sequential Actions during Drosophila Courtship. Curr Biol 2019; 29:426-434.e6. [PMID: 30661796 DOI: 10.1016/j.cub.2018.12.019] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 11/01/2018] [Accepted: 12/13/2018] [Indexed: 01/09/2023]
Abstract
Goal-directed animal behaviors are typically composed of sequences of motor actions whose order and timing are critical for a successful outcome. Although numerous theoretical models for sequential action generation have been proposed, few have been supported by the identification of control neurons sufficient to elicit a sequence. Here, we identify a pair of descending neurons that coordinate a stereotyped sequence of engagement actions during Drosophila melanogaster male courtship behavior. These actions are initiated sequentially but persist cumulatively, a feature not explained by existing models of sequential behaviors. We find evidence consistent with a ramp-to-threshold mechanism, in which increasing neuronal activity elicits each action independently at successively higher activity thresholds.
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Affiliation(s)
- Claire E McKellar
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Joshua L Lillvis
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Daniel E Bath
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - James E Fitzgerald
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - John G Cannon
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Julie H Simpson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Queensland Brain Institute, University of Queensland, St Lucia, QLD 4072, Australia.
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164
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Delahunt CB, Riffell JA, Kutz JN. Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets. Front Comput Neurosci 2018; 12:102. [PMID: 30618694 PMCID: PMC6306094 DOI: 10.3389/fncom.2018.00102] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Accepted: 12/03/2018] [Indexed: 11/23/2022] Open
Abstract
The insect olfactory system, which includes the antennal lobe (AL), mushroom body (MB), and ancillary structures, is a relatively simple neural system capable of learning. Its structural features, which are widespread in biological neural systems, process olfactory stimuli through a cascade of networks where large dimension shifts occur from stage to stage and where sparsity and randomness play a critical role in coding. Learning is partly enabled by a neuromodulatory reward mechanism of octopamine stimulation of the AL, whose increased activity induces synaptic weight updates in the MB through Hebbian plasticity. Enforced sparsity in the MB focuses Hebbian growth on neurons that are the most important for the representation of the learned odor. Based upon current biophysical knowledge, we have constructed an end-to-end computational firing-rate model of the Manduca sexta moth olfactory system which includes the interaction of the AL and MB under octopamine stimulation. Our model is able to robustly learn new odors, and neural firing rates in our simulations match the statistical features of in vivo firing rate data. From a biological perspective, the model provides a valuable tool for examining the role of neuromodulators, like octopamine, in learning, and gives insight into critical interactions between sparsity, Hebbian growth, and stimulation during learning. Our simulations also inform predictions about structural details of the olfactory system that are not currently well-characterized. From a machine learning perspective, the model yields bio-inspired mechanisms that are potentially useful in constructing neural nets for rapid learning from very few samples. These mechanisms include high-noise layers, sparse layers as noise filters, and a biologically-plausible optimization method to train the network based on octopamine stimulation, sparse layers, and Hebbian growth.
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Affiliation(s)
- Charles B. Delahunt
- Department of Electrical Engineering, University of Washington, Seattle, WA, United States
- Computational Neuroscience Center, University of Washington, Seattle, WA, United States
| | - Jeffrey A. Riffell
- Department of Biology, University of Washington, Seattle, WA, United States
| | - J. Nathan Kutz
- Department of Applied Mathematics, University of Washington, Seattle, WA, United States
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165
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Rossi N, Baracchi D, Giurfa M, d'Ettorre P. Pheromone-Induced Accuracy of Nestmate Recognition in Carpenter Ants: Simultaneous Decrease in Type I and Type II Errors. Am Nat 2018; 193:267-278. [PMID: 30720368 DOI: 10.1086/701123] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The ecological and evolutionary success of social insects relies on their ability to efficiently discriminate between group members and aliens. Nestmate recognition occurs by phenotype matching, the comparison of the referent (colony) phenotype to the one of an encountered individual. Based on the level of dissimilarity between the two, the discriminator accepts or rejects the target. The tolerated degree of mismatch is predicted by the acceptance threshold model, which assumes adaptive threshold shifts depending on the costs of discrimination errors. Inherent in the model is that rejection (type I) and acceptance (type II) errors are reciprocally related: if one type decreases, the other increases. We studied whether alarm pheromones modulate the acceptance threshold. We exposed Camponotus aethiops ants to formic acid and subsequently measured aggression toward nestmates and nonnestmates. Formic acid induced both more nonnestmate rejection and more nestmate acceptance than a control treatment, thus uncovering an unexpected effect of an alarm pheromone on responses to nestmates. Nestmate discrimination accuracy was improved via a decrease in both types of errors, a result that cannot be explained by a shift in the acceptance threshold. We propose that formic acid increases the amount of information available to the ants, thus decreasing the perceived phenotypic overlap between nestmate and nonnestmate recognition cues. This mechanism for improved discrimination reveals a novel function of alarm pheromones in recognition processes and may have far-reaching implications in our understanding of the modus operandi of recognition systems in general.
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166
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Xiong J, Ren J, Luo L, Horowitz M. Mapping Histological Slice Sequences to the Allen Mouse Brain Atlas Without 3D Reconstruction. Front Neuroinform 2018; 12:93. [PMID: 30618698 PMCID: PMC6297281 DOI: 10.3389/fninf.2018.00093] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 11/22/2018] [Indexed: 11/13/2022] Open
Abstract
Histological brain slices are widely used in neuroscience to study the anatomical organization of neural circuits. Systematic and accurate comparisons of anatomical data from multiple brains, especially from different studies, can benefit tremendously from registering histological slices onto a common reference atlas. Most existing methods rely on an initial reconstruction of the volume before registering it to a reference atlas. Because these slices are prone to distortions during the sectioning process and often sectioned with non-standard angles, reconstruction is challenging and often inaccurate. Here we describe a framework that maps each slice to its corresponding plane in the Allen Mouse Brain Atlas (2015) to build a plane-wise mapping and then perform 2D nonrigid registration to build a pixel-wise mapping. We use the L2 norm of the histogram of oriented gradients difference of two patches as the similarity metric for both steps and a Markov random field formulation that incorporates tissue coherency to compute the nonrigid registration. To fix significantly distorted regions that are misshaped or much smaller than the control grids, we train a context-aggregation network to segment and warp them to their corresponding regions with thin plate spline. We have shown that our method generates results comparable to an expert neuroscientist and is significantly better than reconstruction-first approaches. Code and sample dataset are available at sites.google.com/view/brain-mapping.
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Affiliation(s)
- Jing Xiong
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States
| | - Jing Ren
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA, United States
| | - Liqun Luo
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA, United States
| | - Mark Horowitz
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States
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167
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Prenatal Neuropathologies in Autism Spectrum Disorder and Intellectual Disability: The Gestation of a Comprehensive Zebrafish Model. J Dev Biol 2018; 6:jdb6040029. [PMID: 30513623 PMCID: PMC6316217 DOI: 10.3390/jdb6040029] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 11/20/2018] [Accepted: 11/27/2018] [Indexed: 12/27/2022] Open
Abstract
Autism spectrum disorder (ASD) and intellectual disability (ID) are neurodevelopmental disorders with overlapping diagnostic behaviors and risk factors. These include embryonic exposure to teratogens and mutations in genes that have important functions prenatally. Animal models, including rodents and zebrafish, have been essential in delineating mechanisms of neuropathology and identifying developmental critical periods, when those mechanisms are most sensitive to disruption. This review focuses on how the developmentally accessible zebrafish is contributing to our understanding of prenatal pathologies that set the stage for later ASD-ID behavioral deficits. We discuss the known factors that contribute prenatally to ASD-ID and the recent use of zebrafish to model deficits in brain morphogenesis and circuit development. We conclude by suggesting that a future challenge in zebrafish ASD-ID modeling will be to bridge prenatal anatomical and physiological pathologies to behavioral deficits later in life.
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168
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Mamiya A, Gurung P, Tuthill JC. Neural Coding of Leg Proprioception in Drosophila. Neuron 2018; 100:636-650.e6. [PMID: 30293823 PMCID: PMC6481666 DOI: 10.1016/j.neuron.2018.09.009] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 07/01/2018] [Accepted: 09/05/2018] [Indexed: 01/12/2023]
Abstract
Animals rely on an internal sense of body position and movement to effectively control motor behavior. This sense of proprioception is mediated by diverse populations of mechanosensory neurons distributed throughout the body. Here, we investigate neural coding of leg proprioception in Drosophila, using in vivo two-photon calcium imaging of proprioceptive sensory neurons during controlled movements of the fly tibia. We found that the axons of leg proprioceptors are organized into distinct functional projections that contain topographic representations of specific kinematic features. Using subclass-specific genetic driver lines, we show that one group of axons encodes tibia position (flexion/extension), another encodes movement direction, and a third encodes bidirectional movement and vibration frequency. Overall, our findings reveal how proprioceptive stimuli from a single leg joint are encoded by a diverse population of sensory neurons, and provide a framework for understanding how proprioceptive feedback signals are used by motor circuits to coordinate the body.
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Affiliation(s)
- Akira Mamiya
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Pralaksha Gurung
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA.
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169
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Dolan MJ, Belliart-Guérin G, Bates AS, Frechter S, Lampin-Saint-Amaux A, Aso Y, Roberts RJV, Schlegel P, Wong A, Hammad A, Bock D, Rubin GM, Preat T, Plaçais PY, Jefferis GSXE. Communication from Learned to Innate Olfactory Processing Centers Is Required for Memory Retrieval in Drosophila. Neuron 2018; 100:651-668.e8. [PMID: 30244885 PMCID: PMC6226615 DOI: 10.1016/j.neuron.2018.08.037] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 05/18/2018] [Accepted: 08/27/2018] [Indexed: 11/19/2022]
Abstract
The behavioral response to a sensory stimulus may depend on both learned and innate neuronal representations. How these circuits interact to produce appropriate behavior is unknown. In Drosophila, the lateral horn (LH) and mushroom body (MB) are thought to mediate innate and learned olfactory behavior, respectively, although LH function has not been tested directly. Here we identify two LH cell types (PD2a1 and PD2b1) that receive input from an MB output neuron required for recall of aversive olfactory memories. These neurons are required for aversive memory retrieval and modulated by training. Connectomics data demonstrate that PD2a1 and PD2b1 neurons also receive direct input from food odor-encoding neurons. Consistent with this, PD2a1 and PD2b1 are also necessary for unlearned attraction to some odors, indicating that these neurons have a dual behavioral role. This provides a circuit mechanism by which learned and innate olfactory information can interact in identified neurons to produce appropriate behavior. VIDEO ABSTRACT.
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Affiliation(s)
- Michael-John Dolan
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Ghislain Belliart-Guérin
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University, 75005 Paris, France
| | | | - Shahar Frechter
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
| | - Aurélie Lampin-Saint-Amaux
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University, 75005 Paris, France
| | - Yoshinori Aso
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Philipp Schlegel
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK
| | - Allan Wong
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Adnan Hammad
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
| | - Davi Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Thomas Preat
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University, 75005 Paris, France
| | - Pierre-Yves Plaçais
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University, 75005 Paris, France.
| | - Gregory S X E Jefferis
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.
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170
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Mushroom Body Specific Transcriptome Analysis Reveals Dynamic Regulation of Learning and Memory Genes After Acquisition of Long-Term Courtship Memory in Drosophila. G3-GENES GENOMES GENETICS 2018; 8:3433-3446. [PMID: 30158319 PMCID: PMC6222587 DOI: 10.1534/g3.118.200560] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The formation and recall of long-term memory (LTM) requires neuron activity-induced gene expression. Transcriptome analysis has been used to identify genes that have altered expression after memory acquisition, however, we still have an incomplete picture of the transcriptional changes that are required for LTM formation. The complex spatial and temporal dynamics of memory formation creates significant challenges in defining memory-relevant gene expression changes. The Drosophila mushroom body (MB) is a signaling hub in the insect brain that integrates sensory information to form memories across several different experimental memory paradigms. Here, we performed transcriptome analysis in the MB at two time points after the acquisition of LTM: 1 hr and 24 hr. The MB transcriptome was compared to biologically paired whole head (WH) transcriptomes. In both, we identified more transcript level changes at 1 hr after memory acquisition (WH = 322, MB = 302) than at 24 hr (WH = 23, MB = 20). WH samples showed downregulation of developmental genes and upregulation of sensory response genes. In contrast, MB samples showed vastly different changes in transcripts involved in biological processes that are specifically related to LTM. MB-downregulated genes were highly enriched for metabolic function. MB-upregulated genes were highly enriched for known learning and memory processes, including calcium-mediated neurotransmitter release and cAMP signaling. The neuron activity inducible genes Hr38 and sr were also specifically induced in the MB. These results highlight the importance of sampling time and cell type in capturing biologically relevant transcript level changes involved in learning and memory. Our data suggests that MB cells transiently upregulate known memory-related pathways after memory acquisition and provides a critical frame of reference for further investigation into the role of MB-specific gene regulation in memory.
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171
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Zheng Z, Lauritzen JS, Perlman E, Robinson CG, Nichols M, Milkie D, Torrens O, Price J, Fisher CB, Sharifi N, Calle-Schuler SA, Kmecova L, Ali IJ, Karsh B, Trautman ET, Bogovic JA, Hanslovsky P, Jefferis GSXE, Kazhdan M, Khairy K, Saalfeld S, Fetter RD, Bock DD. A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster. Cell 2018; 174:730-743.e22. [PMID: 30033368 PMCID: PMC6063995 DOI: 10.1016/j.cell.2018.06.019] [Citation(s) in RCA: 528] [Impact Index Per Article: 75.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 02/28/2018] [Accepted: 06/10/2018] [Indexed: 12/16/2022]
Abstract
Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly at synaptic resolution. To validate the dataset, we traced brain-spanning circuitry involving the mushroom body (MB), which has been extensively studied for its role in learning. All inputs to Kenyon cells (KCs), the intrinsic neurons of the MB, were mapped, revealing a previously unknown cell type, postsynaptic partners of KC dendrites, and unexpected clustering of olfactory projection neurons. These reconstructions show that this freely available EM volume supports mapping of brain-spanning circuits, which will significantly accelerate Drosophila neuroscience. VIDEO ABSTRACT.
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Affiliation(s)
- Zhihao Zheng
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - J Scott Lauritzen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Eric Perlman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Camenzind G Robinson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Matthew Nichols
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | | | - Omar Torrens
- Coleman Technologies, Newtown Square, PA 19073, USA
| | - John Price
- Hudson Price Designs, Hingham, MA 02043, USA
| | - Corey B Fisher
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Nadiya Sharifi
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | | | - Lucia Kmecova
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Iqbal J Ali
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Bill Karsh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Eric T Trautman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - John A Bogovic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Philipp Hanslovsky
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Gregory S X E Jefferis
- Division of Neurobiology, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK
| | - Michael Kazhdan
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Khaled Khairy
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Stephan Saalfeld
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Richard D Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Davi D Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
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172
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Sugie A, Marchetti G, Tavosanis G. Structural aspects of plasticity in the nervous system of Drosophila. Neural Dev 2018; 13:14. [PMID: 29960596 PMCID: PMC6026517 DOI: 10.1186/s13064-018-0111-z] [Citation(s) in RCA: 24] [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: 12/22/2017] [Accepted: 06/12/2018] [Indexed: 12/15/2022] Open
Abstract
Neurons extend and retract dynamically their neurites during development to form complex morphologies and to reach out to their appropriate synaptic partners. Their capacity to undergo structural rearrangements is in part maintained during adult life when it supports the animal's ability to adapt to a changing environment or to form lasting memories. Nonetheless, the signals triggering structural plasticity and the mechanisms that support it are not yet fully understood at the molecular level. Here, we focus on the nervous system of the fruit fly to ask to which extent activity modulates neuronal morphology and connectivity during development. Further, we summarize the evidence indicating that the adult nervous system of flies retains some capacity for structural plasticity at the synaptic or circuit level. For simplicity, we selected examples mostly derived from studies on the visual system and on the mushroom body, two regions of the fly brain with extensively studied neuroanatomy.
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Affiliation(s)
- Atsushi Sugie
- Center for Transdisciplinary Research, Niigata University, Niigata, 951-8585 Japan
- Brain Research Institute, Niigata University, Niigata, 951-8585 Japan
| | | | - Gaia Tavosanis
- Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
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173
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Jeanne JM, Fişek M, Wilson RI. The Organization of Projections from Olfactory Glomeruli onto Higher-Order Neurons. Neuron 2018; 98:1198-1213.e6. [PMID: 29909998 PMCID: PMC6051339 DOI: 10.1016/j.neuron.2018.05.011] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Revised: 04/19/2018] [Accepted: 05/04/2018] [Indexed: 11/27/2022]
Abstract
Each odorant receptor corresponds to a unique glomerulus in the brain. Projections from different glomeruli then converge in higher brain regions, but we do not understand the logic governing which glomeruli converge and which do not. Here, we use two-photon optogenetics to map glomerular connections onto neurons in the lateral horn, the region of the Drosophila brain that receives the majority of olfactory projections. We identify 39 morphological types of lateral horn neurons (LHNs) and show that different types receive input from different combinations of glomeruli. We find that different LHN types do not have independent inputs; rather, certain combinations of glomeruli converge onto many of the same LHNs and so are over-represented. Notably, many over-represented combinations are composed of glomeruli that prefer chemically dissimilar ligands whose co-occurrence indicates a behaviorally relevant "odor scene." The pattern of glomerulus-LHN connections thus represents a prediction of what ligand combinations will be most salient.
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Affiliation(s)
- James M Jeanne
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Mehmet Fişek
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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174
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Namiki S, Dickinson MH, Wong AM, Korff W, Card GM. The functional organization of descending sensory-motor pathways in Drosophila. eLife 2018; 7:e34272. [PMID: 29943730 PMCID: PMC6019073 DOI: 10.7554/elife.34272] [Citation(s) in RCA: 195] [Impact Index Per Article: 27.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 05/09/2018] [Indexed: 12/12/2022] Open
Abstract
In most animals, the brain controls the body via a set of descending neurons (DNs) that traverse the neck. DN activity activates, maintains or modulates locomotion and other behaviors. Individual DNs have been well-studied in species from insects to primates, but little is known about overall connectivity patterns across the DN population. We systematically investigated DN anatomy in Drosophila melanogaster and created over 100 transgenic lines targeting individual cell types. We identified roughly half of all Drosophila DNs and comprehensively map connectivity between sensory and motor neuropils in the brain and nerve cord, respectively. We find the nerve cord is a layered system of neuropils reflecting the fly's capability for two largely independent means of locomotion -- walking and flight -- using distinct sets of appendages. Our results reveal the basic functional map of descending pathways in flies and provide tools for systematic interrogation of neural circuits.
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Affiliation(s)
- Shigehiro Namiki
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Michael H Dickinson
- Division of Biology and BioengineeringCalifornia Institute of TechnologyPasadenaUnited States
| | - Allan M Wong
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
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175
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von Hadeln J, Althaus V, Häger L, Homberg U. Anatomical organization of the cerebrum of the desert locust Schistocerca gregaria. Cell Tissue Res 2018; 374:39-62. [DOI: 10.1007/s00441-018-2844-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 04/17/2018] [Indexed: 11/27/2022]
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176
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Yamada D, Ishimoto H, Li X, Kohashi T, Ishikawa Y, Kamikouchi A. GABAergic Local Interneurons Shape Female Fruit Fly Response to Mating Songs. J Neurosci 2018; 38:4329-4347. [PMID: 29691331 PMCID: PMC6596007 DOI: 10.1523/jneurosci.3644-17.2018] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Revised: 03/19/2018] [Accepted: 03/26/2018] [Indexed: 12/16/2022] Open
Abstract
Many animals use acoustic signals to attract a potential mating partner. In fruit flies (Drosophila melanogaster), the courtship pulse song has a species-specific interpulse interval (IPI) that activates mating. Although a series of auditory neurons in the fly brain exhibit different tuning patterns to IPIs, it is unclear how the response of each neuron is tuned. Here, we studied the neural circuitry regulating the activity of antennal mechanosensory and motor center (AMMC)-B1 neurons, key secondary auditory neurons in the excitatory neural pathway that relay song information. By performing Ca2+ imaging in female flies, we found that the IPI selectivity observed in AMMC-B1 neurons differs from that of upstream auditory sensory neurons [Johnston's organ (JO)-B]. Selective knock-down of a GABAA receptor subunit in AMMC-B1 neurons increased their response to short IPIs, suggesting that GABA suppresses AMMC-B1 activity at these IPIs. Connection mapping identified two GABAergic local interneurons that synapse with AMMC-B1 and JO-B. Ca2+ imaging combined with neuronal silencing revealed that these local interneurons, AMMC-LN and AMMC-B2, shape the response pattern of AMMC-B1 neurons at a 15 ms IPI. Neuronal silencing studies further suggested that both GABAergic local interneurons suppress the behavioral response to artificial pulse songs in flies, particularly those with a 15 ms IPI. Altogether, we identified a circuit containing two GABAergic local interneurons that affects the temporal tuning of AMMC-B1 neurons in the song relay pathway and the behavioral response to the courtship song. Our findings suggest that feedforward inhibitory pathways adjust the behavioral response to courtship pulse songs in female flies.SIGNIFICANCE STATEMENT To understand how the brain detects time intervals between sound elements, we studied the neural pathway that relays species-specific courtship song information in female Drosophila melanogaster We demonstrate that the signal transmission from auditory sensory neurons to key secondary auditory neurons antennal mechanosensory and motor center (AMMC)-B1 is the first-step to generate time interval selectivity of neurons in the song relay pathway. Two GABAergic local interneurons are suggested to shape the interval selectivity of AMMC-B1 neurons by receiving auditory inputs and in turn providing feedforward inhibition onto AMMC-B1 neurons. Furthermore, these GABAergic local interneurons suppress the song response behavior in an interval-dependent manner. Our results provide new insights into the neural circuit basis to adjust neuronal and behavioral responses to a species-specific communication sound.
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Affiliation(s)
- Daichi Yamada
- Graduate School of Science, Nagoya University, Chikusa, Nagoya, Aichi 464-8602, Japan
| | - Hiroshi Ishimoto
- Graduate School of Science, Nagoya University, Chikusa, Nagoya, Aichi 464-8602, Japan
| | - Xiaodong Li
- Graduate School of Science, Nagoya University, Chikusa, Nagoya, Aichi 464-8602, Japan
| | - Tsunehiko Kohashi
- Graduate School of Science, Nagoya University, Chikusa, Nagoya, Aichi 464-8602, Japan
| | - Yuki Ishikawa
- Graduate School of Science, Nagoya University, Chikusa, Nagoya, Aichi 464-8602, Japan
| | - Azusa Kamikouchi
- Graduate School of Science, Nagoya University, Chikusa, Nagoya, Aichi 464-8602, Japan
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177
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Kumaraswamy A, Kai K, Ai H, Ikeno H, Wachtler T. Spatial registration of neuron morphologies based on maximization of volume overlap. BMC Bioinformatics 2018; 19:143. [PMID: 29669537 PMCID: PMC5907365 DOI: 10.1186/s12859-018-2136-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 03/26/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Morphological features are widely used in the study of neuronal function and pathology. Invertebrate neurons are often structurally stereotypical, showing little variance in gross spatial features but larger variance in their fine features. Such variability can be quantified using detailed spatial analysis, which however requires the morphologies to be registered to a common frame of reference. RESULTS We outline here new algorithms - Reg-MaxS and Reg-MaxS-N - for co-registering pairs and groups of morphologies, respectively. Reg-MaxS applies a sequence of translation, rotation and scaling transformations, estimating at each step the transformation parameters that maximize spatial overlap between the volumes occupied by the morphologies. We test this algorithm with synthetic morphologies, showing that it can account for a wide range of transformation differences and is robust to noise. Reg-MaxS-N co-registers groups of more than two morphologies by iteratively calculating an average volume and registering all morphologies to this average using Reg-MaxS. We test Reg-MaxS-N using five groups of morphologies from the Droshophila melanogaster brain and identify the cases for which it outperforms existing algorithms and produce morphologies very similar to those obtained from registration to a standard brain atlas. CONCLUSIONS We have described and tested algorithms for co-registering pairs and groups of neuron morphologies. We have demonstrated their application to spatial comparison of stereotypic morphologies and calculation of dendritic density profiles, showing how our algorithms for registering neuron morphologies can enable new approaches in comparative morphological analyses and visualization.
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Affiliation(s)
- Ajayrama Kumaraswamy
- Department of Biology II, Ludwig-Maximilians-Universität München, Grosshadernerstr, 2, Planegg-Martinsried, 82152, Germany.
| | - Kazuki Kai
- Department of Earth System Science, Fukuoka University, 8-19-1 Nanakuma, Jonan-ku, Fukuoka-shi, Fukuoka, 814-0180, Japan
| | - Hiroyuki Ai
- Department of Earth System Science, Fukuoka University, 8-19-1 Nanakuma, Jonan-ku, Fukuoka-shi, Fukuoka, 814-0180, Japan
| | - Hidetoshi Ikeno
- School of Human Science and Environment, University of Hyogo, 1-1-12 Shinazaike-Honcho, Himeji, 670-0092, Hyogo, Japan
| | - Thomas Wachtler
- Department of Biology II, Ludwig-Maximilians-Universität München, Grosshadernerstr, 2, Planegg-Martinsried, 82152, Germany
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178
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Li H, Shuster SA, Li J, Luo L. Linking neuronal lineage and wiring specificity. Neural Dev 2018; 13:5. [PMID: 29653548 PMCID: PMC5899351 DOI: 10.1186/s13064-018-0102-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Accepted: 03/14/2018] [Indexed: 02/01/2023] Open
Abstract
Brain function requires precise neural circuit assembly during development. Establishing a functional circuit involves multiple coordinated steps ranging from neural cell fate specification to proper matching between pre- and post-synaptic partners. How neuronal lineage and birth timing influence wiring specificity remains an open question. Recent findings suggest that the relationships between lineage, birth timing, and wiring specificity vary in different neuronal circuits. In this review, we summarize our current understanding of the cellular, molecular, and developmental mechanisms linking neuronal lineage and birth timing to wiring specificity in a few specific systems in Drosophila and mice, and review different methods employed to explore these mechanisms.
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Affiliation(s)
- Hongjie Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - S. Andrew Shuster
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
- Neurosciences Graduate Program, Stanford University, Stanford, CA 94305 USA
| | - Jiefu Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Liqun Luo
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
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179
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Contribution of DA Signaling to Appetitive Odor Perception in a Drosophila Model. Sci Rep 2018; 8:5978. [PMID: 29654277 PMCID: PMC5899149 DOI: 10.1038/s41598-018-24334-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 03/28/2018] [Indexed: 12/14/2022] Open
Abstract
Understanding cognitive processes that translate chemically diverse olfactory stimuli to specific appetitive drives remains challenging. We have shown that food-related odors arouse impulsive-like feeding of food media that are palatable and readily accessible in well-nourished Drosophila larvae. Here we provide evidence that two assemblies of four dopamine (DA) neurons, one per brain hemisphere, contribute to perceptual processing of the qualitative and quantitative attributes of food scents. These DA neurons receive neural representations of chemically diverse food-related odors, and their combined neuronal activities become increasingly important as the chemical complexity of an appetizing odor stimulus increases. Furthermore, in each assembly of DA neurons, integrated odor signals are transformed to one-dimensional DA outputs that have no intrinsic reward values. Finally, a genetic analysis has revealed a D1-type DA receptor (Dop1R1)-gated mechanism in neuropeptide Y-like neurons that assigns appetitive significance to selected DA outputs. Our findings suggest that fly larvae provide a useful platform for elucidation of molecular and circuit mechanisms underlying cognitive processing of olfactory and possibly other sensory cues.
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180
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Arganda-Carreras I, Manoliu T, Mazuras N, Schulze F, Iglesias JE, Bühler K, Jenett A, Rouyer F, Andrey P. A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain. Front Neuroinform 2018; 12:13. [PMID: 29628885 PMCID: PMC5876320 DOI: 10.3389/fninf.2018.00013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 03/01/2018] [Indexed: 11/13/2022] Open
Abstract
Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila, one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species.
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Affiliation(s)
- Ignacio Arganda-Carreras
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France.,Ikerbasque, Basque Foundation for Science, Bilbao, Spain.,Donostia International Physics Center, Donostia-San Sebastian, Spain
| | - Tudor Manoliu
- Institut des Neurosciences Paris-Saclay, Université Paris Sud, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Nicolas Mazuras
- Institut des Neurosciences Paris-Saclay, Université Paris Sud, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Florian Schulze
- VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria
| | - Juan E Iglesias
- Basque Center on Cognition, Brain and Language, Donostia-San Sebastian, Spain
| | - Katja Bühler
- VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria
| | - Arnim Jenett
- Tefor Core Facility, Institut des Neurosciences Paris-Saclay, Université Paris Sud, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France
| | - François Rouyer
- Institut des Neurosciences Paris-Saclay, Université Paris Sud, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Philippe Andrey
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
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181
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Pandey S, Shekhar K, Regev A, Schier AF. Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq. Curr Biol 2018; 28:1052-1065.e7. [PMID: 29576475 DOI: 10.1016/j.cub.2018.02.040] [Citation(s) in RCA: 117] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 01/10/2018] [Accepted: 02/15/2018] [Indexed: 12/26/2022]
Abstract
The identification of cell types and marker genes is critical for dissecting neural development and function, but the size and complexity of the brain has hindered the comprehensive discovery of cell types. We combined single-cell RNA-seq (scRNA-seq) with anatomical brain registration to create a comprehensive map of the zebrafish habenula, a conserved forebrain hub involved in pain processing and learning. Single-cell transcriptomes of ∼13,000 habenular cells with 4× cellular coverage identified 18 neuronal types and dozens of marker genes. Registration of marker genes onto a reference atlas created a resource for anatomical and functional studies and enabled the mapping of active neurons onto neuronal types following aversive stimuli. Strikingly, despite brain growth and functional maturation, cell types were retained between the larval and adult habenula. This study provides a gene expression atlas to dissect habenular development and function and offers a general framework for the comprehensive characterization of other brain regions.
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Affiliation(s)
- Shristi Pandey
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Karthik Shekhar
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA; Howard Hughes Medical Institute and Koch Institute of Integrative Cancer Research Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02140, USA
| | - Alexander F Schier
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA; Center for Brain Science, Harvard University, 52 Oxford Street, Cambridge, MA 02138, USA; Biozentrum, University of Basel, Basel, Switzerland; Allen Discovery Center for Cell Lineage Tracing, University of Washington, Seattle, WA 98195, USA.
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182
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Tsao CH, Chen CC, Lin CH, Yang HY, Lin S. Drosophila mushroom bodies integrate hunger and satiety signals to control innate food-seeking behavior. eLife 2018; 7:35264. [PMID: 29547121 PMCID: PMC5910021 DOI: 10.7554/elife.35264] [Citation(s) in RCA: 103] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 03/15/2018] [Indexed: 12/28/2022] Open
Abstract
The fruit fly can evaluate its energy state and decide whether to pursue food-related cues. Here, we reveal that the mushroom body (MB) integrates hunger and satiety signals to control food-seeking behavior. We have discovered five pathways in the MB essential for hungry flies to locate and approach food. Blocking the MB-intrinsic Kenyon cells (KCs) and the MB output neurons (MBONs) in these pathways impairs food-seeking behavior. Starvation bi-directionally modulates MBON responses to a food odor, suggesting that hunger and satiety controls occur at the KC-to-MBON synapses. These controls are mediated by six types of dopaminergic neurons (DANs). By manipulating these DANs, we could inhibit food-seeking behavior in hungry flies or promote food seeking in fed flies. Finally, we show that the DANs potentially receive multiple inputs of hunger and satiety signals. This work demonstrates an information-rich central circuit in the fly brain that controls hunger-driven food-seeking behavior.
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Affiliation(s)
- Chang-Hui Tsao
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Chien-Chun Chen
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Chen-Han Lin
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.,Department of Life Sciences and the Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Hao-Yu Yang
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Suewei Lin
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.,Department of Life Sciences and the Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
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183
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Tsubouchi A, Yano T, Yokoyama TK, Murtin C, Otsuna H, Ito K. Topological and modality-specific representation of somatosensory information in the fly brain. Science 2018; 358:615-623. [PMID: 29097543 DOI: 10.1126/science.aan4428] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 09/25/2017] [Indexed: 12/11/2022]
Abstract
Insects and mammals share similarities of neural organization underlying the perception of odors, taste, vision, sound, and gravity. We observed that insect somatosensation also corresponds to that of mammals. In Drosophila, the projections of all the somatosensory neuron types to the insect's equivalent of the spinal cord segregated into modality-specific layers comparable to those in mammals. Some sensory neurons innervate the ventral brain directly to form modality-specific and topological somatosensory maps. Ascending interneurons with dendrites in matching layers of the nerve cord send axons that converge to respective brain regions. Pathways arising from leg somatosensory neurons encode distinct qualities of leg movement information and play different roles in ground detection. Establishment of the ground pattern and genetic tools for neuronal manipulation should provide the basis for elucidating the mechanisms underlying somatosensation.
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Affiliation(s)
- Asako Tsubouchi
- Institute of Molecular and Cellular Biosciences, The University of Tokyo, Yayoi, Bunkyo-ku, 113-0032 Tokyo, Japan
| | - Tomoko Yano
- Institute of Molecular and Cellular Biosciences, The University of Tokyo, Yayoi, Bunkyo-ku, 113-0032 Tokyo, Japan.,Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha, Kashiwa, 277-0882 Chiba, Japan
| | - Takeshi K Yokoyama
- Institute of Molecular and Cellular Biosciences, The University of Tokyo, Yayoi, Bunkyo-ku, 113-0032 Tokyo, Japan
| | - Chloé Murtin
- Institute of Molecular and Cellular Biosciences, The University of Tokyo, Yayoi, Bunkyo-ku, 113-0032 Tokyo, Japan.,Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha, Kashiwa, 277-0882 Chiba, Japan
| | - Hideo Otsuna
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | - Kei Ito
- Institute of Molecular and Cellular Biosciences, The University of Tokyo, Yayoi, Bunkyo-ku, 113-0032 Tokyo, Japan. .,Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha, Kashiwa, 277-0882 Chiba, Japan.,Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA.,Institute of Zoology, University of Cologne, 50674 Cologne, Germany
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184
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Abstract
Digital reconstruction of a single neuron occupies an important position in computational neuroscience. Although many novel methods have been proposed, recent advances in molecular labeling and imaging systems allow for the production of large and complicated neuronal datasets, which pose many challenges for neuron reconstruction, especially when discontinuous neuronal morphology appears in a strong noise environment. Here, we develop a new pipeline to address this challenge. Our pipeline is based on two methods, one is the region-to-region connection (RRC) method for detecting the initial part of a neurite, which can effectively gather local cues, i.e., avoid the whole image analysis, and thus boosts the efficacy of computation; the other is constrained principal curves method for completing the neurite reconstruction, which uses the past reconstruction information of a neurite for current reconstruction and thus can be suitable for tracing discontinuous neurites. We investigate the reconstruction performances of our pipeline and some of the best state-of-the-art algorithms on the experimental datasets, indicating the superiority of our method in reconstructing sparsely distributed neurons with discontinuous neuronal morphologies in noisy environment. We show the strong ability of our pipeline in dealing with the large-scale image dataset. We validate the effectiveness in dealing with various kinds of image stacks including those from the DIADEM challenge and BigNeuron project.
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185
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Schubert FK, Hagedorn N, Yoshii T, Helfrich-Förster C, Rieger D. Neuroanatomical details of the lateral neurons of Drosophila melanogaster support their functional role in the circadian system. J Comp Neurol 2018; 526:1209-1231. [PMID: 29424420 PMCID: PMC5873451 DOI: 10.1002/cne.24406] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 01/30/2018] [Accepted: 01/30/2018] [Indexed: 12/29/2022]
Abstract
Drosophila melanogaster is a long‐standing model organism in the circadian clock research. A major advantage is the relative small number of about 150 neurons, which built the circadian clock in Drosophila. In our recent work, we focused on the neuroanatomical properties of the lateral neurons of the clock network. By applying the multicolor‐labeling technique Flybow we were able to identify the anatomical similarity of the previously described E2 subunit of the evening oscillator of the clock, which is built by the 5th small ventrolateral neuron (5th s‐LNv) and one ITP positive dorsolateral neuron (LNd). These two clock neurons share the same spatial and functional properties. We found both neurons innervating the same brain areas with similar pre‐ and postsynaptic sites in the brain. Here the anatomical findings support their shared function as a main evening oscillator in the clock network like also found in previous studies. A second quite surprising finding addresses the large lateral ventral PDF‐neurons (l‐LNvs). We could show that the four hardly distinguishable l‐LNvs consist of two subgroups with different innervation patterns. While three of the neurons reflect the well‐known branching pattern reproduced by PDF immunohistochemistry, one neuron per brain hemisphere has a distinguished innervation profile and is restricted only to the proximal part of the medulla‐surface. We named this neuron “extra” l‐LNv (l‐LNvx). We suggest the anatomical findings reflect different functional properties of the two l‐LNv subgroups.
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Affiliation(s)
- Frank K Schubert
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, Würzburg, 97074, Germany
| | - Nicolas Hagedorn
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, Würzburg, 97074, Germany
| | - Taishi Yoshii
- Graduate School of Natural Science and Technology, Okayama University, Okayama, 700-8530, Japan
| | - Charlotte Helfrich-Förster
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, Würzburg, 97074, Germany
| | - Dirk Rieger
- Neurobiology and Genetics, Theodor-Boveri Institute, Biocenter, University of Würzburg, Würzburg, 97074, Germany
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186
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Elucidating the Neuronal Architecture of Olfactory Glomeruli in the Drosophila Antennal Lobe. Cell Rep 2018; 16:3401-3413. [PMID: 27653699 DOI: 10.1016/j.celrep.2016.08.063] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2016] [Revised: 07/15/2016] [Accepted: 08/18/2016] [Indexed: 11/21/2022] Open
Abstract
Olfactory glomeruli are morphologically conserved spherical compartments of the olfactory system, distinguishable solely by their chemosensory repertoire, anatomical position, and volume. Little is known, however, about their numerical neuronal composition. We therefore characterized their neuronal architecture and correlated these anatomical features with their functional properties in Drosophila melanogaster. We quantitatively mapped all olfactory sensory neurons (OSNs) innervating each glomerulus, including sexually dimorphic distributions. Our data reveal the impact of OSN number on glomerular dimensions and demonstrate yet unknown sex-specific differences in several glomeruli. Moreover, we quantified uniglomerular projection neurons for each glomerulus, which unraveled a glomerulus-specific numerical innervation. Correlation between morphological features and functional specificity showed that glomeruli innervated by narrowly tuned OSNs seem to possess a larger number of projection neurons and are involved in less lateral processing than glomeruli targeted by broadly tuned OSNs. Our study demonstrates that the neuronal architecture of each glomerulus encoding crucial odors is unique.
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187
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Rimal S, Lee Y. The multidimensional ionotropic receptors of Drosophila melanogaster. INSECT MOLECULAR BIOLOGY 2018; 27:1-7. [PMID: 28857341 DOI: 10.1111/imb.12347] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Ionotropic receptors (IRs), which form ion channels, can be categorized into conserved 'antennal IRs', which define the first olfactory receptor family of insects, and species-specific 'divergent IRs', which are expressed in gustatory receptor neurones. These receptors are located primarily in cell bodies and dendrites, and are highly enriched in the tips of the dendritic terminals that convey sensory information to higher brain centres. Antennal IRs play important roles in odour and thermosensation, whereas divergent IRs are involved in other important biological processes such as taste sensation. Some IRs are known to play specific biological roles in the perception of various molecules; however, many of their functions have not yet been defined. Although progress has been made in this field, many functions and mechanisms of these receptors remain unknown. In this review, we provide a comprehensive summary of the current state of knowledge in this field.
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Affiliation(s)
- S Rimal
- Department of Bio and Fermentation Convergence Technology, BK21 PLUS Project, Kookmin University, Seoul, Republic of Korea
| | - Y Lee
- Department of Bio and Fermentation Convergence Technology, BK21 PLUS Project, Kookmin University, Seoul, Republic of Korea
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188
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Sayin S, Boehm AC, Kobler JM, De Backer JF, Grunwald Kadow IC. Internal State Dependent Odor Processing and Perception-The Role of Neuromodulation in the Fly Olfactory System. Front Cell Neurosci 2018; 12:11. [PMID: 29440990 PMCID: PMC5797598 DOI: 10.3389/fncel.2018.00011] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Accepted: 01/08/2018] [Indexed: 12/21/2022] Open
Abstract
Animals rely heavily on their sense of olfaction to perform various vital interactions with an ever-in-flux environment. The turbulent and combinatorial nature of air-borne odorant cues demands the employment of various coding strategies, which allow the animal to attune to its internal needs and past or present experiences. Furthermore, these internal needs can be dependent on internal states such as hunger, reproductive state and sickness. Neuromodulation is a key component providing flexibility under such conditions. Understanding the contributions of neuromodulation, such as sensory neuron sensitization and choice bias requires manipulation of neuronal activity on a local and global scale. With Drosophila's genetic toolset, these manipulations are feasible and even allow a detailed look on the functional role of classical neuromodulators such as dopamine, octopamine and neuropeptides. The past years unraveled various mechanisms adapting chemosensory processing and perception to internal states such as hunger and reproductive state. However, future research should also investigate the mechanisms underlying other internal states including the modulatory influence of endogenous microbiota on Drosophila behavior. Furthermore, sickness induced by pathogenic infection could lead to novel insights as to the neuromodulators of circuits that integrate such a negative postingestive signal within the circuits governing olfactory behavior and learning. The enriched emporium of tools Drosophila provides will help to build a concrete picture of the influence of neuromodulation on olfaction and metabolism, adaptive behavior and our overall understanding of how a brain works.
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Affiliation(s)
- Sercan Sayin
- Neural Circuits and Metabolism, School of Life Sciences, Technische Universität München, Munich, Germany
| | - Ariane C Boehm
- Neural Circuits and Metabolism, School of Life Sciences, Technische Universität München, Munich, Germany.,Chemosensory Coding, Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Johanna M Kobler
- Neural Circuits and Metabolism, School of Life Sciences, Technische Universität München, Munich, Germany.,Chemosensory Coding, Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Jean-François De Backer
- Neural Circuits and Metabolism, School of Life Sciences, Technische Universität München, Munich, Germany
| | - Ilona C Grunwald Kadow
- Neural Circuits and Metabolism, School of Life Sciences, Technische Universität München, Munich, Germany.,Chemosensory Coding, Max Planck Institute of Neurobiology, Martinsried, Germany
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189
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Li H, Horns F, Wu B, Xie Q, Li J, Li T, Luginbuhl DJ, Quake SR, Luo L. Classifying Drosophila Olfactory Projection Neuron Subtypes by Single-Cell RNA Sequencing. Cell 2017; 171:1206-1220.e22. [PMID: 29149607 DOI: 10.1016/j.cell.2017.10.019] [Citation(s) in RCA: 176] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2017] [Revised: 08/05/2017] [Accepted: 10/12/2017] [Indexed: 11/19/2022]
Abstract
The definition of neuronal type and how it relates to the transcriptome are open questions. Drosophila olfactory projection neurons (PNs) are among the best-characterized neuronal types: different PN classes target dendrites to distinct olfactory glomeruli, while PNs of the same class exhibit indistinguishable anatomical and physiological properties. Using single-cell RNA sequencing, we comprehensively characterized the transcriptomes of most PN classes and unequivocally mapped transcriptomes to specific olfactory function for six classes. Transcriptomes of closely related PN classes exhibit the largest differences during circuit assembly but become indistinguishable in adults, suggesting that neuronal subtype diversity peaks during development. Transcription factors and cell-surface molecules are the most differentially expressed genes between classes and are highly informative in encoding cell identity, enabling us to identify a new lineage-specific transcription factor that instructs PN dendrite targeting. These findings establish that neuronal transcriptomic identity corresponds with anatomical and physiological identity defined by connectivity and function.
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Affiliation(s)
- Hongjie Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Felix Horns
- Biophysics Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Bing Wu
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Qijing Xie
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Neurosciences Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Jiefu Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Tongchao Li
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - David J Luginbuhl
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Stephen R Quake
- Departments of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, Stanford, CA 94305, USA.
| | - Liqun Luo
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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190
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Schlegel P, Costa M, Jefferis GS. Learning from connectomics on the fly. CURRENT OPINION IN INSECT SCIENCE 2017; 24:96-105. [PMID: 29208230 DOI: 10.1016/j.cois.2017.09.011] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 09/18/2017] [Accepted: 09/19/2017] [Indexed: 06/07/2023]
Abstract
Parallels between invertebrates and vertebrates in nervous system development, organisation and circuits are powerful reasons to use insects to study the mechanistic basis of behaviour. The last few years have seen the generation in Drosophila melanogaster of very large light microscopy data sets, genetic driver lines and tools to report or manipulate neural activity. These resources in conjunction with computational tools are enabling large scale characterisation of neuronal types and their functional properties. These are complemented by 3D electron microscopy, providing synaptic resolution data. A whole brain connectome of the fly larva is approaching completion based on manual reconstruction of electron-microscopy data. An adult whole brain dataset is already publicly available and focussed reconstruction is under way, but its 40× greater volume would require ∼500-5000 person-years of manual labour. Nevertheless rapid technical improvements in imaging and especially automated segmentation will likely deliver a complete adult connectome in the next 5 years. To enhance our understanding of the circuit basis of behaviour, light and electron microscopy outputs must be integrated with functional and physiological information into comprehensive databases. We review presently available data, tools and opportunities in Drosophila. We then consider the limits and potential of future progress and how this may impact neuroscience in rich model systems provided by larger insects and vertebrates.
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Affiliation(s)
- Philipp Schlegel
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
| | - Gregory Sxe Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
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191
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Brown EB, Patterson C, Pancoast R, Rollmann SM. Artificial selection for odor-guided behavior in Drosophila reveals changes in food consumption. BMC Genomics 2017; 18:867. [PMID: 29132294 PMCID: PMC5683340 DOI: 10.1186/s12864-017-4233-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 10/23/2017] [Indexed: 11/20/2022] Open
Abstract
Background The olfactory system enables organisms to detect chemical cues in the environment and can signal the availability of food or the presence of a predator. Appropriate behavioral responses to these chemical cues are therefore important for organismal survival and can influence traits such as organismal life span and food consumption. However, understanding the genetic mechanisms underlying odor-guided behavior, correlated responses in other traits, and how these constrain or promote their evolution, remain an important challenge. Here, we performed artificial selection for attractive and aversive behavioral responses to four chemical compounds, two aromatics (4-ethylguaiacol and 4-methylphenol) and two esters (methyl hexanoate and ethyl acetate), for thirty generations. Results Artificial selection for odor-guided behavior revealed symmetrical responses to selection for each of the four chemical compounds. We then investigated whether selection for odor-guided behavior resulted in correlated responses in life history traits and/or food consumption. We found changes in food consumption upon selection for behavioral responses to aromatics. In many cases, lines selected for increased attraction to aromatics showed an increase in food consumption. We then performed RNA sequencing of lines selected for responses to 4-ethylguaiacol to identify candidate genes associated with odor-guided behavior and its impact on food consumption. We identified 91 genes that were differentially expressed among lines, many of which were associated with metabolic processes. RNAi-mediated knockdown of select candidate genes further supports their role in odor-guided behavior and/or food consumption. Conclusions This study identifies novel genes underlying variation in odor-guided behavior and further elucidates the genetic mechanisms underlying the interrelationship between olfaction and feeding. Electronic supplementary material The online version of this article (10.1186/s12864-017-4233-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elizabeth B Brown
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH, 45221-0006, USA
| | - Cody Patterson
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH, 45221-0006, USA
| | - Rayanne Pancoast
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH, 45221-0006, USA.,Department of Biology, Xavier University, Cincinnati, OH, 45207, USA
| | - Stephanie M Rollmann
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH, 45221-0006, USA.
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192
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Transsynaptic Mapping of Second-Order Taste Neurons in Flies by trans-Tango. Neuron 2017; 96:783-795.e4. [PMID: 29107518 DOI: 10.1016/j.neuron.2017.10.011] [Citation(s) in RCA: 193] [Impact Index Per Article: 24.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 06/30/2017] [Accepted: 10/05/2017] [Indexed: 12/27/2022]
Abstract
Mapping neural circuits across defined synapses is essential for understanding brain function. Here we describe trans-Tango, a technique for anterograde transsynaptic circuit tracing and manipulation. At the core of trans-Tango is a synthetic signaling pathway that is introduced into all neurons in the animal. This pathway converts receptor activation at the cell surface into reporter expression through site-specific proteolysis. Specific labeling is achieved by presenting a tethered ligand at the synapses of genetically defined neurons, thereby activating the pathway in their postsynaptic partners and providing genetic access to these neurons. We first validated trans-Tango in the Drosophila olfactory system and then implemented it in the gustatory system, where projections beyond the first-order receptor neurons are not fully characterized. We identified putative second-order neurons within the sweet circuit that include projection neurons targeting known neuromodulation centers in the brain. These experiments establish trans-Tango as a flexible platform for transsynaptic circuit analysis.
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193
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Grabe V, Sachse S. Fundamental principles of the olfactory code. Biosystems 2017; 164:94-101. [PMID: 29054468 DOI: 10.1016/j.biosystems.2017.10.010] [Citation(s) in RCA: 83] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Revised: 10/13/2017] [Accepted: 10/16/2017] [Indexed: 02/06/2023]
Abstract
Sensory coding represents a basic principle of all phyla in nature: species attempt to perceive their natural surroundings and to make sense of them. Ultimately, sensory coding is the only way to allow a species to make the kinds of crucial decisions that lead to a behavioral response. In this manner, animals are able to detect numerous parameters, ranging from temperature and humidity to light and sound to volatile or non-volatile chemicals. Most of these environmental cues represent a clearly defined stimulus array that can be described along a single physical parameter, such as wavelength or frequency; odorants, in contrast, cannot. The odor space encompasses an enormous and nearly infinite number of diverse stimuli that cannot be classified according to their positions along a single dimension. Hence, the olfactory system has to encode and translate the vast odor array into an accurate neural map in the brain. In this review, we will outline the relevant steps of the olfactory code and describe its progress along the olfactory pathway, i.e., from the peripheral olfactory organs to the first olfactory center in the brain and then to the higher processing areas where the odor perception takes place, enabling an organism to make odor-guided decisions. We will focus mainly on studies from the vinegar fly Drosophila melanogaster, but we will also indicate similarities to and differences from the olfactory system of other invertebrate species as well as of the vertebrate world.
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Affiliation(s)
- Veit Grabe
- Max Planck Institute for Chemical Ecology, Department of EvolutionaryNeuroethology, Hans-Knoell-Str. 8, 07745 Jena, Germany
| | - Silke Sachse
- Max Planck Institute for Chemical Ecology, Department of EvolutionaryNeuroethology, Hans-Knoell-Str. 8, 07745 Jena, Germany.
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194
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Robles E. The power of projectomes: genetic mosaic labeling in the larval zebrafish brain reveals organizing principles of sensory circuits. J Neurogenet 2017; 31:61-69. [PMID: 28797199 DOI: 10.1080/01677063.2017.1359834] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
In no vertebrate species do we possess an accurate, comprehensive tally of neuron types in the brain. This is in no small part due to the vast diversity of neuronal types that comprise complex vertebrate nervous systems. A fundamental goal of neuroscience is to construct comprehensive catalogs of cell types defined by structure, connectivity, and physiological response properties. This type of information will be invaluable for generating models of how assemblies of neurons encode and distribute sensory information and correspondingly alter behavior. This review summarizes recent efforts in the larval zebrafish to construct sensory projectomes, comprehensive analyses of axonal morphologies in sensory axon tracts. Focusing on the olfactory and optic tract, these studies revealed principles of sensory information processing in the olfactory and visual systems that could not have been directly quantified by other methods. In essence, these studies reconstructed the optic and olfactory tract in a virtual manner, providing insights into patterns of neuronal growth that underlie the formation of sensory axon tracts. Quantitative analysis of neuronal diversity revealed organizing principles that determine information flow through sensory systems in the zebrafish that are likely to be conserved across vertebrate species. The generation of comprehensive cell type classifications based on structural, physiological, and molecular features will lead to testable hypotheses on the functional role of individual sensory neuron subtypes in controlling specific sensory-evoked behaviors.
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Affiliation(s)
- Estuardo Robles
- a Department of Biological Sciences and Institute for Integrative Neuroscience , Purdue University , West Lafayette , IN , USA
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195
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Chen D, Sitaraman D, Chen N, Jin X, Han C, Chen J, Sun M, Baker BS, Nitabach MN, Pan Y. Genetic and neuronal mechanisms governing the sex-specific interaction between sleep and sexual behaviors in Drosophila. Nat Commun 2017; 8:154. [PMID: 28754889 PMCID: PMC5533705 DOI: 10.1038/s41467-017-00087-5] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 05/30/2017] [Indexed: 12/13/2022] Open
Abstract
Animals execute one particular behavior among many others in a context-dependent manner, yet the mechanisms underlying such behavioral choice remain poorly understood. Here we studied how two fundamental behaviors, sex and sleep, interact at genetic and neuronal levels in Drosophila. We show that an increased need for sleep inhibits male sexual behavior by decreasing the activity of the male-specific P1 neurons that coexpress the sex determination genes fruM and dsx, but does not affect female sexual behavior. Further, we delineate a sex-specific neuronal circuit wherein the P1 neurons encoding increased courtship drive suppressed male sleep by forming mutually excitatory connections with the fruM-positive sleep-controlling DN1 neurons. In addition, we find that FRUM regulates male courtship and sleep through distinct neural substrates. These studies reveal the genetic and neuronal basis underlying the sex-specific interaction between sleep and sexual behaviors in Drosophila, and provide insights into how competing behaviors are co-regulated. Genes and circuits involved in sleep and sexual arousal have been extensively studied in Drosophila. Here the authors identify the sex determination genes fruitless and doublesex, and a sex-specific P1-DN1 neuronal feedback that governs the interaction between these competing behaviors
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Affiliation(s)
- Dandan Chen
- The Key Laboratory of Developmental Genes and Human Disease, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Divya Sitaraman
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, USA. .,Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, Connecticut, 06520, USA. .,Department of Psychological Sciences, University of San Diego, San Diego, California, 92110, USA.
| | - Nan Chen
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, USA
| | - Xin Jin
- Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, Connecticut, 06520, USA
| | - Caihong Han
- The Key Laboratory of Developmental Genes and Human Disease, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Jie Chen
- The Key Laboratory of Developmental Genes and Human Disease, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Mengshi Sun
- The Key Laboratory of Developmental Genes and Human Disease, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Bruce S Baker
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, USA
| | - Michael N Nitabach
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, USA. .,Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, Connecticut, 06520, USA. .,Department of Genetics, Yale School of Medicine, New Haven, Connecticut, 06520, USA. .,Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, Connecticut, 06520, USA.
| | - Yufeng Pan
- The Key Laboratory of Developmental Genes and Human Disease, Institute of Life Sciences, Southeast University, Nanjing, 210096, China. .,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu, 226001, China.
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196
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Whole-Brain Calcium Imaging Reveals an Intrinsic Functional Network in Drosophila. Curr Biol 2017; 27:2389-2396.e4. [PMID: 28756955 DOI: 10.1016/j.cub.2017.06.076] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 05/09/2017] [Accepted: 06/29/2017] [Indexed: 02/07/2023]
Abstract
A long-standing goal of neuroscience has been to understand how computations are implemented across large-scale brain networks. By correlating spontaneous activity during "resting states" [1], studies of intrinsic brain networks in humans have demonstrated a correspondence with task-related activation patterns [2], relationships to behavior [3], and alterations in processes such as aging [4] and brain disorders [5], highlighting the importance of resting-state measurements for understanding brain function. Here, we develop methods to measure intrinsic functional connectivity in Drosophila, a powerful model for the study of neural computation. Recent studies using calcium imaging have measured neural activity at high spatial and temporal resolution in zebrafish, Drosophila larvae, and worms [6-10]. For example, calcium imaging in the zebrafish brain recently revealed correlations between the midbrain and hindbrain, demonstrating the utility of measuring intrinsic functional connections in model organisms [8]. An important component of human connectivity research is the use of brain atlases to compare findings across individuals and studies [11]. An anatomical atlas of the central adult fly brain was recently described [12]; however, combining an atlas with whole-brain calcium imaging has yet to be performed in vivo in adult Drosophila. Here, we measure intrinsic functional connectivity in Drosophila by acquiring calcium signals from the central brain. We develop an alignment procedure to assign functional data to atlas regions and correlate activity between regions to generate brain networks. This work reveals a large-scale architecture for neural communication and provides a framework for using Drosophila to study functional brain networks.
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197
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A Defensive Kicking Behavior in Response to Mechanical Stimuli Mediated by Drosophila Wing Margin Bristles. J Neurosci 2017; 36:11275-11282. [PMID: 27807168 DOI: 10.1523/jneurosci.1416-16.2016] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 09/08/2016] [Indexed: 01/22/2023] Open
Abstract
Mechanosensation, one of the fastest sensory modalities, mediates diverse behaviors including those pertinent for survival. It is important to understand how mechanical stimuli trigger defensive behaviors. Here, we report that Drosophila melanogaster adult flies exhibit a kicking response against invading parasitic mites over their wing margin with ultrafast speed and high spatial precision. Mechanical stimuli that mimic the mites' movement evoke a similar kicking behavior. Further, we identified a TRPV channel, Nanchung, and a specific Nanchung-expressing neuron under each recurved bristle that forms an array along the wing margin as being essential sensory components for this behavior. Our electrophysiological recordings demonstrated that the mechanosensitivity of recurved bristles requires Nanchung and Nanchung-expressing neurons. Together, our results reveal a novel neural mechanism for innate defensive behavior through mechanosensation. SIGNIFICANCE STATEMENT We discovered a previously unknown function for recurved bristles on the Drosophila melanogaster wing. We found that when a mite (a parasitic pest for Drosophila) touches the wing margin, the fly initiates a swift and accurate kick to remove the mite. The fly head is dispensable for this behavior. Furthermore, we found that a TRPV channel, Nanchung, and a specific Nanchung-expressing neuron under each recurved bristle are essential for its mechanosensitivity and the kicking behavior. In addition, touching different regions of the wing margin elicits kicking directed precisely at the stimulated region. Our experiments suggest that recurved bristles allow the fly to sense the presence of objects by touch to initiate a defensive behavior (perhaps analogous to touch-evoked scratching; Akiyama et al., 2012).
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198
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Olfactory coding from the periphery to higher brain centers in the Drosophila brain. BMC Biol 2017; 15:56. [PMID: 28666437 PMCID: PMC5493115 DOI: 10.1186/s12915-017-0389-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Accepted: 06/02/2017] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Odor information is processed through multiple receptor-glomerular channels in the first order olfactory center, the antennal lobe (AL), then reformatted into higher brain centers and eventually perceived by the fly. To reveal the logic of olfaction, it is fundamental to map odor representations from the glomerular channels into higher brain centers. RESULTS We characterize odor response profiles of AL projection neurons (PNs) originating from 31 glomeruli using whole cell patch-clamp recordings in Drosophila melanogaster. We reveal that odor representation from olfactory sensory neurons to PNs is generally conserved, while transformation of odor tuning curves is glomerulus-dependent. Reconstructions of PNs reveal that attractive and aversive odors are represented in different clusters of glomeruli in the AL. These separate representations are preserved into higher brain centers, where attractive and aversive odors are segregated into two regions in the lateral horn and partly separated in the mushroom body calyx. CONCLUSIONS Our study reveals spatial representation of odor valence coding from the AL to higher brain centers. These results provide a global picture of the olfactory circuit design underlying innate odor-guided behavior.
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199
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Ishikawa Y, Okamoto N, Nakamura M, Kim H, Kamikouchi A. Anatomic and Physiologic Heterogeneity of Subgroup-A Auditory Sensory Neurons in Fruit Flies. Front Neural Circuits 2017; 11:46. [PMID: 28701929 PMCID: PMC5487475 DOI: 10.3389/fncir.2017.00046] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Accepted: 06/08/2017] [Indexed: 12/18/2022] Open
Abstract
The antennal ear of the fruit fly detects acoustic signals in intraspecific communication, such as the courtship song and agonistic sounds. Among the five subgroups of mechanosensory neurons in the fly ear, subgroup-A neurons respond maximally to vibrations over a wide frequency range between 100 and 1,200 Hz. The functional organization of the neural circuit comprised of subgroup-A neurons, however, remains largely unknown. In the present study, we used 11 GAL4 strains that selectively label subgroup-A neurons and explored the diversity of subgroup-A neurons by combining single-cell anatomic analysis and Ca2+ imaging. Our findings indicate that the subgroup-A neurons that project into various combinations of subareas in the brain are more anatomically diverse than previously described. Subgroup-A neurons were also physiologically diverse, and some types were tuned to a narrow frequency range, suggesting that the response of subgroup-A neurons to sounds of a wide frequency range is due to the existence of several types of subgroup-A neurons. Further, we found that an auditory behavioral response to the courtship song of flies was attenuated when most subgroup-A neurons were silenced. Together, these findings characterize the heterogeneous functional organization of subgroup-A neurons, which might facilitate species-specific acoustic signal detection.
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Affiliation(s)
- Yuki Ishikawa
- Division of Biological Science, Graduate School of Science, Nagoya UniversityNagoya, Japan
| | - Natsuki Okamoto
- Division of Biological Science, Graduate School of Science, Nagoya UniversityNagoya, Japan
| | - Mizuki Nakamura
- Division of Biological Science, Graduate School of Science, Nagoya UniversityNagoya, Japan
| | - Hyunsoo Kim
- Division of Biological Science, Graduate School of Science, Nagoya UniversityNagoya, Japan
| | - Azusa Kamikouchi
- Division of Biological Science, Graduate School of Science, Nagoya UniversityNagoya, Japan
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200
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MaBouDi H, Shimazaki H, Giurfa M, Chittka L. Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities. PLoS Comput Biol 2017. [PMID: 28640825 PMCID: PMC5480824 DOI: 10.1371/journal.pcbi.1005551] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons' outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several-but not all-types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees' antennal lobes with their behavioural performances over the course of their life.
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Affiliation(s)
- HaDi MaBouDi
- School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom
| | | | - Martin Giurfa
- Research Centre on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
| | - Lars Chittka
- School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom
- * E-mail:
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